Metab Algeffari

Introduction Diabetic foot ulceration (DFU) is a major complication of diabetes and is a leading cause of lower-extremity amputation. This study evaluated the cross-sectional discriminative performance of the International Working Group on the Diabetic Foot (IWGDF) risk classification for prevalent active DFU, described gender-disaggregated ulcer prevalence, and identified factors independently associated with moderate/high IWGDF risk in a specialist diabetes center. Methods In this retrospective cross-sectional study, 713 adults with diabetes mellitus who attended the diabetic foot service of a university diabetes center were classified according to the IWGDF risk system. The prevalence of active DFU was compared across risk categories using the Cochran–Armitage trend test. Multivariable logistic regression was used to identify factors associated with moderate/high IWGDF risk and active DFU. Results Active DFU was present in 21 patients (2.9%), with no significant difference between men (3.8%) and women (2.1%). Overall, 17.3% of the patients were classified as having moderate or high risk. Ulcer prevalence increased progressively across the IWGDF categories, from 0.0% in the very-low-risk group to 38.5% in the high-risk group (p < 0.001). The IWGDF classification showed excellent cross-sectional discrimination for prevalent active DFU (c-statistic 0.938), with 90.5% sensitivity and 99.7% negative predictive value at the moderate/high-risk threshold. Older age and higher glycated hemoglobin (HbA1c) levels were independently associated with moderate/high IWGDF risk, whereas gender was not. Conclusion The IWGDF classification showed excellent cross-sectional discrimination for prevalent active DFU. Older age and poorer glycemic control, but not gender, were independently associated with moderate/high IWGDF risk. These findings support routine IWGDF-guided risk stratification in specialist diabetes care, although prospective studies are required to establish its performance in predicting future ulceration.

Background/Objectives: Left ventricular hypertrophy (LVH) is an important cardiovascular complication, but regional data on this condition among patients with type 2 diabetes mellitus (T2DM) in Saudi Arabia remain limited. This study determined the prevalence of LVH and associated factors among adults with T2DM without documented cardiac disease undergoing clinically indicated echocardiography at a specialized cardiac center in Saudi Arabia. Methods: This retrospective cross-sectional study included 625 patients with T2DM who underwent clinically indicated echocardiography at Prince Sultan Cardiac Center, Qassim, between January 2023 and December 2025. Of 878 patients with T2DM and no documented cardiac disease assessed for eligibility, 253 (28.8%) were excluded because at least one required clinical variable was missing or unavailable, leaving 625 patients (71.2%) in the final analysis. LVH was assessed according to American Society of Echocardiography/European Association of Cardiovascular Imaging recommendations. Multivariable logistic regression was used to evaluate factors associated with LVH. Results: LVH was identified in 146/625 patients (23.4%; 95% CI, 20.0–26.7). After multivariable adjustment, male sex (aOR = 1.71, 95% CI: 1.11–2.63; p = 0.015) and uncontrolled/elevated blood pressure (aOR = 2.18, 95% CI: 1.26–3.80; p = 0.006) were associated with LVH. Diabetes duration showed a significant nonlinear association with LVH (overall p < 0.001; p for nonlinearity = 0.001). Conclusions: LVH was common among this clinically selected group of patients with T2DM undergoing clinically indicated echocardiography. Male sex and uncontrolled/elevated blood pressure were associated with LVH after adjustment, while diabetes duration showed a nonlinear association. Although causal relationships cannot be established, the observed association between uncontrolled/elevated blood pressure and LVH highlights the importance of optimal blood pressure management as part of comprehensive cardiovascular risk reduction in patients with T2DM.

Background: Achieving remission of type 2 diabetes mellitus (T2DM) after bariatric surgery represents a critical opportunity to reduce long-term diabetes-related complications, including cardiovascular disease, nephropathy, neuropathy, and retinopathy. However, remission rates vary widely across patients, and identifying modifiable clinical and behavioral determinants remains essential for optimizing integrated metabolic care. Objectives: In the current study, we aimed to (1) classify type 2 diabetes mellitus (T2DM) remission status after bariatric surgery through clinical, anthropometric, and behavioral variables at follow-up; (2) identify the main model-based determinants of remission status and explainable machine learning using the preoperative model for baseline risk stratification with surgical candidates. Methods: We performed a retrospective cross-sectional study on 233 patients with T2DM who had bariatric surgery at a tertiary referral center. We made use of two analytical frameworks: a full-feature approach to identify the current remission status in a cross-sectional manner and a preoperative approach to make a temporal classification of the baseline for the first time. We trained and internally assessed 14 machine learning and deep learning classifiers. We evaluated model interpretability using SHAP. Results: In the full-feature cross-sectional classification, the Bottleneck Network performed best (ROC AUC = 0.889). SHAP data identified percentage weight regain, pre- and post-surgical body mass index, HbA1c, and oral hypoglycemic agent use as the dominant model-associated factors. In the restricted preoperative setting, the Extra Trees model achieved an AUC of 0.707, which is a lower level but still represents good baseline risk stratification performance. Conclusions: The findings indicate that remission status after bariatric surgery is both clinical as well as behavioral, but the post-operative or contemporaneously assessed variables should be looked at as classification (as opposed to prediction) models. The preoperative model may be able to be used in risk stratification, but clinical validation and prospective evaluation should be made prior to clinical implementation.

Background: Tricuspid valve dysfunction is historically underdiagnosed, and right-sided cardiac abnormalities are clinically important in high-risk diabetic populations. Diabetes may promote right-sided dysfunction through cardiometabolic remodeling, diastolic dysfunction, and elevated pulmonary pressures. This study introduces an explainable, lightweight artificial intelligence framework to infer extreme right heart phenotypes from left-sided echocardiographic and systemic clinical markers. Methods: We retrospectively analyzed an existing clinical dataset of approximately 370 Saudi Arabian individuals with diabetes mellitus. Seven baseline machine learning classifiers were evaluated using leak-aware preprocessing. To reduce optimism bias, models were validated with a True Nested Cross-Validation protocol. Probabilistic calibration, parameter reduction, and computational efficiency were prioritized for clinical triage, and SHapley Additive exPlanations (SHAP) supported transparent decision-making. Results: Random Forest was selected for its balance of discrimination and calibration. Under True Nested Cross-Validation, it achieved an AUC-ROC of 0.8602, AUC-PR of 0.8343, accuracy of 0.8075, sensitivity of 0.7733, specificity of 0.8239, Brier Score of 0.1281, Calibration Slope of 1.1720, and Observed/Expected Ratio of 0.8522. Feature ablation indicated a holistic cardiometabolic severity signal, with left atrial dimensions, diastolic dysfunction grade, and diuretic use as primary predictors. The model required 205.00 kilobytes of storage and 14.1956 milliseconds for inference. Conclusions: Left-sided cardiac markers combined with systemic indicators can flag concurrent severe right-sided abnormalities. This lightweight framework is a promising triage-oriented screening prototype for prioritizing echocardiographic assessment in high-risk diabetic patients during routine clinical visits without requiring specialized hardware; however, until prospective external validation is completed, this study must strictly be viewed as hypothesis-generating.

Type 2 diabetes is a global health issue, with unique challenges in Qassim, Saudi Arabia. Patients face barriers such as lifestyle, diet, healthcare access, and psychological impacts. Understanding these challenges is crucial for improving diabetes care and support. The aim of this study was to explore the challenges and barriers faced by patients in managing Type 2 diabetes at a University Hospital in Qassim, Saudi Arabia, to provide insights for improving diabetes care and support. A qualitative descriptive phenomenological design used semi-structured interviews and purposive sampling. Face-to-face interviews (Sept 2024-Jan 2025) were audio recorded and transcribed verbatim. Data were analyzed using Collaizi's thematic analysis. This study provides a comprehensive understanding of the key challenges and facilitators influencing the management of Type 2 diabetes. Thematic analysis identified five core themes: Challenges in Adapting Lifestyle and Behavior, Dietary Struggles and Social Pressures, Barriers to Effective Healthcare and Medication Use, Psychological and Emotional Burden of Diabetes, and Gaps in Patient Education and Support for Self-Management. Participants faced challenges of balancing self-care with work and social duties, dietary struggles tied to culture, healthcare barriers, emotional distress, and the vital role of education in disease management. A patient-centered approach is key to managing Type 2 diabetes in Qassim, Saudi Arabia. Addressing lifestyle, healthcare, and psychological challenges can improve self-management and outcomes. Providers should offer tailored education, enhance care access, and support emotional and social needs. Policies should promote culturally sensitive, community-based interventions to improve adherence and quality of life.

Individuals with diabetes, particularly those using insulin, face substantial challenges when fasting during the Islamic month of Ramadan due to prolonged periods without food or drink and an increased risk of hypoglycemia. Mini-dose glucagon (MDG) has been considered as an alternative to oral carbohydrate intake for mild or impending hypoglycemia without breaking the fast; however, current evidence is limited and remains preliminary, derived largely from small pilot studies and limited real-world data.

Background/Objectives: Mini—dose glucagon (MDG) is a safe and effective option for managing hypoglycemia during prolonged, repetitive fasts in people with type 1 diabetes (pwT1D) during Ramadan. We aimed in this study to evaluate the effectiveness and patient satisfaction of MDG for the management of fasting—induced hypoglycemia from the perspective of pwT1D fasting during Ramadan. Methods: We conducted an online survey shared via social media platforms and email announcements from May 2021 to April 2023 to collect feedback from 136 (72 female) persons with T1D about their experiences using MDG. In the survey, participants were asked to answer questions about diabetes history, hypoglycemia management during Ramadan, the efficacy of MDG treatment, the psychological impact of breaking the fast, side effects, injection experiences, and preferred future treatments for hypoglycemia caused by fasting. Results: After using MDG, 123 (91%) of participants reported they were able to complete their fasts. A total of 110 (80%) of participants reported that they prefer to use MDG over oral options in the future to correct fasting—induced hypoglycemia. Furthermore, participants showed significant change in their habits, which would otherwise have left them exposed to hypoglycemia or hyperglycemia for longer periods of time during fasts. Conclusions: These data demonstrate positive user experience and satisfaction following MDG as a treatment for fasting—induced hypoglycemia in pwT1D. Furthermore, MDG can promote the successful completion of fasts in Ramadan and encourage a change in unhealthy habits that may lead to prolonged hypoglycemia during fasts.

Background: The coronavirus disease 2019 (COVID-19) vaccine is one of the few vaccines that obtained emergency authorization to combat the fatal pandemic. Despite the fact that some available literature addressed its short-term side effects, there are still limitations on its effects on type 1 diabetes mellitus (T1DM). Objectives: The aim of the present study was to assess the association between COVID-19 vaccination and diabetic ketoacidosis (DKA) among individuals with T1DM. Additionally, the study aimed to determine the effects of the vaccine on glucose control, variability, and risk of hypoglycemia. Methods: This retrospective study was conducted at King Fahad Specialist Hospital (KFSH) in Qassim Region, Saudi Arabia. Diabetic ketoacidosis cases admitted to the hospital within February 2020 and August 2022 were included in the study based on specific inclusion criteria. Finally, a total of 49 patients were included in statistical analyses. Results: Out of the 62 patients admitted to the hospital, 49 met the diagnostic criteria for DKA and agreed to participate in the study. The majority of the remaining patients (n = 13) refused to participate, and only a few of them lacked complete documentation. Of the 49 patients who were included in the study, 46 cases had a history of T1DM; nevertheless, 3 patients were newly diagnosed with T1DM. Additionally, among these participants, 16 (32.7%), 19 (38.8%), and 14 (28.6%) patients had mild, moderate, and severe DKA, respectively. There were 27 male (55.1%) and 22 female (44.9%) patients. About 91% of the patients were vaccinated against COVID-19, 30.6% of whom were vaccinated within 29 days of being diagnosed with DKA. The pH and bicarbonate levels were observed to be significantly high among those who were diagnosed with DKA within 29 days of vaccination, with p-values of 0.031 and 0.037, respectively. Similarly, pH and random blood sugar (RBS) were observed to be significantly higher among the vaccinated patients than in the non-vaccinated subjects (P = 0.044 and P = 0.032, respectively). Conclusions: The study findings revealed that some of the DKA indicators were evident among the vaccinated patients. However, larger-scale and multi-center studies are recommended in order to have more conclusive evidence and generalize the findings.