Abstract
Introduction
Evidence has found that high-sensitivity C-reactive protein (hs-CRP) can predict cardiovascular disease (CVD). Additionally, some research has suggested a combined effect of hs-CRP and remnant cholesterol (RC) in the development of CVD. Recognizing the significance of assessing both markers as predictive factors, this study aims to examine the association between RC and hs-CRP levels with the occurrence of CVD, coronary artery disease (CAD), and brain ischemic stroke in the Iranian population, categorized by gender.
Materials and methods
The research involved 6985 participants from an Iranian cohort study. At the onset of the study, serum hs-CRP and RC levels were assessed. After ten years, occurrences of CVD, CAD, and brain ischemic events were evaluated. Furthermore, a survival and gender-stratified analysis was conducted to understand this association better.
Results
Participants with high RC but low hs-CRP had a 23.5% and 24% increase in CVD and CAD risk, while those with both elevated RC and hs-CRP had a 44.9% and 57% higher risk for CVD and CAD. Among women, the combination of elevated RC and hs-CRP was linked to a 36.7% increase in CAD risk. Survival analysis supported these findings, showing that individuals with elevated RC and hs-CRP levels had the shortest survival times for CVD (134.55 months) and CAD (135.30 months).
Conclusion
The combined use of RC and hs-CRP markers can strongly predict CVD and CAD, particularly in men. However, no association was found between RC and hs-CRP in brain ischemic stroke. To definitively address this issue, it is crucial to conduct future studies with a larger sample size that specifically target brain ischemic stroke.
Keywords: Remnant cholesterol, hs-CRP, Cardiovascular disease, Coronary artery disease, Brain ischemic
Graphical Abstract
Introduction
Cardiovascular diseases (CVD), including coronary artery disease (CAD) and brain ischemic events, continue to be among the leading causes of morbidity and mortality worldwide despite significant advancements in prevention strategies [1–4]. CAD, characterized by the narrowing of coronary arteries, and brain ischemia, marked by reduced blood flow to the brain, represent significant contributors to this global health burden [1, 4]. Although these conditions differ in their clinical symptoms, they are driven by similar underlying mechanisms. Atherosclerosis, the accumulation of fatty plaques within arterial walls, is a central process driving the development and progression of both CAD and brain ischemic events, as well as other forms of CVD [5, 6].
For many years, the main focus of preventing CVD has been reducing low-density lipoprotein (LDL) cholesterol, supported by extensive evidence from observational, genetic, and clinical trials [7]. However, even after reaching the recommended LDL and other lipid profile targets, there remains a residual risk of atherosclerosis. This residual risk may be partly due to remnant cholesterol (RC), which is found in triglyceride-rich lipoproteins [8, 9]. RC is calculated as total cholesterol minus LDL and high-density lipoprotein (HDL) cholesterol, and it includes cholesterol in very low-density lipoproteins (VLDL), intermediate-density lipoproteins (IDL), and chylomicron remnants [10].
Atherosclerosis is an inflammatory process, and biomarkers like high-sensitivity C-reactive protein (hs-CRP) provide measurable indicators of this inflammation, which drives atherosclerosis development [11, 12]. Elevated levels of RC contribute to lipid accumulation within arterial walls [13], while increased hs-CRP levels signal ongoing inflammation that can destabilize plaques [14]. Together, these factors heighten the risk of plaque rupture and subsequent cardiovascular events. While RC further fuels the inflammatory process, hs-CRP directly reflects the inflammatory activity within the arteries [15–18]. Incorporating these markers into practice helps identify at-risk individuals earlier and more accurately, enabling more effective and targeted interventions to prevent CVD progression.
Limited research has been conducted on the simultaneous association between RC and hs-CRP level changes and cardio-metabolic outcomes. Evidence suggests that, compared to RC, hs-CRP is a stronger predictor of CVD outcomes. Individuals with high levels of both RC and hs-CRP are at a significantly greater risk of developing CVD compared to those with elevated levels of each factor individually [19, 20]. Although survival analysis has been attempted in a few studies to verify this association, a similar study in Iran has not yet utilized this analytical approach [20]. Furthermore, the specific role of RC in the development of brain ischemic events such as stroke has not been thoroughly investigated. These gaps underscore the need for a more comprehensive analysis, which this study aims to provide within the framework of an Iranian cohort. The study focuses on how these biomarkers influence the progression of atherosclerosis and contribute to the development of CVD, CAD, and brain ischemic stroke while considering gender differences.
Methods
Study population
Participants were recruited from the Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort study. The MASHAD study is a prospective cohort study comprising 9704 men and women aged 35–65 from Mashhad in Iran [21]. Participants were selected from three areas in Mashhad, situated in northeastern Iran, utilizing a stratified cluster random sampling method. Each area was segmented into nine locations based around the divisions of Mashhad Healthcare Center. Households containing individuals aged between 35 and 65 were located, and local population authorities provided those families with an informational brochure about the study. Community leaders acquainted with the families in the area also helped in the process of identifying and recruiting potential participants. The MASHAD study excluded individuals with CVD at the baseline [21]. Follow-up assessments are conducted every three years via telephone, and after a decade, participants are invited to attend a medical and biochemical evaluation.
In the current analysis, a total of 9704 subjects were followed for 10 years from the baseline. After excluding 1715 subjects who were lost to follow-up and 429 participants who passed away, a total of 7560 participants were recruited for the second follow-up. Participants with incomplete data regarding blood sample information or cardiovascular complications incidence (N = 575) were excluded from the study. The final analysis was undertaken in N = 6985 Subjects (Fig. 1). All participants provided informed written consent, and the study was approved by the Human Research Ethics Committee of Mashhad University of Medical Sciences (IR.MUMS.IRH.REC.1403.135).
Fig. 1.
Study Flowchart
Baseline measurements
The participants’ blood samples were collected following a 14-hour overnight fast. Serum samples were utilized to analyze the lipid profile and hs-CRP. Enzymatic methods on an automated analyzer were used to estimate serum TG, LDL-C, HDL-C, and TC, and fasting blood glucose (FBG) was measured using similar enzymatic methods on an autoanalyzer. RC is calculated by subtracting HDL-C and LDL-C from TC [10]. The hs-CRP was quantified using an automated analyzer (BioSystems) with a sensitivity threshold of 0.06 mg/L [22]. Although no official guidelines, averages, or standards exist for healthy RC levels, ongoing research in this area has shown that individuals with RC levels exceeding 24 mg/dl may be at an increased risk of heart disease or stroke within the next two decades [23]. Therefore, 24 mg/dl is considered the cut-off point for RC. Previous studies have indicated that a serum hs-CRP level > 3 mg/dl may indicate a future risk of CVD [24]. This threshold was used to identify a high hs-CRP level.
Follow-up and endpoint assessment
After identifying CVD participants, each underwent a 12-lead electrocardiogram (ECG), which a cardiologist then evaluated. CVD was diagnosed based on ECG results, clinical findings, and medical history. If necessary, additional medical tests such as stress echocardiography, radioisotope, angiography, computed tomography (CT), angiography exercise tolerance test (ETT), and a review of available medical records were conducted. Ultimately, cases with potential CVD events were reviewed by a team of specialists who made a definitive diagnosis. CAD is a type of CVD characterized by the presence of 50% or more stenosis in the diameter of at least one major coronary artery (which includes the left main, right coronary artery, left anterior descending artery, or circumflex artery) is defined as CAD [25]. The World Health Organization (WHO) defines a stroke as “the rapid onset of signs indicating focal or global disturbances in cerebral function, lasting 24 hours or more, with no identifiable cause other than vascular origin.” [26].
During the follow-up period, 837 participants were diagnosed with CVD, of whom 749 were classified as CAD patients and 118 were identified as having experienced an ischemic stroke.
Statistical analysis
The data was summarized using the appropriate mean (± SD) or proportions. Differences between means and proportions were tested using ANOVA and Pearson’s Chi-square tests. RC and hs-CRP were categorized into four groups based on cut-off values of 24 mg/dl for RC and 3 mg/dl for hs-CRP to comprehensively explore the impact of the exposure. The Kaplan-Meier method was performed to assess the survival time, and the Classic Cox’s Model was used to find the association between RC, hs-CRP, and CVD. Additionally, data were adjusted for confounding factors such as age, education, job, marriage, smoking, BMI, SBP, DBP, lipid profile, and FBG. Data analysis was conducted using SPSS-26, and a p-value < 0.05 was considered statistically significant.
Results
In a study of 6,985 participants, significant variations were observed across groups categorized by RC and hs-CRP levels. Participants were mainly middle-aged, with higher levels of RC and hs-CRP associated with increased age, BMI, waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), FBG, TC, and TG levels (p for all < 0.001). Additionally, demographic characteristics and HDL and LDL cholesterol levels showed differences between groups (p < 0.05) (Table 1).
Table 1.
Baseline characteristics according to concordant and discordant groups of RC and HsCRP
| RC < 24 & hsCRP < 3 | RC < 24 & hsCRP > = 3 | RC > = 24 & hsCRP < 3 | RC > = 24 & hsCRP > = 3 | P-value | ||
|---|---|---|---|---|---|---|
| N (%) | 2571 (36.8%) | 574 (8.2%) | 2835 (40.6%) | 1005 (14.4%) | ||
| Male, N (%) | 971 (34.5%) | 170 (6.0%) | 1339 (47.5%) | 336 (11.9%) | < 0.001 | |
| Age, y | 46.41 ± 7.93 | 47.88 ± 8.25a | 47.98 ± 7.98a | 48.81 ± 7.82abc | < 0.001 | |
| Marriage status | Single | 20 (57.1%) | 1 (2.9%) | 10 (28.6%) | 4 (11.4%) | 0.004 |
| Married | 2418 (36.8%) | 545 (8.3%) | 2686 (40.8%) | 927 (14.1%) | ||
| Divorced | 40 (48.2%) | 4 (4.8%) | 23 (27.7%) | 16 (19.3%) | ||
| Widow | 93 (32.0%) | 24 (8.2%) | 116 (39.9%) | 58 (19.9%)abc | ||
| Job status | Employee | 985 (36.6%) | 174 (6.5%) | 1192 (44.3%) | 337 (12.5%) | < 0.001 |
| Unemployed | 1395 (38.5%) | 362 (10.0%) | 1293 (35.7%) | 569 (15.7%) | ||
| Retired | 190 (28.1%) | 38 (5.6%) | 349 (51.6%)abd | 99 (14.6%) | ||
| Education level | Low | 1377 (37.6%) | 331 (9.0%) | 1382 (37.7%) | 573 (15.6%) | < 0.001 |
| Moderate | 898 (36.1%) | 200 (8.0%) | 1060 (42.6%) | 331 (13.3%) | ||
| High | 295 (35.6%) | 43 (5.2%) | 390 (47.1%)abd | 100 (12.1%) | ||
| Smoking status | non smoker | 1841 (37.3%) | 421 (8.5%) | 1970 (39.9%) | 706 (14.3%) | 0.012 |
| Ex-smoker | 225 (34.4%) | 36 (5.5%) | 307 (46.9%)abd | 87 (13.3%) | ||
| current smoker | 505 (36.3%) | 117 (8.4%) | 558 (40.1%) | 212 (15.2%) | ||
| BMI, kg/m2 | 26.28 ± 4.37 | 28.52 ± 4.75a | 28.02 ± 4.10a | 30.07 ± 4.85abc | < 0.001 | |
| WC, cm | 91.59 ± 11.33 | 96.60 ± 12.3a | 95.65 ± 10.94a | 99.42 ± 12.72abc | < 0.001 | |
| SBP, mmHg | 131.09 ± 21.44 | 135.43 ± 22.57 a | 136.48 ± 20.21 a | 140.42 ± 23.23abc | < 0.001 | |
| DBP, mmHg | 80.45 ± 17.57 | 81.27 ± 14.30 | 83.00 ± 20.43 ab | 83.37 ± 15.34 ab | < 0.001 | |
| Glucose, mg/dl | 84.54 ± 29.27 | 91.95 ± 36.66 a | 91.10 ± 34.19 a | 102.18 ± 48.69abc | < 0.001 | |
| Cholesterol, mg/dl | 177.73 ± 34.84 | 185.56 ± 36.62 a | 196.82 ± 37.47 ab | 206.19 ± 39.20abc | < 0.001 | |
| TG, mg/dl | 83.59 ± 27.40 | 88.32 ± 27.73 | 185.78 ± 98.50 ab | 186.23 ± 94.39abc | < 0.001 | |
| HDL, mg/dl | 45.32 ± 10.11 | 44.89 ± 10.29 | 40.40 ± 9.04ab | 41.93 ± 9.28ab | < 0.001 | |
| LDL, mg/dl | 116.40 ± 31.01 | 124.50 ± 34.74 | 113.83 ± 36.15 | 117.91 ± 39.26 | < 0.001 | |
| RC, mg/dl | 15.99 ± 6.21 | 16.16 ± 8.19 | 42.56 ± 21.56ab | 46.34 ± 23.3ab | < 0.001 | |
| hs-CRP, mg/l | 1.24 ± 0.61 | 5.01 ± 1.78 a | 1.41 ± 0.66b | 5.24 ± 1.82 ac | < 0.001 | |
| CVD (N = 837) | 204 (8.2) | 78 (10.8) | 329 (12.4) | 226 (18)abc | < 0.001 | |
| CAD (N = 749) | 178 (7) | 70 (9.5) | 290 (10.7) | 211 (16.5)abc | < 0.001 | |
| Brain ischemic (N = 118) | 36 (1.4) | 9 (1.2) | 45 (1.7) | 28 (2.2) | 0.24 | |
Data presented as mean ± SD or number and percentage; One-Way ANOVA has been done
a: RC < 24 & hsCRP < 3 vs. RC < 24 & hsCRP > = 3, RC > = 24 & hsCRP < 3 and RC > = 24 & hsCRP > = 3; b: RC < 24 & hsCRP > = 3 vs. RC > = 24 & hsCRP < 3 and RC > = 24 & hsCRP > = 3; c: RC > = 24 & hsCRP < 3 vs. RC > = 24 & hsCRP > = 3, d: RC > = 24 & hsCRP > = 3
Education level: Low: illiterate and elementary, Moderate: diploma and under diploma, High: university educated
BMI: Body mass index, WC: Waist circumference, SBP: Systolic blood pressure, DBP: Diastolic blood pressure, TG: Triglyceride, HDL: High density lipoprotein, LDL: Low density lipoprotein, RC: Remnant cholesterol, hs-CRP: High Sensitivity C Reactive Protein
In Table 2, the evaluation of the incidence of CVD, CAD, and brain ischemic events showed significant differences across four groups based on levels of RC and hs-CRP. The reference group was made up of participants with RC < 24 mg/dl and hs-CRP < 3 mg/dl was used as the baseline for comparison. Participants with elevated RC (≥ 24 mg/dl) had a notably higher risk of CVD. Those with high RC but low hs-CRP had a 23.5% increase in CVD risk (RR 1.235, 95% CI 1.031–1.478, p = 0.022), while the group with both elevated RC and hs-CRP had a 44.9% higher risk compared to the reference group (RR 1.449, 95% CI 1.165–1.803, p = 0.001). Notably, RC and hs-CRP levels were not linked to CVD in women across all groups. For CAD, a similar pattern emerged, with participants having high RC but low hs-CRP showing a 24.0% increase in risk (RR 1.240, 95% CI 1.023–1.502, p = 0.029), and those with both high RC and hs-CRP exhibiting a 57.0% higher risk (RR 1.570, 95% CI 1.25–1.973, p < 0.001). Notably, the group with both high RC and hs-CRP had a significantly higher risk of CAD in both women and men (RR 1.367, 95% CI 1.014–1.842, p = 0.040 for females vs. RR 1.79, 95% CI 1.25–2.563, p = 0.001 for males). Conversely, no significant association was found between low RC combined with high hs-CRP and CVD or CAD outcomes (p > 0.05). Additionally, no significant association was observed between RC and hs-CRP levels and the risk of brain ischemic stroke, as all groups demonstrated non-significant p-values.
Table 2.
Association between concordant and discordant groups of RC and HsCRP with incidence of outcomes
| Total | Male | Female | ||||
|---|---|---|---|---|---|---|
| RR (95% CI) | p-value | RR (95% CI) | p-value | RR (95% CI) | p-value | |
| CVD | ||||||
| RC < 24 & hsCRP < 3 | Reference level | |||||
| RC < 24 & hsCRP > = 3 | 1.077 (0.794–1.462) | 0.630 | 1.242 (0.746–2.069) | 0.400 | 0.957 (0.653–1.403) | 0.820 |
| RC > = 24 & hsCRP < 3 | 1.235 (1.031–1.478) | 0.022 | 1.414 (1.088–1.836) | 0.009 | 1.076 (0.836–1.384) | 0.570 |
| RC > = 24 & hsCRP > = 3 | 1.449 (1.165–1.803) | 0.001 | 1.692 (1.204–2.376) | 0.002 | 1.254 (0.941–1.67) | 0.120 |
| CAD | ||||||
| RC < 24 & hsCRP < 3 | Reference level | |||||
| RC < 24 & hsCRP > = 3 | 1.095(0.791–1.515) | 0.580 | 1.296 (0.763-2.2) | 0.330 | 0.943 (0.624–1.424) | 0.780 |
| RC > = 24 & hsCRP < 3 | 1.24 (1.023–1.502) | 0.029 | 1.476 (1.118–2.563) | 0.006 | 1.034 (0.789–1.424) | 0.800 |
| RC > = 24 & hsCRP > = 3 | 1.57 (1.25–1.973) | < 0.001 | 1.79 (1.25–2.563) | 0.001 | 1.367 (1.014–1.842) | 0.040 |
| Brain ischemic | ||||||
| RC < 24 & hsCRP < 3 | Reference level | |||||
| RC < 24 & hsCRP > = 3 | 0.757(0.335–1.713) | 0.590 | 1.076 (0.24–1.718) | 0.920 | 0.649 (0.245–1.718) | 0.800 |
| RC > = 24 & hsCRP < 3 | 0.974 (0.62–1.53) | 0.900 | 1.012 (0.485–2.111) | 0.970 | 0.94 (0.526–1.679) | 0.830 |
| RC > = 24 & hsCRP > = 3 | 0.87 (0.474–1.596) | 0.650 | 1.232 (0.475–3.196) | 0.950 | 0.677 (0.305–1.503) | 0.330 |
Cox regression model has been done
CVD: Cardiovascular disease, CAD: Coronary artery disease, RC: Remnant cholesterol, hs-CRP: High Sensitivity C Reactive Protein
Adjusted by age, education, job, marriage, smoking, BMI, SBP, DBP, lipid profile and FBG
The data in Table 3 shows that elevated RC and hs-CRP levels have a significant survival time change. Participants with RC levels less than 24 mg/dl and hs-CRP levels under 3 mg/dl had the longest estimated mean survival times for both CVD (140.89 months) and CAD (141.78 months). On the other hand, those with elevated RC and hs-CRP levels experienced the shortest survival times for CVD (134.55 months) and CAD (135.30 months), indicating a significant reduction in survival (p < 0.001 for both). No significant difference in survival time was observed across the groups for brain ischemic stroke (p = 0.770). These findings are confirmed by Fig. 2.
Table 3.
Median survival time and 95% CI in month by concordant and discordant groups according to CVD, CAD and brain ischemic
| Estimate mean time for event, 95% Cl | P-value | |
|---|---|---|
| CVD | < 0.001 | |
| RC < 24 & hsCRP < 3 | 140.89 (139.95, 141.82) | |
| RC < 24 & hsCRP > = 3 | 138.69 (137.20, 140.17) | |
| RC > = 24 & hsCTRP < 3 | 137.85 (136.93, 138.77) | |
| RC > = 24 & hsCRP > = 3 | 134.55 (133.01, 136.08) | |
| CAD | < 0.001 | |
| RC < 24 & hsCRP < 3 | 141.78 (140.89, 142.66) | |
| RC < 24 & hsCRP > = 3 | 139.32 (137.90, 140.75) | |
| RC > = 24 & hsCTRP < 3 | 138.88 (138.00, 139.76) | |
| RC > = 24 & hsCRP > = 3 | 135.30 (133.81, 136.79) | |
| Brain ischemic | 0.770 | |
| RC < 24 & hsCRP < 3 | 145.66 (145.11, 146.21) | |
| RC < 24 & hsCRP > = 3 | 143.22 (142.64, 143.81) | |
| RC > = 24 & hsCTRP < 3 | 144.74 (144.25, 145.22) | |
| RC > = 24 & hsCRP > = 3 | 142.59 (141.73, 143.44) |
Kaplan-Meier has used to estimate mean event time
CVD: Cardiovascular disease, CAD: Coronary artery disease, RC: Remnant cholesterol, hs-CRP: High Sensitivity C Reactive Protein
Fig. 2.
Survival Time in month A) CVD, B) CAD, and C) Brain stroke patients. Caption- CVD: Cardiovascular disease, CAD: Coronary artery disease, RC: Remnant cholesterol, hs-CRP: High Sensitivity C Reactive Protein
Discussion
The current investigation delved into the relationship between RC and hs-CRP concentrations for predicting CVD, CAD, and brain ischemic stroke incidence. The findings are significant, revealing that an RC level of 24 or higher is linked to an increased risk of CVD and CAD, regardless of normal or abnormal levels of hs-CRP. This association is particularly pronounced among individuals with hs-CRP levels of 3 or higher. Notably, men showed a significantly higher incidence of CAD in the group with elevated levels of both RC (≥ 24) and hs-CRP (≥ 3). Importantly, no correlation was found between RC and hs-CRP level changes and the occurrence of brain ischemic stroke in any gender group. Furthermore, an increasing trend in BMI, WC, blood pressure, FBG, TC, and TG was observed among the RC/hs-CRP groups. As expected, these markers, which are risk factors for inflammation and dyslipidemia, were highest in the group with elevated levels of both RC and hs-CRP [27, 28].
Inflammation plays a crucial role in the development of atherosclerosis, and hs-CRP is widely regarded as one of the most valuable and easily accessible serum markers of inflammation [29]. Therefore, statin treatment may lower hs-CRP levels, reduce inflammation, and lower the risk of CVD [30]. hs-CRP has commonly been used as a risk assessment tool for CVD and has been helpful for years for screening and primary prevention [31, 32]. The latest recommendations in American and European guidelines for preventing CVD and managing dyslipidemias suggest incorporating hs-CRP levels as supplementary information to improve CVD risk evaluation and guide discussions between clinicians and patients [1, 33, 34]. In a study by Tayefi et al., the decision tree algorithm demonstrated that serum hs-CRP levels are the most significant variable associated with CAD, demonstrating a closer link to coronary heart disease (CHD) than traditional biomarkers such as FBG and LDL [35]. Another meta-analysis showed statistically significant results regarding the capability of hs-CRP to predict incident CVD among middle-aged adults [36].
While it has been commonly believed that individuals with high HDL levels and low LDL levels face a lower risk of heart disease [37], recent studies suggest that RC levels can predict CVD events, irrespective of LDL-C levels [38]. RC can increase the production of reactive oxygen species (ROS), which leads to endothelial dysfunction. It can also induce endothelial cell apoptosis by increasing the secretion of TNF-α and IL-1β, promoting atherosclerosis [39–41]. Additionally, RC enhances platelet activity and aggregation, resulting in thrombosis and atherosclerosis [42]. A recent meta-analysis of 31 cohort studies showed that elevated RC was associated with a 53% increase in CVD incidence compared with low RC [10]. In line with the current findings, shreds of evidence suggest that having high levels of both RC and hs-CRP significantly increases the risk of CVD as compared to having elevated levels of either factor individually [19, 20]. Given the interconnected nature of RC and hs-CRP [19], it is plausible that predicting survival time will be the lowest in the category where both markers show increased levels. Interestingly, in the group with elevated RC levels (both in those with elevated and lowered hs-CRP levels), there was an increased risk of CVD and CAD. However, in the group with elevated hs-CRP levels, the increased risk for CVD and CAD was observed only when combined with elevated RC levels. This pioneering study may highlight the significance of elevated RC levels over hs-CRP in assessing the risk of cardiovascular outcomes.
Research has shown that while RC is linked to an increased risk of cardio-metabolic diseases [43], its association with ischemic brain conditions is less understood. Studies have produced conflicting findings regarding hs-CRP. For instance, Jiang reported significantly higher levels of plasma hs-CRP (≥ 3.0 mg/L) in ischemic stroke patients compared to controls [44]. However, the current study yielded contradictory results due to the small number of brain ischemic cases in the MASHAD study cohort population. This highlights the need for additional research to achieve a deeper insight.
The existing literature has linked combined elevated levels of RC and hs-CRP to a higher risk of CVD outcomes, which aligns with the current findings [19, 20]. The results indicated that elevated levels of RC were more strongly associated with incidences of CVD and CAD than elevated hs-CRP levels. However, previous studies have shown that higher hs-CRP levels are associated with a greater risk of CVD outcomes compared to elevated RC levels [19, 20]. This discrepancy may be attributed to the broader range of study population ages (20–100 years) [19]. In elderly participants, elevated levels of hs-CRP present a risk marker of the attenuated relationship between serum cholesterol and cardiovascular events [45]. Additionally, the present study considered a wider range of confounders that previous studies overlooked. For instance, for FBG and BMI in the statistical analysis may lead to more accurate and reliable findings compared to earlier research [19, 20]. Consequently, the findings suggest that RC may serve as a better predictor of CVD outcomes than hs-CRP, in line with previous literature that has highlighted its advantages over LDL, HDL, and apoB [8, 23].
The current study’s gender-stratified analysis revealed that the relationship between increased RC (regardless of a decrease or increase in hs-CRP) and CVD and CAD is more robust in men than women. Research has highlighted the impact of gender in this particular domain. For instance, a study by Yang et al. found that while both men and women with elevated RC were associated with the first CVD event, this association was more pronounced in men (12.8% of men and 4.3% of women) [38]. Other studies have also indicated a direct and significant relationship between increased RC and CVD. Although these studies did not specifically analyze data by gender, the high percentage of male participants (73.1% and over 76%, respectively) suggests that RC is notably associated with CVD, particularly in men [46, 47]. Additionally, some studies have shown an association between being female and elevated hs-CRP [48]. The findings of the present study align with this observation, demonstrating that in women, the association between RC and CAD is evident only when both RC and hs-CRP levels are elevated.
Strengths and limitations
This research is the first in Iran to investigate the relationship between levels of RC and hs-CRP with cardiovascular outcomes. The study has several strengths. It has a large sample size and categorizes RC and hs-CRP levels into four groups. The cohort design allows for the establishment of causal relationships. Additionally, the use of survival analysis and the simultaneous measurement of the relationship between changes in RC and hs-CRP with the occurrence of related diseases provide a better understanding of the predictive value of these serum factors. RC is determined through direct measurement and indirect calculation [10]. The indirect calculation method is advantageous due to its simplicity and speed. Research indicates that in patients with previous ischemic heart disease, calculated RC served as a more accurate predictor of all-cause mortality compared to direct measurement [49]. However, the indirect calculation method for RC does have certain limitations. A comparison revealed that calculated RC correlated well with measured RC at high TG levels (≥ 150 mg/dL) but not as effectively at lower TG levels (< 150 mg/dL) [50]. Furthermore, the study primarily concentrated on a middle-aged population (ages 35–65), taking into account the age-related incidence of CVDs [51], which represents another limitation of this research.
Conclusion
The research findings indicate that high levels of RC (above 24 mg/dl) and hs-CRP (exceeding 3 mg/dl) are linked to an increased risk of CVD and CAD, particularly in men. In women, RC and hs-CRP levels did not demonstrate a direct association with these outcomes, except when both were elevated, which was associated with a higher risk of CAD. Increased levels of both RC and hs-CRP led to reduced survival times. However, changes in RC and hs-CRP levels were not associated with the incidence and survival time of brain ischemic stroke. Due to their rarity, further studies, particularly those using a case-control design, are crucial to confirm these findings.
Acknowledgements
We thank Mashhad University of Medical Sciences for providing the data.
Author contributions
F.K. and A.H. wrote the main manuscript text, with F.K. also contributing to conceptualization and graphical abstract design. R.A., S.D., A.R., A.N.M., M.H.T., and F.H. gathered the data. S.D. and H.E. conducted data analysis and contributed to the study design. G.A.F. performed scientific and grammatical editing. L.B., H.A., and M.M. designed the scientific approach and confirmed the CVD patients. M.M. and M.G.-M. designed the study and served as corresponding authors. All authors reviewed the manuscript.
Funding
This work was supported by the Mashhad University of Medical Sciences [grant number: 4030900].
Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.
Declarations
Ethical approval and consent to participate
Ethical Approval and Consent to participate -All individuals were well informed and their written consent was drawn. Accordingly, the study protocol was validated by the Ethics Committee of the Mashhad University of Medical Sciences (MUMS) and the Institutional Review Board of Mashhad University Medical Center. This project is supported by Mashhad University of Medical Sciences. Funding number: 4030900 and ethical approval cod: IR.MUMS.IRH.REC.1403.010.
Consent for publication
This section as not applicable. It is not applicable to the Consent of Image Publication for this manuscript. The figures were designed only in this manuscript to present the results of the current paper.
Competing interests
The Authors declare that there is no conflict of interest.
Footnotes
Publisher’s note
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Farzam Kamrani, Ali Rezaee equally first.
Contributor Information
Majid Ghayour-Mobarhan, Email: GhayourM@mums.ac.ir, Email: ghayourmobarhan@yahoo.com.
Mohsen Moohebati, Email: mouhebatim@mums.a.cir.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.