The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population: A cross-sectional study

Natalia Anna Zieleniewska; Jacek Jamiołkowski; Małgorzata Chlabicz; Adam Łukasiewicz; Marlena Dubatówka; Marcin Kondraciuk; Paweł Sowa; Irina Kowalska; Karol Adam Kamiński

doi:10.1371/journal.pone.0309896

. 2024 Oct 29;19(10):e0309896. doi: 10.1371/journal.pone.0309896

The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population: A cross-sectional study

Natalia Anna Zieleniewska ^1,², Jacek Jamiołkowski ¹, Małgorzata Chlabicz ^1,³, Adam Łukasiewicz ⁴, Marlena Dubatówka ¹, Marcin Kondraciuk ¹, Paweł Sowa ¹, Irina Kowalska ⁵, Karol Adam Kamiński ^1,^2,^*

Editor: Andreas Beyerlein⁶

PMCID: PMC11521245 PMID: 39471178

Abstract

Background

The hypothesis that not only diagnosed diabetes (DM), but also milder dysglycemia may affect the development of atherosclerosis still requires further study. In our population-based study, we aimed to evaluate the impact of prediabetic state on preclinical atherosclerosis and whether it may affect the cardiovascular risk (CVR) in the general population.

Methods

The analysis was a part of the Bialystok PLUS cohort study and represented a random sample of Bialystok (Poland) residents aged 20–79 years at the time of sampling (July 2017-January 2023). The cross-sectional analysis included 1431 participants of a population-based study (mean age 46.82 years). Comprehensive biochemical assessments were performed. An Oral Glucose Tolerance Test (OGTT) was performed on fasting patients who did not report having a DM.

Results

The population with prediabetes, based on HbA1c and OGTT, accounted for more than half of the study participants (n = 797, 55.7%). Atherosclerotic plaques in the carotid arteries were significantly more common in individuals with prediabetes considering all CVR categories. Prediabetes was associated with the occurrence of more advanced preclinical atherosclerosis, especially in the low to moderate CVR category. Serum glucose concentration after 1h and HbA1c proved to be statistically significant indicators of the presence of atherosclerotic plaques in ultrasound (respectively, AUC = 0.73 and 0.72). In multivariate logistic regression, prediabetes was independently associated with significantly increased risk of preclinical atherosclerosis (OR = 1.56, 95% CI 1.09–2.24), along with CVR categories, pulse wave velocity and central blood pressure augmentation index.

Conclusions

Prediabetes is associated with the occurrence and progression of the preclinical atherosclerosis. Importantly, many of those patients are in the low to moderate cardiovascular risk category, hence may have a severely underestimated risk. Inclusion of prediabetes into CVR assessment may improve risk stratification. An early identification of dysglycemic population is necessary to effectively implement the cardiovascular and metabolic prevention measures.

Introduction

Prediabetes is an intermediate state defined as raised blood glycemic parameters above the normal range, but below the threshold for diabetes [1]. Prediabetes is specifically defined as impaired fasting glucose (IFG) or impaired glucose tolerance (IGT) [1]. Such a condition is classified as dysglycemia and a prelude to diabetes mellitus (DM) [2]. The incidence of type 2 DM progression five years after the diagnosis of IGT or IFG is estimated at 26% and 50%, respectively [2]. The natural progression of prediabetes is increasing insulin resistance and pancreatic B-cell dysfunction, leading to overt DM [3]. The prevalence of non-diabetic hyperglycaemia is steadily increasing: 541 million adults (10.6% of adults worldwide) are estimated to have IGT and 319 million adults (6.2%) to have IFG [4].

Early diagnosis of prediabetes is crucial from clinical standpoint. First, the presence of non-diabetic hyperglycemia signifies an increased risk of developing type 2 DM [5, 6], which accounts for over 90% of all diabetes worldwide [4]. Prediabetes identifies an enhanced incidence of cardiovascular disease [7, 8]. Importantly, early diagnosis of prediabetes opens up opportunities for therapeutic interventions to prevent progression to DM [9]. However, the difficulty in diagnosing hyperglycemia is that it often remains asymptomatic. Symptoms, such as excessive thirst, frequent urination and fatigue, often appear very late in the course of the disease and may be ignored by the patient or considered insignificant. As a result, even half of people with dysglycemia in the population may be undiagnosed [4]. There is marked diagnostic inertia both in diagnosing and treating prediabetes, therefore it is of utmost clinical importance to present and advocate the unfavourable consequences of dysglycemia. Importantly many of these people consider themselves healthy and their increased risk remains unrecognized by healthcare providers, as prediabetes is not included in the major cardiovascular risk scores.

Obesity, hypertension, cigarette smoking, and DM are well-recognized risk factors for atherosclerotic cardiovascular disease (ASCVD) [10]. ASCVD remains the most widespread cardiovascular problem, moreover, myocardial infarction is considered to be the leading cause of death [1]. A previously conducted study of patients with first-time acute coronary syndrome (ACS) who underwent urgent coronary angiography showed that coronary atherosclerosis is more advanced in patients with prediabetes than in patients without DM [38]. Furthermore, the association of the occurrence of coronary atherosclerosis was shown to be comparable between patients with prediabetes and patients with DM at the time of first ACS [38]. Another study using percutaneous coronary intervention showed that coronary lesions in prediabetic patients were associated with higher levels of lipid-rich atherosclerotic plaques [39]. Prediabetes is associated with inflammation and vasoconstriction, which promote atherosclerosis in the coronary arteries [40]. Notably, limited evidence comes from research on both, prediabetes and carotid atherosclerosis in general population.

Recently, cardiovascular prevention and identifying people at risk for ASCVD as early as possible have grown in importance. The aim of our study was to analyse whether prediabetes affects the development of preclinical atherosclerosis in the general population.

Material and methods

Cohort study Bialystok PLUS

Our analysis was a part of the Bialystok PLUS cohort study and represented a random sample of Bialystok residents aged 20–79 years at the time of sampling (July 2017-January 2023). Bialystok is a medium-sized city located in eastern Poland with a population of 293,400. The recruitment of participants for the population-based study uses a pseudonymized list of residents of Bialystok obtained from the Local Municipal Office. Annually, we randomly sampled citizens to obtain a distribution of proportions in terms of age and gender similar to that of the city’s population. A more detailed study design was described in previously published paper [11]. On June 1, 2023, the data was made available for research purposes. The study authors did not have access to information that could identify individual participants after data collection.

The study was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants. Ethical approval for this study was provided by the Ethics Committee of the Medical University of Bialystok (Poland) on 31 March 2016 (approval number: R-I-002/108/2016).

Data collection and assays

All the clinical and biochemical measurements were conducted by qualified medical personnel. High reproducibility of the examinations was achieved by performing them based on verified Standard Operating Procedures. The details of the subjects’ medical history were collected from questionnaires at the time of study entry. In the morning of the visit, peripheral intravenous fasting blood samples were collected after at least eight hours of fasting. Patients also declared that they slept through the night. Comprehensive biochemical assessments were performed: total cholesterol (TC), LDL-cholesterol (LDL-C) and HDL-cholesterol (HDL-C) fractions, triglycerides (TG), glucose, glycated hemoglobin (HbA1c). The samples were then prepared for further analysis by centrifugation and storage at −70°C. As recommended by the World Health Organization (WHO), we performed an Oral Glucose Tolerance Test (OGTT) on fasting patients who did not report having a history of DM. 75 grams of glucose dissolved in water was administered and then blood was taken sequentially after 1 and 2 hours.

Fasting glucose concentration at 60 min and 120 min glucose levels were assessed in plasma drawn on EDTA with sodium fluoride using a reference enzymatic method with hexokinase (Cobas c111, Roche). Using the homogeneous enzymatic colorimetric method on the Cobas c111 from ROCHE (ROCHE, Meylan, Isère, France), the concentration of low- and high-density lipoprotein cholesterols (LDL-C and HDL-C, respectively) were determined. Total cholesterol and triglycerides were determined using the enzymatic colorimetric method on the Cobas c111 from ROCHE. Glycated hemoglobin A1c (HbA1c) was determined by ion-exchange high performance liquid chromatography (HPLC) on D-10 from Bio-Rad (Bio-Rad, Hercules, CA, USA). Serum insulin was determined by electrochemiluminescence (ECLIA) on the Cobas e411 device (ROCHE).

Anthropometric measurements including height and circumferences of the waist, abdomen and hips were taken (SECA 201 tape, Hamburg, Germany). Body mass index (BMI) was calculated as weight in kilograms divided by height in metres squared and is expressed in units of kg/m². Waist-to-hip ratio (WHR) was calculated as a ratio between waist and hips circumference. Blood pressure (BP) was measured using the oscillometric method (obtained with the Omron Healthcare Co. Ltd MG Comfort device) after the participants were seated for at least 5 minutes—two measurements were taken 5 minutes apart and the average was drawn. The weight and body mass composition were determined using the InBody 770.

Ultrasound examination (US) of the carotid arteries was used to evaluate early atherosclerotic lesions. The ultrasonography measurements were made using the ultrasound Vivid 9 (GE Healthcare, Chicago, IL, USA). The presence of any atherosclerotic plaques in 1) right common carotid artery (CCA), 2) left CCA, 3) right external carotid artery (ECA), 4) left ECA, 5) right internal carotid artery (ICA), 6) left ICA, 7) right bifurcation (BIF), 8) left BIF were evaluated. We assessed atherosclerotic plaques as binomial quality variables and marked them as present when 1 of the following criteria was fulfilled: 1) the local thickening IMT towards the lumen of the vessel, exceeding the surrounding IMT by > 0.5 mm, 2) the local thickening IMT towards the lumen of the vessel, surpassing the surrounding IMT by 50%, 3) IMT thickening > 1.5 mm [12]. A constant element of the study was the estimation of intima media thickness (IMT) in right and left CCA and the result is presented as an average value from 5 measurements. In addition, we assessed the advanced stage of early atherosclerotic lesions based on the presence of ICA stenosis. Stenosis severity was determined using the North American Symptomatic Carotid Endarterectomy Trial (NASCET) criteria [13].

The parameters for assessing arterial stiffness, i.e. carotid-femoral pulse wave velocity (PWV) and augmentation index (AIx), were measured using an oscillometric method (Vascular Explorer, Enverdis, Jena, Germany) in the supine position preceded by 10 minutes of rest.

Division into cardiovascular risk classes

To calculate CV risk in primary prevention were used Systematic Coronary Risk Estimation 2 (SCORE2) and Systematic Coronary Risk Estimation 2-Older Persons (SCORE2-OP) [10]. The SCORE2 and SCORE2-OP estimates an individual’s 10-year risk of fatal and non-fatal CVD events (myocardial infarction, stroke) in apparently healthy people. The SCORE2 and SCORE2-OP was calculated, excluding participants who were pre-qualified in the high and very high CV risk classes, i.e. participants with previously diagnosed CVD (myocardial infarction—MI, ischemic heart disease—IHD, stroke, transient ischemic attack—TIA, peripheral arterial disease—PAD, significant plaque on carotid ultrasound >50% of arterial stenosis), moderate or severe chronic kidney disease (CKD) at the time of study entry, and younger than 40 years old. The SCORE2 was calculated for those aged 40–69, while SCORE2-OP was calculated for those aged 70–89. The calculator for high CVD risk countries was used, as Poland belongs to this category.

The study population was divided according to the latest recommendation “2021 ESC Guidelines on cardiovascular disease prevention in clinical practice” [10] into low-to-moderate, high and very-high CVD categories. Firstly, high and very-high risk individuals were identified. The previously calculated SCORE2 and SCORE2-OP values were then used to categorize apparently healthy individuals.

Subjects with familial hypercholesterolemia, DM type 1 and 2 and with established ASCVD were assigned to appropriate categories according to “2021 ESC Guidelines on cardiovascular disease prevention in clinical practice” [10]. Individuals with CKD were assigned to high and very-high CVD risk categories according to previous guidelines: “2019 ESC/EAS guidelines for the management of dyslipidemias: lipid modification to reduce cardiovascular risk” [14] due to lacking the albumin-to-creatinine ratio (ACR) in the studied population. To high CVD risk category were classified people with estimated glomerular filtration rate (eGFR) 30-59mL/min/1.73m², while to very high CVD risk category with eGFR <30mL/min/1.73m².

Definition of diabetes, prediabetes and assessment of insulin sensitivity

We used the diagnostic criteria for DM and prediabetes according to ESC and the European Association for the Study of Diabetes (EASD) recommendations [1]. DM was not diagnosed based on fasting glucose due to availability of a single measurement. Prediabetes was diagnosed in participants who had no previous diabetes: 1) IFG if fasting glycaemia was between 100–125 mg/dl (5.6–6.9 mmol/l) and after 2h was less than 140 mg/dl (7.8 mmol/l); 2) IGT if at 2h glycaemia was ≥140 mg/dl (7.8 mmol/l) and < 200 mg/dl (11.1 mmol/l); 3) based on HbA1c when it ranged from 5.7–6.4% (42–47 mmol/mol). Those who had fasting glucose in a single measurement above 125 mg/dl and after 2h below 200 mg/dl were categorised as IGTs. Newly diagnosed DM was diagnosed based on OGTT ≥ 200 mg/dl and an HbA1c ≥ 6.5%. We used several well-described indicators to assess insulin resistance. Quantitative insulin sensitivity check index (QUICKI) was defined as 1/[log(I₀) + log(G₀)], where I₀ is the fasting insulin (μU/ml), and G₀ is the fasting glucose (mmol/l) [15]. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated using the formula: I₀ × G₀ /22.5 [16]. When assessing insulin sensitivity, we used the Matsuda index calculated from the formula 10000/ √ (G₀ mg/dl x I₀ μU/ml) x (Mean OGTT glucose concentration mg/dl × mean OGTT insulin concentration mg/dl) [17].

Statistical analysis

Descriptive statistics for continuous variables were presented as means and 95% Confidence Intervals for means and for categorical variables as proportions and 95% Confidence Intervals for proportions. The sample size is large enough to assume that the variables followed a normal distribution according to Central Limit Theorem. Comparisons of variables between subgroups were analysed using the chi-squared test for qualitative variables. Two regression logistic models were performed. In one model, the independent variables were classic well-described cardiovascular risk factors and in the other one we used stratification into cardiovascular risk classes (which includes few of these classic risk factors). Regression models were presented using regression coefficients, p-value of Wald tests and coefficients of determination for the model. The IBM SPSS Statistics 27.0 statistical software (Armonk, NY, USA) was used for all the calculations. The criterion for statistical significance was set at p < 0.05. The figures have been made in Excel and R 4.2.1.

Results

Study population

The study enrolled 1866 participants. According to STROBE guidelines, the flowchart represents the study population (Fig 1). Prevalent diabetes (n = 252, 13.5%) was diagnosed on the basis of medical history (n = 140) and glucose levels after 2h OGGT (n = 112). All prevalent diabetic patients were excluded from further analysis. Additionally, 183 patients were excluded from further analysis for technical reasons–inability to perform an OGTT (n = 132) or US of the carotid arteries (n = 4) or lack of the HbA1c measurement (n = 7) or lack of CVR assessment (n = 40) [18]. After applying these exclusion criteria, the data of 1431 participants (mean age 46.82 years) remained for analysis. The population of attendees without dysglycemia consisted of 634 patients (44.3%). The population with prediabetes accounted for more than half of the study participants (n = 797, 55.7%). Subsequently, we outlined the differences in the diagnosis of prediabetes considering the diagnostic method. It is worth noting that as many as 84 (approximately 5.9%) patients with normal OGTT results had elevated hemoglobin HbA1c values.

Table 1 presents the basic characteristics of the study group by glucose metabolism status. The population without glucose metabolism disturbances was significantly different in all parameters describing metabolic and anthropometric values and preclinical atherosclerosis comparing to that of prediabetes. Patients with normal glycemia (both fasting and OGTT), but with elevated HbA1c values significantly differed from patients without impaired glucose metabolism in the following parameters: age, diastolic blood pressure, LDL-C, QUICKI, glucose levels after 1h, mean CCA IMT, as well as the presence of atherosclerotic plaques and arterial stiffness parameters. Moreover, we found no differences in anthropometric parameters and body composition. We also noted that there was a statistically significant difference in the presence of atherosclerotic plaques between the group with IFG and those with IGT.

Table 1. Baseline clinical and metabolic characteristics of population group and groups with prediabetes.

	Total n = 1431	No glucose metabolism disturbances n = 634 Mean (95% CI)	Population with prediabetes n = 797
	Total n = 1431	No glucose metabolism disturbances n = 634 Mean (95% CI)	IFG n = 415 Mean (95% CI)	IGT n = 298 Mean (95% CI)	Population with prediabetes based on HbA1c alone n = 84 Mean (95% CI)
Age, years	46.82 (46.05–47.59)	39.60 (38.62–40.57)	50.15 (48.83–51.46)	55.46 (53.87–57.05)	54.23 (50.99–57.47)
Sex, male, n, %	52.8% (43.4%-62.1%)	38.8% (35.1%-42.7%)	57.8% (53.0%-62.5%)	45.3% (39.7%-51.0%)	26.2% (18.0%-36.5%)
BMI, kg/m²	26.30 (26.06–26.54)	24.70 (24.39–25.02)	27.48 (27.06–27.90)	28.21 (27.67–28.76)	25.78 (24.85–26.71)
WHR	0.86 (0.85–0.86)	0.83 (0.82–0.83)	0.89 (0.88–0.90)	0.89 (0.88–0.90)	0.84 (0.83–0.86)
SBP mmHg	122.18 (121.31–123.04)	116.63 (115.51–117.76)	126.91 (125.33–128.49)	128.03 (125.97–130.08)	119.93 (116.81–123.06)
DBP mmHg	80.48 (79.96–80.99)	78.04 (77.36–78.72)	82.79 (81.82–83.77)	82.98 (81.76–84.20)	78.60 (76.44–80.77)
Total cholesterol, mg/dl,	193.63 (191.59–195.67)	185.15 (182.46–187.84)	202.46 (198.47–206.45)	195.97 (191.36–200.58)	205.70 (196.20–215.21)
Triglycerides, mg/dl	109.45 (105.34–113.56)	96.59 (89.84–103.34)	116.00 (109.74–122.25)	128.71 (119.21–138.21)	105.86 (95.64–116.08)
HDL-C, mg/dl,	62.17 (61.31–63.03)	63.83 (62.58–65.09)	60.91 (59.23–62.59)	59.47 (57.72–61.21)	65.42 (61.63–69.21)
LDL-C, mg/dl,	123.86 (122.00–125.72)	115.68 (113.23–118.13)	132.76 (129.14–136.38)	126.15 (122.03–130.26)	133.36 (124.28–142.45)
Cholesterol-lowering treatment, %	25.5% (18.1%-34.5%)	2.7% (1.7%-4.3%)	10.8% (8.2%-14.2%)	20.5% (16.3%-25.4%)	17.9% (11.1%-27.4%)
Fasting glucose level, mg/dl	97.87 (97.38–98.36)	90.78 (90.34–91.22)	105.77 (105.25–106.28)	103.40 (102.38–104.41)	92.70 (91.60–93.80)
Serum glucose concentration, 1h after glucose loading, mg/dl	143.57 (141.33–145.82)	120.85 (118.29–123.40)	152.38 (148.91–155.85)	178.48 (173.99–182.97)	133.75 (124.61–142.89)
Serum glucose concentration, 2h of glucose loading, mg/dl,	117.70 (116.24–119.17)	102.43 (100.99–103.87)	112.54 (110.70–114.37)	158.98 (157.20–160.75)	112.08 (107.88–116.29)
Fasting insulin concentration, mg/dl,	11.81 (11.41–12.21)	9.63 (9.23–10.04)	13.45 (12.71–14.20)	14.92 (13.71–16.14)	9.94 (8.96–10.91)
Serum insulin concentration, 1h after glucose loading, mg/dl,	84.87 (81.09–88.65)	66.26 (62.43–70.09)	98.36 (90.74–105.98)	105.73 (95.33–116.12)	77.68 (66.20–89.16)
Serum insulin concentration, 2h after glucose loading, mg/dl,	61.99 (58.78–65.21)	43.38 (40.99–45.77)	56.55 (52.03–61.07)	110.48 (99.53–121.42)	55.82 (47.75–63.88)
HbA1c, %	5.36 (5.34–5.38)	5.16 (5.14–5.18)	5.45 (5.42–5.48)	5.51 (5.47–5.55)	5.84 (5.81–5.86)
HOMA-IR	2.90 (2.80–3.01)	2.17 (2.08–2.27)	3.52 (3.32–3.72)	3.87 (3.54–4.20)	2.29 (2.06–2.52)
QUICKI	0.34 (0.33–0.34)	0.35 (0.35–0.35)	0.32 (0.32–0.33)	0.32 (0.32–0.33)	0.34 (0.34–0.35)
Matsuda Index	4.69 (4.52–4.85)	6.04 (5.77–6.31)	3.79 (3.57–4.01)	3.05 (2.82–3.28)	5.29 (4.46–6.12)
Average CCA IMT	0.63 (0.62–0.64)	0.58 (0.57–0.59)	0.65 (0.64–0.66)	0.70 (0.68–0.71)	0.67 (0.64–0.69)
Presence of any atherosclerotic plaques	70.8% (61.5%-78.6%)	23.3% (20.2%-26.8%)	50.4% (45.6%-55.1%)	61.4% (55.8%-66.8%)	50.0% (39.5%-60.5%)
Brachial- Ankle PWV, m/s	10.36 (10.24–10.49)	9.58 (9.42–9.74)	10.72 (10.51–10.93)	11.30 (11.03–11.57)	10.72 (9.95–11.50)
AIx	14.71 (14.06–15.36)	12.20 (11.28–13.11)	15.40 (14.20–16.60)	17.86 (16.51–19.20)	18.22 (14.88–21.56)

Open in a new tab

BMI–Body Mass Index, WHR–Waist-Hip Ratio, SBP–systolic blood pressure, DBP–diastolic blood pressure, HbA1c –glycated hemoglobin A1c, LDL -low density lipoprotein, HDL–high density lipoprotein, HOMA-IR—Homeostasis Model Assessment of Insulin Resistance, QUICKI- quantitative insulin sensitivity check index, CCA IMT—Carotid Artery Intima Media Thickness, PWV–pulse wave velocity, Aix- augmentation index, CI–Confidence interval.

To estimate possible predictors of the atherosclerotic plaques’ formation (dependent variable), ROC curves for glycemic parameters and insulin resistance indices were created (S1 Fig, S1 Table). We observed that all examined parameters proved to be statistically significant indicators of the presence of atherosclerotic plaques in carotid ultrasound, also upon application of Bonferroni correction. However, the highest AUC values were obtained for serum glucose concentration after 1h and HbA1c (AUC = 0.73; 95% CI 0.70–0.76 for glucose level after 1 h and AUC = 0.72; 95% CI 0.69–0.75 for HbA1c).

Atherosclerotic plaque presence in particular cardiovascular risk categories.

Fig 2 presented the prevalence of prediabetes in the general population with cardiovascular risk categories and the presence of atherosclerotic plaques in the carotid arteries. The majority, two-thirds of the study population were patients classified in CVR category 1. Moreover, prediabetes was associated with the occurrence of preclinical atherosclerosis in the low to moderate CVR category (p<0.001, S2 Table). Atherosclerotic plaques in the carotid arteries were significantly more common in hyperglycemic individuals considering all CVR categories (p<0.001, S3 Table). In the next tables, we showed that more advanced preclinical atherosclerotic lesions are statistically more common in prediabetic patients (p<0.001; S4 and S5 Tables).

In the Table 2, we have presented the characteristics of the study group by the presence or absence of atherosclerotic lesions and their severity. In all three conditions, individuals with the presence of advanced atherosclerotic lesions were significantly older than those without. As expected, subjects with and without any atherosclerotic plaques differed both in lipid profile, glycemic and insulin resistance tests and also in anthropometric measurements. Observing more advanced lesions (ICA stenosis >50%), we could see that the groups do not vary in lipid profile or BMI, although we may observed significant differences in glycemic and glycated hemoglobin measurements and cholesterol-lowering treatment. Moreover, patients with any of the three conditions had significantly higher arterial stiffness parameters.

Table 2. Evaluation of the relationship of vascular early atherosclerotic parameters with anthropometric, metabolic and insulin resistance parameters.

	The occurrence of any atherosclerotic plaques in the carotid arteries		ICA stenosis >50%		Local IMT thickening
			Mean (95% Confidence interval)		Mean (95% Confidence interval)
	Mean (95% Confidence interval)		Mean (95% Confidence interval)		Mean (95% Confidence interval)
Age	without any plaques	38.54 (37.80–39.27)	Without stenosis	46.56 (45.79–47.33)	Without IMT thickening	38.59 (37.79–39.38)
Age	with plaques	58.90 (57.98–59.81)	With ICA stenosis >50%	69.93 (65.85–74.01)	With IMT thickening	58.17 (57.15–59.18)
BMI kg/m2	without any plaques	25.28 (24.99–25.57)	Without stenosis	26.28 (26.04–26.52)	Without IMT thickening	25.34 (25.03–25.66)
BMI kg/m2	with plaques	27.79 (27.42–28.17)	With ICA stenosis >50%	28.17 (26.08–30.26)	With IMT thickening	27.72 (27.33–28.11)
WHR	without any plaques	0.83 (0.83–0.84)	Without stenosis	0.86 (0.85–0.86)	Without IMT thickening	0.83 (0.83–0.84)
WHR	with plaques	0.89 (0.89–0.90)	With ICA stenosis >50%	0.92 (0.88–0.97)	With IMT thickening	0.90 (0.89–0.90)
LDL-C mg/dl	without any plaques	117.74 (115.55–119.93)	Without stenosis	123.91 (122.05–125.78)	Without IMT thickening	118.24 (115.81–120.67)
LDL-C mg/dl	with plaques	132.80 (129.66–135.93)	With ICA stenosis >50%	116.08 (93.80–138.37)	With IMT thickening	131.45 (128.23–134.68)
Fasting glucose level, mg/dl	without any plaques	95.48 (94.88–96.08)	Without stenosis	97.77 (97.28–98.27)	Without IMT thickening	96.37 (95.72–97.01)
Fasting glucose level, mg/dl	with plaques	101.35 (100.61–102.08)	With ICA stenosis >50%	105.93 (102.08–109.77)	With IMT thickening	101.84 (101.11–102.57)
Serum glucose concentration after 1h in OGTT, mg/dl	without any plaques	132.08 (129.43–134.74)	Without stenosis	143.12 (140.87–145.37)	Without IMT thickening	132.13 (129.41–134.85)
Serum glucose concentration after 1h in OGTT, mg/dl	with plaques	160.18 (156.74–163.62)	With ICA stenosis >50%	179.50 (163.25–195.75)	With IMT thickening	159.19 (155.82–162.56)
Serum glucose concentration after 2h in OGTT, mg/dl	without any plaques	111.67 (109.91–113.43)	Without stenosis	117.57 (116.10–119.05)	Without IMT thickening	112.93 (111.03–114.83)
Serum glucose concentration after 2h in OGTT, mg/dl	with plaques	126.50 (124.16–128.85)	With ICA stenosis >50%	126.07 (113.90–138.25)	With IMT thickening	126.24 (123.86–128.62)
HbA1c %	without any plaques	5.24 (5.22–5.27)	Without stenosis	5.35 (5.33–5.37)	Without IMT thickening	5.24 (5.22–5.27)
HbA1c %	with plaques	5.52 (5.49–5.55)	With ICA stenosis >50%	5.90 (5.72–6.08)	With IMT thickening	5.51 (5.48–5.54)
Fasting insulin concentration, μU/ml	without any plaques	10.92 (10.47–11.37)	Without stenosis	11.77 (11.37–12.18)	Without IMT thickening	11.11 (10.61–11.61)
Fasting insulin concentration, μU/ml	with plaques	13.09 (12.38–13.81)	With ICA stenosis >50%	13.45 (10.07–16.83)	With IMT thickening	13.23 (12.46–14.00)
Serum insulin concentration after 1h in OGTT, μU/ml	without any plaques	75.74 (71.81–79.67)	Without stenosis	84.37 (80.58–88.17)	Without IMT thickening	75.38 (71.43–79.34)
Serum insulin concentration after 1h in OGTT, μU/ml	with plaques	97.97 (90.86–105.08)	With ICA stenosis >50%	126.66 (90.83–162.48)	With IMT thickening	97.22 (90.27–104.17)
Serum insulin concentration after 2h in OGTT, μU/ml	without any plaques	52.79 (49.74–55.83)	Without stenosis	61.75 (58.52–64.98)	Without IMT thickening	53.96 (50.31–57.61)
Serum insulin concentration after 2h in OGTT, μU/ml	with plaques	75.29 (68.94–81.63)	With ICA stenosis >50%	76.92 (47.47–106.37)	With IMT thickening	74.08 (67.56–80.61)
HOMA-IR	without any plaques	2.61 (2.49–2.73)	Without stenosis	2.89 (2.79–3.00)	Without IMT thickening	2.69 (2.55–2.82)
HOMA-IR	with plaques	3.33 (3.13–3.52)	With ICA stenosis >50%	3.52 (2.63–4.41)	With IMT thickening	3.38 (3.17–3.59)
QUICKI	without any plaques	0.34 (0.34–0.34)	Without stenosis	0.34 (0.33–0.34)	Without IMT thickening	0.34 (0.34–0.34)
QUICKI	with plaques	0.33 (0.33–0.33)	With ICA stenosis >50%	0.32 (0.31–0.34)	With IMT thickening	0.33 (0.33–0.33)
Matsuda Index	without any plaques	5.21 (4.98–5.44)	Without stenosis	4.71 (4.54–4.87)	Without IMT thickening	5.23 (5.00–5.46)
Matsuda Index	with plaques	3.94 (3.71–4.16)	With ICA stenosis >50%	3.11 (1.65–4.58)	With IMT thickening	3.96 (3.74–4.18)
Carotid-femoral PWV, m/s	without any plaques	8.13 (7.99–8.26)	Without stenosis	8.57 (8.44–8.69)	Without IMT thickening	8.14 (8.00–8.27)
Carotid-femoral PWV, m/s	with plaques	9.23 (9.00–9.45)	With ICA stenosis >50%	8.75 (6.87–10.62)	With IMT thickening	9.17 (8.95–9.39)
AIx	without any plaques	10.50 (9.78–11.21)	Without stenosis	14.60 (13.95–15.25)	Without IMT thickening	10.55 (9.83–11.28)
AIx	with plaques	20.77 (19.81–21.74)	With ICA stenosis >50%	22.85 (15.15–30.55)	With IMT thickening	20.35 (19.38–21.31)

Open in a new tab

Aix- augmentation index, PWV–pulse wave velocity, QUICKI -quantitative insulin sensitivity check index, HOMA-IR–homeostatic model assessment, HbA1c –glycated hemoglobin A1c, BMI–body mass index, WHR–waist to hip ratio, LDL-C–low density lipoprotein, ICA–internal carotid artery, IMT–intima media thickening.

We also performed multivariate logistic regression model where the dependent variable was the presence of any atherosclerotic plaques (Table 3). We built a model in which we included CVR categories (which already include classic cardiovascular risk factors, including gender and age), glucose metabolism and vascular stiffness parameters. Prediabetes was associated with significantly increased risk of preclinical atherosclerosis (OR = 1.56, 95% CI 1.09–2.24; p = 0.014), along with CVR categories, pulse wave velocity and central blood pressure augmentation index. Based on these results, we conclude that prediabetes was independently associated with preclinical atherosclerosis. This association remained significant after adjustment for confounders and the final findings were shown in Table 3.

Table 3. Regression models performed for the whole study population.

The dependent variable was the presence of atherosclerotic plaques. Well-known cardiovascular risk factors were replaced by cardiovascular risk categories.

	Full model				Reduced model
	OR	95% CI for OR		p	OR	95% CI for OR		p
Prediabetes	1.563	1.093	2.236	0.014	1.692	1.195	2.394	0.003
CV risk				<0.001				<0.001
CV risk 2 vs 1	5.903	3.917	8.896	<0.001	6.033	4.009	9.077	<0.001
CV risk 3 vs 1	16.408	7.941	33.903	<0.001	16.968	8.193	35.143	<0.001
Brachial-ankle PWV	1.184	1.069	1.312	0.001	1.192	1.075	1.320	0.001
AIx	1.060	1.043	1.078	<0.001	1.060	1.043	1.077	<0.001
Serum insulin level after 2h	1.003	1.000	1.006	0.074
Nagelkerke R²	0.51				0.50
Model specificity	88.89%				87.56%
Model sensitivity	69.34%				68.87%

Open in a new tab

CV–cardiovascular, PWV–pulse wave velocity, Aix- augmentation index, CI–Confidence interval, OR–odds ratio.

Discussion

Our findings indicate an association between prediabetes and preclinical atherosclerosis based on the presence of plaques in the carotid arteries, both in the general population and in the low-to-moderate CVR category. This is particularly important considering that up to 2/3 of all examined participants were categorized in this category. Patients with a low-to-moderate CVR may have an underestimated cardiovascular risk, due to impaired glucose metabolism, which is simply not considered in risk calculators. In a recent meta-analysis, researchers demonstrated that nondiabetic hyperglycaemia is associated with an increased risk of all-cause mortality and cardiovascular disease in the general population and in patients with atherosclerotic CVD [19]. A Norwegian population-based study showed that DM and prediabetic patients, compared to normoglycemic patients, had statistically significantly more often elevated CVD risk factors: higher BMI, higher waist circumference, lower HDL-C and higher CRP, besides being more likely to take lipid-lowering and blood pressure normalizing medications [20]. Our study also indicates significantly elevated ASCVD risk factors in patients with prediabetes compared to population without impaired glucose metabolism. Another meta-analysis found that people with prediabetes have a roughly 20% increased risk of CVD, regardless of its type (IFG vs IGT) [21]. Another large study revealed that both elevated fasting blood glucose and after 2h on the OGTT were associated with a higher risk of ASCVD, but with slightly higher relative effects of 2-hour glucose than fasting glucose [22]. Moreover, duration of prediabetes during adulthood is independently associated with subclinical atherosclerosis as shown in Coronary Artery Risk Development in Young Adults Study [23]. These data point out that early identification of patients with prediabetes and assessment of CVR factors may be important in early implementation of non- and pharmacological interventions and prevent the development of early atherosclerotic lesions. Recently published results indicated that prediabetes might be less related to subclinical atherosclerosis in older adults than in middle-aged adults, which further underlines the importance of our results [24]. In a prior research paper containing data from the Bialystok PLUS cohort, it was shown that FLAIS represents a useful index to assess the cluster of insulin resistance-associated cardiovascular risk factors in general population [25].

According to our findings, HbA1c appears to be a preferable biomarker of early atherosclerotic changes than glucose parameters. Previously, higher blood HbA1c levels were linked to an increased risk of preclinical atherosclerosis in those at low CVR, while there was no association in those at moderate risk [26]. A study using dynamic contrast-enhanced plaque imaging showed that leaky plaque neovascularization correlated with HbA1c levels and may be associated with faster progression of atherosclerosis in diabetic patients [27]. Moreover, elevating HbA1c is separately connected with the occurrence of high-risk plaque in non-diabetic individuals even if LDL-C was controlled by statin therapy [28]. Wang et al. showed that HbA1c level was an independent indicator of poor functional outcome in patients with acute anterior circulation ischemic stroke, especially with the large-artery atherosclerosis subtype [29]. The reported data, confirmed by our results, suggest that the inclusion of HbA1c in CVR calculators may prove clinically beneficial.

Our outcomes showed that both, early and more advanced atherosclerotic lesions, occur in non-diabetic hyperglycemic patients more often than in normoglycemic subjects. Moreover, a published literature review outlined that effective glycemic control, especially in earlier stages of DM, reduces the progression of subclinical atherosclerosis, which was assessed by the coronary artery calcification, carotid IMT and arterial stiffness [29, 30]. Other researchers have found that non-invasive early atherosclerotic parameters such as epicardial fat thickness and carotid IMT are increased in patients with prediabetes (especially with IGT) and could be useful indicators of ASCVD risk in this group [31, 32]. We also highlight the use of non-invasive measurements–carotid ultrasound or PWV–as parameters that may be particularly useful in early identification of patients with prediabetes and increased risk of symptomatic ASCVD in the future. Another cross-sectional study showed high carotid plaque presence and burden in new-onset T2DM subjects, especially in women [33] and indicates earlier preventive interventions in this group of patients.

Limited evidence comes from recent research about prevalence of moderate hyperglycemia. Referring to data from the International Diabetes Federation, an estimated 17% of the world’s population is diagnosed with non-diabetic hyperglycemia [4], which is less than half of what is presented in our study. Recently, another population-based study also indicated an alarming rise in prediabetes in the population—30.29% in the Hoveyzeh Cohort Study (n = 10,009), especially in overweight and obese patients [34, 35]. Our previously reported research revealed that more than half of the general population has impaired glucose metabolism (including 40% of prediabetes) [18]. An unusually high prevalence of prediabetes (approximately 5%) has been shown in a group of children between 6 and 10 years old, indicating the need for prevention even at a young age [36]. There was also a very high prevalence of prediabetes at 72.3% in patients with chronic coronary syndrome [37]. The moment of diagnosis of prediabetes provides a therapeutic window to incorporate early lifestyle or pharmacological interventions to prevent cardiovascular events.

There is a consensus that the cutoff identifying prediabetes using HbA1c is 5.7% [38, 39]. In our study, we used both OGTT and hemoglobin HbA1c to diagnose prediabetes–using HbA1c alone could underestimate the group with hyperglycemia. Another very large population-based study used only HbA1c to diagnose prediabetes and estimated a prevalence of 6.4%—less than our findings which might be due to the used method and particular, lower risk population [40]. We believe that an OGTT and HbA1c should be used to actively search for prediabetes in the general population. In addition, elevated HbA1c values may be an indicator of higher ASCVD risk in cardiovascular risk category 1 and may prompt further non-invasive diagnostics for subclinical atherosclerosis.

In the study, a single fasting glucose measurement was performed and therefore our population of patients with diabetes may be underestimated. In addition, some patients did not have the OGTT performed for technical reasons–inability to draw blood or vomiting reflex when consuming dissolved glucose. We used GFR to classify patients for cardiovascular risk. This is a cross-sectional analysis of the data and therefore causality cannot be inferred. Despite these limitations of our study, we believe that both the large sample and the thorough data analysis performed indicate the value of the publication. Our findings may have implications for the management of patients with preclinical conditions such as prediabetes and asymptomatic carotid atherosclerosis. Our study suggests that expansion of outpatient care in higher-risk patients who are not included in the risk calculators proposed in the recommendations. SCORE-2 does not include prediabetes and thus may underestimate the risk of preclinical atherosclerosis. Our results support this conclusion, as prediabetes significantly contributes to the risk of atherosclerosis when analyzed with CVR classes and provides additional pivotal information. Once prediabetes, especially IGT, is diagnosed, the GP should suggest lifestyle changes and increased physical activity and intensify follow-up visits to observe the development of preclinical atherosclerosis.

Conclusions

The study demonstrates the high prevalence of non-diabetic hyperglycemia in the general population, which is associated with the occurrence of preclinical atherosclerosis, especially in the low to moderate cardiovascular risk category. The more advanced preclinical atherosclerotic lesions are also significantly more common in the prediabetic population. Our study suggests that cardiovascular risk may be underestimated in people with prediabetes. The identification of this group in an apparently low-risk population may improve appropriate risk assessment and help implement early interventions to prevent cardiovascular incidents. Further studies on predictors of subclinical atherosclerosis in prediabetes are needed.

Supporting information

S1 Checklist. Human participants research checklist.

(DOCX)

pone.0309896.s001.docx^{(54.2KB, docx)}

S1 Fig. Receiver operating characteristic (ROC) curves; larger values of the test result variable indicate stronger evidence for a positive actual state.

Dependent variable: the presence of any atherosclerotic plaques on ultrasound of the carotid arteries.

(TIFF)

pone.0309896.s002.tiff^{(1.9MB, tiff)}

S1 Table. Receiver operating characteristic.

(TIFF)

pone.0309896.s003.tiff^{(2.4MB, tiff)}

S2 Table. Prevalence of prediabetes in the general population with cardiovascular risk categories and the presence of atherosclerotic plaques in the carotid arteries.

P-values were derived from Chi-square tests.

(TIFF)

pone.0309896.s004.tiff^{(1.8MB, tiff)}

S3 Table. Prevalence of prediabetes in the general population with cardiovascular risk categories and the presence of atherosclerotic plaques in the carotid arteries (included subpopulation IFG+IGT alone).

P-values were derived from Chi-square tests.

(TIFF)

pone.0309896.s005.tiff^{(3.2MB, tiff)}

S4 Table. The occurrence of a stenosis of more than 50% in the right or left internal carotid artery in the study population considering glucose metabolism disturbances.

(TIFF)

pone.0309896.s006.tiff^{(1.8MB, tiff)}

S5 Table. Assessment of preclinical atherosclerotic progression based on the level of stenosis of the right or left internal carotid artery (ICA).

P-values were derived from Chi-square tests.

(TIFF)

pone.0309896.s007.tiff^{(2MB, tiff)}

Abbreviations

IFG: impaired fasting glucose
IGT: impaired glucose tolerance
DM: diabetes mellitus
ASCVD: atherosclerotic cardiovascular disease
TC: total cholesterol
LDL-C: LDL-cholesterol
HDL-C: HDL-cholesterol
TG: triglycerides
HbA1c: glycated hemoglobin
WHO: World Health Organization
OGTT: Oral Glucose Tolerance Test
Cobas c111: Roche, reference enzymatic method with hexokinase
HPLC: ion-exchange high performance liquid chromatography
ECLIA: electrochemiluminescence
BMI: body mass index
WHR: Waist-to-hip ratio
BP: blood pressure
CCA: common carotid artery
ECA: external carotid artery
ICA: internal carotid artery
BIF: bifurcation
IMT: intima media thickness
PWV: pulse wave velocity
AIx: augmentation index
CP: central pressure
SCORE2: Systematic Coronary Risk Estimation 2
SCORE2-OP: Systematic Coronary Risk Estimation 2-Older Persons
CVD: cardiovascular disease
MI: myocardial infarction
IHD: ischemic heart disease
TIA: transient ischemic attack
PAD: peripheral arterial disease
CKD: chronic kidney disease
ESC: European Society of Cardiology
EAS: European Atherosclerosis Society
ACR: albumin-to-creatinine ratio
eGFR: estimated glomerular filtration rate
HOMA-IR: Homeostasis model assessment of insulin resistance
QUICKI: Quantitative insulin sensitivity check index
EASD: European Association for the Study of Diabetes
AUC: area under the curve
US: ultrasound
ACS: acute coronary syndrome
CI: Confidence interval

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

The project was supported by statutory funds of the Medical University of Bialystok (B.SUB.23.172). The manuscript contains data acquired during the project VAMP financed by the National Centre for Research and Development (POIR.04.01.04-00-0052/18) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1.Cosentino Francesco, Peter J Grant Victor Aboyans, Clifford J Bailey Antonio Ceriello, Delgado Victoria, et al. ESC Scientific Document Group, 2019. ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD: The Task Force for diabetes, pre-diabetes, and cardiovascular diseases of the European Society of Cardiology (ESC) and the European Association for the Study of Diabetes (EASD), European Heart Journal, Volume 41, Issue 2, 7 January 2020, Pages 255–323, 10.1093/eurheartj/ehz486 [DOI] [PubMed] [Google Scholar]
2.Richter B, Hemmingsen B, Metzendorf M-I, Takwoingi Y. Development of type 2 diabetes mellitus in people with intermediate hyperglycaemia. Cochrane Database Syst Rev. 2018. Oct 29;10:CD012661; doi: 10.1002/14651858.CD012661.pub2 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Kitabchi AE, Temprosa M, Knowler WC, Kahn SE, Fowler SE, Haffner SM, et al. Diabetes Prevention Program Research Group. Role of insulin secretion and sensitivity in the evolution of type 2 diabetes in the diabetes prevention program: effects of lifestyle intervention and metformin. Diabetes. 2005. Aug;54(8):2404–14. doi: 10.2337/diabetes.54.8.2404 ; PMCID: PMC1360738. [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. 2022 Jan;183:109119. doi: 10.1016/j.diabres.2021.109119 Epub 2021. Dec 6. . [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Heianza Y, Hara S, Arase Y, Saito K, Fujiwara K, Tsuji H, et al. HbA1c 5·7–6·4% and impaired fasting plasma glucose for diagnosis of prediabetes and risk of progression to diabetes in Japan (TOPICS 3): a longitudinal cohort study. Lancet. 2011. Jul 9;378(9786):147–55; doi: 10.1016/S0140-6736(11)60472-8 [DOI] [PubMed] [Google Scholar]
6.Tabák AG, Herder C, Rathmann W, Brunner EJ, Kivimäki M. Prediabetes: a high-risk state for diabetes development. Lancet. 2012. Jun 16;379(9833):2279–90; doi: 10.1016/S0140-6736(12)60283-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Huang Y, Cai X, Mai W, Li M, Hu Y. Association between prediabetes and risk of cardiovascular disease and all-cause mortality: systematic review and meta-analysis. BMJ. 2016. Nov 23;355:i5953; doi: 10.1136/bmj.i5953 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Yeboah J, Bertoni AG, Herrington DM, Post WS, Burke GL. Impaired fasting glucose and the risk of incident diabetes mellitus and cardiovascular events in an adult population: MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol. 2011. Jul 5;58(2):140–6. doi: 10.1016/j.jacc.2011.03.025 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Diabetes Prevention Program Research Group, Knowler WC, Fowler SE, Hamman RF, Christophi CA, Hoffman HJ, et al. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet. 2009. Nov 14;374(9702):1677–86; doi: 10.1016/S0140-6736(09)61457-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Visseren Frank L J et al. ESC Scientific Document Group, 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice: Developed by the Task Force for cardiovascular disease prevention in clinical practice with representatives of the European Society of Cardiology and 12 medical societies With the special contribution of the European Association of Preventive Cardiology (EAPC), European Heart Journal, Volume 42, Issue 34, 7 September 2021, Pages 3227–333734458905 [Google Scholar]
11.Chlabicz M, Jamiołkowski J, Łaguna W, Dubatówka M, Sowa P, Łapińska M, et al. Effectiveness of Lifestyle Modification vs. Therapeutic, Preventative Strategies for Reducing Cardiovascular Risk in Primary Prevention—A Cohort Study. Journal of Clinical Medicine. 2022; 11(3):688. doi: 10.3390/jcm11030688 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Touboul P.-J.; Hennerici M.; Meairs S.; Adams H.; Amarenco P.; Bornstein N.; et al. Mannheim Carotid Intima-Media Thickness Consensus (2004–2006). Cerebrovasc. Dis. 2006, 23, 75–80. [DOI] [PubMed] [Google Scholar]
13.Barnett H.J.M.; Taylor D.W.; Haynes R.B.; Sackett D.L.; Peerless S.J.; Ferguson G.G.; et al. Beneficial Effect of Carotid Endarterectomy in Symptomatic Patients with High-Grade Carotid Stenosis. N. Engl. J. Med. 1991, 325, 445–453. doi: 10.1056/NEJM199108153250701 [DOI] [PubMed] [Google Scholar]
14.Mach F., et al., 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J, 2020. 41(1): p. 111–188. doi: 10.1093/eurheartj/ehz455 [DOI] [PubMed] [Google Scholar]
15.Katz Arie, Nambi Sridhar S., Mather Kieren, Baron Alain D., Follmann Dean A., Sullivan Gail, et al. Quantitative Insulin Sensitivity Check Index: A Simple, Accurate Method for Assessing Insulin Sensitivity In Humans, The Journal of Clinical Endocrinology & Metabolism, Volume 85, Issue 7, 1 July 2000, Pages 2402–2410, doi: 10.1210/jcem.85.7.6661 [DOI] [PubMed] [Google Scholar]
16.Gayoso-Diz P., Otero-González A., Rodriguez-Alvarez M.X. et al. Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study. BMC Endocr Disord 13, 47 (2013). doi: 10.1186/1472-6823-13-47 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Matsuda M, DeFronzo RA: Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care 1999; 22: 1462–1470 doi: 10.2337/diacare.22.9.1462 [DOI] [PubMed] [Google Scholar]
18.Zieleniewska NA, Szum-Jakubowska A, Chlabicz M, Jamiołkowski J, Kowalska I, Kamiński KA. The prevalence of diabetes and prediabetes: a population-based study. Pol Arch Intern Med. 2023. Jan 5:16407. doi: 10.20452/pamw.16407 Epub ahead of print. . [DOI] [PubMed] [Google Scholar]
19.Cai X, Zhang Y, Li M, Wu JH, Mai L, Li J, et al. Association between prediabetes and risk of all cause mortality and cardiovascular disease: updated meta-analysis. BMJ. 2020. Jul 15;370:m2297. doi: 10.1136/bmj.m2297 ; PMCID: PMC7362233. [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Ford ES, Zhao G, Li C. Pre-diabetes and the risk for cardiovascular disease: a systematic review of the evidence. J Am Coll Cardiol. 2010;55:1310–7. This review and meta-analysis shows that both impaired fasting glucose and impaired glucose tolerance are asso- ciated with ∼20% increased risk of developing cardiovascular disease doi: 10.1016/j.jacc.2009.10.060 [DOI] [PubMed] [Google Scholar]
21.Kodama S, Saito K, Tanaka S, et al. Fasting and post-challenge glucose as quantitative cardiovascular risk factors: a meta-analysis. J Atheroscler Thromb. 2012; [Epub ahead of print]. This review and meta-analysis shows that both fasting and postload glucose is associated with cardiovascular disease, but the effect of postload glucose is larger than that of fasting glucose. doi: 10.5551/jat.10975 [DOI] [PubMed] [Google Scholar]
22.Reis Jared P., Allen Norrina B., Bancks Michael P., Carr J. Jeffrey, Lewis Cora E., Lima Joao A., et al. Duration of Diabetes and Prediabetes During Adulthood and Subclinical Atherosclerosis and Cardiac Dysfunction in Middle Age: The CARDIA Study. Diabetes Care 1 April 2018; 41 (4): 731–738. doi: 10.2337/dc17-2233 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Cao Q., Xin Z., He R. et al. Age-specific difference in the association between prediabetes and subclinical atherosclerosis: an analysis of a chinese prospective cohort study. Cardiovasc Diabetol 21, 153 (2022). doi: 10.1186/s12933-022-01592-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Antoniou S, Naka KK, Papadakis M, Bechlioulis A, Tsatsoulis A, Michalis LK, et al. Effect of glycemic control on markers of subclinical atherosclerosis in patients with type 2 diabetes mellitus: A review. World J Diabetes. 2021. Nov 15;12(11):1856–1874. doi: 10.4239/wjd.v12.i11.1856 ; PMCID: PMC8613661 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Karczewska-Kupczewska M, Nikołajuk A, Kondraciuk M, Stachurska Z, Dubatówka M, Szpakowicz A, et al. The relationships between FLAIS, a novel insulin sensitivity index, and cardiovascular risk factors in a population-based study. Cardiovasc Diabetol. 2022. Apr 19;21(1):55. doi: 10.1186/s12933-022-01491-y ; PMCID: PMC9020075. [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Altin C, Sade LE, Gezmis E, et al. Assessment of Subclinical Atherosclerosis by Carotid Intima–Media Thickness and Epicardial Adipose Tissue Thickness in Prediabetes. Angiology. 2016;67(10):961–969. doi: 10.1177/0003319716643669 [DOI] [PubMed] [Google Scholar]
27.Rossello X, Raposeiras-Roubin S, Oliva B, Sánchez-Cabo F, García-Ruíz JM, Caimari F, et al. Glycated Hemoglobin and Subclinical Atherosclerosis in People Without Diabetes. J Am Coll Cardiol. 2021. Jun 8;77(22):2777–2791. doi: 10.1016/j.jacc.2021.03.335 . [DOI] [PubMed] [Google Scholar]
28.Sun B, Ge X, Li X, Zhang J, Zhao Z, Liu X, et al. Elevated Hemoglobin A1c Is Associated With Leaky Plaque Neovasculature as Detected by Dynamic Contrast-Enhanced Magnetic Resonance Imaging. Arterioscler Thromb Vasc Biol. 2022 Apr;42(4):504–513. doi: 10.1161/ATVBAHA.121.317190 Epub 2022. Mar 3. . [DOI] [PubMed] [Google Scholar]
29.T Wang W., F Hsu P., J Wang Y., Z Ding Y., L Liou T., W Wang Y., et al. 5198HbA1C correlates subclinical atherosclerosis in non-diabetes, European Heart Journal, Volume 40, Issue Supplement_1, October 2019, ehz746.0057, 10.1093/eurheartj/ehz746.0057 [DOI] [Google Scholar]
30.Acar B., Ozeke O., Karakurt M., Ozen Y., Ozbay M.B., Unal S., et al. Association of Prediabetes With Higher Coronary Atherosclerotic Burden Among Patients With First Diagnosed Acute Coronary Syndrome. Angiology. 2019;70:174–180. doi: 10.1177/0003319718772420 [DOI] [PubMed] [Google Scholar]
31.Amano T., Matsubara T., Uetani T., Nanki M., Marui N., Kato M., et al. Abnormal glucose regulation is associated with lipid-rich coronary plaque: Relationship to insulin resistance. JACC Cardiovasc Imaging. 2008;1:39–45. doi: 10.1016/j.jcmg.2007.09.003 [DOI] [PubMed] [Google Scholar]
32.Dong N, Shen X, Wu X, Guo X, Fang Q. Elevated Glycated Hemoglobin Levels Are Associated With Poor Outcome in Acute Ischemic Stroke. Front Aging Neurosci. 2022. Feb 3;13:821336. doi: 10.3389/fnagi.2021.821336 ; PMCID: PMC8851318. [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Catalan M, Herreras Z, Pinyol M, Sala-Vila A, Amor AJ, de Groot E, et al. Prevalence by sex of preclinical carotid atherosclerosis in newly diagnosed type 2 diabetes. Nutr Metab Cardiovasc Dis. 2015. Aug;25(8):742–8. doi: 10.1016/j.numecd.2015.04.009 Epub 2015 May 7. . [DOI] [PubMed] [Google Scholar]
34.Ferrannini E., Gastaldelli A., Iozzo P. Pathophysiology of prediabetes. Med. Clin. N. Am. 2011;95:327–339. doi: 10.1016/j.mcna.2010.11.005 [DOI] [PubMed] [Google Scholar]
35.Hashemi S.J., Karandish M., Cheraghian B. et al. Prevalence of prediabetes and associated factors in southwest iran: results from Hoveyzeh cohort study. BMC Endocr Disord 22, 72 (2022). doi: 10.1186/s12902-022-00990-z [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Breyer MK, Ofenheimer A, Altziebler J, Hartl S, Burghuber OC, Studnicka M, et al. Marked differences in prediabetes- and diabetes-associated comorbidities between men and women-Epidemiological results from a general population-based cohort aged 6–80 years-The LEAD (Lung, hEart, sociAl, boDy) study. Eur J Clin Invest. 2020. Mar;50(3):e13207. doi: 10.1111/eci.13207 Epub 2020 Feb 12. . [DOI] [PubMed] [Google Scholar]
37.Drobek N, Sowa P, Jankowski P, Haberka M, Gąsior Z, Kosior D, et al. Undiagnosed Diabetes and Prediabetes in Patients with Chronic Coronary Syndromes-An Alarming Public Health Issue. J Clin Med. 2021. May 5;10(9):1981. doi: 10.3390/jcm10091981 ; PMCID: PMC8124594. [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Kato M, Noda M, Suga H, Nakamura T, Matsumoto M, Kanazawa Y, et al. Haemoglobin A1c cut-off point to identify a high risk group of future diabetes: results from the Omiya MA Cohort Study. Diabet Med. 2012. Jul;29(7):905–10. doi: 10.1111/j.1464-5491.2012.03572.x ; PMCID: PMC3504345. [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Heianza Y, Arase Y, Fujihara K, Tsuji H, Saito K, Hsieh SD, et al. Screening for pre-diabetes to predict future diabetes using various cut-off points for HbA(1c) and impaired fasting glucose: the Toranomon Hospital Health Management Center Study 4 (TOPICS 4). Diabet Med. 2012. Sep;29(9):e279–85. doi: 10.1111/j.1464-5491.2012.03686.x . [DOI] [PubMed] [Google Scholar]
40.Bjarkø VV, Haug EB, Sørgjerd EP, Stene LC, Ruiz PL, Birkeland KI, et al. Undiagnosed diabetes: Prevalence and cardiovascular risk profile in a population-based study of 52,856 individuals. The HUNT Study, Norway. Diabet Med. 2022. Jun;39(6):e14829. doi: 10.1111/dme.14829 Epub 2022 Mar 21. ; PMCID: PMC9310609. [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0309896.r001

Decision Letter 0

Andreas Beyerlein

16 Feb 2024

PONE-D-23-42492The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population.PLOS ONE

Dear Dr. Kaminski,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

Comments from PLOS Editorial Office:

We apologize for the difficulties you were having with your submission. For your convenience, we have summarized the points previously raised by the academic editor below:

- Accept all changes and cancel tracking mode

- Use a uniform font and font size throughout the manuscript including references, tables and figure legends

- Mention all tables (including the supplementary ones) in the main text and sort them according to their order of appearance in the text

- Move the study limitations into the Discussion

- Put the Declarations part on a separate page and arrange it more clearly

- Rearrange the figures and tables so that they are readable: In particular, the authors should put each item on a separate page and format it in a way so that it does not exceed this page.

- Use no colours in the tables

- Use "." as decimal separators in all tables

==============================

Please submit your revised manuscript by Apr 01 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Andreas Beyerlein

Academic Editor

PLOS ONE

Additional Editor Comments:

Please revise the files as discussed.

[Note: HTML markup is below. Please do not edit.]

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2024 Oct 29;19(10):e0309896. doi: 10.1371/journal.pone.0309896.r002

Author response to Decision Letter 0

19 Feb 2024

17th February 2024

Dear Editor

We would like to thank you for your helpful comments on the manuscript The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population. We have edited the manuscript to address all the concerns. All the changes we have made are marked in red.

We hope that after corrections suggested by the Editorial Office, the manuscript is now suitable for publication in the PLOS ONE.

We are looking forward to hearing from you soon.

Yours sincerely

Karol Kamiński

On behalf of all authors.

Comments from PLOS Editorial Office:

We apologize for the difficulties you were having with your submission. For your convenience, we have summarized the points previously raised by the academic editor below:

- Accept all changes and cancel tracking mode.

The changes have been accepted. Tracking mode has been canceled.

- Use a uniform font and font size throughout the manuscript including references, tables and figure legends.

The font has been standardized to Times New Roman, font size 12.

- Mention all tables (including the supplementary ones) in the main text and sort them according to their order of appearance in the text

Tables and figures are mentioned in the main text of the manuscript.

- Move the study limitations into the Discussion

Study limitations have been moved to the last paragraph of the Discussion.

- Put the Declarations part on a separate page and arrange it more clearly

The declarations were placed on page 2 of the manuscript and prepared in accordance with the journal's recommendations.

- Rearrange the figures and tables so that they are readable: In particular, the authors should put each item on a separate page and format it in a way so that it does not exceed this page.

The figures were prepared in accordance with these rules. The tables have been reformatted according to this recommendation, but Tables 1 and 3 contains too much information to fit on one page.

- Use no colours in the tables

Well, it has been corrected.

- Use "." as decimal separators in all tables

Commas have been changed to dots.

Attachment

Submitted filename: Response to Reviewers.docx

pone.0309896.s008.docx^{(20.4KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0309896.r003

Decision Letter 1

Andreas Beyerlein

8 May 2024

PONE-D-23-42492R1The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population.PLOS ONE

Dear Dr. Kaminski,

Please submit your revised manuscript by Jun 22 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Andreas Beyerlein

Academic Editor

PLOS ONE

Additional Editor Comments:

General:

- The authors should make sure that their manuscript follows the STROBE guidelines.

- Both the title and the abstract sholud mention the cross-sectional study design.

- At some occasions, the results are presented in present tense. Instead, all results should be described in past tense.

- The authors present a bunch of similar analyses on the same dataset, leading to issues of multiple testing. Preferably, only those results which are directly related to the main hypothesis should be shown, while several side analyses might just be left out. I added some suggestions below. Additionally, p-values and interpretations of statistical significance should be presented only for the most relevant associations.

- In the spirit of Open and Reproducible Science, the analysis code should be made available in an online repository together with a data dictionary, and the respective URL should be mentioned in the Methods section.

Abstract:

- The abstract should mention setting, locations, periods of recruitment, duration of follow-up, and age of the participants.

- The sentence "In multivariate logistic regression, prediabetes significantly increased risk for preclinical atherosclerosis (p=0.015)." should be rephrased to "...was associated with significantly increased risk...", and OR with 95% CI should be shown instead of a p-value.

- It seems not correct to state that the analysis included 1866 participants given that a large proportion of them were excluded due to technical reasons or prevalent DM, and it also does not fit to the statement ..."more than half of the study participants (n=797, 51.9%)"

Introduction:

- "...and 319 million adults (6.2%) with IFG" should be rephrased as "... to have IFG".

- When introduced, abbreviations should be used throughout the manuscript, which is e.g. not the case in the sentence "First, the presence of nondiabetic hyperglycemia signifies an increased risk of developing type 2 diabetes..."

- The study hypothesis is not properly motivated. For example, the authors state that prediabetes is associated with a higher risk of cardiovascular disease. So would it not just be expected that it is also associated with a higher risk of preclinical atherosclerosis? Are there already any other studies on this topic?

Methods:

- In the sentence "We randomly sampled citizens in such numbers as to obtain a distribution of proportions in terms of age and gender similar to that of the city's population.", what is meant by "in such numbers"? Please add that this sentence only pertains to the age range mentioned before.

- What is meant by "research tests"?

- In the Matsuda formula, a bracket seems to be missing. Can the abbreviations I0 and G0 also be used in the HOMA-IR and Matsuda formulas?

- "... for checking variable normality." should be revised to "... for checking whether the variables followed a normal distribution."

- Supplementary Tables 1 and 2 seem superfluous, as these definitions can easily be mentioned in the main text in the methods section.

Results:

- Please add a descriptive table 1 to characterize the whole study population (excluding the participants excluded).

- Supplementary Figure 2 seems superfluous, the more so as it is not mentioned in the main text.

- The current tables 1 and 3 are heavily overloaded and need to be condensed or split into two separate tables each (e.g. with and without prediabetes markers). The p-values should be removed, as they are sensitive to sample size and prone to multiple testing. Instead, I would suggest to show mean and 95% confidence intervals instead of median and IQR (see also the comments of Reviewer 1 concerning this).

- The sentence "We used the diagnostic criteria for DM and prediabetes..." seems out of place in the results section.

- The numbers in Suppl. Figure 1 do not add up to 1866. The authors should show a proper flowchart as requested in the STROBE guidelines (which would not include the numbers of participants with or without prediabetes).

- Did the persons excluded due to technical reasons differ from the remaining population with respect to age, sex or other characteristics? If so, potential bias by exclusion of these participants needs to be discussed.

- "The population of attendees without dysglycemia consisted of 634 patients (41.2%). Importantly, the population with prediabetes accounted for more than half of the study participants (n=797, 51.85%)." Why do these two numbers not add up to 100%? As a minor point, percentages should presented with the same number of digits throughout the whole manuscript (main text and tables).

- "Importantly, the population without glucose metabolism disturbances": Leave out "Importantly" (there should be no interpretation in the results section)

- What is meant by "a statistically relevant difference"?

- All supplementary tables should be named by the order of their appearance in the main text.

- The abbreviation USG should be explained in the main text and each figure / table where it appears.

- The legends of Figure 1 and Supplementary Table 5 should not be selective in mentioning the AUC values of the predictors, i.e. show all or none of them.

- "most statistically significant indicators" is wrong wording. A result can either be statistically significant or not.

- Why does Supplementary Table 5 not include glucose level after 1 h, and why is the AUC of HbA1c different in the table to the AUC mentioned in the main text?

- Table 2 is difficult to read and might rather be replaced by e.g. stacked barplots.

- It is confusing that some tables are arranged with CVR as columns and glucose metabolism and rows and vice versa. The appearance of these tables should be unified.

- Supplementary Tables 4 and 12: The p** values should be removed.

- The logistic regression analyses are confusing and contradictory in their results, which is particularly irritating given that there seem to be quite strong associations between prediabetes and preclinical atherosclerosis in bivariate analyses. The results from Supplementary Table 8 seem to be based on the most reasonable approach (while the other regression analyses seem superfluous), but they indicate a ngeative association between the two factors. Can the authors please comment on this issue?

Discussion:

- The discussion may need to be revised in accordance with the revision of the logistic regression analyses.

- The authors applied a large number of tests, but did not correct for multiple testing. This should be clearly stated in the discussion together with the consequence that their results should be seen as hypothesis-generating and need confirmation from other studies.

- "This study confirms a very high prevalence of prediabetes in a general population." The statements in this paragraph and also in the conclusion are too general and need to be more specific to the underlying population. Further, the authors might discuss how generalizable their results are with respect to other populations in Europe and across the world.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: (No Response)

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: I Don't Know

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This manucript examines the impact of prediabetes on preclinical atherosclerosis in general apparently healthy

population in Poland.

The paper is well written and organised.

Please find my comments below:

- Statistical analysis section: It is stated that continuous variables are described using medians (IQR). However, in Table 1, it seems that some variables (i.e. Age) are described using mean +/- sd. This should be clarified in the statistical analysis section as well as the results for this.

- Statistical analysis section: Shapiro-Wilks test is sensitive to large sample sizes and the null hypothesis can be rejected even with small deviations from normality. Kolmogorov-Smirnov is a better option when sample size is >50. However, here the sample size is quite large so the central limit theorem holds. The authors could have proceeded with using only parametric tests.

- Fig.2: SPSS 27 does not produce forest plots. The authors should state clearly the software used for the data analysis and visualisation.

- Any p-values=0.000 should be changed to <0.001.

Reviewer #2: The manuscript entitled "The impact of prediabetes on preclinical atherosclerosis in an apparently healthy general population" addresses a highly interesting and significant clinical issue. Early identification of individuals with dysglycemia is essential for the effective implementation of cardiovascular and metabolic prevention measures. Considering the authors' understanding of the research problem, the reviewer requests a discussion on the practical application of the obtained results - whether this data is sufficient for updating/altering recommendations, particularly for General Practitioners, and what those changes should involve?

Reviewer #3: The paper PONE-D-23-42492R1 » The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population« describes the relation of prediabetes (diagnosed by fasting glucose levels or by oral glucose tolerance test) and the presence of carotid artery plaques in a random sample of 1866 subjects from the Bialystok PLUS study. Prediabetes significantly increased risk for preclinical carotid atherosclerosis according to a multivariate logistic regression model.

I have the following comments:

Materials and methods, Assessment of insulin sensitivity. Please, list thel criteria for diagnosing prediabetes.

Typographical corrections:

Abstract, line 9: Atherosclerotic plaques in the carotid arteries were …

Fig. 1. The x-axis should be labeled »1-specificity«.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

**********

PLoS One. 2024 Oct 29;19(10):e0309896. doi: 10.1371/journal.pone.0309896.r004

Author response to Decision Letter 1

18 Jun 2024

General:

- The authors should make sure that their manuscript follows the STROBE guidelines.

Thank you for suggestion. We have corrected the manuscript accordingly and clearly stated this in the manuscript. We have created a revised Flowchart (Figure 1 Supplementary Material). We have described the population study method in detail. Moreover, our data has been recalculated and completed, due to numerous statistical comments.

- Both the title and the abstract should mention the cross-sectional study design.

I added in the title: The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population: a cross-sectional study.

I added also in Abstract, Methods: The cross-sectional analysis included 1431 participants of a population-based cohort study. Comprehensive biochemical assessments were performed.

- At some occasions, the results are presented in present tense. Instead, all results should be described in past tense.

I have changed the tense as suggested.

Thank you for your comment. We have made the corrections as suggested below.

We did not used pre-programmed scripts. We have done ad hoc analysis in the SPSS.

Abstract:

- The abstract should mention setting, locations, periods of recruitment, duration of follow-up, and age of the participants.

The following sentence has been added:

The analysis was a part of the Bialystok PLUS cohort study and represented a random sample of Bialystok residents aged 20-79 at the time of sampling (July 2017-January 2023).

Thank you, it has been corrected.

In multivariate logistic regression, prediabetes was independently associated with significantly increased risk of preclinical atherosclerosis (OR= 1.56, 95% CI 1.09-2.24), along with CVR categories, pulse wave velocity and central blood pressure augmentation index.

In accordance with the Editor's comments, we have included the correct flowchart of study population (Figure 1 Supplementary Materials) and changed the number given as size of the population to 1431.

The cross-sectional analysis included 1431 participants of a population-based study (mean age 48.82).

Introduction:

- "...and 319 million adults (6.2%) with IFG" should be rephrased as "... to have IFG"

Both corrections have been applied.

Indeed, the introduction was too brief. An additional paragraph has been added to further motivate the research hypothesis. It should be emphasized that there are quite strong controversies about the effect of prediabetes on atherosclerosis and hence cardiovascular risk. Currently European Society of Cardiology guidelines do not incorporate prediabetes in their cardiovascular risk calculators, mainly due to limited evidence from general population. Therefore the evidence our study provides contributes to this scientific discussion.

A previously conducted study of patients with first-time acute coronary syndrome (ACS) who underwent urgent coronary angiography showed that coronary atherosclerosis is more advanced in patients with prediabetes than in patients without DM [38]. Furthermore, the association of the occurrence of coronary atherosclerosis was shown to be comparable between patients with prediabetes and patients with DM at the time of first ACS [38]. Another study using percutaneous coronary intervention showed that coronary lesions in prediabetic patients were associated with higher levels of lipid-rich atherosclerotic plaques [39]. Prediabetes is associated with inflammation and vasoconstriction, which promote atherosclerosis in the coronary arteries [40]. Notably, limited evidence comes from research on both, prediabetes and carotid atherosclerosis in general population.

Methods:

The text has been transformed for better understanding.

Our analysis was a part of the Bialystok PLUS cohort study and represented a random sample of Bialystok residents aged 20-79 at the time of sampling (July 2017-January 2023). Bialystok is a medium-sized city located in eastern Poland with a population of 293,400. The recruitment of participants for the population-based study uses a pseudonymized list of residents of Bialystok obtained from the Local Municipal Office. Annually, we randomly sampled citizens to obtain a distribution of proportions in terms of age and gender reflecting that of the city's population. A more detailed study design was described in previously published paper [11].

- What is meant by "research tests"?

We meant all the tests performed in the course of the study, as they were performed solely for the purpose of the study. For greater clarity, we have changed the research test to “the clinical and biochemical measurements”.

All the clinical and biochemical measurements were conducted by qualified medical personnel.

- In the Matsuda formula, a bracket seems to be missing. Can the abbreviations I0 and G0 also be used in the HOMA-IR and Matsuda formulas?

Thank you for helpful suggestions. Corrections have been made in accordance with it.

Quantitative insulin sensitivity check index (QUICKI) was defined as 1/[log(I0) + log(G0)], where I0 is the fasting insulin (μU/ml), and G0 is the fasting glucose (mmol/l) [16]. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated using the formula: I0 × G0 /22.5 [15]. When assessing insulin sensitivity, we used the Matsuda index calculated from the formula 10000/ √ (G0 mg/dl x I0 μU/ml) x (Mean OGTT glucose concentration mg/dl × mean OGTT insulin concentration mg/dl) [17].

- "... for checking variable normality." should be revised to "... for checking whether the variables followed a normal distribution."

Done.

- Supplementary Tables 1 and 2 seem superfluous, as these definitions can easily be mentioned in the main text in the methods section.

The tables have been removed. A description has been added in Methods, Assessment of Insulin sensitivity.

Results:

- Please add a descriptive table 1 to characterize the whole study population (excluding the participants excluded).

A description of the whole study population has been added to Table 1, in the last column ‘Total’.

- Supplementary Figure 2 seems superfluous, the more so as it is not mentioned in the main text.

Indeed, according to this Supplementary Figure 2 has been deleted.

In accordance with this comment and the suggestions of Reviewer 1, all tables have been revised.

- The sentence "We used the diagnostic criteria for DM and prediabetes..." seems out of place in the results section.

It has been moved to Methods section.

Figure 1 Supplementary Material has been modified.

Variable Excluded population for technical reasons n=183

Mean, 95% CI Study population

n=1431

Mean, 95% CI Total

n=1866

Mean, 95% CI

Age 49.67 (47.49-51.85) 46.82 (46.05-47.59) 47.14 (46.41-47.87)

BMI 27.29 (26.24-28.33) 26.30 (26.06-26.54) 26.39 (26.15-26.62)

WHR 0.85 (0.84-0.87) 0.86 (0.85-0.86) 0.86 (0.85-0.86)

SBP 118.08 (115.10-121.06) 122.18 (121.31-123.04) 121.85 (121.02-122.68)

DBP 79.56 (77.73-81.39) 80.48 (79.96-80.99) 80.40 (79.91-80.90)

Total cholesterol 196.56 (188.78-204.33) 193.63 (191.59-195.67) 193.86 (191.89-195.84)

LDL-C 124.30 (117.27-131.32) 123.86 (122.00-125.72) 123.89 (122.09-125.69)

Fasting glucose 97.38 (95.55-99.21) 97.87 (97.38-98.36) 97.83 (97.35-98.30)

HbA1c 5.42 (5.35-5.49) 5.36 (5.34-5.38) 5.36 (5.34-5.38)

Sex, %male 29.0% (22.9%-35.9%) 44.9% (42.4%-47.5%) 43.1% (40.7%-45.6%)

The presence of atherosclerotic plaque 43.0% (34.7%-51.6%) 40.7% (38.2%-43.2%) 40.9% (38.4%-43.3%)

Cholesterol-lowering treatment 75.6% (65.8%-83.3%) 78.7% (75.4%-81.7%) 78.3% (75.2%-81.2%)

In the table we have included a comparison between those excluded for technical reasons (n=183) and the analysed population (n=1431). The values of the parameters we were able to compare are not considerably different from each other. We believe that, despite the statistical difference, the compared populations do not differ clinically.

Percentages have been rounded to 1 decimal places in the texts. Previously, the percentages were counted to the whole group (including those who were excluded). For a better understanding of the analysis, changes have been made.

In further analysis, we considered 1431 participants. The population of attendees without dysglycemia consisted of 634 patients (44.3%). The population with prediabetes accounted for more than half of the study participants (n=797, 55.7%).

- "Importantly, the population without glucose metabolism disturbances": Leave out "Importantly" (there should be no interpretation in the results section)

Thank you.

- What is meant by "a statistically relevant difference"?

We have changed to “statistically significant difference”.

- All supplementary tables should be named by the order of their appearance in the main text.

Done.

- The abbreviation USG should be explained in the main text and each figure / table where it appears.

Done.

- The legends of Figure 1 and Supplementary Table 5 should not be selective in mentioning the AUC values of the predictors, i.e. show all or none of them.

OK, the AUC values have been removed from the legends.

- "most statistically significant indicators" is wrong wording. A result can either be statistically significant or not.

Indeed. This has been corrected.

We observed that all examined parameters proved to be statistically significant indicators of the presence of atherosclerotic plaques in carotid ultrasound, also upon application of Bonferroni correction. However, the highest AUC values were obtained for serum glucose concentration after 1h and HbA1c (AUC=0.73; 95% CI 0.70-0.76 for glucose level after 1 h and AUC=0.72; 95% CI 0.69-0.75 for HbA1c).

- Why does Supplementary Table 5 not include glucose level after 1 h, and why is the AUC of HbA1c different in the table to the AUC mentioned in the main text?

Many thanks for your thorough review of the manuscript. Table 5 Supplementary Materials has been corrected. The values entered in the Manuscript were correct. This was a mistake in transferring data from a statistical programme to a word document.

- Table 2 is difficult to read and might rather be replaced by e.g. stacked barplots.

Table 2 has been transformed into stacked barplots.

- It is confusing that some tables are arranged with CVR as columns and glucose metabolism and rows and vice versa. The appearance of these tables should be unified.

We wanted to emphasise what exactly is being compared in the tables by using this approach. These are additional analyses and have therefore been placed in Supplementary Materials.

- Supplementary Tables 4 and 12: The p** values should be removed.

Done.

- The logistic regression analyses are confusing and contradictory in their results, which is particularly irritating given that there seem to be quite strong associations between prediabetes and preclinical atherosclerosis in bivariate analyses. The results from Supplementary Table 8 seem to be based on the most reasonable approach (while the other regression analyses seem superfluous), but they indicate a negative association between the two factors. Can the authors please comment on this issue?

To sum up, bivariate analyses suggest that there are positive associations between prediabetes and preclinical atherosclerosis. In the multivariate analyses, we used two separate approaches. In the first multivariate model, we included individual classical CVR factors (age, sex, SBP, total cholesterol, LDL-C, cigarette smoking, BMI) as co-variates. In this model, we did not show a statistically significant association between prediabetes and the occurrence of atherosclerotic plaques, which may be due to strong association of prediabetes with other risk factors (age, blood pressure, BMI) and the fact that they may have a strong association with preclinical plaques. In the second approach, we used a cardiovascular risk scale considering the cardiovascular risk factors in a synthetic way proposed by the European Society of Cardiology. In this model, we present an independent positive relationship (Table 10, Supplementary Materials) between prediabetes and the presence of preclinical carotid artery lesions (95% CI 1.091-2.232, OR 1.561), which emphasizes potential value of including prediabetes in cardiovascular risk assessment. Model 2 informs us that the prediabetes in addition to CVR categories is associated with a higher risk of preclinical atherosclerosis, which may be relevant for physicians in clinical practice.

Discussion:

Thank you for this comment. In our case, we tested the hypothesis whether prediabetes increases the risk of preclinical atherosclerosis. Additional analyses were hypothesis generating and assessed the mechanism of this association. A Bonferroni cor

Attachment

Submitted filename: Response to Reviewers.docx

pone.0309896.s009.docx^{(35.1KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0309896.r005

Decision Letter 2

Andreas Beyerlein

10 Jul 2024

PONE-D-23-42492R2The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population: a cross-sectional studyPLOS ONE

Dear Dr. Kaminski,

Please submit your revised manuscript by Aug 24 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Andreas Beyerlein

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

The authors have improved their manuscript considerably. Only a few points remain to be addressed:

General:

- There are still some results described in present tense, e.g. those under "Atherosclerotic plaque presence in particular cardiovascular risk categories". The whole manuscript should be checked and revised again regarding this issue.

- Throughout the whole manuscript (including tables and figures), only black font should be used.

- Please re-check and confirm that all numbers mentioned in the main text fit to the numbers presented in the tables and figures.

Abstract:

- Please add "years" after 20-79 and 48.82 (also in the main text), and mention that Bialystok is a city from Poland.

- Please omit "the" in "proved to be the statistically significant indicators".

Results:

- Figure 1 should be moved from the main document to the Supplement, and vice versa for Supplementary Figure 1 (flowchart).

- Suggest to show vertical bars in Figure 2 and to remove the yellow bars (sorry, my previous comment hinting to a "stacked barplot" was somewhat misleading).

- Suggest to move the "Total column" in Table 1 to the very left.

- Supplementary Table 1 seems superfluous, as these numbers might just be described in the main text.

- "Additionally, 166 patients were excluded from further analysis for technical reasons...". This number cannot be found in the flowchart. Please explain.

- Suggest to revise "In further analysis we considered 1431 participants." by e.g. "After applying these exclusion criteria, the data of 1431 participants remained for analysis."

- It makes no sense to present the Supplementary Tables 5 and 6 as they are likely to be prone to collinearity issues as mentioned in the text. Instead, the choice (and exclusion) of the predictors in Supplementary Table 7 should be properly motivated and described in detail, possibly accompanied by a stepwise variable selection process. The predictor prediabetes should be shown at the top of this table. Why were sex and age not included here?

- Finally, it would seem more appropriate to move Supplementary Table 7 to the main results and to remove Figure 3 instead.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: I Don't Know

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: (No Response)

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #1: The authors have replied to my comments adequately. I only have one minor comment. Please indicate the dependent variable in the captions of Tables 5 and 6.

Reviewer #2: (No Response)

Reviewer #3: The manuscript is now substantially improved. The reviewers' comments have been adequately addressed.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

**********

PLoS One. 2024 Oct 29;19(10):e0309896. doi: 10.1371/journal.pone.0309896.r006

Author response to Decision Letter 2

16 Jul 2024

Dear Editor

We would like to thank you for your comments on the manuscript The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population: a cross-sectional study. We have edited the manuscript to address all the concerns. All the changes we have made are marked in red.

We hope that after corrections suggested by the reviewer, the manuscript is now suitable for publication in the PLOS One Journal.

We are looking forward to hearing from you soon.

On behalf of all authors.

Yours sincerely

Karol Kamiński

Journal Requirements:

The list has been checked. All references are correct and have not been changed or retracted.

Additional Editor Comments:

The authors have improved their manuscript considerably. Only a few points remain to be addressed:

General:

Indeed, the tense used has been corrected.

- Throughout the whole manuscript (including tables and figures), only black font should be used.

Done.

- Please re-check and confirm that all numbers mentioned in the main text fit to the numbers presented in the tables and figures.

Done.

Abstract:

- Please add "years" after 20-79 and 48.82 (also in the main text), and mention that Bialystok is a city from Poland.

Done.

- Please omit "the" in "proved to be the statistically significant indicators".

Thank you, corrected.

Results:

- Figure 1 should be moved from the main document to the Supplement, and vice versa for Supplementary Figure 1 (flowchart).

Done.

- Suggest to show vertical bars in Figure 2 and to remove the yellow bars (sorry, my previous comment hinting to a "stacked barplot" was somewhat misleading).

Done.

- Suggest to move the "Total column" in Table 1 to the very left.

Done.

- "Additionally, 166 patients were excluded from further analysis for technical reasons...". This number cannot be found in the flowchart. Please explain.

Thank you, it was a typing mistake. Everything now corresponds with Flowchart.

The study enrolled 1866 participants. According to STROBE guidelines, the flowchart represents the study population (Figure 1 Supplementary Materials). Prevalent diabetes (n=252, 13.5%) was diagnosed on the basis of medical history (n=140) and glucose levels after 2h OGGT (n=112). All prevalent diabetic patients were excluded from further analysis. Additionally, 183 patients were excluded from further analysis for technical reasons – inability to draw blood, perform an OGTT or US of the carotid arteries [31]. After applying these exclusion criteria, the data of 1431 participants remained for analysis.

- Suggest to revise "In further analysis we considered 1431 participants." by e.g. "After applying these exclusion criteria, the data of 1431 participants remained for analysis."

Ok.

That's fine, in that case we deleted Table 5 and Table 6 Supplementary Materials. Gender and age were not included because they are already included in the cardiovascular risk categories. We used SCORE calculators to calculate CVR categories, which take gender and age into account. We decided to exclude these variables to avoid potential multicollinearity problem in regression model. We have changed the description in the main text.

We also performed multivariate logistic regression model where the dependent variable was the presence of any atherosclerotic plaques (Table 3). We built a model in which we included CVR categories (which already include classic cardiovascular risk factors, including gender and age), glucose metabolism and vascular stiffness parameters. Figure 2 Supplementary Materials is a graphical summary of the fully adjusted logistic regression model. Prediabetes was associated with significantly increased risk of preclinical atherosclerosis (OR= 1.56, 95% CI 1.09-2.24; p=0.014), along with CVR categories, pulse wave velocity and central blood pressure augmentation index.

- Finally, it would seem more appropriate to move Supplementary Table 7 to the main results and to remove Figure 3 instead.

Done.

Reviewer #1: The authors have replied to my comments adequately. I only have one minor comment. Please indicate the dependent variable in the captions of Tables 5 and 6.

Thank you. According to the editor's comments, these tables have been deleted from the supplement. We added caption in Table 3 of the main text considering the dependent variable.

Reviewer #3: The manuscript is now substantially improved. The reviewers' comments have been adequately addressed.

Thank you.

Attachment

Submitted filename: Response to Reviewers.docx

pone.0309896.s010.docx^{(21.2KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0309896.r007

Decision Letter 3

Andreas Beyerlein

19 Jul 2024

PONE-D-23-42492R3The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population: a cross-sectional studyPLOS ONE

Dear Dr. Kaminski,

Please submit your revised manuscript by Sep 02 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Andreas Beyerlein

Academic Editor

PLOS ONE

Journal Requirements:

Additional Editor Comments:

The manuscript is now almost ready for journal acceptance. Please accept all changes made so far so that only changes required for this (hopefully last) revision are clearly visible. The following points remain to be addressed:

- Unit "years" is still lacking behind "20-79" in the Abstract, in the Results and in Figure 1.

- Any results which are mentioned in the Abstract should also be mentioned in the main text (e.g. mean age).

- The interpretation that prediabetes was independently associated with preclinical atherosclerosis is very important for the main message of this paper and should therefore also be mentioned in the results section and explained how this conclusion was arrived at (i.e. that this association remained significant after adjustment for confounders). I would also suggest to move prediabetes above CV risk in table 3 to make this result more visible. It might also be worth to mention in the text how the OR of preclinical atherosclerosis by prediabetes would look like without adjustment for the confounders mentioned in table 3.

- It would be helpful to mention all the numbers from the flowchart also in the main text to explain to the Reader how the number of 183 patients who were excluded from further analysis for technical reasons was achieved.

- Figure 1: "n=7 subjects were exclused" should read "excluded", and "USG" be replaced by "US".

- Please mention which version of R was used.

- In all tables including the supplement, "C.I." should be replaced by "CI" for reasons of consistency.

- In table 3, the p-values should be mentioned to the right of the 95% CIs.

Further, as the supplementary figures and tables will probably not be quality-checked after acceptance, it is important that they fulfil the necessary standards right now. Please see specific comments below:

- Please add "Supplementary" before each figure and table.

- The supplementary tables should be ordered in the way they are mentioned in the text (i.e. supplementary table 1 should be placed between supplementary tables 4 and 5).

- Asteriks should be removed from the p-values, all p-values >0.01 should be presented with 2 decimals.

- Each table should start on a new page.

- In supplementary table 2, the sentence "* there is a statistically significant difference after Bonferroni correction." should be replaced by "P-values were calculated using Bonferroni correction for the number of variables investigated (n=7)".

- In supplementary tables 3 and 5, the sentence "Significance differences obtained by Chi2 test at the .05 level." should be replaced by "P-values were derived from Chi-square tests." and put into the figure legend (not in the footnote).

- Which test was applied in supplementary table 4?

- Combined columns such as in supplementary tables 3 (All participants with prediabetes) and 4 (Total) should be avoided.

- Supplementary table 5 still contains coloured font. "p* Differences between population with or without prediabetes in a particular CVR category." should be removed.

- Supplementary figure 2: This Figure might be removed altogether. If the authors decide to keep it, the following changes should be considered: The title "Model: Full" is not informative. "Logistic regression models" in the legend is confusing, as the ORs seem to have been derived from only one model. The values on the x-axis should be presented in horizontal direction. It should be mentioned that the values on the x-axis follow a logarithmic scale. Suggest to remove the OR of serum insulin level from this plot.

PLoS One. 2024 Oct 29;19(10):e0309896. doi: 10.1371/journal.pone.0309896.r008

Author response to Decision Letter 3

12 Aug 2024

Additional Editor Comments:

- Unit "years" is still lacking behind "20-79" in the Abstract, in the Results and in Figure 1.

Done.

- Any results which are mentioned in the Abstract should also be mentioned in the main text (e.g. mean age).

Done.

Prediabetes was moved at the top of Table 3. We also added in the Results section:

Based on these results, we conclude that prediabetes was independently associated with preclinical atherosclerosis. This association remained significant after adjustment for confounders and the final findings were shown in Table 3.

We have changed to “Additionally, 183 patients were excluded from further analysis for technical reasons – inability to perform an OGTT (n=132) or US of the carotid arteries (n=4) or lack of the HbA1c measurement (n=7) or lack of CVR assessment (n=40)”.

- Figure 1: "n=7 subjects were exclused" should read "excluded", and "USG" be replaced by "US".

Done.

- Please mention which version of R was used.

Done.

- In all tables including the supplement, "C.I." should be replaced by "CI" for reasons of consistency.

Done.

- In table 3, the p-values should be mentioned to the right of the 95% CIs.

Done.

- Please add "Supplementary" before each figure and table.

Done.

- The supplementary tables should be ordered in the way they are mentioned in the text (i.e. supplementary table 1 should be placed between supplementary tables 4 and 5).

Changed.

- Asteriks should be removed from the p-values, all p-values >0.01 should be presented with 2 decimals.

Done

- Each table should start on a new page.

Done

Done.

- Which test was applied in supplementary table 4?

Chi2 test was applied. I added in the caption of Supplementary table 4.

- Combined columns such as in supplementary tables 3 (All participants with prediabetes) and 4 (Total) should be avoided.

Done.

- Supplementary table 5 still contains coloured font. "p* Differences between population with or without prediabetes in a particular CVR category." should be removed.

Done.

Thank you. We decided to remove this figure.

Attachment

Submitted filename: Response to Reviewers.docx

pone.0309896.s011.docx^{(20.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0309896.r009

Decision Letter 4

Andreas Beyerlein

21 Aug 2024

The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population: a cross-sectional study

PONE-D-23-42492R4

Dear Dr. Kaminski,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Andreas Beyerlein

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0309896.r010

Acceptance letter

Andreas Beyerlein

28 Aug 2024

PONE-D-23-42492R4

PLOS ONE

Dear Dr. Kamiński ,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Andreas Beyerlein

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Checklist. Human participants research checklist.

(DOCX)

pone.0309896.s001.docx^{(54.2KB, docx)}

S1 Fig. Receiver operating characteristic (ROC) curves; larger values of the test result variable indicate stronger evidence for a positive actual state.

Dependent variable: the presence of any atherosclerotic plaques on ultrasound of the carotid arteries.

(TIFF)

pone.0309896.s002.tiff^{(1.9MB, tiff)}

S1 Table. Receiver operating characteristic.

(TIFF)

pone.0309896.s003.tiff^{(2.4MB, tiff)}

S2 Table. Prevalence of prediabetes in the general population with cardiovascular risk categories and the presence of atherosclerotic plaques in the carotid arteries.

P-values were derived from Chi-square tests.

(TIFF)

pone.0309896.s004.tiff^{(1.8MB, tiff)}

P-values were derived from Chi-square tests.

(TIFF)

pone.0309896.s005.tiff^{(3.2MB, tiff)}

S4 Table. The occurrence of a stenosis of more than 50% in the right or left internal carotid artery in the study population considering glucose metabolism disturbances.

(TIFF)

pone.0309896.s006.tiff^{(1.8MB, tiff)}

S5 Table. Assessment of preclinical atherosclerotic progression based on the level of stenosis of the right or left internal carotid artery (ICA).

P-values were derived from Chi-square tests.

(TIFF)

pone.0309896.s007.tiff^{(2MB, tiff)}

Attachment

Submitted filename: Response to Reviewers.docx

pone.0309896.s008.docx^{(20.4KB, docx)}

Attachment

Submitted filename: Response to Reviewers.docx

pone.0309896.s009.docx^{(35.1KB, docx)}

Attachment

Submitted filename: Response to Reviewers.docx

pone.0309896.s010.docx^{(21.2KB, docx)}

Attachment

Submitted filename: Response to Reviewers.docx

pone.0309896.s011.docx^{(20.8KB, docx)}

Data Availability Statement

All relevant data are within the manuscript and its Supporting Information files.

[pone.0309896.ref001] 1.Cosentino Francesco, Peter J Grant Victor Aboyans, Clifford J Bailey Antonio Ceriello, Delgado Victoria, et al. ESC Scientific Document Group, 2019. ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD: The Task Force for diabetes, pre-diabetes, and cardiovascular diseases of the European Society of Cardiology (ESC) and the European Association for the Study of Diabetes (EASD), European Heart Journal, Volume 41, Issue 2, 7 January 2020, Pages 255–323, 10.1093/eurheartj/ehz486 [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref002] 2.Richter B, Hemmingsen B, Metzendorf M-I, Takwoingi Y. Development of type 2 diabetes mellitus in people with intermediate hyperglycaemia. Cochrane Database Syst Rev. 2018. Oct 29;10:CD012661; doi: 10.1002/14651858.CD012661.pub2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref003] 3.Kitabchi AE, Temprosa M, Knowler WC, Kahn SE, Fowler SE, Haffner SM, et al. Diabetes Prevention Program Research Group. Role of insulin secretion and sensitivity in the evolution of type 2 diabetes in the diabetes prevention program: effects of lifestyle intervention and metformin. Diabetes. 2005. Aug;54(8):2404–14. doi: 10.2337/diabetes.54.8.2404 ; PMCID: PMC1360738. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref004] 4.Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. 2022 Jan;183:109119. doi: 10.1016/j.diabres.2021.109119 Epub 2021. Dec 6. . [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref005] 5.Heianza Y, Hara S, Arase Y, Saito K, Fujiwara K, Tsuji H, et al. HbA1c 5·7–6·4% and impaired fasting plasma glucose for diagnosis of prediabetes and risk of progression to diabetes in Japan (TOPICS 3): a longitudinal cohort study. Lancet. 2011. Jul 9;378(9786):147–55; doi: 10.1016/S0140-6736(11)60472-8 [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref006] 6.Tabák AG, Herder C, Rathmann W, Brunner EJ, Kivimäki M. Prediabetes: a high-risk state for diabetes development. Lancet. 2012. Jun 16;379(9833):2279–90; doi: 10.1016/S0140-6736(12)60283-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref007] 7.Huang Y, Cai X, Mai W, Li M, Hu Y. Association between prediabetes and risk of cardiovascular disease and all-cause mortality: systematic review and meta-analysis. BMJ. 2016. Nov 23;355:i5953; doi: 10.1136/bmj.i5953 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref008] 8.Yeboah J, Bertoni AG, Herrington DM, Post WS, Burke GL. Impaired fasting glucose and the risk of incident diabetes mellitus and cardiovascular events in an adult population: MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol. 2011. Jul 5;58(2):140–6. doi: 10.1016/j.jacc.2011.03.025 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref009] 9.Diabetes Prevention Program Research Group, Knowler WC, Fowler SE, Hamman RF, Christophi CA, Hoffman HJ, et al. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet. 2009. Nov 14;374(9702):1677–86; doi: 10.1016/S0140-6736(09)61457-4 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref010] 10.Visseren Frank L J et al. ESC Scientific Document Group, 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice: Developed by the Task Force for cardiovascular disease prevention in clinical practice with representatives of the European Society of Cardiology and 12 medical societies With the special contribution of the European Association of Preventive Cardiology (EAPC), European Heart Journal, Volume 42, Issue 34, 7 September 2021, Pages 3227–333734458905 [Google Scholar]

[pone.0309896.ref011] 11.Chlabicz M, Jamiołkowski J, Łaguna W, Dubatówka M, Sowa P, Łapińska M, et al. Effectiveness of Lifestyle Modification vs. Therapeutic, Preventative Strategies for Reducing Cardiovascular Risk in Primary Prevention—A Cohort Study. Journal of Clinical Medicine. 2022; 11(3):688. doi: 10.3390/jcm11030688 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref012] 12.Touboul P.-J.; Hennerici M.; Meairs S.; Adams H.; Amarenco P.; Bornstein N.; et al. Mannheim Carotid Intima-Media Thickness Consensus (2004–2006). Cerebrovasc. Dis. 2006, 23, 75–80. [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref013] 13.Barnett H.J.M.; Taylor D.W.; Haynes R.B.; Sackett D.L.; Peerless S.J.; Ferguson G.G.; et al. Beneficial Effect of Carotid Endarterectomy in Symptomatic Patients with High-Grade Carotid Stenosis. N. Engl. J. Med. 1991, 325, 445–453. doi: 10.1056/NEJM199108153250701 [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref014] 14.Mach F., et al., 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J, 2020. 41(1): p. 111–188. doi: 10.1093/eurheartj/ehz455 [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref015] 15.Katz Arie, Nambi Sridhar S., Mather Kieren, Baron Alain D., Follmann Dean A., Sullivan Gail, et al. Quantitative Insulin Sensitivity Check Index: A Simple, Accurate Method for Assessing Insulin Sensitivity In Humans, The Journal of Clinical Endocrinology & Metabolism, Volume 85, Issue 7, 1 July 2000, Pages 2402–2410, doi: 10.1210/jcem.85.7.6661 [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref016] 16.Gayoso-Diz P., Otero-González A., Rodriguez-Alvarez M.X. et al. Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study. BMC Endocr Disord 13, 47 (2013). doi: 10.1186/1472-6823-13-47 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref017] 17.Matsuda M, DeFronzo RA: Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care 1999; 22: 1462–1470 doi: 10.2337/diacare.22.9.1462 [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref018] 18.Zieleniewska NA, Szum-Jakubowska A, Chlabicz M, Jamiołkowski J, Kowalska I, Kamiński KA. The prevalence of diabetes and prediabetes: a population-based study. Pol Arch Intern Med. 2023. Jan 5:16407. doi: 10.20452/pamw.16407 Epub ahead of print. . [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref019] 19.Cai X, Zhang Y, Li M, Wu JH, Mai L, Li J, et al. Association between prediabetes and risk of all cause mortality and cardiovascular disease: updated meta-analysis. BMJ. 2020. Jul 15;370:m2297. doi: 10.1136/bmj.m2297 ; PMCID: PMC7362233. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref020] 20.Ford ES, Zhao G, Li C. Pre-diabetes and the risk for cardiovascular disease: a systematic review of the evidence. J Am Coll Cardiol. 2010;55:1310–7. This review and meta-analysis shows that both impaired fasting glucose and impaired glucose tolerance are asso- ciated with ∼20% increased risk of developing cardiovascular disease doi: 10.1016/j.jacc.2009.10.060 [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref021] 21.Kodama S, Saito K, Tanaka S, et al. Fasting and post-challenge glucose as quantitative cardiovascular risk factors: a meta-analysis. J Atheroscler Thromb. 2012; [Epub ahead of print]. This review and meta-analysis shows that both fasting and postload glucose is associated with cardiovascular disease, but the effect of postload glucose is larger than that of fasting glucose. doi: 10.5551/jat.10975 [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref022] 22.Reis Jared P., Allen Norrina B., Bancks Michael P., Carr J. Jeffrey, Lewis Cora E., Lima Joao A., et al. Duration of Diabetes and Prediabetes During Adulthood and Subclinical Atherosclerosis and Cardiac Dysfunction in Middle Age: The CARDIA Study. Diabetes Care 1 April 2018; 41 (4): 731–738. doi: 10.2337/dc17-2233 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref023] 23.Cao Q., Xin Z., He R. et al. Age-specific difference in the association between prediabetes and subclinical atherosclerosis: an analysis of a chinese prospective cohort study. Cardiovasc Diabetol 21, 153 (2022). doi: 10.1186/s12933-022-01592-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref024] 24.Antoniou S, Naka KK, Papadakis M, Bechlioulis A, Tsatsoulis A, Michalis LK, et al. Effect of glycemic control on markers of subclinical atherosclerosis in patients with type 2 diabetes mellitus: A review. World J Diabetes. 2021. Nov 15;12(11):1856–1874. doi: 10.4239/wjd.v12.i11.1856 ; PMCID: PMC8613661 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref025] 25.Karczewska-Kupczewska M, Nikołajuk A, Kondraciuk M, Stachurska Z, Dubatówka M, Szpakowicz A, et al. The relationships between FLAIS, a novel insulin sensitivity index, and cardiovascular risk factors in a population-based study. Cardiovasc Diabetol. 2022. Apr 19;21(1):55. doi: 10.1186/s12933-022-01491-y ; PMCID: PMC9020075. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref026] 26.Altin C, Sade LE, Gezmis E, et al. Assessment of Subclinical Atherosclerosis by Carotid Intima–Media Thickness and Epicardial Adipose Tissue Thickness in Prediabetes. Angiology. 2016;67(10):961–969. doi: 10.1177/0003319716643669 [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref027] 27.Rossello X, Raposeiras-Roubin S, Oliva B, Sánchez-Cabo F, García-Ruíz JM, Caimari F, et al. Glycated Hemoglobin and Subclinical Atherosclerosis in People Without Diabetes. J Am Coll Cardiol. 2021. Jun 8;77(22):2777–2791. doi: 10.1016/j.jacc.2021.03.335 . [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref028] 28.Sun B, Ge X, Li X, Zhang J, Zhao Z, Liu X, et al. Elevated Hemoglobin A1c Is Associated With Leaky Plaque Neovasculature as Detected by Dynamic Contrast-Enhanced Magnetic Resonance Imaging. Arterioscler Thromb Vasc Biol. 2022 Apr;42(4):504–513. doi: 10.1161/ATVBAHA.121.317190 Epub 2022. Mar 3. . [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref029] 29.T Wang W., F Hsu P., J Wang Y., Z Ding Y., L Liou T., W Wang Y., et al. 5198HbA1C correlates subclinical atherosclerosis in non-diabetes, European Heart Journal, Volume 40, Issue Supplement_1, October 2019, ehz746.0057, 10.1093/eurheartj/ehz746.0057 [DOI] [Google Scholar]

[pone.0309896.ref030] 30.Acar B., Ozeke O., Karakurt M., Ozen Y., Ozbay M.B., Unal S., et al. Association of Prediabetes With Higher Coronary Atherosclerotic Burden Among Patients With First Diagnosed Acute Coronary Syndrome. Angiology. 2019;70:174–180. doi: 10.1177/0003319718772420 [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref031] 31.Amano T., Matsubara T., Uetani T., Nanki M., Marui N., Kato M., et al. Abnormal glucose regulation is associated with lipid-rich coronary plaque: Relationship to insulin resistance. JACC Cardiovasc Imaging. 2008;1:39–45. doi: 10.1016/j.jcmg.2007.09.003 [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref032] 32.Dong N, Shen X, Wu X, Guo X, Fang Q. Elevated Glycated Hemoglobin Levels Are Associated With Poor Outcome in Acute Ischemic Stroke. Front Aging Neurosci. 2022. Feb 3;13:821336. doi: 10.3389/fnagi.2021.821336 ; PMCID: PMC8851318. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref033] 33.Catalan M, Herreras Z, Pinyol M, Sala-Vila A, Amor AJ, de Groot E, et al. Prevalence by sex of preclinical carotid atherosclerosis in newly diagnosed type 2 diabetes. Nutr Metab Cardiovasc Dis. 2015. Aug;25(8):742–8. doi: 10.1016/j.numecd.2015.04.009 Epub 2015 May 7. . [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref034] 34.Ferrannini E., Gastaldelli A., Iozzo P. Pathophysiology of prediabetes. Med. Clin. N. Am. 2011;95:327–339. doi: 10.1016/j.mcna.2010.11.005 [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref035] 35.Hashemi S.J., Karandish M., Cheraghian B. et al. Prevalence of prediabetes and associated factors in southwest iran: results from Hoveyzeh cohort study. BMC Endocr Disord 22, 72 (2022). doi: 10.1186/s12902-022-00990-z [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref036] 36.Breyer MK, Ofenheimer A, Altziebler J, Hartl S, Burghuber OC, Studnicka M, et al. Marked differences in prediabetes- and diabetes-associated comorbidities between men and women-Epidemiological results from a general population-based cohort aged 6–80 years-The LEAD (Lung, hEart, sociAl, boDy) study. Eur J Clin Invest. 2020. Mar;50(3):e13207. doi: 10.1111/eci.13207 Epub 2020 Feb 12. . [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref037] 37.Drobek N, Sowa P, Jankowski P, Haberka M, Gąsior Z, Kosior D, et al. Undiagnosed Diabetes and Prediabetes in Patients with Chronic Coronary Syndromes-An Alarming Public Health Issue. J Clin Med. 2021. May 5;10(9):1981. doi: 10.3390/jcm10091981 ; PMCID: PMC8124594. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref038] 38.Kato M, Noda M, Suga H, Nakamura T, Matsumoto M, Kanazawa Y, et al. Haemoglobin A1c cut-off point to identify a high risk group of future diabetes: results from the Omiya MA Cohort Study. Diabet Med. 2012. Jul;29(7):905–10. doi: 10.1111/j.1464-5491.2012.03572.x ; PMCID: PMC3504345. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0309896.ref039] 39.Heianza Y, Arase Y, Fujihara K, Tsuji H, Saito K, Hsieh SD, et al. Screening for pre-diabetes to predict future diabetes using various cut-off points for HbA(1c) and impaired fasting glucose: the Toranomon Hospital Health Management Center Study 4 (TOPICS 4). Diabet Med. 2012. Sep;29(9):e279–85. doi: 10.1111/j.1464-5491.2012.03686.x . [DOI] [PubMed] [Google Scholar]

[pone.0309896.ref040] 40.Bjarkø VV, Haug EB, Sørgjerd EP, Stene LC, Ruiz PL, Birkeland KI, et al. Undiagnosed diabetes: Prevalence and cardiovascular risk profile in a population-based study of 52,856 individuals. The HUNT Study, Norway. Diabet Med. 2022. Jun;39(6):e14829. doi: 10.1111/dme.14829 Epub 2022 Mar 21. ; PMCID: PMC9310609. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population: A cross-sectional study

Natalia Anna Zieleniewska

Jacek Jamiołkowski

Małgorzata Chlabicz

Adam Łukasiewicz

Marlena Dubatówka

Marcin Kondraciuk

Paweł Sowa

Irina Kowalska

Karol Adam Kamiński

Roles

Abstract

Background

Methods

Results

Conclusions

Introduction

Material and methods

Cohort study Bialystok PLUS

Data collection and assays

Division into cardiovascular risk classes

Definition of diabetes, prediabetes and assessment of insulin sensitivity

Statistical analysis

Results

Study population

Fig 1. Flowchart of study population.

Table 1. Baseline clinical and metabolic characteristics of population group and groups with prediabetes.

Fig 2. Prevalence of prediabetes in the general population with cardiovascular risk categories and the presence of atherosclerotic plaques in the carotid arteries.

Table 2. Evaluation of the relationship of vascular early atherosclerotic parameters with anthropometric, metabolic and insulin resistance parameters.

Table 3. Regression models performed for the whole study population.

Discussion

Conclusions

Supporting information

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Andreas Beyerlein

Roles

Author response to Decision Letter 0

Decision Letter 1

Andreas Beyerlein

Roles

Author response to Decision Letter 1

Decision Letter 2

Andreas Beyerlein

Roles

Author response to Decision Letter 2

Decision Letter 3

Andreas Beyerlein

Roles

Author response to Decision Letter 3

Decision Letter 4

Andreas Beyerlein

Roles

Acceptance letter

Andreas Beyerlein

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases