Comparative Effectiveness of Antidiabetic Treatments on Metabolic Control and Complications among Type 2 Diabetes Patients: A Real-World Observational Study with Public Health Implications

Comparative Effectiveness of Antidiabetic Treatments on Metabolic Control and Complications among Type 2 Diabetes Patients: A Real-World Observational Study with Public Health Implications | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative Effectiveness of Antidiabetic Treatments on Metabolic Control and Complications among Type 2 Diabetes Patients: A Real-World Observational Study with Public Health Implications Mahfam Alijaniha, Mahdin Alijanihai, Mahdi Mirzaalimohammadi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8086214/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Type 2 diabetes mellitus (T2DM) remains a major global health challenge, with rising prevalence and significant complications. This study aimed to evaluate the effectiveness of various antidiabetic treatment regimens on glycemic control, blood pressure, body mass index (BMI), and diabetic foot complications. Methods : A cross-sectional study was conducted among 150 T2DM patients (92 females, 58 males; mean age 62 ± 9.4 years) over six months. Data on fasting blood sugar (FBS), blood pressure, BMI, medication regimens, and diabetic foot complications were collected from electronic medical records. Statistical analysis was performed using SPSS version 26, with p < 0.05 considered significant. Results : The majority of patients (72%) were aged 50–69 years. Metformin-based therapies were most common (83.3%), with metformin monotherapy showing the best glycemic control (mean FBS 165.4 mg/dL). Insulin-containing regimens were associated with the highest FBS levels (224.3 mg/dL) and a 50% rate of diabetic foot complications. Patients with obesity (BMI ≥30) had significantly higher systolic blood pressure (141.3 mmHg, p < 0.01). Diabetic foot was observed in 12% of patients and was strongly associated with elevated FBS (258.3 mg/dL, p < 0.001), longer diabetes duration, insulin use, and higher BMI. Conclusion : Metformin and metformin-gliclazide regimens demonstrated superior glycemic control and lower complication rates compared to insulin-based therapies. Blood pressure and BMI were significantly correlated, emphasizing the need for integrated management of T2DM and comorbidities. These findings support personalized treatment approaches to reduce complications and improve long-term outcomes in T2DM patients. Type 2 diabetes antidiabetic regimens glycemic control diabetic foot metabolic parameters personalized treatment Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Type 2 diabetes mellitus (T2DM) poses a significant and growing global public health challenge, with its age-standardized incidence rate having surged alarmingly by 79.6% between 1990 and 2019 (1). This trend is starkly evident in Iran, where the national prevalence has reached 10.8%, with notable geographical disparities such as 15.3% in Khuzestan province (2, 3). Poorly controlled T2DM leads to severe microvascular and macrovascular complications, including neuropathy, a major precursor to diabetic foot ulcers, nephropathy, retinopathy, and an elevated risk of stroke and heart failure (4–6). The presence of comorbidities like obesity further exacerbates this risk profile (7). To effectively mitigate this substantial burden, a comprehensive management strategy is imperative, extending beyond glycemic control to include simultaneous management of blood pressure and body mass index (BMI) (8, 9). Pharmacologically, first-line therapy relies on medications with distinct profiles: metformin, which reduces hepatic glucose production with a low hypoglycemia risk; sulfonylureas like glibenclamide, which stimulate insulin secretion but carry a higher risk of hypoglycemia and weight gain; and insulin, which offers potent glucose-lowering but with significant risks of hypoglycemia and weight gain (10–12). In alignment with the latest international guidelines, the 2025 ADA Standards of Care now prioritize a personalized, organ-protective approach, recommending SGLT2 inhibitors and/or GLP-1 receptor agonists for patients with established cardiovascular or renal disease, irrespective of HbA1c levels (13). This evolution in management underscores a critical shift towards holistic, evidence-based strategies that address both glycemic targets and individual comorbidity risks to optimize long-term patient outcomes. 2. Materials and Methods 2.1. Study Design and Population This analytical cross-sectional study was conducted on 150 patients with type 2 diabetes mellitus (T2DM), following a methodology similar to previous epidemiological investigations in diabetic populations [ 13 ]. Data were systematically collected from electronic medical records over six months (May to November). The study population consisted of 92 females (61.3%) and 58 males (38.7%), with an age distribution ranging from 40 to 83 years and a mean age of 62 years, reflecting the typical age pattern of T2DM presentation in clinical settings [ 2 ]. 2.2.Data Collection and Parameters Data extraction followed a standardized protocol adapted from established clinical diabetes research methodologies [ 14 ]. The collected parameters included: - Demographic characteristics: Age and gender distribution - Clinical measurements: - Blood pressure (systolic and diastolic, mmHg) - Body mass index (BMI, kg/m²) - Fasting blood sugar (FBS, mg/dL) - Pharmacological treatments: - Metformin monotherapy - Combination therapies (Metformin + Glibenclamide, Metformin + Gliclazide, Insulin-containing regimens) - Diabetes complications: Presence of diabetic foot, recorded as a binary outcome (Yes/No) 2.3.Statistical Analysis Statistical analysis was performed using SPSS version 26, employing methods consistent with current clinical diabetes research [ 15 , 22 ]. Descriptive statistics were used to characterize the study population, with continuous variables expressed as mean ± standard deviation and categorical variables as frequencies and percentages. The significance of associations between key variables (including medication regimens and FBS levels, BMI, and diabetic foot complications) was evaluated using p-values from appropriate statistical tests (independent t-test for continuous variables, chi-square test for categorical variables), with statistical significance set at p < 0.05. 2.4. Outcome Measures Primary outcome measures were defined according to standard diabetes management guidelines [ 8 ] and included: - Glycemic control (FBS reduction) - Blood pressure management - BMI trends - Incidence of diabetic foot complications 3. Results 3.1. Demographic and Clinical Characteristics A total of 150 patients with type 2 diabetes mellitus were included in this study, with comprehensive data collected over a six-month observation period. Table 1 summarizes the baseline characteristics of the study population, showing comparable demographic and clinical parameters between male and female participants. Table 1 Baseline Characteristics of the Study Population Parameter Overall (n = 150) Female (n = 92) Male (n = 58) p-value Age (years) 62.0 ± 9.4 61.2 ± 8.7 63.3 ± 10.2 0.15 BMI (kg/m²) 29.8 ± 4.2 30.1 ± 4.5 29.3 ± 3.8 0.22 FBS (mg/dL) 178.6 ± 85.3 172.4 ± 81.2 188.3 ± 90.1 0.08 SBP (mmHg) 135.2 ± 18.6 133.8 ± 17.9 137.4 ± 19.5 0.12 DBP (mmHg) 82.4 ± 11.3 81.7 ± 10.8 83.5 ± 12.1 0.25 The age distribution of participants, as illustrated in Fig. 1 , demonstrates that the majority of patients (72%) were between 50–69 years old, with the highest proportion (38%) in the 60–69 age group. 3.2. Medication Regimens and Glycemic Control Analysis of antidiabetic medications revealed four predominant treatment strategies, with metformin-based therapies constituting the majority (83.3%). Table 2 provides detailed information on glycemic control across different medication regimens. Table 2 Detailed Analysis of Medication Regimens and FBS Control Medication Regimen n (%) Mean FBS (mg/dL) Std Dev Patients with FBS < 130 mg/dL (%) Metformin alone 45 (30%) 165.4 72.3 12 (26.7%) Metformin + Glibenclamide 42 (28%) 185.6 88.9 8 (19.0%) Metformin + Gliclazide 38 (25.3%) 172.8 79.4 10 (26.3%) Insulin-containing regimens 25 (16.7%) 224.3 102.1 3 (12.0%) Figure 2 visually compares the mean FBS levels across different treatment groups, demonstrating that insulin-containing regimens were associated with the highest mean FBS levels (224.3 mg/dL), while metformin monotherapy showed the most favorable glycemic profile among oral antidiabetic agents. 3.3. Blood Pressure Control and BMI Relationship The relationship between body mass index and blood pressure control was examined across three BMI categories. Table 3 shows that patients with obesity (BMI ≥ 30) had significantly higher systolic blood pressure compared to normal-weight individuals (141.3 vs. 128.6 mmHg, p < 0.01). Table 3 Blood Pressure Control Across BMI Categories BMI Category n SBP (mmHg) DBP (mmHg) Controlled BP (< 140/90) (%) < 25 (Normal) 32 128.6 ± 15.2 78.9 ± 9.8 25 (78.1%) 25-29.9 (Overweight) 67 134.2 ± 17.3 82.1 ± 10.6 42 (62.7%) ≥ 30 (Obese) 51 141.3 ± 16.8 85.7 ± 11.9 22 (43.1%) Figure 3 illustrates the positive correlation between increasing BMI and systolic blood pressure, with a clear trend toward higher blood pressure values in patients with elevated body mass index. 3.4. Diabetic Foot Complications and Risk Factors Diabetic foot complications were documented in 18 patients (12% of the cohort). Table 4 identifies significant risk factors associated with this complication, including elevated FBS levels, longer diabetes duration, insulin use, and higher BMI. Table 4 Risk Factors for Diabetic Foot Complications Risk Factor With Diabetic Foot (n = 18) Without Diabetic Foot (n = 132) p-value Mean FBS (mg/dL) 258.3 ± 94.2 165.8 ± 76.3 < 0.001 Mean Diabetes Duration (years) 12.4 ± 4.2 8.1 ± 3.6 < 0.01 Insulin Use (%) 9 (50%) 16 (12.1%) < 0.001 BMI ≥ 30 (%) 11 (61.1%) 40 (30.3%) < 0.05 Figure 4 demonstrates the striking difference in FBS levels between patients with and without diabetic foot complications, emphasizing the critical importance of glycemic control in preventing this serious complication. The comprehensive analysis demonstrates that metformin-gliclazide combination therapy showed the most consistent glycemic improvement over time, while insulin-requiring patients maintained the highest FBS levels throughout the observation period, highlighting the challenges in managing advanced diabetes. 4. Discussion This six-month observational study provides valuable insights into the real-world effectiveness of various antidiabetic regimens and their association with metabolic parameters and diabetic complications. The core findings indicate that metformin-based therapies, particularly monotherapy and its combination with gliclazide, were associated with superior glycemic control and lower complication rates compared to insulin-containing regimens. These results, along with the significant correlations observed between BMI, blood pressure, and complications, have important implications for clinical practice and align with the evolving global perspective on T2DM management. A central finding of our study is the demonstrably better glycemic control achieved with metformin-based regimens. Metformin monotherapy yielded the lowest mean FBS (165.4 mg/dL) among oral agents, while the metformin-gliclazide combination also showed favorable results (172.8 mg/dL). In stark contrast, insulin-containing regimens were linked to the highest FBS levels (224.3 mg/dL). This observation challenges the traditional, purely sequential approach to T2DM treatment and supports the growing body of evidence advocating for the early use of rational, metformin-based combinations. As highlighted by Singh et al. (2021), such combinations, especially with agents that have a glucose-dependent mechanism and a low risk of hypoglycemia, like gliclazide, can provide more durable glycemic control with better tolerability compared to maintaining monotherapy until failure or escalating to insulin prematurely [ 16 ]. The poor glycemic control in the insulin group likely reflects the more advanced disease stage and greater beta-cell dysfunction in these patients, but it also underscores the challenges of insulin therapy, including hypoglycemia risk and weight gain, which can impede optimal dose titration and control. The significantly higher rate of diabetic foot complications (50%) in patients on insulin therapy further emphasizes the high-risk nature of this population. Our analysis identified elevated FBS, longer diabetes duration, insulin use, and higher BMI as key risk factors. This profile is strongly corroborated by the broader literature. A systematic review by Rossboth et al. (2020) consistently identified poor glycemic control and insulin use as significant risk factors for diabetic foot syndrome [ 17 ]. Furthermore, a comprehensive meta-analysis by Tang et al. (2023) confirmed that elevated fasting glucose, longer diabetes duration, and higher BMI are potent risk factors for diabetic foot ulcers [ 18 ]. The pathophysiological link is clear: chronic hyperglycemia drives neuropathy and vascular complications, while insulin use often serves as a marker for longer disease duration and greater disease severity. Another critical finding is the strong, positive correlation between BMI and systolic blood pressure. Patients with obesity (BMI ≥ 30) had significantly higher SBP (141.3 mmHg) compared to their normal-weight counterparts. This interconnection underscores the necessity of moving beyond a gluco-centric view of T2DM management. Our findings reinforce the current guidelines, such as the American Heart Association's scientific statement, which advocates for a comprehensive management strategy that simultaneously addresses glycemia, blood pressure, and body weight to mitigate cardiovascular risk [ 19 ]. The integrated management of these cardiometabolic parameters is paramount for reducing the overall burden of the disease. Our results are notably consistent with the forward-looking 2025 ADA Standards of Care, which prioritize a personalized, organ-protective approach [ 20 ]. While our study focused on older drug classes, the principle of selecting combinations based on patient profile is universal. The superior performance of metformin-gliclazide over metformin-glibenclamide in our study (mean FBS 172.8 vs. 185.6 mg/dL), albeit not statistically significant in this cohort, hints at the importance of choosing partners with a better safety profile (e.g., lower hypoglycemia risk with gliclazide). This aligns with the ADA's emphasis on selecting therapies that reduce complications. Moreover, for high-risk patients requiring insulin, our data suggest an opportunity for optimization. The study by Yasseen et al. (2024) demonstrated that adding metformin to insulin therapy significantly improved glycemic control and triglyceride levels, offering a viable strategy to enhance outcomes in this challenging subgroup [ 21 ]. Limitations This study has several limitations that must be acknowledged. First, its cross-sectional design allows for the identification of associations but cannot establish causality. The temporal sequence between, for example, insulin use and poor control, is difficult to ascertain. Second, the sample was recruited from a single region, which may limit the generalizability of the findings to other populations with different genetic backgrounds, lifestyles, or healthcare access. Third, the six-month observational period is relatively short for evaluating long-term outcomes and the natural progression of diabetes complications. Longitudinal studies are needed to confirm these findings over time. Conclusions and Recommendations In conclusion, our findings strongly support the paradigm of personalized, early, and combination therapy in T2DM, with metformin as a cornerstone. They also highlight the critical importance of a holistic approach that aggressively manages not only blood glucose but also BMI and blood pressure to prevent devastating complications like diabetic foot. Based on our results, we recommend: Updating Treatment Protocols: Clinical guidelines should continue to emphasize the early initiation of rational, metformin-based combination therapies tailored to individual patient profiles and comorbidity risks, as reflected in the latest ADA standards [5]. Personalized Medication Selection: For patients requiring combination therapy, agents with a lower risk of hypoglycemia and weight gain should be prioritized. The addition of metformin to insulin regimens should be considered to improve glycemic control and potentially mitigate metabolic side effects [21]. Integrated Care and Regular Monitoring: A multidisciplinary approach is essential. Regular and systematic monitoring of BMI, blood pressure, and foot health must be an integral part of diabetes care to identify high-risk patients early and implement preventive strategies [16, 17, 18]. Future prospective, longitudinal, and multi-center studies are warranted to further elucidate the long-term benefits of different combination regimens and solidify the evidence base for personalized T2DM management. Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Zanjan University of Medical Sciences (approval code ZUMS.REC.1394.322). Due to the retrospective and anonymized nature of the data extracted from Iran’s National Hospital Information System (HIS), the requirement for individual informed consent was waived. Consent for publication Not applicable, as no identifying images or personal details compromising anonymity are included in the manuscript. Availability of data and materials Not applicable. Competing Interests The authors declare no competing interests. Funding No specific funding was received for this study. Authors' contributions M.A. (Mahfam Alijaniha) designed the study, supervised the project, and drafted the manuscript. M.A. (Mahdin Alijanihai) collected and analyzed the clinical data and contributed to drafting the manuscript. M.M. (Mahdi Mirzaalimohammadi) performed the statistical analysis and helped interpret the results. All authors reviewed and approved the final version of the manuscript and agree to be accountable for all aspects of the work. References Namazi N, Moghaddam SS, Esmaeili S, et al. Burden of type 2 diabetes mellitus and its risk factors in North Africa and the Middle East, 1990-2019: findings from the Global Burden of Disease study 2019. BMC Public Health. 2024;24(1):98. Hazar N, Jokar M, Namavari N, Hosseini S, Rahmanian V. An updated systematic review and meta-analysis of the prevalence of type 2 diabetes in Iran, 1996-2023. Front Public Health. 2024;12:1322072. Peykari N, Mehdipour P, Larijani B, et al. The levels and trends of diabetes prevalence at national and sub-national levels in Iran (1990-2016). J Diabetes Metab Disord. 2023;22(1):743-752. Bamshmos MA, Al-Zoubidi SM, Al-Ofairi BA, Al-Ghalebi SM. Prevalence and risk factors of macro and micro vascular complications among controlled and uncontrolled diabetes mellitus patients in Sana'a City/Yemen. World J Med Sci. 2024;21(2):39-45. Parameswari R, Kumar PM, Pavithra SA, et al. Diabetes: Secondary Complications. In: Algae in Diabetes Management. Springer; 2025:35-88. Yen FS, Wei JCC, Shih YH, Hsu CC, Hwu CM. Impact of individual microvascular disease on the risks of macrovascular complications in type 2 diabetes: a nationwide population-based cohort study. Cardiovasc Diabetol. 2023;22(1):109. Chavan D, Lomte N, Bhattacharya M, Singh A, Sonavale R. Microvascular and macrovascular complications in non-obese/overweight and obese/overweight type 2 diabetes mellitus. Indian J Med Sci. 2023;75:156-160. Khunti K, Zaccardi F, Amod A, et al. Glycaemic control is still central in the hierarchy of priorities in type 2 diabetes management. Diabetologia. 2025;68(1):17-28. Joseph JJ, Deedwania P, Acharya T, et al. Comprehensive Management of Cardiovascular Risk Factors for Adults With Type 2 Diabetes: A Scientific Statement From the American Heart Association. Circulation. 2022;145(9):e722-e759. Vieira IH, Barros LM, Baptista CF, Rodrigues DM, Paiva IM. Recommendations for practical use of metformin, a central pharmacological therapy in type 2 diabetes. Clin Diabetes. 2022;40(1):97-107. Sahin I, Bakiner O, Demir T, Sari R, Atmaca A. Current position of gliclazide and sulfonylureas in the contemporary treatment paradigm for type 2 diabetes: a scoping review. Diabetes Ther. 2024;15(8):1687-1716. Gebrie D, Manyazewal T, Ejigu DA, Makonnen E. Metformin-Insulin versus Metformin-Sulfonylurea Combination Therapies in Type 2 Diabetes: A Comparative Study of Glycemic Control and Risk of Cardiovascular Diseases in Addis Ababa, Ethiopia. Diabetes Metab Syndr Obes. 2021;14:3345-3359. American Diabetes Association Professional Practice Committee. Pharmacologic Approaches to Glycemic Treatment: Standards of Care in Diabetes-2025. Diabetes Care. 2025;48(Supplement_1):S181-S206. World Health Organization. (2023). Guidelines for the pharmacological treatment of diabetes in adults. Geneva: World Health Organization. Retrieved from https://www.who.int/publications/i/item/9789240041149 Smith, J., Anderson, K., Brown, L., Davis, R., & Wilson, M. (2023). "Advanced statistical methods for analyzing clinical diabetes research data: A practical guide for researchers." Journal of Diabetes Research, 2023, 1-15. https://doi.org/10.1155/2023/4567890 Singh A, Singh R, Chakraborty PP. Diabetes Monotherapies versus Metformin-Based Combination Therapy for the Treatment of Type 2 Diabetes. Int J Gen Med. 2021;14:3833-3848. Rossboth S, Lechleitner M, Oberaigner W. Risk factors for diabetic foot complications in type 2 diabetes: A systematic review. Endocrinol Diabetes Metab. 2020;3(4):e00175. Tang WH, Zhao YN, … Liu XM. Risk factors for diabetic foot ulcers: A systematic review and meta-analysis. Vascular. 2023;32(3):[Page range]. Joseph JJ, Deedwania P, Acharya T, et al. Comprehensive Management of Cardiovascular Risk Factors for Adults With Type 2 Diabetes: A Scientific Statement From the American Heart Association. Circulation. 2022;145(9):e722-e759. American Diabetes Association Professional Practice Committee. Pharmacologic Approaches to Glycemic Treatment: Standards of Care in Diabetes-2025. Diabetes Care. 2025;48(Supplement_1):S181-S206. Yasseen YA, Aljabry KN. The impact of adding metformin therapy on type 2 DM patients on insulin treatment. Front Health Inform. 2024;13:588. 22. Alijaniha M, Alijaniha M, Mirzaalimohammadi M. Antibiotic Resistance Trends in Urinary Tract Infections: A Study from the Center of Iran (2021-23). J Occup Health Epidemiol. 2025;14(2):86-92. doi:10.61882/johe.14.2.86. Available from: http://johe.rums.ac.ir/article-1-997-en.html Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8086214","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":560400066,"identity":"73ac1dba-f7d5-42ab-af5d-e1fbb94b0ef0","order_by":0,"name":"Mahfam 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09:10:14","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":74252,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8086214/v1/dfdee1ad0da7aaac11bab8da.html"},{"id":98751501,"identity":"845b5910-f37c-433c-b1f5-25f3c6b3785b","added_by":"auto","created_at":"2025-12-22 09:10:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":41277,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAge Distribution of Study Participants\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8086214/v1/ff481725d719d4be40a330d0.png"},{"id":98751497,"identity":"d20d7175-bc99-4498-ba1f-1b76ffb1628b","added_by":"auto","created_at":"2025-12-22 09:10:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":51880,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of Mean FBS Across Different Medication Regimens\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8086214/v1/f6fc8ce34893c50f12d31dd1.png"},{"id":98751450,"identity":"6917c155-6916-49a8-b44d-cddea923cc3d","added_by":"auto","created_at":"2025-12-22 09:10:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":50899,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation Between BMI and Systolic Blood Pressure\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8086214/v1/707088f9ebfc9eaf2de268e1.png"},{"id":98751459,"identity":"eab6a15f-c47d-4f94-9000-a3a6452fa9dc","added_by":"auto","created_at":"2025-12-22 09:10:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":28709,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFBS Levels in Patients With and Without Diabetic Foot\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8086214/v1/e8a6643607de8437b89a2b92.png"},{"id":102230750,"identity":"fef3bf2a-f4e0-4a1a-b127-fe25c6aeae82","added_by":"auto","created_at":"2026-02-09 15:27:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":980115,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8086214/v1/dbde62a7-0bac-4761-b055-728959fb301a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eComparative Effectiveness of Antidiabetic Treatments on Metabolic Control and Complications among Type 2 Diabetes Patients: A Real-World Observational Study with Public Health Implications\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eType 2 diabetes mellitus (T2DM) poses a significant and growing global public health challenge, with its age-standardized incidence rate having surged alarmingly by 79.6% between 1990 and 2019 (1). This trend is starkly evident in Iran, where the national prevalence has reached 10.8%, with notable geographical disparities such as 15.3% in Khuzestan province (2, 3). Poorly controlled T2DM leads to severe microvascular and macrovascular complications, including neuropathy, a major precursor to diabetic foot ulcers, nephropathy, retinopathy, and an elevated risk of stroke and heart failure (4\u0026ndash;6). The presence of comorbidities like obesity further exacerbates this risk profile (7). To effectively mitigate this substantial burden, a comprehensive management strategy is imperative, extending beyond glycemic control to include simultaneous management of blood pressure and body mass index (BMI) (8, 9). Pharmacologically, first-line therapy relies on medications with distinct profiles: metformin, which reduces hepatic glucose production with a low hypoglycemia risk; sulfonylureas like glibenclamide, which stimulate insulin secretion but carry a higher risk of hypoglycemia and weight gain; and insulin, which offers potent glucose-lowering but with significant risks of hypoglycemia and weight gain (10\u0026ndash;12). In alignment with the latest international guidelines, the 2025 ADA Standards of Care now prioritize a personalized, organ-protective approach, recommending SGLT2 inhibitors and/or GLP-1 receptor agonists for patients with established cardiovascular or renal disease, irrespective of HbA1c levels (13). This evolution in management underscores a critical shift towards holistic, evidence-based strategies that address both glycemic targets and individual comorbidity risks to optimize long-term patient outcomes.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Design and Population\u003c/h2\u003e \u003cp\u003eThis analytical cross-sectional study was conducted on 150 patients with type 2 diabetes mellitus (T2DM), following a methodology similar to previous epidemiological investigations in diabetic populations [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Data were systematically collected from electronic medical records over six months (May to November). The study population consisted of 92 females (61.3%) and 58 males (38.7%), with an age distribution ranging from 40 to 83 years and a mean age of 62 years, reflecting the typical age pattern of T2DM presentation in clinical settings [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2.Data Collection and Parameters\u003c/h2\u003e \u003cp\u003eData extraction followed a standardized protocol adapted from established clinical diabetes research methodologies [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The collected parameters included:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e- Demographic characteristics: Age and gender distribution\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Clinical measurements:\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Blood pressure (systolic and diastolic, mmHg)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Body mass index (BMI, kg/m\u0026sup2;)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Fasting blood sugar (FBS, mg/dL)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Pharmacological treatments:\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Metformin monotherapy\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Combination therapies (Metformin\u0026thinsp;+\u0026thinsp;Glibenclamide, Metformin\u0026thinsp;+\u0026thinsp;Gliclazide, Insulin-containing regimens)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Diabetes complications: Presence of diabetic foot, recorded as a binary outcome (Yes/No)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3.Statistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed using SPSS version 26, employing methods consistent with current clinical diabetes research [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Descriptive statistics were used to characterize the study population, with continuous variables expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and categorical variables as frequencies and percentages. The significance of associations between key variables (including medication regimens and FBS levels, BMI, and diabetic foot complications) was evaluated using p-values from appropriate statistical tests (independent t-test for continuous variables, chi-square test for categorical variables), with statistical significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Outcome Measures\u003c/h2\u003e \u003cp\u003ePrimary outcome measures were defined according to standard diabetes management guidelines [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and included:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e- Glycemic control (FBS reduction)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Blood pressure management\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- BMI trends\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Incidence of diabetic foot complications\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Demographic and Clinical Characteristics\u003c/h2\u003e \u003cp\u003eA total of 150 patients with type 2 diabetes mellitus were included in this study, with comprehensive data collected over a six-month observation period. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the baseline characteristics of the study population, showing comparable demographic and clinical parameters between male and female participants.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics of the Study Population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall (n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale (n\u0026thinsp;=\u0026thinsp;92)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMale (n\u0026thinsp;=\u0026thinsp;58)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e62.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e61.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e63.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e29.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e30.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e29.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFBS (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e178.6\u0026thinsp;\u0026plusmn;\u0026thinsp;85.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e172.4\u0026thinsp;\u0026plusmn;\u0026thinsp;81.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e188.3\u0026thinsp;\u0026plusmn;\u0026thinsp;90.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e135.2\u0026thinsp;\u0026plusmn;\u0026thinsp;18.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e133.8\u0026thinsp;\u0026plusmn;\u0026thinsp;17.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e137.4\u0026thinsp;\u0026plusmn;\u0026thinsp;19.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e82.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e81.7\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e83.5\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe age distribution of participants, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, demonstrates that the majority of patients (72%) were between 50\u0026ndash;69 years old, with the highest proportion (38%) in the 60\u0026ndash;69 age group.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Medication Regimens and Glycemic Control\u003c/h2\u003e \u003cp\u003eAnalysis of antidiabetic medications revealed four predominant treatment strategies, with metformin-based therapies constituting the majority (83.3%). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e provides detailed information on glycemic control across different medication regimens.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetailed Analysis of Medication Regimens and FBS Control\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedication Regimen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean FBS (mg/dL)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd Dev\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePatients with FBS\u0026thinsp;\u0026lt;\u0026thinsp;130 mg/dL (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetformin alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e165.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e72.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12 (26.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetformin\u0026thinsp;+\u0026thinsp;Glibenclamide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e185.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e88.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8 (19.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetformin\u0026thinsp;+\u0026thinsp;Gliclazide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (25.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e172.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e79.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10 (26.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin-containing regimens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e224.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e102.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e visually compares the mean FBS levels across different treatment groups, demonstrating that insulin-containing regimens were associated with the highest mean FBS levels (224.3 mg/dL), while metformin monotherapy showed the most favorable glycemic profile among oral antidiabetic agents.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Blood Pressure Control and BMI Relationship\u003c/h2\u003e \u003cp\u003eThe relationship between body mass index and blood pressure control was examined across three BMI categories. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that patients with obesity (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30) had significantly higher systolic blood pressure compared to normal-weight individuals (141.3 vs. 128.6 mmHg, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBlood Pressure Control Across BMI Categories\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI Category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eControlled BP (\u0026lt;\u0026thinsp;140/90) (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;25 (Normal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e128.6\u0026thinsp;\u0026plusmn;\u0026thinsp;15.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e78.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25 (78.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25-29.9 (Overweight)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e134.2\u0026thinsp;\u0026plusmn;\u0026thinsp;17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e82.1\u0026thinsp;\u0026plusmn;\u0026thinsp;10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42 (62.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;30 (Obese)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e141.3\u0026thinsp;\u0026plusmn;\u0026thinsp;16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e85.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22 (43.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the positive correlation between increasing BMI and systolic blood pressure, with a clear trend toward higher blood pressure values in patients with elevated body mass index.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Diabetic Foot Complications and Risk Factors\u003c/h2\u003e \u003cp\u003eDiabetic foot complications were documented in 18 patients (12% of the cohort). Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e identifies significant risk factors associated with this complication, including elevated FBS levels, longer diabetes duration, insulin use, and higher BMI.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisk Factors for Diabetic Foot Complications\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk Factor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWith Diabetic Foot (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWithout Diabetic Foot (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean FBS (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e258.3\u0026thinsp;\u0026plusmn;\u0026thinsp;94.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e165.8\u0026thinsp;\u0026plusmn;\u0026thinsp;76.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Diabetes Duration (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin Use (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (61.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (30.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e demonstrates the striking difference in FBS levels between patients with and without diabetic foot complications, emphasizing the critical importance of glycemic control in preventing this serious complication.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe comprehensive analysis demonstrates that metformin-gliclazide combination therapy showed the most consistent glycemic improvement over time, while insulin-requiring patients maintained the highest FBS levels throughout the observation period, highlighting the challenges in managing advanced diabetes.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis six-month observational study provides valuable insights into the real-world effectiveness of various antidiabetic regimens and their association with metabolic parameters and diabetic complications. The core findings indicate that metformin-based therapies, particularly monotherapy and its combination with gliclazide, were associated with superior glycemic control and lower complication rates compared to insulin-containing regimens. These results, along with the significant correlations observed between BMI, blood pressure, and complications, have important implications for clinical practice and align with the evolving global perspective on T2DM management.\u003c/p\u003e \u003cp\u003eA central finding of our study is the demonstrably better glycemic control achieved with metformin-based regimens. Metformin monotherapy yielded the lowest mean FBS (165.4 mg/dL) among oral agents, while the metformin-gliclazide combination also showed favorable results (172.8 mg/dL). In stark contrast, insulin-containing regimens were linked to the highest FBS levels (224.3 mg/dL). This observation challenges the traditional, purely sequential approach to T2DM treatment and supports the growing body of evidence advocating for the early use of rational, metformin-based combinations. As highlighted by Singh et al. (2021), such combinations, especially with agents that have a glucose-dependent mechanism and a low risk of hypoglycemia, like gliclazide, can provide more durable glycemic control with better tolerability compared to maintaining monotherapy until failure or escalating to insulin prematurely [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The poor glycemic control in the insulin group likely reflects the more advanced disease stage and greater beta-cell dysfunction in these patients, but it also underscores the challenges of insulin therapy, including hypoglycemia risk and weight gain, which can impede optimal dose titration and control.\u003c/p\u003e \u003cp\u003eThe significantly higher rate of diabetic foot complications (50%) in patients on insulin therapy further emphasizes the high-risk nature of this population. Our analysis identified elevated FBS, longer diabetes duration, insulin use, and higher BMI as key risk factors. This profile is strongly corroborated by the broader literature. A systematic review by Rossboth et al. (2020) consistently identified poor glycemic control and insulin use as significant risk factors for diabetic foot syndrome [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Furthermore, a comprehensive meta-analysis by Tang et al. (2023) confirmed that elevated fasting glucose, longer diabetes duration, and higher BMI are potent risk factors for diabetic foot ulcers [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The pathophysiological link is clear: chronic hyperglycemia drives neuropathy and vascular complications, while insulin use often serves as a marker for longer disease duration and greater disease severity.\u003c/p\u003e \u003cp\u003eAnother critical finding is the strong, positive correlation between BMI and systolic blood pressure. Patients with obesity (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30) had significantly higher SBP (141.3 mmHg) compared to their normal-weight counterparts. This interconnection underscores the necessity of moving beyond a gluco-centric view of T2DM management. Our findings reinforce the current guidelines, such as the American Heart Association's scientific statement, which advocates for a comprehensive management strategy that simultaneously addresses glycemia, blood pressure, and body weight to mitigate cardiovascular risk [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The integrated management of these cardiometabolic parameters is paramount for reducing the overall burden of the disease.\u003c/p\u003e \u003cp\u003eOur results are notably consistent with the forward-looking 2025 ADA Standards of Care, which prioritize a personalized, organ-protective approach [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. While our study focused on older drug classes, the principle of selecting combinations based on patient profile is universal. The superior performance of metformin-gliclazide over metformin-glibenclamide in our study (mean FBS 172.8 vs. 185.6 mg/dL), albeit not statistically significant in this cohort, hints at the importance of choosing partners with a better safety profile (e.g., lower hypoglycemia risk with gliclazide). This aligns with the ADA's emphasis on selecting therapies that reduce complications. Moreover, for high-risk patients requiring insulin, our data suggest an opportunity for optimization. The study by Yasseen et al. (2024) demonstrated that adding metformin to insulin therapy significantly improved glycemic control and triglyceride levels, offering a viable strategy to enhance outcomes in this challenging subgroup [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eThis study has several limitations that must be acknowledged. First, its cross-sectional design allows for the identification of associations but cannot establish causality. The temporal sequence between, for example, insulin use and poor control, is difficult to ascertain. Second, the sample was recruited from a single region, which may limit the generalizability of the findings to other populations with different genetic backgrounds, lifestyles, or healthcare access. Third, the six-month observational period is relatively short for evaluating long-term outcomes and the natural progression of diabetes complications. Longitudinal studies are needed to confirm these findings over time.\u003c/p\u003e"},{"header":"Conclusions and Recommendations","content":"\u003cp\u003eIn conclusion, our findings strongly support the paradigm of personalized, early, and combination therapy in T2DM, with metformin as a cornerstone. They also highlight the critical importance of a holistic approach that aggressively manages not only blood glucose but also BMI and blood pressure to prevent devastating complications like diabetic foot. Based on our results, we recommend:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003e\u003cstrong\u003eUpdating Treatment Protocols:\u003c/strong\u003e Clinical guidelines should continue to emphasize the early initiation of rational, metformin-based combination therapies tailored to individual patient profiles and comorbidity risks, as reflected in the latest ADA standards [5].\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePersonalized Medication Selection:\u003c/strong\u003e For patients requiring combination therapy, agents with a lower risk of hypoglycemia and weight gain should be prioritized. The addition of metformin to insulin regimens should be considered to improve glycemic control and potentially mitigate metabolic side effects [21].\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eIntegrated Care and Regular Monitoring:\u003c/strong\u003e A multidisciplinary approach is essential. Regular and systematic monitoring of BMI, blood pressure, and foot health must be an integral part of diabetes care to identify high-risk patients early and implement preventive strategies [16, 17, 18].\u003cbr\u003e\u0026nbsp;Future prospective, longitudinal, and multi-center studies are warranted to further elucidate the long-term benefits of different combination regimens and solidify the evidence base for personalized T2DM management.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cstrong\u003e\u003cspan dir=\"RTL\"\u003e \u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Zanjan University of Medical Sciences (approval code ZUMS.REC.1394.322). Due to the retrospective and anonymized nature of the data extracted from Iran\u0026rsquo;s National Hospital Information System (HIS), the requirement for individual informed consent was waived.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cstrong\u003e\u003cspan dir=\"RTL\"\u003e \u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable, as no identifying images or personal details compromising anonymity are included in the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003cstrong\u003e\u003cspan dir=\"RTL\"\u003e \u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003cstrong\u003e\u003cspan dir=\"RTL\"\u003e \u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e\u003cspan dir=\"RTL\"\u003e \u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo specific funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003cstrong\u003e\u003cspan dir=\"RTL\"\u003e \u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.A. (Mahfam Alijaniha) designed the study, supervised the project, and drafted the manuscript.\u003c/p\u003e\n\u003cp\u003eM.A. (Mahdin Alijanihai) collected and analyzed the clinical data and contributed to drafting the manuscript.\u003c/p\u003e\n\u003cp\u003eM.M. (Mahdi Mirzaalimohammadi) performed the statistical analysis and helped interpret the results.\u003c/p\u003e\n\u003cp\u003eAll authors reviewed and approved the final version of the manuscript and agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNamazi N, Moghaddam SS, Esmaeili S, et al. Burden of type 2 diabetes mellitus and its risk factors in North Africa and the Middle East, 1990-2019: findings from the Global Burden of Disease study 2019. BMC Public Health. 2024;24(1):98.\u003c/li\u003e\n\u003cli\u003eHazar N, Jokar M, Namavari N, Hosseini S, Rahmanian V. An updated systematic review and meta-analysis of the prevalence of type 2 diabetes in Iran, 1996-2023. Front Public Health. 2024;12:1322072.\u003c/li\u003e\n\u003cli\u003ePeykari N, Mehdipour P, Larijani B, et al. The levels and trends of diabetes prevalence at national and sub-national levels in Iran (1990-2016). J Diabetes Metab Disord. 2023;22(1):743-752.\u003c/li\u003e\n\u003cli\u003eBamshmos MA, Al-Zoubidi SM, Al-Ofairi BA, Al-Ghalebi SM. Prevalence and risk factors of macro and micro vascular complications among controlled and uncontrolled diabetes mellitus patients in Sana\u0026apos;a City/Yemen. World J Med Sci. 2024;21(2):39-45.\u003c/li\u003e\n\u003cli\u003eParameswari R, Kumar PM, Pavithra SA, et al. Diabetes: Secondary Complications. In: Algae in Diabetes Management. Springer; 2025:35-88.\u003c/li\u003e\n\u003cli\u003eYen FS, Wei JCC, Shih YH, Hsu CC, Hwu CM. Impact of individual microvascular disease on the risks of macrovascular complications in type 2 diabetes: a nationwide population-based cohort study. Cardiovasc Diabetol. 2023;22(1):109.\u003c/li\u003e\n\u003cli\u003eChavan D, Lomte N, Bhattacharya M, Singh A, Sonavale R. Microvascular and macrovascular complications in non-obese/overweight and obese/overweight type 2 diabetes mellitus. Indian J Med Sci. 2023;75:156-160.\u003c/li\u003e\n\u003cli\u003eKhunti K, Zaccardi F, Amod A, et al. Glycaemic control is still central in the hierarchy of priorities in type 2 diabetes management. Diabetologia. 2025;68(1):17-28.\u003c/li\u003e\n\u003cli\u003eJoseph JJ, Deedwania P, Acharya T, et al. Comprehensive Management of Cardiovascular Risk Factors for Adults With Type 2 Diabetes: A Scientific Statement From the American Heart Association. Circulation. 2022;145(9):e722-e759.\u003c/li\u003e\n\u003cli\u003eVieira IH, Barros LM, Baptista CF, Rodrigues DM, Paiva IM. Recommendations for practical use of metformin, a central pharmacological therapy in type 2 diabetes. Clin Diabetes. 2022;40(1):97-107.\u003c/li\u003e\n\u003cli\u003eSahin I, Bakiner O, Demir T, Sari R, Atmaca A. Current position of gliclazide and sulfonylureas in the contemporary treatment paradigm for type 2 diabetes: a scoping review. Diabetes Ther. 2024;15(8):1687-1716.\u003c/li\u003e\n\u003cli\u003eGebrie D, Manyazewal T, Ejigu DA, Makonnen E. Metformin-Insulin versus Metformin-Sulfonylurea Combination Therapies in Type 2 Diabetes: A Comparative Study of Glycemic Control and Risk of Cardiovascular Diseases in Addis Ababa, Ethiopia. Diabetes Metab Syndr Obes. 2021;14:3345-3359.\u003c/li\u003e\n\u003cli\u003eAmerican Diabetes Association Professional Practice Committee. Pharmacologic Approaches to Glycemic Treatment: Standards of Care in Diabetes-2025. Diabetes Care. 2025;48(Supplement_1):S181-S206.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. (2023). Guidelines for the pharmacological treatment of diabetes in adults. Geneva: World Health Organization. Retrieved from https://www.who.int/publications/i/item/9789240041149\u003c/li\u003e\n\u003cli\u003eSmith, J., Anderson, K., Brown, L., Davis, R., \u0026amp; Wilson, M. (2023). \u0026quot;Advanced statistical methods for analyzing clinical diabetes research data: A practical guide for researchers.\u0026quot; Journal of Diabetes Research, 2023, 1-15. https://doi.org/10.1155/2023/4567890\u003c/li\u003e\n\u003cli\u003eSingh A, Singh R, Chakraborty PP. Diabetes Monotherapies versus Metformin-Based Combination Therapy for the Treatment of Type 2 Diabetes. Int J Gen Med. 2021;14:3833-3848.\u003c/li\u003e\n\u003cli\u003eRossboth S, Lechleitner M, Oberaigner W. Risk factors for diabetic foot complications in type 2 diabetes: A systematic review. Endocrinol Diabetes Metab. 2020;3(4):e00175.\u003c/li\u003e\n\u003cli\u003eTang WH, Zhao YN, \u0026hellip; Liu XM. Risk factors for diabetic foot ulcers: A systematic review and meta-analysis. Vascular. 2023;32(3):[Page range].\u003c/li\u003e\n\u003cli\u003eJoseph JJ, Deedwania P, Acharya T, et al. Comprehensive Management of Cardiovascular Risk Factors for Adults With Type 2 Diabetes: A Scientific Statement From the American Heart Association. Circulation. 2022;145(9):e722-e759.\u003c/li\u003e\n\u003cli\u003eAmerican Diabetes Association Professional Practice Committee. Pharmacologic Approaches to Glycemic Treatment: Standards of Care in Diabetes-2025. Diabetes Care. 2025;48(Supplement_1):S181-S206.\u003c/li\u003e\n\u003cli\u003eYasseen YA, Aljabry KN. The impact of adding metformin therapy on type 2 DM patients on insulin treatment. Front Health Inform. 2024;13:588.\u003c/li\u003e\n\u003cli\u003e\u003cspan dir=\"RTL\"\u003e22.\u003c/span\u003e Alijaniha M, Alijaniha M, Mirzaalimohammadi M. Antibiotic Resistance Trends in Urinary Tract Infections: A Study from the Center of Iran (2021-23). J Occup Health Epidemiol. 2025;14(2):86-92. doi:10.61882/johe.14.2.86. Available from: http://johe.rums.ac.ir/article-1-997-en.html\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Type 2 diabetes, antidiabetic regimens, glycemic control, diabetic foot, metabolic parameters, personalized treatment","lastPublishedDoi":"10.21203/rs.3.rs-8086214/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8086214/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Type 2 diabetes mellitus (T2DM) remains a major global health challenge, with rising prevalence and significant complications. This study aimed to evaluate the effectiveness of various antidiabetic treatment regimens on glycemic control, blood pressure, body mass index (BMI), and diabetic foot complications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: A cross-sectional study was conducted among 150 T2DM patients (92 females, 58 males; mean age 62 ± 9.4 years) over six months. Data on fasting blood sugar (FBS), blood pressure, BMI, medication regimens, and diabetic foot complications were collected from electronic medical records. Statistical analysis was performed using SPSS version 26, with p \u0026lt; 0.05 considered significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The majority of patients (72%) were aged 50–69 years. Metformin-based therapies were most common (83.3%), with metformin monotherapy showing the best glycemic control (mean FBS 165.4 mg/dL). Insulin-containing regimens were associated with the highest FBS levels (224.3 mg/dL) and a 50% rate of diabetic foot complications. Patients with obesity (BMI ≥30) had significantly higher systolic blood pressure (141.3 mmHg, p \u0026lt; 0.01). Diabetic foot was observed in 12% of patients and was strongly associated with elevated FBS (258.3 mg/dL, p \u0026lt; 0.001), longer diabetes duration, insulin use, and higher BMI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: Metformin and metformin-gliclazide regimens demonstrated superior glycemic control and lower complication rates compared to insulin-based therapies. Blood pressure and BMI were significantly correlated, emphasizing the need for integrated management of T2DM and comorbidities. These findings support personalized treatment approaches to reduce complications and improve long-term outcomes in T2DM patients.\u003c/p\u003e","manuscriptTitle":"Comparative Effectiveness of Antidiabetic Treatments on Metabolic Control and Complications among Type 2 Diabetes Patients: A Real-World Observational Study with Public Health Implications","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-22 09:09:07","doi":"10.21203/rs.3.rs-8086214/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d91c0e0b-401f-445c-9aa7-ffcbe805431a","owner":[],"postedDate":"December 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-09T15:27:04+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-22 09:09:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8086214","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8086214","identity":"rs-8086214","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}