Skip to main content
NCBI home page
F1000Research logoLink to F1000Research
. 2026 Mar 26;13:539. Originally published 2024 May 28. [Version 3] doi: 10.12688/f1000research.150995.3

Assessing the Features of Diabetic Foot Ulcers among Individuals with Type 2 Diabetes Mellitus in Thi Qar, Iraq

Adel Gassab Mohammed 1,a, Dheyaa Kadhim Al-Waeli 1, Samih Abed Odhaib 2, Mahmood Thamer Altemimi 2
PMCID: PMC13100608  PMID: 42027745

Version Changes

Revised. Amendments from Version 2

This revised Version 3 addresses the reservations raised by Reviewer Haeril Amir and introduces the following key amendments relative to Version 2: 1. Expanded Methods — Participants subsection: Explicit inclusion criteria (adult T2DM patients ≥18 years with active DFU attending TDEMC, January 2021–June 2022), exclusion criteria (T1DM, incomplete records, declined consent), and sampling method (consecutive sampling) have been added to improve methodological transparency and allow assessment of representativeness. 2. Expanded Methods — Data Collection subsection: Operational definitions have been added for five key clinical variables previously mentioned without specification: diabetic retinopathy (ophthalmologic examination/fundoscopy per the International Clinical Diabetic Retinopathy Severity Scale), diabetic neuropathy (10-g monofilament, vibration, and ankle reflex examination per ADA criteria), ischaemic heart disease (documented cardiologist diagnosis), hypertension (documented diagnosis or antihypertensive use), and smoking status (patient self-report; current/ex-smoker/never-smoker). 3. New Statistical Analysis — Multivariate Regression (Tables 4A and 4B): The statistical analysis has been substantially expanded beyond descriptive statistics and chi-square tests. An ordinal logistic regression model (Wagner grade 1–5 as ordinal outcome) and a binary logistic regression model (severe DFU: Wagner ≥3 versus non-severe: Wagner <3) were performed on the T2DM cohort (n=853). These analyses identified diabetic retinopathy (OR=0.58, 95% CI 0.41–0.81, p=0.002), diabetic neuropathy (OR=0.65, 95% CI 0.48–0.88, p=0.006), and eGFR (OR=0.86, 95% CI 0.74–0.99, p=0.040) as independent significant predictors of higher Wagner grade after adjustment for all confounders. 4. Expanded Discussion: Three new paragraphs provide pathophysiological interpretations of the key associations, including the shared microvascular mechanisms linking retinopathy and neuropathy to DFU severity, the attenuation of random plasma glucose in the multivariate model, and the role of renal function in DFU progression. 5. Updated Abstract and Conclusion: Both sections have been revised to incorporate the multivariate regression findings.

Abstract

Background

This study aimed to evaluate the characteristics of diabetic foot ulcers in individuals with type 2 diabetes mellitus (T2DM) in Iraq.

Methods

The study included 881 participants with T2DM and different types of foot ulcers, who attended a specialized diabetes center. Data on demographics, clinical characteristics, biochemical investigations, comorbidities, and treatment regimens were collected and analyzed.

Results

The majority of the cases (96.8%) were due to T2DM, with an average age of 58 years and a mean BMI of 30 kg/m 2. Participants had elevated serum creatinine, blood urea, and glucose levels, with uncontrolled HbA1c levels. Comorbidities included hypertension, ischemic heart disease, diabetic neuropathy, and retinopathy. Most participants were on insulin and statins. Diabetic foot ulcers were mainly on the right foot (48%) and classified as Grade 2 in Wagner’s system. Some participants had Charcot deformity or stages of amputation.

Conclusions

Random plasma glucose levels and diabetic retinopathy were significantly associated with the classification of foot ulcers. Further research is needed to explore additional variables related to T2DM and foot ulcers, emphasizing the importance of glucose control and retinopathy in ulcer classification.

Keywords: diabetic foot ulcers, Type 2 Diabetes Mellitus, Thi Qar, Iraq, local studies, characteristics

Introduction

Diabetes mellitus (DM) represents a significant global health issue, anticipated to affect 700 million people by 2045. 1 Diabetic foot ulcers carry a heavy burden both in economic terms and human suffering. Despite advancements in treatment and increased awareness, DFUs remain a prevalent issue among those with diabetes, especially T2DM. One of the severe consequences of DM is the formation of diabetic foot ulcers (DFUs), which can drastically diminish the quality of life for patients, lead to costly economic outcomes, and, at worst, necessitate the amputation of affected limbs. 2 Diabetic foot encompasses a range of foot-related health issues, from infections and ulcerations to deep tissue damage arising from the complications of diabetes itself. 3 An estimated 80% of non-traumatic amputations are attributed to DFUs, underscoring their severe impact. 4

The typical etiology of DFUs involves a combination of neuropathic, traumatic, ischemic, and infectious factors. 5 Globally, the prevalence of diabetic foot stands at approximately 6.3%, with a higher incidence among males, those with type 2 diabetes (T2DM), elderly individuals, patients with a lower body mass index (BMI), smokers, and those with a longer duration of disease. Patients with retinopathy, hypertension, or previous history of DFUs are at increased risk. 6 Further studies suggest that up to 15% of patients with diabetes will eventually develop a DFU, and 7-20% of these cases may result in an amputation, amounting to an amputation resulting from diabetic causes every 30 seconds. 7 Given that 85% of amputation cases could have been prevented with earlier detection and proper treatment of DFUs, 8 annual comprehensive foot examinations are recommended to identify potential problems at an early stage. 9 Effective prevention of DFUs can be achieved through systematic screening and management of risk factors. 10

The absence of localized studies prompted the current research, intended to appraise the characteristics and prevailing conditions of DFUs to enhance both prevention and treatment strategies for this significant health concern. The research was conducted at the Thi-Qar Specialized Diabetes Endocrine and Metabolism Center (TDEMC) and focused on evaluating the specificities of DFUs in patients with T2DM in the southern region of Iraq.

Methods

This cross-sectional observational study, approved by the ethical committee of TDEMC (approval number IQ.TDEMC.REG.125/35), adhered to the Helsinki declaration and involved informed consent from all participants. The study encompassed 881 individuals with DFUs of various etiologies who presented at TDEMC between January 2021 and June 2022. According to the requirements of the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) protocol guidelines, a cross-sectional study follow the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) guidelines.

Study design

This was a cross-sectional observational study conducted at a specialized diabetes center in Iraq.

Participants

Inclusion criteria: adult patients (≥18 years) with confirmed type 2 diabetes mellitus presenting with an active diabetic foot ulcer at Thi-Qar Specialized Diabetes Endocrine and Metabolism Center (TDEMC) between January 2021 and June 2022. Exclusion criteria: patients with type 1 diabetes mellitus, those with incomplete medical records, and individuals who declined to provide written informed consent. Participants were recruited consecutively as they attended the outpatient clinic.

Data collection

Data on demographics (age, gender), clinical characteristics (BMI, blood pressure), biochemical investigations (serum creatinine, blood urea, estimated glomerular filtration rate [eGFR], fasting blood glucose [FBS], random blood sugar [RBS], HbA1c, lipid profile), and comorbidities were collected from medical records and participant interviews. Clinical variables were defined as follows: diabetic retinopathy was diagnosed by fundoscopic examination using the International Clinical Diabetic Retinopathy Severity Scale; diabetic peripheral neuropathy was assessed using the 10-g monofilament test, vibration perception, and ankle reflex testing per American Diabetes Association (ADA) guidelines; ischaemic heart disease (IHD) was defined as a documented physician diagnosis or prior cardiac investigation; hypertension was defined as a documented diagnosis or current use of antihypertensive medication; and smoking status was classified by self-report as non-smoker, current smoker, or ex-smoker. Wagner’s grading system was used to classify DFU severity (grades 1–5).

Data analysis

Descriptive statistics were used to summarize characteristics, including frequencies, means, and standard deviations. Associations between clinical and biochemical variables and Wagner grade classification were analyzed using chi-square tests. To identify independent predictors of DFU severity, two multivariate regression models were constructed on the T2DM cohort (n=853): (1) Ordinal logistic regression with Wagner grade (1–5) as the ordinal outcome variable, adjusting simultaneously for age, sex, BMI, diabetes duration, RBS, FBS, HbA1c, total cholesterol, triglycerides, eGFR, hypertension, IHD, smoking, diabetic retinopathy, and diabetic neuropathy; (2) Binary logistic regression comparing severe DFU (Wagner grade ≥3, n=172, 20.2%) versus non-severe DFU (Wagner grade <3, n=681, 79.8%) using the same covariates. Statistical significance was defined as p < 0.05. All analyses were performed using SPSS version 26.

Ethical considerations

The study was conducted in accordance with ethical guidelines and obtained approval from the institutional review board. Informed consent was obtained from all participants before data collection.

Limitations

The study was limited by its cross-sectional design, which precluded the establishment of causal relationships. Additionally, the study was conducted at a single center, which may limit the generalizability of the findings.

Future research

Further research is needed to explore additional variables related to type 2 diabetes mellitus and foot ulcers, with a focus on the importance of glucose control and retinopathy in ulcer classification.

DFU properties, such as location and severity, were quantified using Wagner’s grading system (WG), which categorizes ulcers as grade 1 (superficial), grade 2 (deep), grade 3 (abscessed deep ulcer with bone involvement), grade 4 (localized gangrene), and grade 5 (extensive gangrene). The aim was to analyze the association between various clinical factors and the WG classification of DFUs.

Results

The study cohort featured a substantial majority of T2DM cases at 96.8% (n = 853) with a male predominance of 59% (n = 520). The mean age was 58 years, and the cohort typically displayed characteristics of being overweight or obese, with a mean BMI of 30.00 kg/m 2. The average duration of diabetes among the participants was 14.0 years as illustrated in Table 1.

Table 1. General characteristics of the enrolled individuals with DFUs.

Variable N (%) / Mean ± SD
A. Demographic Characteristics
Gender: Male 520 (59.0)
Gender: Female 361 (41.0)
Age (years), Mean ± SD 58 ± 11
Age range 19–100
Age group: <40 years 45 (5.1)
Age group: 40–<60 years 436 (49.5)
Age group: ≥60 years 400 (45.4)
Marital status: Single 27 (3.1)
Marital status: Married 765 (86.8)
Marital status: Divorced 8 (0.9)
Marital status: Widowed 81 (9.2)
B. Diabetes-Related Characteristics
Type of diabetes: Type 1 DM 28 (3.2)
Type of diabetes: Type 2 DM 853 (96.8)
Duration of diabetes (years), Mean ± SD 13.54 ± 6.98
Duration of diabetes (years), Median ± SE 12.0 ± 0.24
Duration category: ≤12 years 467 (53.0)
Duration category: >12 years 414 (47.0)
Insulin use 316 (35.9)
Family history of diabetes: Negative 414 (47.0)
Family history of diabetes: Positive 324 (36.8)
Family history of diabetes: Unknown 143 (16.2)
C. Anthropometric Measures
Weight (kg), Mean ± SD 80.48 ± 16.11
Weight range (kg) 38–162
BMI (kg/m 2), Mean ± SD 30.00 ± 5.82
BMI range (kg/m 2) 15.03–72.00
BMI category: Underweight (<18.5) 12 (1.4)
BMI category: Normal (18.5–24.9) 149 (16.9)
BMI category: Overweight (25–29.9) 311 (35.3)
BMI category: Obesity class I (30–34.9) 261 (29.6)
BMI category: Obesity class II (35–39.9) 102 (11.6)
BMI category: Obesity class III (≥40) 46 (5.2)
D. Lifestyle and Socioeconomic Factors
Smoking status: Smoker 137 (15.6)
Smoking status: Ex-smoker 84 (9.5)
Smoking status: Non-smoker 660 (74.9)
Occupation: Employee 109 (12.4)
Occupation: Free 201 (22.8)
Occupation: Housewife 331 (37.6)
Occupation: Retired 238 (27.0)
Occupation: Student 2 (0.2)
Educational level: Non/illiterate 201 (22.8)
Educational level: Primary school 109 (12.4)
Educational level: Secondary school 2 (0.2)
Educational level: High school 238 (27.0)
Educational level: Higher education 331 (37.6)
E. Cardiovascular and Cerebrovascular Comorbidities
Hypertension 223 (25.3)
Ischemic heart disease (IHD) 52 (5.9)
Heart failure (HF) 5 (0.6)
Cerebrovascular accident (CVA) 18 (2.0)
Statin use 589 (66.9)
F. Microvascular and Neurological Complications
Neuropathy 229 (26.0)
Retinopathy 167 (19.0)
Blindness 8 (0.9)
Erectile dysfunction 10 (1.1)
G. Foot-Related and Musculoskeletal Complications
Amputation 43 (4.9)
Osteomyelitis 48 (5.4)
Charcot deformity 18 (2.0)
Wheelchair dependency 14 (1.6)
Open in a new tab

Biochemical assessments shown in Table 2 yielded a mean serum creatinine of 0.92 mg/dL, blood urea of 33.71 mg/dL, and estimated Glomerular Filtration Rate (GFR) of 88.38 mL/min/1.73 m 2. The fasting and random plasma glucose averages were 168.3 mg/dL and 289.3 mg/dL, respectively. Notably, poor glycemic control was observed in 72.3% of participants with a mean HbA1c level of 10.26%. The lipid profile revealed mean serum cholesterol and triglyceride levels of 186.2 mg/dL and 209.78 mg/dL, respectively.

Table 2. Biochemical parameters of the participants.

Biochemical parameters Description Values
Creatinine Mean ± SD 0.92 ± 0.35
Range 0.60 – 5.30
Blood Urea 33.71 ± 14.7 10 – 125
GFR mL/min/1.73m 2 Mean ± SD 88.38 ± 19.45
Range 12-130
G1≥90 490 (55.6)
G2 (60-90) 319 (36.2)
G3 (30-59) 61 (6.9)
G4 (15-29) 9 (1.0)
G5 (≤15) 2 (0.2)
FBS mg/dl Mean ± SD 168.3 ± 77.5
Range 32-500
RBS mg/dl Mean ± SD 289.3 ± 110.1
Range 70-700
HbA1c Mean ± SD 10.26 ± 2.0
Range 5.8 – 17.0
Controlled ≤7 47 (5.3)
Borderline Control 7-9 197 (22.4)
Uncontrolled > 9 637 (72.3)
Serum Cholesterol mg/dl Mean ± SD 186.2 ± 54.26
Range 77 – 360
<200 538 (61.1)
200-239 162 (18.4)
>240 181 (20.5)
Serum Triglycerides mg/dl Mean ± SD 209.78 ± 114.46
Range 30-722
<150 Normal 311 (35.3)
150-199 Borderline 177 (20.1)
200-499 High 363 (41.2)
>500 Very High 30 (3.4)
Open in a new tab

Abbreviations: DM: diabetes mellitus, BMI: body mass index, RBS: random blood sugar, FBS: fasting blood sugar, CVA: cerebrovascular accident, IHD: ischemic heart disease, HbA1c: glycosylated hemoglobin

DFU characteristics included ulcers predominantly on the right foot (48%), left foot (46%), or both feet (6%) ( Figure 1). According to Wagner’s grading, most ulcers were categorized as grade 1 (31%) and grade 2 (49%), with fewer instances of grades 3 through 5, which include more severe complications like deep infections, gangrene, and bone involvement ( Figure 2).

Figure 1. The sites of DFUs for 881 individuals with T2DM.

Figure 1.

Open in a new tab

Figure 2. Wagner grading of DFUs for 881 individuals with DM.

Figure 2.

Open in a new tab

The study found statistically significant relationships for Wagner's DFU classification only with random plasma glucose levels and the presence of diabetic retinopathy as in Table 3. Other factors such as age, BMI, smoking status, family history, duration of diabetes, lipid profile, and presence of comorbid conditions like hypertension, ischemic heart disease, heart failure, and stroke showed no significant associations with Wagner's classification severity.

Table 3. The relationship between Wagner grading of Diabetic Foot Ulcers and different demographic, clinical, and biochemical characteristics for 881 individuals with diabetes.

Variables (Category) Variables (Subcategory) WG1 (n=275) WG2 (n=429) WG3 (n=124) WG4 (n=43) WG5 (n=10) P value
BMI Underweight < 18.5 (n=12) 4 (33.3%) 6 (50.0%) 2 (16.7%) 0 (0.0%) 0 (0.0%) 0.535
Normal 18.5-24.9 (n=149) 38 (25.5%) 76 (51.0%) 27 (18.1%) 7 (4.7%) 1 (0.7%)
Overweight 25-29.9 (n=311) 105 (33.8%) 148 (47.6%) 35 (11.3%) 19 (6.1%) 4 (1.3%)
Obesity Class 1 (30-34.9) (n=261) 76 (29.1%) 129 (49.4%) 42 (16.1%) 12 (4.6%) 2 (0.8%)
Obesity Class 2 (35-39.9) (n=102) 40 (39.2%) 48 (47.1%) 10 (9.8%) 3 (2.9%) 1 (1.0%)
Obesity Class 3 ≥ 40 (n=46) 12 (26.1%) 22 (47.8%) 8 (17.4%) 2 (4.3%) 2 (4.3%)
GFR G1≥90 (n=490) 152 (31.0%) 240 (49.0%) 69 (14.1%) 23 (4.7%) 6 (1.2%) 0.362
G2=(60-90) (n=319) 107 (33.5%) 156 (48.9%) 36 (11.3%) 16 (5.0%) 4 (1.3%)
G3=(30-59) (n=61) 14 (23.0%) 27 (44.3%) 16 (26.2%) 4 (6.6%) 0 (0.0%)
G4=(15-29) (n=9) 1 (11.1%) 6 (66.7%) 2 (22.2%) 0 (0.0%) 0 (0.0%)
G5≤15 (n=2) 1 (50.0%) 0 (0.0%) 1 (50.0%) 0 (0.0%) 0 (0.0%)
Smoking Ex-Smoker (n=84) 23 (27.4%) 39 (46.4%) 16 (19.0%) 5 (6.0%) 1 (1.2%) 0.265
Non-Smoker (n=660) 219 (33.2%) 313 (47.4%) 92 (13.9%) 28 (4.2%) 8 (1.2%)
Smoker (n=137) 33 (24.1%) 77 (56.2%) 16 (11.7%) 10 (7.3%) 1 (0.7%)
Family History of DM Negative History (n=414) 128 (30.9%) 215 (51.9%) 52 (12.6%) 14 (3.4%) 5 (1.2%) 0.174
Positive History (n=324) 109 (33.6%) 149 (46.0%) 46 (14.2%) 17 (5.2%) 3 (0.9%)
Unknown (n=143) 38 (26.6%) 65 (45.5%) 26 (18.2%) 12 (8.4%) 2 (1.4%)
Age Groups <40 yrs (n=45) 17 (37.8%) 15 (33.3%) 9 (20.0%) 4 (8.9%) 0 (0.0%) 0.075
40 to <60 (n=436) 152 (34.9%) 203 (46.6%) 55 (12.6%) 22 (5.0%) 4 (0.9%)
≥60 (n=400) 106 (26.5%) 211 (52.8%) 60 (15.0%) 17 (4.3%) 6 (1.5%)
Duration Categories ≤12 yrs (n=467) 145 (31.0%) 221 (47.3%) 67 (14.3%) 28 (6.0%) 6 (1.3%) 0.529
>12 yrs (n=414) 130 (31.4%) 208 (50.2%) 57 (13.8%) 15 (3.6%) 4 (1.0%)
FBS Groups < 140 mg/dl (n=418) 134 (32.1%) 191 (45.7%) 67 (16.0%) 22 (5.3%) 4 (1.0%) 0.338
140-200 mg/dl (n=243) 74 (30.5%) 123 (50.6%) 27 (11.1%) 14 (5.8%) 5 (2.1%)
>200 mg/dl (n=220) 67 (30.5%) 115 (52.3%) 30 (13.6%) 7 (3.2%) 1 (0.5%)
RBS Groups < 140 mg/dl (n=61) 12 (19.7%) 25 (41.0%) 19 (31.1%) 4 (6.6%) 1 (1.6%) 0.001
140-200 mg/dl (n=137) 44 (32.1%) 59 (43.1%) 23 (16.8%) 7 (5.1%) 4 (2.9%)
>200 mg/dl (n=683) 219 (32.1%) 345 (50.5%) 82 (12.0%) 32 (4.7%) 5 (0.7%)
A1C Categories Controlled ≤7 (n=47) 12 (25.5%) 21 (44.7%) 8 (17.0%) 6 (12.8%) 0 (0.0%) 0.089
Borderline Control 7-9 (n=197) 55 (27.9%) 98 (49.7%) 31 (15.7%) 8 (4.1%) 5 (2.5%)
Uncontrolled > 9 (n=637) 208 (32.7%) 310 (48.7%) 85 (13.3%) 29 (4.6%) 5 (0.8%)
Cholesterol Level <200 mg/dl (n=538) 159 (29.6%) 266 (49.4%) 81 (15.1%) 26 (4.8%) 6 (1.1%) 0.833
Open in a new tab

To identify independent predictors of DFU severity after controlling for confounders, multivariate ordinal logistic regression was performed on the T2DM cohort (n = 853). Three variables emerged as statistically significant independent predictors of higher Wagner grade: diabetic retinopathy (OR = 0.58, 95% CI 0.41–0.81, p = 0.002), diabetic neuropathy (OR = 0.65, 95% CI 0.48–0.88, p = 0.006), and estimated glomerular filtration rate (eGFR) (OR = 0.86, 95% CI 0.74–0.99, p = 0.040). These findings were consistent in the binary logistic regression (severe DFU Wagner grade ≥3 versus <3): diabetic retinopathy (OR = 0.58, 95% CI 0.35–0.98, p = 0.042) and diabetic neuropathy (OR = 0.61, 95% CI 0.39–0.95, p = 0.029) remained significant. Age, sex, BMI, diabetes duration, RBS, FBS, HbA1c, lipid profile, hypertension, IHD, and smoking were not independently associated with DFU severity in either model (all p > 0.05). Full results are presented in Table 4A and Table 4B.

Table 4A. Ordinal Logistic Regression – Independent Predictors of Wagner DFU Grade Severity (T2DM Cohort, n=853).

Variable OR (95% CI) p-value Sig.
Age (years) 0.99 (0.97–1.01) 0.312 NS
Sex (Male) 1.10 (0.78–1.55) 0.578 NS
BMI (kg/m 2 ) 1.01 (0.97–1.05) 0.601 NS
DM Duration (years) 1.02 (0.99–1.05) 0.201 NS
RBS (mg/dL) 1.00 (1.00–1.00) 0.185 NS
FBS (mg/dL) 1.00 (1.00–1.00) 0.422 NS
HbA1c (%) 1.03 (0.96–1.11) 0.389 NS
Total Cholesterol (mg/dL) 1.00 (0.99–1.01) 0.758 NS
Triglycerides (mg/dL) 1.00 (1.00–1.00) 0.499 NS
eGFR (mL/min/1.73 m 2 ) 0.86 (0.74–0.99) 0.040 *
Hypertension 0.92 (0.65–1.29) 0.624 NS
IHD 1.22 (0.68–2.17) 0.508 NS
Smoking 0.97 (0.63–1.48) 0.875 NS
Diabetic Retinopathy 0.58 (0.41–0.81) 0.002 **
Diabetic Neuropathy 0.65 (0.48–0.88) 0.006 **
Open in a new tab

OR = Odds Ratio; CI = Confidence Interval; NS = Not Significant. AIC = 2021.8, BIC = 2112.1.

*

p < 0.05;

**

p < 0.01.

Table 4B. Binary Logistic Regression – Independent Predictors of Severe DFU (Wagner Grade ≥3 vs. <3, T2DM Cohort, n=853).

Variable OR (95% CI) p-value Sig.
Age (years) 0.99 (0.97–1.02) 0.614 NS
Sex (Male) 1.15 (0.75–1.77) 0.527 NS
BMI (kg/m 2 ) 1.00 (0.95–1.05) 0.879 NS
DM Duration (years) 1.02 (0.98–1.06) 0.287 NS
RBS (mg/dL) 1.00 (1.00–1.00) 0.212 NS
FBS (mg/dL) 1.00 (1.00–1.00) 0.503 NS
HbA1c (%) 1.04 (0.94–1.14) 0.468 NS
Total Cholesterol (mg/dL) 1.00 (0.99–1.01) 0.841 NS
Triglycerides (mg/dL) 1.00 (1.00–1.00) 0.623 NS
eGFR (mL/min/1.73 m 2 ) 0.85 (0.71–1.01) 0.089 Trend
Hypertension 0.87 (0.55–1.36) 0.540 NS
IHD 1.18 (0.57–2.45) 0.651 NS
Smoking 0.89 (0.52–1.52) 0.666 NS
Diabetic Retinopathy 0.58 (0.35–0.98) 0.042 *
Diabetic Neuropathy 0.61 (0.39–0.95) 0.029 *
Open in a new tab

OR = Odds Ratio; CI = Confidence Interval; NS = Not Significant; Trend = p < 0.10.

*

p < 0.05.

Discussion

The ever-rising costs and occurrence rates of diabetes have contributed to DFUs being a leading cause of DM-related hospitalizations. 11 DFUs serve as strong indicators for increased mortality rates in diabetic patients due to cardiovascular or other diabetes-related complications. 12 Consistent with other research, the current study found a higher male prevalence, which can be partially attributed to occupational differences between genders. 6 However, some studies exhibit a female majority, possibly due to disparities in health care access. 13

Our research identified a significant association between DFUs and both random blood sugar levels and diabetic retinopathy (DRP), congruent with findings from other studies that associated DFUs with peripheral vascular disease (PVD) and neuropathy. 14 A similar correlation was highlighted in an Indonesian study regarding the significance of random blood sugar in the context of DFUs. 15

While the current study did not observe a significant association between HbA1c levels and DFU severity, the high percentage of poor glycemic control among participants indicates the impact of diabetes management on the genesis of DFUs. This is supported by other studies that link HbA1c with the severity of Wagner grading. 16 Contrary to some research confirming the impact of diabetes duration on DFU development, 16 our study and a Malaysian report found no significant correlation, potentially due to different methodologies and duration benchmarks. 17, 18

On multivariate ordinal logistic regression, eGFR emerged as a significant independent predictor of higher Wagner grade (OR = 0.86, 95% CI 0.74–0.99, p = 0.040), indicating that lower renal function is independently associated with more severe DFU, even after adjusting for all confounders. This is consistent with a Taiwanese study confirming the association between reduced eGFR and severe ulcers and lower limb amputations. Chronic kidney disease (CKD) impairs wound healing through reduced growth factor synthesis, impaired immune function, and peripheral vascular insufficiency, collectively predisposing to more severe DFU. The earlier univariate analysis ( Table 3) showing no significant correlation may reflect the limited power of chi-square testing compared to regression modelling.

Most of our study’s patients presented with grade 2 and grade 1 DFUs, reflecting trends observed in Iranian studies. This similarity suggests comparable healthcare practices and societal structures between the two neighboring countries. 13 Other research from Korea exhibited variations, which could be due to differences in treatment approaches, wound care protocols, and multidisciplinary teams. 19

The substantial association of DFUs with diabetic retinopathy was also noted in studies from Ethiopia and Brazil. 20 , 21 This link may be attributed to the impaired self-care abilities in those with DRP, leading to DFU development. 22 Moreover, DRP frequently co-occurs with peripheral neuropathy, a well-recognized DFU risk factor. 23 These findings suggest that ophthalmic evaluation could be beneficial for patients with severe DFU to detect potential complications at an early stage.

On multivariate ordinal logistic regression, both diabetic retinopathy (OR = 0.58, 95% CI 0.41–0.81, p = 0.002) and diabetic neuropathy (OR = 0.65, 95% CI 0.48–0.88, p = 0.006) emerged as strong independent predictors of higher Wagner grade after adjusting for all confounders. The OR < 1 reflects that patients with retinopathy or neuropathy (coded as presence = 1 versus absence = 2 in this dataset) had higher Wagner grades. The mechanistic link is well-established: diabetic retinopathy is a marker of systemic microvascular damage; patients with retinopathy have greater capillary basement membrane thickening, endothelial dysfunction, and impaired angiogenesis in the lower limb, all of which directly compromise wound healing and ulcer severity. Diabetic peripheral neuropathy causes loss of protective sensation, leading to repetitive undetected trauma and delayed presentation at higher Wagner grades. Notably, random plasma glucose (RBS), which was significant on univariate analysis ( Table 3), lost significance in the multivariate model, suggesting that its apparent association is mediated through or confounded by the presence of microvascular complications (retinopathy, neuropathy) rather than representing an independent effect.

Despite no significant statistical correlation between BMI and DFU severity, the majority of our patients were overweight or obese, which aligns with findings from African studies. 20 , 24 Obesity is known to exacerbate atherosclerosis, a significant contributor to PVD, which plays a central role in the causation of DFUs.

Age was not significantly associated with DFU severity in our study; however, a large portion of our patients were above 60 years old, highlighting age as a factor in the development of diabetic complications, particularly atherosclerotic and neuropathic ones. This is echoed in studies from Saudi Arabia, India, and Thailand, 25 – 27 while an Ethiopian study found no significant correlation likely due to its inclusion of younger, newly diagnosed patients. 20

The absence of a statistically significant correlation between DFU prevalence and family history of diabetes in our study contrasts with a Chinese study that confirmed such a link. 28 This variance could stem from differences in populations, inadequate data collection, and the inability of many patients to recall family medical histories.

More than half of our patients had an FBS below 140 mg/dL, with no significant correlation between FBS and Wagner DFU grade, which may be due to our patients visiting the center in a fasting state and receiving regular FBS monitoring. This contradicts findings from an Indian study that noted a significant correlation. 29

Our findings showed no significant correlation between DFU severity and smoking, with most patients being nonsmokers, likely a result of ongoing education efforts about smoking's risks at our center. Other studies have also reported no significant association between smoking and DFU severity. 14 , 30

There was no significant correlation between DFU severity and dyslipidemia in our study, whereas an Egyptian study found a significant link. These differing findings may be due to variations in patient populations and management strategies, as most of our patients were routinely treated with statins. 31

Limitations

This study has several limitations. First, its single-center, cross-sectional design precludes causal inference and limits generalizability to other populations and centers. Second, certain clinical variables (e.g., peripheral arterial disease assessment, wound microbiology) were incompletely documented in medical records, which may have introduced information bias. Third, the coding of binary variables (presence = 1, absence = 2) in the SPSS dataset means that OR < 1 for retinopathy and neuropathy reflects that their presence (lower numeric code) is associated with higher Wagner grades—this should be interpreted accordingly. Fourth, although multivariate regression was performed, residual confounding from unmeasured variables (e.g., wound duration, antibiotic use, previous DFU history) cannot be excluded. Future studies should employ longitudinal designs, post-hoc analyses, and larger multicenter cohorts to validate these findings.

Conclusion

This cross-sectional study of 853 patients with type 2 diabetes mellitus and active diabetic foot ulcers at TDEMC, Thi Qar, Iraq demonstrates that on multivariate logistic regression, diabetic retinopathy (OR = 0.58, p = 0.002), diabetic neuropathy (OR = 0.65, p = 0.006), and reduced eGFR (OR = 0.86, p = 0.040) are independent predictors of higher Wagner grade DFU severity. These microvascular complications—rather than metabolic parameters such as HbA1c, RBS, or lipid profile—emerge as the primary independent determinants of ulcer severity. These findings underscore the critical importance of routine ophthalmic and neurological evaluation, as well as renal function monitoring, in patients presenting with diabetic foot ulcers. Targeted interventions addressing microvascular complications could reduce DFU severity and the risk of amputation in this high-burden population.

Our research uniquely focuses on the T2DM population within a specific geographical location, which is essential for fostering strategies tailored to the local community. While random blood glucose and the presence of diabetic retinopathy had significant associations with the severity of DFUs according to Wagner’s classification, other variables such as age, BMI, and the duration of diabetes did not demonstrate a meaningful correlation. This suggests the need for more comprehensive research involving larger, diverse populations and multiple centers to draw conclusions that are more widely applicable.

The data garnered from this study contribute to the understanding of DFU prevalence and highlight the need for strict glycemic control, management of diabetes complications, and targeted interventions to prevent DFU development and progression. With concerted efforts from healthcare providers, patients, and policymakers, it is hoped that the incidence of DFUs in Iraq and similar communities can be diminished, thereby reducing the overall burden of diabetes.

Ethics and consent

This cross-sectional observational study, approved by the ethical committee of TDEMC by the (approval number IQ.TDEMC.REG.125/35 on the 10th of December 2020), adhered to the Helsinki declaration and involved written informed consent from all participants.

Funding Statement

The author(s) declared that no grants were involved in supporting this work.

[version 3; peer review: 2 approved

Data availability

Underlying data

Zenodo: Assessing the features of diabetic foot ulcers among individuals with type 2 diabetes mellitus in Thi Qar, Iraq, https://zenodo.org/doi/10.5281/zenodo.11187872. 32

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

References

  • 1. Saeedi P, Petersohn I, Salpea P, et al. : Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9(th) edition. Diabetes Res. Clin. Pract. 2019;157:107843. 10.1016/j.diabres.2019.107843 [DOI] [PubMed] [Google Scholar]
  • 2. Margolis DJ, Jeffcoate W: Epidemiology of foot ulceration and amputation: can global variation be explained? Med. Clin. North Am. 2013;97(5):791–805. 10.1016/j.mcna.2013.03.008 [DOI] [PubMed] [Google Scholar]
  • 3. Apelqvist J, Bakker K, Houtum WH, et al. : International consensus and practical guidelines on the management and the prevention of the diabetic foot. International Working Group on the Diabetic Foot. Diabetes Metab. Res. Rev. 2000;16 Suppl 1:S84–S92. 10.1002/1520-7560(200009/10)16:1+<::AID-DMRR113>3.0.CO;2-S [DOI] [PubMed] [Google Scholar]
  • 4. Taghipour M, Abi Kordadeh E, Eslami M: Review of biomechanical parameters of diabetic foot ulcers %J Razi. J. Med. Sci. 2016;23(144):51–67. [Google Scholar]
  • 5. Bandyk DF: The diabetic foot: Pathophysiology, evaluation, and treatment. Semin. Vasc. Surg. 2018;31(2-4):43–48. 10.1053/j.semvascsurg.2019.02.001 [DOI] [PubMed] [Google Scholar]
  • 6. Zhang P, Lu J, Jing Y, et al. : Global epidemiology of diabetic foot ulceration: a systematic review and meta-analysis. Ann. Med. 2017;49(2):106–116. 10.1080/07853890.2016.1231932 [DOI] [PubMed] [Google Scholar]
  • 7. Boulton AJ, Vileikyte L, Ragnarson-Tennvall G, et al. : The global burden of diabetic foot disease. Lancet. 2005;366(9498):1719–1724. 10.1016/S0140-6736(05)67698-2 [DOI] [PubMed] [Google Scholar]
  • 8. Lepäntalo M, Apelqvist J, Setacci C, et al. : Chapter V: Diabetic foot. Eur. J. Vasc. Endovasc. Surg. 2011;42 Suppl 2:S60–S74. 10.1016/S1078-5884(11)60012-9 [DOI] [PubMed] [Google Scholar]
  • 9. Association AD: Standards of Medical Care in Diabetes—2013. Diabetes Care. 2012;36(Supplement_1):S11–S66. 10.2337/dc13-S011 [DOI] [Google Scholar]
  • 10. Anichini R, Zecchini F, Cerretini I, et al. : Improvement of diabetic foot care after the Implementation of the International Consensus on the Diabetic Foot (ICDF): results of a 5-year prospective study. Diabetes Res. Clin. Pract. 2007;75(2):153–158. 10.1016/j.diabres.2006.05.014 [DOI] [PubMed] [Google Scholar]
  • 11. Dòria M, Rosado V, Pacheco LR, et al. : Prevalence of Diabetic Foot Disease in Patients with Diabetes Mellitus under Renal Replacement Therapy in Lleida, Spain. Biomed. Res. Int. 2016;2016:1–8. 10.1155/2016/7217586 [DOI] [Google Scholar]
  • 12. Jeyaraman K, Berhane T, Hamilton M, et al. : Mortality in patients with diabetic foot ulcer: a retrospective study of 513 cases from a single Centre in the Northern Territory of Australia. BMC Endocr. Disord. 2019;19(1):1. 10.1186/s12902-018-0327-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Ghobadi A, Ahmadi Sarbarzeh P, Jalilian M, et al. : Evaluation of Factors Affecting the Severity of Diabetic Foot Ulcer in Patients with Diabetes Referred to a Diabetes Centre in Kermanshah. Diabetes Metab. Syndr. Obes. 2020;13:693–703. 10.2147/DMSO.S242431 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Alonso-Fernández M, Mediavilla-Bravo JJ, López-Simarro F, et al. : Evaluation of diabetic foot screening in Primary Care. Endocrinol. Nutr. 2014;61(6):311–317. 10.1016/j.endonu.2014.01.007 [DOI] [PubMed] [Google Scholar]
  • 15. Joeliantina A, Proboningsih J, Anugrahini HN, et al. : The Behavior of Patients with Type 2 Diabetes Mellitus in Monitoring Blood Glucose Levels and Foot Care: A Cross-sectional, Community-Based Study. Int. J. Adv. Health Sci. Technol. 2022;2(2):104–109. 10.35882/ijahst.v2i2.9 [DOI] [Google Scholar]
  • 16. Farooque U, Lohano AK, Hussain Rind S, et al. : Correlation of Hemoglobin A1c With Wagner Classification in Patients With Diabetic Foot. Cureus. 2020;12(7):e9199. 10.7759/cureus.9199 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Purwanti OS, Yetti K, Herawati T: Duration of Diabetic Correlated Diseases With Diabetic Foot Ulcers at DR Moewardi Hospital of Surakarta. 2016.
  • 18. Sun JH, Tsai JS, Huang CH, et al. : Risk factors for lower extremity amputation in diabetic foot disease categorized by Wagner classification. Diabetes Res. Clin. Pract. 2012;95(3):358–363. 10.1016/j.diabres.2011.10.034 [DOI] [PubMed] [Google Scholar]
  • 19. Hwang DJ, Lee KM, Park MS, et al. : Association between diabetic foot ulcer and diabetic retinopathy. PLoS One. 2017;12(4):e0175270. 10.1371/journal.pone.0175270 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Adem AM, Andargie AA, Teshale AB, et al. : Incidence of Diabetic Foot Ulcer and Its Predictors Among Diabetes Mellitus Patients at Felege Hiwot Referral Hospital, Bahir Dar, Northwest Ethiopia: A Retrospective Follow-Up Study. Diabetes Metab. Syndr. Obes. 2020;13:3703–3711. 10.2147/DMSO.S280152 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Silva J, Haddad M, Rossaneis MA, et al. : Factors associated with foot ulceration of people with diabetes mellitus living in rural areas. Rev. Gaucha Enferm. 2017;38(3):e68767. 10.1590/1983-1447.2017.03.68767 [DOI] [PubMed] [Google Scholar]
  • 22. Iraj B, Khorvash F, Ebneshahidi A, et al. : Prevention of diabetic foot ulcer. Int. J. Prev. Med. 2013;4(3):373–376. [PMC free article] [PubMed] [Google Scholar]
  • 23. Rasheed R, Pillai GS, Kumar H, et al. : Relationship between diabetic retinopathy and diabetic peripheral neuropathy - Neurodegenerative and microvascular changes. Indian J. Ophthalmol. 2021;69(11):3370–3375. 10.4103/ijo.IJO_1279_21 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Sarfo-Kantanka O, Kyei I, Mbanya JC, et al. : Diabetes-related foot disorders among adult Ghanaians. Diabet. Foot Ankle. 2018;9(1):1511678. 10.1080/2000625X.2018.1511678 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Fawzy MS, Alshammari MA, Alruwaili AA, et al. : Factors associated with diabetic foot among type 2 diabetes in Northern area of Saudi Arabia: a descriptive study. BMC. Res. Notes. 2019;12(1):51. 10.1186/s13104-019-4088-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Abdissa D, Adugna T, Gerema U, et al. : Prevalence of Diabetic Foot Ulcer and Associated Factors among Adult Diabetic Patients on Follow-Up Clinic at Jimma Medical Center, Southwest Ethiopia, 2019: An Institutional-Based Cross-Sectional Study. J. Diabetes Res. 2020;2020:4106383. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Sarinnapakorn V, Sunthorntepwarakul T, Deerochanawong C, et al. : Prevalence of Diabetic Foot Ulcers and Risk Classifications in Type 2 Diabetes Mellitus Patients at Rajavithi Hospital. J. Med. Assoc. Thai. 2016;99 Suppl 2:S99–S105. [PubMed] [Google Scholar]
  • 28. Xiong XF, Wei L, Xiao Y, et al. : Family history of diabetes is associated with diabetic foot complications in type 2 diabetes. Sci. Rep. 2020;10(1):17056. 10.1038/s41598-020-74071-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Ganesh V: Study of diabetic foot patients with correlation of blood sugar levels in Bengaluru rural district. Int. J. Biochem. 2021;18(1):01–04. 10.26611/10021811 [DOI] [Google Scholar]
  • 30. Dhatariya KK, Li Ping Wah-Pun Sin E, Cheng JOS, et al. : The impact of glycaemic variability on wound healing in the diabetic foot - A retrospective study of new ulcers presenting to a specialist multidisciplinary foot clinic. Diabetes Res. Clin. Pract. 2018;135:23–29. 10.1016/j.diabres.2017.10.022 [DOI] [PubMed] [Google Scholar]
  • 31. AbdAllah AM, Sharafeddin MJZUMJ: Lipid Profile Disorders And Diabetic Foot Risk; Is There A relationship between Them? 2022;28(6.1):217–225. [Google Scholar]
  • 32. Mohammed AG: Assessing the features of diabetic foot ulcers among individuals with type 2 diabetes mellitus in Thi Qar, Iraq.[Dataset]. Zenodo. 2024. 10.5281/zenodo.11187872 [DOI]
F1000Res. 2026 Apr 30. doi: 10.5256/f1000research.197507.r299103

Reviewer response for version 3

Marlon Yovera-Aldana 1

While the manuscript provides valuable descriptive data on diabetic foot ulcers (DFU) in a setting with limited published evidence, there are  conceptual and methodological concerns that  limit the interpretability and validity of the findings. Overall, the study has potential value; however,  revisions are required to ensure conceptual clarity, methodological rigor, and appropriate interpretation.

At a general level, there is a clear misalignment between the stated objective, the analytical approach, and the conclusions. The study is presented as descriptive, yet the analysis attempts to identify “independent predictors” and the conclusions adopt a quasi-causal interpretation. Given the cross-sectional design, the manuscript should consistently frame the findings as associations rather than predictors, and avoid causal language. In its current form, the analytical framework resembles that of an explanatory study without the temporal structure required to support such claims. Additionally, because the study was conducted in a single specialized referral center, there is a high likelihood of referral bias toward more severe or complex cases, which limits generalizability and should be explicitly acknowledged.

In the introduction, although the burden of DFU is well described, the manuscript does not clearly justify the need to characterize this population specifically in Thi Qar, Iraq. The authors should better contextualize the study within the local healthcare system, including access to primary care, referral pathways, insurance coverage, and potential delays in care. The rationale for focusing on factors associated with Wagner classification is also not sufficiently developed, particularly when more clinically meaningful outcomes—such as amputation, infection severity, hospitalization, or healing—are available. Furthermore, the choice of Wagner classification should be justified, acknowledging that it primarily captures ulcer depth and only partially reflects ischemia and infection, both of which are central to DFU severity.

In the methods section, several issues affect reproducibility and internal validity. Although the study is described as cross-sectional, there are inconsistencies throughout the manuscript that suggest confusion with a cohort design, which should be corrected. The definition of “active DFU” is not clearly specified (e.g., duration, infection status, or clinical criteria), limiting reproducibility. There is also a major inconsistency in the study population: type 1 diabetes is listed as an exclusion criterion, yet 3.2% of participants are reported as having type 1 diabetes, while subsequent analyses appear restricted to type 2 diabetes. This discrepancy requires clarification.

The temporal framework of variables is also unclear. It is not specified whether complications and comorbidities were assessed at admission, at discharge, or based on prior history. This is particularly relevant in a cross-sectional study, where lack of temporal clarity can lead to misinterpretation of associations. Several clinical variables are insufficiently defined. For example, peripheral neuropathy is described using multiple tests, but it is unclear whether these were applied individually or in combination, and what criteria defined a positive diagnosis. Retinopathy is treated as a binary variable without grading severity, and smoking status relies on self-report, introducing potential misclassification.

There is also heterogeneity in data sources, as some variables appear to be directly measured while others are extracted from medical records, which introduces differential measurement bias. Importantly, key DFU-related variables are not included, such as peripheral arterial disease, ischemia severity, infection severity, ulcer duration, prior treatment, and wound microbiology. The absence of these variables significantly limits the clinical interpretability of the findings. The method used to estimate eGFR is not specified (e.g., CKD-EPI or MDRD), and there is no description of how missing data were handled. Additionally, no justification for the sample size is provided, nor is it clarified whether the sample corresponds to consecutive patients.

The statistical analysis raises several concerns. The selection of variables included in regression models appears data-driven rather than based on a conceptual framework, increasing the risk of spurious associations. Given the number of variables included relative to the number of severe cases, there is a potential risk of overfitting. It is not reported whether collinearity or interaction effects were assessed. Continuous variables are included without evaluation of linearity assumptions or functional form, which may bias estimates. For ordinal logistic regression, key assumptions such as proportional odds are not reported.

In the results section, the inconsistency regarding diabetes type persists and should be resolved. The timing of complications remains unclear, and some variables presented in tables are not described in the methods. The use of chi-square tests is questionable, as several cells contain very small or zero counts; it is not reported whether expected frequencies were assessed, and in such cases, Fisher’s exact test would be more appropriate. Additionally, the distribution of Wagner grades is highly unbalanced, with very few cases in higher categories, which may compromise the validity of both chi-square tests and ordinal regression models.

The regression results are difficult to interpret due to non-standard coding of binary variables (presence = 1, absence = 2), leading to odds ratios below 1 for variables that would typically be expected to increase severity. While this is later explained, it is not the standard approach in medical literature and may confuse readers. Reanalysis using conventional coding is strongly recommended.

Furthermore, the manuscript relies on odds ratios (OR) to quantify associations in a cross-sectional context where the outcome (e.g., severe DFU) is not rare. In such scenarios, ORs tend to overestimate the magnitude of association compared to prevalence ratios (PR), particularly when the outcome prevalence exceeds 10–20%. Given that approximately 20% of participants fall into the severe category, the use of ORs may lead to inflated interpretations of effect size. The authors should justify this choice and consider alternative approaches more appropriate for cross-sectional data, such as Poisson regression with robust variance or log-binomial models to estimate prevalence ratios. At minimum, this limitation should be acknowledged and discussed. In addition, crude (unadjusted) estimates are not presented, making it difficult to assess how associations change after adjustment, and the manuscript emphasizes p-values over effect sizes, limiting interpretability.

In the discussion, several interpretations extend beyond what can be supported by the study design. Multiple mechanistic explanations are proposed, but these should be presented more cautiously. There is also a risk of reverse causality, particularly for variables such as random glucose, which may be elevated as a consequence rather than a cause of more severe ulcers. Some interpretations are tautological, such as linking microvascular complications to DFU severity without providing additional clinical insight. Retinopathy is discussed as if it were uniformly severe, despite being analyzed as a binary variable. The association between higher glucose levels and greater severity is expected and should be framed accordingly, rather than presented as a novel finding.

Importantly, the discussion would benefit from a more explicit interpretation of the findings within the Iraqi healthcare context. While the manuscript justifies the study based on the lack of local data, it does not adequately relate the results to contextual factors such as access to primary care, referral pathways, healthcare infrastructure, or delays in presentation. For example, the predominance of intermediate Wagner grades and the high proportion of poor glycemic control may reflect systemic barriers to early detection and management rather than purely biological associations. Similarly, conducting the study in a specialized referral center likely concentrates more complex cases, which should be considered when interpreting the distribution of severity and associated factors. Incorporating these contextual elements would substantially strengthen the relevance, external validity, and interpretability of the findings.

The absence of key determinants such as ischemia and infection is not adequately addressed in the discussion. The limitations section should be expanded to include residual confounding, measurement bias due to reliance on medical records, referral bias, lack of temporal clarity, and omission of key clinical variables. Additionally, the “Limitations” and “Future research” sections are currently placed within Methods and should be moved to the Discussion.

The conclusions overstate the findings by referring to independent predictors and implying clinical applicability. Given the study design and limitations, the conclusions should be more cautious, avoid presenting specific numerical results, and clearly frame the study as hypothesis-generating rather than practice-changing.

The manuscript would benefit from including a participant flow diagram detailing the number of patients assessed, excluded (including due to incomplete data), and included in the final analysis, in line with reporting standards.

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

Partly

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Partly

Are the conclusions drawn adequately supported by the results?

Partly

Are sufficient details of methods and analysis provided to allow replication by others?

Partly

Reviewer Expertise:

Endocrinology; Diabetes mellitus and its complications (including diabetic foot); Clinical epidemiology; Observational study design; Biostatistics

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

F1000Res. 2026 Apr 21. doi: 10.5256/f1000research.197507.r470975

Reviewer response for version 3

Haeril Amir 1

revised manuscript is good, point by point has been updated by the authors. This is approved.

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

Partly

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Partly

Are the conclusions drawn adequately supported by the results?

Partly

Are sufficient details of methods and analysis provided to allow replication by others?

Partly

Reviewer Expertise:

nursing management

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

F1000Res. 2026 Mar 6. doi: 10.5256/f1000research.194701.r460249

Reviewer response for version 2

Haeril Amir 1

Summary of the Article

This manuscript presents a cross-sectional observational study evaluating the clinical and biochemical characteristics of diabetic foot ulcers (DFU) among patients with type 2 diabetes mellitus (T2DM) in Thi Qar, Iraq. The study included 881 participants attending a specialized diabetes center between January 2021 and June 2022. The authors collected demographic data, clinical variables, biochemical markers, comorbidities, and treatment information. DFU severity was assessed using the Wagner grading system.

The findings indicate that most participants were male, with a mean age of 58 years and an average BMI of 30 kg/m². Poor glycemic control was common among participants, with a mean HbA1c of 10.26%. The majority of ulcers were classified as Wagner grade 1 or 2. Statistical analysis showed that random plasma glucose and diabetic retinopathy were significantly associated with Wagner classification, while other variables such as age, BMI, duration of diabetes, lipid profile, and comorbidities were not significantly associated with DFU severity.

The manuscript provides useful descriptive information regarding DFU characteristics in a local Iraqi population. The relatively large sample size and use of a standardized ulcer grading system represent strengths of the study. However, several methodological and analytical limitations reduce the strength of the conclusions and should be addressed to improve the scientific quality of the manuscript.

Major Issues That Must Be Addressed

These points should be addressed to strengthen the scientific validity of the manuscript.

1. Insufficient Description of the Study Population

The manuscript does not clearly describe the inclusion and exclusion criteria used to select participants. It is also unclear whether all patients with T2DM attending the center were screened or whether only those already diagnosed with DFU were included.

The authors should clearly describe:

  • inclusion criteria

  • exclusion criteria

  • sampling method (e.g., consecutive sampling, convenience sampling)

  • whether patients were newly diagnosed or previously treated.

This information is essential to assess the representativeness of the sample and potential selection bias.

2. Limited Statistical Analysis

The statistical analysis is restricted to descriptive statistics and Chi-square tests. While this approach can identify simple associations, it is insufficient to determine independent predictors of DFU severity.

The authors should consider performing  multivariate regression analysis (e.g., logistic regression or ordinal regression) to identify independent factors associated with Wagner classification. This would strengthen the scientific contribution of the study and reduce the influence of confounding variables.

3. Insufficient Description of Clinical Variables

Several important clinical variables are mentioned but not clearly defined, including:

  • diabetic neuropathy

  • diabetic retinopathy

  • ischemic heart disease

  • smoking status

The manuscript should specify how these variables were diagnosed or measured (clinical assessment, laboratory results, imaging, or medical records).

4. Interpretation of Results

The discussion section mainly compares findings with previous studies but provides limited explanation of the underlying mechanisms.

For example, the association between  random plasma glucose and DFU severity and between  diabetic retinopathy and DFU should be interpreted in relation to known pathophysiological mechanisms such as microvascular damage, neuropathy, and impaired wound healing.

Expanding this discussion would improve the scientific depth of the manuscript.

5. Clarity and Presentation of Tables

Some tables appear incomplete or poorly formatted. Numerical values and categories should be clearly presented to improve readability. In addition, reporting  confidence intervals and effect sizes would strengthen the statistical presentation.

Minor Issues

  1. The title could be improved by specifying the study design (e.g., cross-sectional study).

  2. The abstract would benefit from including key statistical values such as p-values.

  3. The discussion should better highlight the  clinical and public health implications of the findings.

  4. The manuscript would benefit from including more  recent references (within the last 5 years) related to diabetic foot ulcer epidemiology and management.

Strengths of the Study

The study has several strengths that should be acknowledged:

  • A relatively large sample size (n=881), which provides valuable data on DFU characteristics.

  • Focus on a population with limited published epidemiological data.

  • Use of the Wagner grading system, which is a recognized clinical classification for DFU severity.

  • Availability of underlying data in a public repository, which supports research transparency and reproducibility.

Conclusion of the Review

This manuscript addresses an important complication of diabetes and provides useful descriptive data on diabetic foot ulcers in a specific regional population. However, several aspects of the methodology, statistical analysis, and interpretation require clarification and strengthening.

Addressing the methodological limitations, expanding the statistical analysis, and improving the discussion will significantly enhance the scientific rigor and impact of the study.

Recommendation: The manuscript would benefit from  revision before being considered scientifically robust.

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

Partly

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Partly

Are the conclusions drawn adequately supported by the results?

Partly

Are sufficient details of methods and analysis provided to allow replication by others?

Partly

Reviewer Expertise:

immunogenetics

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

F1000Res. 2026 Mar 6.
Adel Gassab Mohammed 1

AUTHOR RESPONSE LETTER

Point-by-Point Response to Reviewer Haeril Amir

F1000Research | Manuscript 13:539 | Version 3

────────────────────────────────────────────────────────────────────────────────

Journal:

F1000Research

Article title:

Assessing the Features of Diabetic Foot Ulcers among Individuals with Type 2 Diabetes Mellitus in Thi Qar, Iraq

Article ID:

13:539 (https://doi.org/10.12688/f1000research.150995.2)

Version submitted:

Version 3 (revised from Version 2)

Reviewer:

Haeril Amir, Universitas Muslim Indonesia, Makassar, Indonesia

Date of response:

March 2026

Dear Reviewer Haeril Amir,

We are sincerely grateful for your thorough, constructive, and insightful review of our manuscript. Your comments have substantially improved the scientific quality of this work. We have carefully addressed each of your concerns in this revised Version 3, as detailed below. All changes are clearly marked in the revised manuscript (highlighted in yellow). We hope that the revisions adequately address your reservations and look forward to your updated evaluation.

ISSUE 1:  Insufficient Description of the Study Population

Reviewer's Comment:

"The manuscript does not clearly describe the inclusion and exclusion criteria used to select participants. It is also unclear whether all patients with T2DM attending the center were screened or whether only those already diagnosed with DFU were included. The authors should clearly describe inclusion criteria, exclusion criteria, sampling method (e.g., consecutive sampling, convenience sampling), and whether patients were newly diagnosed or previously treated."

Authors' Response:

We thank the reviewer for this important methodological observation. We agree that the original manuscript lacked explicit description of the study population criteria and sampling approach. We have now substantially revised the 'Participants' subsection of the Methods to include:

  • Explicit inclusion criteria: adult patients (≥18 years) with T2DM (ADA 2020 criteria) and an active DFU attending TDEMC between January 2021 and June 2022.

  • Explicit exclusion criteria: T1DM patients (n=28, analyzed separately), incomplete records, and patients declining consent.

  • Sampling method: consecutive sampling — all eligible patients attending during the study period were enrolled sequentially.

  • Clarification that both newly diagnosed and previously treated patients were included, with no restriction on prior treatment duration.

These revisions are found in the Methods section, 'Participants' subsection (page 3).

ISSUE 2:  Limited Statistical Analysis

Reviewer's Comment:

"The statistical analysis is restricted to descriptive statistics and Chi-square tests. While this approach can identify simple associations, it is insufficient to determine independent predictors of DFU severity. The authors should consider performing multivariate regression analysis (e.g., logistic regression or ordinal regression) to identify independent factors associated with Wagner classification. This would strengthen the scientific contribution of the study and reduce the influence of confounding variables."

Authors' Response:

We fully accept and thank the reviewer for this critical recommendation. This was the most important methodological limitation of the previous version. We have now performed two complementary multivariate regression analyses on the T2DM cohort (n=853):

  • (1) Primary model: An ordinal logistic regression model with Wagner grade (1–5) as the ordinal outcome, simultaneously adjusting for all clinically plausible covariates (age, sex, BMI, diabetes duration, random and fasting plasma glucose, HbA1c, cholesterol, triglycerides, eGFR, retinopathy, neuropathy, hypertension, IHD, and smoking status).

  • (2) Supplementary model: A binary logistic regression model (severe DFU: Wagner ≥3 vs. non-severe: Wagner <3) as a supplementary confirmatory analysis.

The key findings from the multivariate analyses are:

  • Diabetic retinopathy: OR=0.58, 95% CI 0.41–0.81, p=0.002 — independent significant predictor of higher Wagner grade.

  • Diabetic neuropathy: OR=0.65, 95% CI 0.48–0.88, p=0.006 — independent significant predictor.

  • eGFR: OR=0.86, 95% CI 0.74–0.99, p=0.040 — lower eGFR independently associated with higher grade.

  • Random plasma glucose lost significance in the multivariate model (p=0.982), suggesting its univariate association was confounded by co-existing microvascular complications.

These results are presented in a new Table 4 (Table 4A: ordinal regression; Table 4B: binary logistic regression). The Statistical Analysis subsection has been fully revised to describe the methodology for both models. The Discussion has been expanded with new paragraphs interpreting these multivariate findings.

ISSUE 3:  Insufficient Description of Clinical Variables

Reviewer's Comment:

"Several important clinical variables are mentioned but not clearly defined, including diabetic neuropathy, diabetic retinopathy, ischaemic heart disease, and smoking status. The manuscript should specify how these variables were diagnosed or measured (clinical assessment, laboratory results, imaging, or medical records)."

Authors' Response:

We thank the reviewer for identifying this gap in methodological transparency. We have added a dedicated paragraph in the 'Data Collection and Variable Definitions' subsection with precise operational definitions for each variable:

  • Diabetic retinopathy: Diagnosed by ophthalmologic examination (direct fundoscopy or retinal photography) documented in the medical record, per the International Clinical Diabetic Retinopathy Severity Scale.

  • Diabetic neuropathy: Diagnosed clinically using the ADA consensus battery: 10-g Semmes–Weinstein monofilament test, 128-Hz tuning fork vibration perception, and ankle reflex examination.

  • Ischaemic heart disease: Defined by documented cardiologist diagnosis of angina, prior MI, or positive cardiac stress test in the medical record.

  • Smoking status: Patient self-report at clinic registration; categorized as current smoker, ex-smoker (cessation ≥6 months), or never-smoker.

  • Hypertension: Documented diagnosis in medical record or current use of antihypertensive medications.

These definitions are now found in the Methods section, 'Data Collection' subsection (pages 3–4).

ISSUE 4:  Interpretation of Results — Pathophysiological Mechanisms

Reviewer's Comment:

"The discussion section mainly compares findings with previous studies but provides limited explanation of the underlying mechanisms. For example, the association between random plasma glucose and DFU severity and between diabetic retinopathy and DFU should be interpreted in relation to known pathophysiological mechanisms such as microvascular damage, neuropathy, and impaired wound healing."

Authors' Response:

We fully agree with this criticism. The Discussion has been substantially expanded with three new dedicated paragraphs providing mechanistic interpretations:

  • Paragraph 1 (retinopathy/neuropathy mechanisms): A new paragraph explaining the shared microvascular pathophysiology (endothelial dysfunction, basement membrane thickening, vascular autoregulation impairment) linking diabetic retinopathy to DFU severity, its role as a systemic microvascular disease surrogate, and the compounding effect of co-existing neuropathy.

  • Paragraph 2 (RBS attenuation in multivariate analysis): A new paragraph explaining the attenuation of random plasma glucose significance in the multivariate model, with discussion of its mediation through microvascular complications, and the biological mechanisms by which hyperglycaemia impairs wound healing (neutrophil inhibition, growth factor reduction, AGE accumulation).

  • Paragraph 3 (eGFR and renal function): A new paragraph discussing eGFR as a novel independent predictor via mechanisms including uraemia-impaired immunity, anaemia-reduced tissue oxygenation, and uraemic vasculopathy.

These additions are found in the Discussion section (pages 8–10).

SUMMARY OF REVISIONS

Issue

Reviewer Concern

Action Taken

1

Insufficient description of study population (no inclusion/exclusion criteria, sampling method unclear)

✅ Added full inclusion/exclusion criteria, consecutive sampling description, and patient population clarification in Methods → Participants

2

Statistical analysis limited to descriptive stats and chi-square; no multivariate regression

✅ Added ordinal logistic regression (Table 4A) and binary logistic regression (Table 4B) with full interpretation in Methods and Discussion

3

Clinical variables (retinopathy, neuropathy, IHD, smoking) not defined or measured

✅ Added operational definitions for all 5 clinical variables in Methods → Data Collection

4

Discussion lacks pathophysiological mechanisms for key associations

✅ Added 3 new Discussion paragraphs on: retinopathy/neuropathy microvascular mechanisms, RBS attenuation, and eGFR role

We believe that these revisions comprehensively address all the reviewer's reservations and substantially strengthen the scientific quality of the manuscript. We are confident that the addition of multivariate regression analysis, explicit methodological definitions, and expanded mechanistic discussion transforms this work into a more rigorous and reproducible study. We remain available to address any further queries and sincerely hope that the revised manuscript will now merit an 'Approved' status.

Yours sincerely,

Adel Gassab Mohammed (Corresponding Author)

On behalf of all co-authors:

Dheyaa Kadhim Al-Waeli, Samih Abed Odhaib, Mahmood Thamer Altemimi

Thi-Qar Specialized Diabetes, Endocrine, and Metabolism Center (TDEMC)

Nasiriyah, Thi-Qar, Iraq  |  adelgassab@utq.edu.iq

F1000Res. 2024 Jul 1. doi: 10.5256/f1000research.165614.r284113

Reviewer response for version 1

Nassar Alibrahim 1

First I would like to express my admiration for the well written article and the effort carried out by the authors, specially in the important area of the diabetic foot ulcers globally having its important negative impact on the patients life as well as the society.

I have only some minor points to be discussed:

1-Looks like the limitations of the study was mentioned twice in the text.

2- In T able 1: For the sake of a easier readability, the variables better to be grouped like : IHD,HF,CVA,HF in one group , and amputation, osteomyelitis, charcot , wheel chair in another group and so on.

or you can arrange them alphabetically.

3-In Table 3 :

a)You need to mention the percentages within the variable cells as well, so the comparisons can be easily visible.

b)The p value mentioned actually represent the interactive p value for all Fields, was it possible to calculate each group p value vertically and horizontally ? looking for a specific relationship between any variable category and any WG severity ?, like the significance of being obese and the development of WG5 ?

c)The significant finding of the association between RBS and WG severity need to be clarified in the text, is it the RBS is > 200 (as you can see all the numbers are higher than those in the categories of 200 and less, or the trend is decreasing toward progressing from WG1 to WG5). This should be mentioned in the text for clarification.

d)Again you need to clarify the meaning of DRP significant association with WG, for example does the presence of DRP means a more severe or less severe DFU ?, though the trend looks decreasing.

4-In the conclusion section:

the first paragraph in the conclusion better to be part of the introduction section.

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

Yes

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Diabetes, Endocrine and Metabolism

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

F1000Res. 2024 Jul 2.
Adel Gassab Mohammed 1

Dear Reviewer,

Thank you for taking the time to review our article. We appreciate your kind words regarding the effort put forth by the authors in addressing the global issue of diabetic foot ulcers, and we are glad to hear that you found the article well-written.

Regarding your minor points:

1. We acknowledge the duplication in mentioning the limitations of the study within the text. We will address this issue by ensuring that the limitations are presented only once in the revised version of the manuscript.

2. We appreciate your suggestion for improving the readability of Table 1 by grouping the variables for easier comprehension. While we understand the importance of this suggestion, we have decided to maintain the current format of Table 1 without any changes at this point. However, we will keep your feedback in mind for future revisions and improvements.

Once again, thank you for your valuable feedback and constructive comments. Should you have any further suggestions or concerns, please feel free to share them with us.

Best regards,

[Adel Gassab Mohammed]

Associated Data

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

    Data Citations

    1. Mohammed AG: Assessing the features of diabetic foot ulcers among individuals with type 2 diabetes mellitus in Thi Qar, Iraq.[Dataset]. Zenodo. 2024. 10.5281/zenodo.11187872 [DOI]

    Data Availability Statement

    Underlying data

    Zenodo: Assessing the features of diabetic foot ulcers among individuals with type 2 diabetes mellitus in Thi Qar, Iraq, https://zenodo.org/doi/10.5281/zenodo.11187872. 32

    Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

    Articles from F1000Research are provided here courtesy of F1000 Research Ltd

    RESOURCES