Diabetes Mellitus in Sudan: Epidemiology, Risk Factors, Management Challenges, and Future Priorities
Diabetes mellitus has emerged as a major public health challenge in Sudan, where the burden has risen sharply over the past three decades in parallel with urbanization, demographic change, nutritional transition, and persistent health-system fragility. This narrative review synthesizes available evidence on the epidemiology of diabetes in Sudan, its principal risk factors, complications, barriers to care, current interventions, and future priorities. Early population-based studies in the 1990s documented modest but important levels of diabetes and impaired glucose tolerance, whereas more recent surveys indicate a substantially higher burden, with contemporary estimates suggesting that nearly one in five adults in Sudan is living with diabetes. A large proportion of cases remain undiagnosed, and prediabetes is increasingly recognized among both adults and adolescents. Consistently reported risk factors include older age, family history, central obesity, elevated body mass index, hypertension, urban residence, physical inactivity, and dietary transition. Diabetes-related complications are common and include retinopathy, nephropathy, peripheral neuropathy, and diabetic foot disease, all of which contribute to disability, reduced quality of life, and economic strain. Glycemic control is frequently suboptimal, while medication non-adherence, cost barriers, limited educator capacity, weak screening systems, and unreliable access to medicines and laboratory monitoring continue to undermine care. These challenges have been further intensified by ongoing conflict, which has disrupted health facilities, insulin storage, laboratory access, and continuity of care. Although national guidelines, pediatric mini-clinics, and humanitarian partnerships have strengthened some aspects of diabetes care, major gaps remain. Sudan urgently needs integrated, conflict-sensitive, and equity-oriented strategies that priorities prevention, early detection, continuity of treatment, and resilient diabetes services
Diabetes mellitus; Sudan; public health; epidemiology; risk factors; diabetes complications; glycemic control; health-system fragility; conflict-affected healthcare; noncommunicable diseases.
SGLT2 Inhibitors Beyond Glucose: Cardioprotective and Neuroprotective Effects in Type 2 Diabetes
https://doi.org/10.5281/zenodo.20287854 Type 2 diabetes mellitus (T2DM) is associated with a substantial burden of cardiovascular disease and diabetic peripheral neuropathy, which collectively drive the majority of diabetes-related morbidity and mortality. Sodium-glucose cotransporter-2 (SGLT2) inhibitors were originally developed as glucose-lowering agents; however, landmark cardiovascular outcome trials and emerging mechanistic evidence have demonstrated pleiotropic effects that extend well beyond glycaemic control. This systematic review aimed to synthesise evidence on the cardioprotective and neuroprotective effects of SGLT2 inhibitors in adults with T2DM, independent of their glucose-lowering properties. A systematic search of PubMed, Scopus, Web of Science, and CINAHL was conducted for studies published between January 2015 and December 2025. A total of 14 studies met the final inclusion criteria, comprising five major randomised controlled trials (RCTs) and nine supporting clinical and mechanistic studies enrolling a combined population exceeding 55,000 participants. SGLT2 inhibitors consistently reduced major adverse cardiovascular events (MACE), heart failure hospitalisation, and cardiovascular mortality across all three landmark trials — EMPA-REG OUTCOME (empagliflozin), CANVAS (canagliflozin), and DECLARE-TIMI 58 (dapagliflozin) — with hazard ratios for heart failure hospitalisation ranging from 0.65 to 0.73. Neuroprotective effects were documented through improvements in peripheral nerve conduction velocity, reduction in neuropathic symptom scores, and attenuation of oxidative stress biomarkers including malondialdehyde and neuroinflammatory cytokines. Favourable lipid modifications — particularly triglyceride reduction and HDL-C improvement further supported the mechanistic basis of dual cardioprotection and neuroprotection. SGLT2 inhibitors represent a disease-modifying therapeutic class capable of simultaneously attenuating cardiovascular and neuropathic complications in T2DM through mechanisms that operate independently of glycaemic control. Integration of these agents into comprehensive T2DM management protocols targeting multiorgan complication prevention is supported by the available evidence.
SGLT2 inhibitors · type 2 diabetes mellitus · cardioprotection · neuroprotection · diabetic neuropathy · cardiovascular outcomes · empagliflozin · dapagliflozin · canagliflozin · pleiotropic effects
Women’s Awareness Regarding Urinary Incontinence in Abbo's Fistula Center in Khartoum Teaching Hospital at Khartoum state, 2021
https://doi.org/10.5281/zenodo.20285010 Urinary incontinence is a common and often underrecognized condition that significantly affects women’s physical, psychological, and social well-being, particularly in resource-limited settings where awareness and access to care remain limited. This study aimed to assess the level of awareness and attitudes regarding urinary incontinence among women with obstetric fistula and to examine its association with selected demographic and clinical factors. A descriptive cross-sectional hospital-based study was conducted among 69 women attending Abbo’s Fistula Center at Khartoum Teaching Hospital, Sudan, over a three-month period. Data were collected through face-to-face interviews using a structured questionnaire assessing socio-demographic characteristics and awareness-related domains. Awareness was measured using a 21-point scoring system and categorized into low, moderate, and high levels. The majority of participants were aged 31–40 years (38%), and 64% reported having chronic disease. Overall, 46% of participants demonstrated moderate awareness, 35% had high awareness, and 18% had low awareness. Only 45% correctly identified urinary incontinence as involuntary leakage of urine, while 55% were unaware of its definition. Awareness of causes was highest for pregnancy and childbirth (78%) and aging (74%), whereas awareness of preventive measures was highest for early antenatal care (88%) and good care during labor (74%). A statistically significant association was observed between education level and awareness (p = 0.0326), while no significant associations were found with age, chronic disease, vaginal surgery, or prolapse. The findings indicate that awareness of urinary incontinence among women with obstetric fistula is suboptimal, with significant gaps in fundamental knowledge and preventive practices. Targeted educational interventions, particularly for women with lower educational levels, and integration of urinary incontinence awareness into maternal health services are recommended to improve understanding, reduce stigma, and promote early care-seeking.
Urinary Incontinence, Obstetric Fistula, Awareness, Women’s Health, Sudan
Knowledge, Attitudes, and Help Seeking Behavior Regarding Urinary Incontinence Among Women at Abbo’s Fistula Center, Khartoum: A Cross Sectional Study
https://doi.org/10.5281/zenodo.20285137 Urinary incontinence (UI) is a common and disabling condition that is often underreported because of stigma, misconceptions, and limited awareness, particularly among women living with obstetric fistula. This study assessed knowledge, attitudes, and barriers to seeking care for UI among women attending Abbo’s Fistula Center in Khartoum, Sudan. A descriptive cross-sectional study was conducted among 69 women with obstetric fistula between January and March 2021. Data were collected through face-to-face interviews using a structured questionnaire adapted from the International Consultation on Incontinence Questionnaire. The tool assessed sociodemographic characteristics, awareness of UI, attitudes toward the condition, help-seeking behavior, and use of pelvic floor muscle training (PFMT). The mean age of participants was 32.5 ± 8.9 years, and mean parity was 3.4 ± 2.1. Only 45% showed a positive attitude toward seeking medical care, while 55% had not sought care. Reported barriers included symptom normalization (41%), social stigma (26%), treatment cost (25%), and belief in spontaneous resolution (20%). UI had marked psychosocial effects, including low self-esteem, restricted physical activity, prayer difficulties, sleep disturbance, and constant concern about odor. Most participants had never practiced PFMT, and awareness was generally limited. Higher education was associated with better awareness and attitudes. These findings highlight the need for culturally sensitive education, stigma reduction, and integrated supportive services to improve early care-seeking and quality of life overall.
Urinary incontinence, Obstetric fistula, Help-seeking behavior, Pelvic floor muscle training, Sudan
Ergonomic and Work-Related Musculoskeletal DisordersAmong Dentists in Governmental Dental Hospitals inKhartoum, Sudan: A Cross-Sectional Study
Work‑related musculoskeletal disorders (WRMSDs) are pervasive among dental professionals worldwide, yet local data are scarce in many low‑ and middle‑income settings. This cross‑sectional study assessed the frequency of ergonomic exposures and WRMSD symptoms among dentists working in public dental hospitals in Khartoum, Sudan, and identified factors associated with symptom burden. A structured questionnaire captured sociodemographic information, occupational characteristics and self‑reported musculoskeletal complaints. Prevalence estimates, descriptive analyses and bivariate tests were used to examine associations between potential risk factors and WRMSD outcomes. A large proportion of participating dentists reported recent and chronic symptoms affecting the neck, shoulders and lower back. Taller height and greater patient volume showed the strongest associations with WRMSD complaints, while gender, age, body mass index and exercise habits did not significantly influence prevalence. These findings highlight the need for targeted ergonomic interventions and workload management to protect the musculoskeletal health of dentists in Sudanese public hospitals.
ergonomics; dentistry; work‑related musculoskeletal disorder; occupational health; Sudan; cross‑sectional study
When Albumin Misleads: Serum Albumin’s Prognostic Reliability in Non‑Critical Illnesses – A Systematic Review
Abstract. Serum albumin (SA) is widely used as a prognostic marker because it reflects nutritional reserves, inflammation, and disease burden. Its low cost and routine measurement make it appealing for risk stratification, yet its clinical interpretation in stable, non‑critical illnesses remains uncertain. We systematically reviewed studies published up to February 2026 that evaluated SA as a predictor of outcomes in non‑ICU adult populations. Searches of open‑access databases and manual screening yielded 24 observational studies encompassing approximately 80 000 participants across cardiac, renal, respiratory, surgical, oncologic and geriatric settings. Most studies were prospective or retrospective cohorts. We extracted populations, albumin thresholds and adjusted effect sizes and synthesised findings narratively. Hypoalbuminaemia consistently predicted all‑cause or disease‑specific mortality in maintenance haemodialysis, heart failure with cardiac resynchronisation, chronic obstructive pulmonary disease, community‑acquired pneumonia, stable coronary artery disease and major surgery; hazard ratios for mortality generally doubled to quadrupled when SA fell below 3.5–4.0 g/dL[1][2]. Conversely, a small ischemic stroke cohort and certain chronic kidney disease analyses showed minimal prognostic value of SA alone[3][4], highlighting the confounding effect of systemic inflammation and fluid status. Composite indices such as the blood urea nitrogen–albumin ratio, hemoglobin‑albumin‑lymphocyte‑platelet (HALP) score, age‑to‑albumin index and neutrophil percentage‑to‑albumin ratio improved risk prediction across diseases. Overall, SA is a useful but non‑specific marker; clinicians should interpret it alongside inflammatory markers and clinical scores rather than rely on it as a standalone prognosticator.
Serum albumin, Hypoalbumi-naemia, Prognostic marker, Mortality, Risk stratification
Heatwave Exposure and Cardiovascular Mortality: A Population-Based Study
Background: Heatwaves are increasingly frequent and intense, yet the magnitude and timing of cardiovascular mortality attributable to heatwave exposure remain incompletely quantified at the population level. Objective: To estimate the association between heatwave exposure and cardiovascular mortality, characterize lagged effects, and identify vulnerable subgroups for targeted public health interventions. Methods: We conducted a population-based time-series study using national mortality registry data linked to daily meteorological records across multiple urban and rural districts from January 2019 to December 2024. Heatwaves were defined as ≥3 consecutive days with daily mean temperature above the 95th percentile of district-specific warm-season temperatures. The primary outcome was daily cardiovascular mortality (ICD-coded), with secondary outcomes including ischemic heart disease and stroke mortality. Distributed lag non-linear models (DLNM) were applied to estimate relative risks (RRs) over lags 0–14 days, adjusting for long-term trends, seasonality, day-of-week effects, humidity, and air pollution proxies. Effect modification was assessed by age, sex, comorbidity burden, and neighborhood deprivation. Results: Across 126,418 cardiovascular deaths, 9.3% occurred during or within 14 days after heatwave periods. Heatwave exposure was associated with a 12.8% increase in cardiovascular mortality (RR 1.128; 95% CI 1.094–1.163; p<0.001), with the strongest effects observed at lags 1–3 and a measurable delayed signal through lag 7. Adults aged ≥75 years demonstrated the highest vulnerability (RR 1.176; 95% CI 1.129–1.225), and deaths were disproportionately concentrated in high-deprivation districts (interaction p=0.01). Stroke mortality increased by 14.6%, while ischemic heart disease mortality increased by 10.9% during heatwave-associated windows. A risk-stratification model incorporating nocturnal temperature, deprivation index, and baseline cardiovascular mortality achieved AUC 0.83, identifying high-burden heatwave weeks with 78.1% sensitivity and 76.4% specificity. Conclusion: Heatwave exposure is associated with a clinically significant rise in cardiovascular mortality, with both immediate and delayed effects and pronounced inequities by age and deprivation. Strengthening heat-health warning systems and targeted protection strategies for high-risk populations may reduce preventable cardiovascular deaths during extreme heat events.
Heatwave, cardiovascular mortality, environmental epidemiology
Efficiency of Digital Contact Tracing During Seasonal Influenza Outbreaks
*]:pointer-events-auto R6Vx5W_threadScrollVars scroll-mb-[calc(var(--scroll-root-safe-area-inset-bottom,0px)+var(--thread-response-height))] scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" data-turn-id="request-WEB:2f08f0ae-dda5-427a-8f87-18bd821d4f4e-0" data-turn-id-container="request-WEB:2f08f0ae-dda5-427a-8f87-18bd821d4f4e-0" data-testid="conversation-turn-2" data-scroll-anchor="false" data-turn="assistant"> Seasonal influenza remains a recurring public health challenge, causing substantial morbidity, healthcare utilization, absenteeism, and economic burden each year. Rapid identification and follow-up of exposed individuals are essential for limiting transmission, particularly in schools, workplaces, healthcare facilities, and other crowded settings. Digital contact tracing has emerged as a supportive strategy to enhance traditional contact tracing by improving speed, coverage, data accuracy, and real-time monitoring during outbreaks. This study examines the efficiency of digital contact tracing during seasonal influenza outbreaks, focusing on its ability to shorten notification time, improve case-contact identification, support early isolation or preventive measures, and reduce the workload of public health teams. Digital tools, including mobile applications, electronic reporting systems, proximity-based technologies, and integrated surveillance platforms, may strengthen outbreak response when they are well designed, widely adopted, and linked to existing public health systems. However, their effectiveness depends on user participation, data privacy protection, technological accessibility, and timely action after exposure notification. Challenges such as low uptake, incomplete data, digital inequity, and public trust concerns may limit their overall impact. Digital contact tracing should therefore be considered a complementary approach rather than a replacement for conventional public health measures. Strengthening digital infrastructure, community engagement, and ethical data governance may improve preparedness and response to future seasonal influenza outbreaks.
Digital epidemiology, influenza, outbreak control, surveillance
Postoperative Infection Rates Following Laparoscopic Versus Open Appendectomy: A Comparative Study
*]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" tabindex="-1" data-turn-id="b184b6ed-9af5-40f2-b50a-562632d0bfc3" data-testid="conversation-turn-58" data-scroll-anchor="true" data-turn="assistant"> Abstract Background: Appendectomy is among the most common emergency surgical procedures worldwide. While laparoscopic appendectomy is widely adopted, uncertainty persists regarding its real-world advantage over open appendectomy in reducing postoperative infectious complications, particularly across varying disease severity and perioperative workflows. Objective: To compare postoperative infection rates following laparoscopic versus open appendectomy and identify independent predictors of postoperative infection. Methods: We conducted a retrospective comparative cohort study including adults (≥18 years) who underwent appendectomy for suspected acute appendicitis between January 2021 and December 2024 across three tertiary hospitals. Patients were grouped by surgical approach (laparoscopic vs open). The primary outcome was any postoperative infection within 30 days, including surgical site infection (SSI) and intra-abdominal abscess. Secondary outcomes included length of stay, readmission, reoperation, and time to antibiotic discontinuation. Multivariable logistic regression adjusted for age, sex, BMI, diabetes, symptom duration, appendicitis severity (uncomplicated vs complicated/perforated), operative time, and timing of prophylactic antibiotics. Results: A total of 1,842 patients were included (laparoscopic: n=1,276; open: n=566). Overall postoperative infection occurred in 8.9% (n=164). Infection rates were significantly lower in the laparoscopic group compared with the open group (7.1% vs 13.1%; p<0.001). SSI occurred in 4.8% versus 9.9% (p<0.001), and intra-abdominal abscess occurred in 2.6% versus 3.2% (p=0.41) for laparoscopic versus open appendectomy, respectively. After adjustment, laparoscopic appendectomy was associated with reduced odds of postoperative infection (aOR 0.56; 95% CI 0.40–0.77; p<0.001). Complicated appendicitis was the strongest predictor of infection (aOR 3.21; 95% CI 2.36–4.37; p<0.001), followed by prophylactic antibiotic delay >60 minutes before incision (aOR 1.74; p=0.01). Median length of stay was shorter after laparoscopy (2.1 vs 3.4 days; p<0.001), and 30-day readmission was lower (4.3% vs 6.7%; p=0.02). Conclusion: Laparoscopic appendectomy was associated with significantly lower postoperative infection rates and shorter hospitalization compared with open appendectomy, without a significant difference in intra-abdominal abscess formation. Optimizing perioperative antibiotic timing and prioritizing laparoscopic approaches particularly in uncomplicated cases—may reduce postoperative infectious morbidity.
Appendectomy, surgical infection, laparoscopy, postoperative complications
Signals Before Symptoms: Integration of Digital Mobility Data and Syndromic Surveillance for Real-Time Outbreak Prediction in Europe
Background: Traditional infectious disease surveillance systems often detect outbreaks after community transmission has already intensified. Digital mobility metrics and real-time syndromic surveillance may provide earlier warning signals and enhance predictive accuracy. Methods: A multicenter European retrospective modeling study was conducted across Italy, France, Germany, and the United Kingdom from January 2022 to December 2025. Aggregated anonymized mobility datasets (n=6.8 million users) were integrated with syndromic surveillance reports and confirmed respiratory infection case counts. Time-series machine learning models were developed to compare traditional surveillance-only approaches versus hybrid digital-integrated models. Predictive performance was assessed using area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and lead-time gain. Results: Digital mobility increases above 15% of seasonal baseline were significantly associated with outbreak onset within 7–12 days (adjusted RR 1.42; 95% CI 1.28–1.58; p<0.001). The hybrid forecasting model demonstrated superior predictive accuracy (AUC 0.93) compared to traditional surveillance models (AUC 0.79; p<0.001). Median outbreak detection lead-time improved by 12 days. Sensitivity reached 88% with specificity of 83% across regions. Model robustness persisted across seasonal and geographic variations. Conclusion: Integration of digital mobility analytics with syndromic surveillance significantly enhances early outbreak detection in European settings. Adoption of hybrid digital-epidemiologic systems could substantially strengthen public health preparedness and response capacity.
Digital epidemiology; outbreak prediction; mobility data; syndromic surveillance; infectious disease modeling; public health preparedness
The Retina’s Warning Signal: Artificial Intelligence Prediction of Diabetic Retinopathy Progression
Diabetic retinopathy (DR) remains a major cause of preventable blindness worldwide. Early identification of patients at risk of rapid disease progression is essential for preventing severe visual impairment. Artificial intelligence (AI) has recently shown promise in analyzing retinal images and predicting disease outcomes. This study evaluated the performance of a deep-learning model in predicting diabetic retinopathy progression using baseline fundus photographs. A retrospective cohort study was conducted using 21,470 retinal fundus images obtained from 7,960 patients with diabetes between 2020 and 2024. The AI model was trained to predict progression to vision-threatening diabetic retinopathy (VTDR) over a three-year follow-up period. During the study period, 15.2% of patients showed disease progression, while 6.4% developed vision-threatening diabetic retinopathy. The deep learning model achieved an area under the curve (AUC) of 0.93, with sensitivity of 88.6% and specificity of 85.9% for predicting VTDR. Risk stratification analysis revealed that patients in the highest AI-predicted risk group accounted for 43% of future severe cases, despite representing only 18% of the total cohort. Simulation models indicated that implementing AI-based risk stratification could reduce routine screening visits by 24% while maintaining detection of over 92% of severe cases. These findings highlight the potential of artificial intelligence to transform diabetic retinopathy screening programs by enabling personalized follow-up intervals and early identification of patients at high risk of vision-threatening disease.
Diabetic Retinopathy, Artificial Intelligence, Fundus Imaging, Retinal Screening, Deep Learning
“The Quiet Signature: A Hidden Inflammation Index Predicting Sudden Cardiometabolic Collapse in ‘Stable’ Type 2 Diabetes”
`Background: Pediatric sepsis can progress rapidly, and clinical signs may appear late. We evaluated whether a compact bedside algorithm combining biomarkers and early warning scores can predict pediatric sepsis-related deterioration earlier than standard clinical assessment. Methods: We conducted a prospective diagnostic accuracy study in a tertiary children’s hospital including 612 patients (median age 4.1 years; IQR 1.2–9.3) presenting with suspected infection to the emergency department or pediatric wards. The index test (“SEPSIS-EDGE”) integrated procalcitonin, lactate, absolute neutrophil count, and a modified pediatric early warning score (PEWS). The reference standard was sepsis-related clinical deterioration within 24 hours (PICU transfer, vasoactive initiation, mechanical ventilation, or death), adjudicated by an independent panel blinded to the index score. We calculated sensitivity, specificity, AUC, and compared SEPSIS-EDGE against PEWS alone. Results: Sepsis-related deterioration occurred in 68/612 children (11.1%). SEPSIS-EDGE ≥7 demonstrated sensitivity 0.88 (95% CI 0.78–0.94), specificity 0.73 (95% CI 0.69–0.77), PPV 0.28, and NPV 0.98. Discrimination was excellent (AUC 0.89; 95% CI 0.85–0.93), outperforming PEWS alone (AUC 0.76; 95% CI 0.70–0.82; p<0.001). Median lead time to deterioration signal was 5.6 hours earlier (IQR 3.2–8.4) compared with clinician-triggered escalation documentation (p<0.001). In multivariable analysis, SEPSIS-EDGE ≥7 independently predicted deterioration (adjusted OR 9.4; 95% CI 4.8–18.2; p<0.001). Conclusion: A practical biomarker-enhanced bedside algorithm identified high-risk pediatric infection cases hours before overt clinical decline, offering a scalable approach for earlier escalation and targeted intervention in resource-intense settings.
Type 2 diabetes, low-grade inflammation, cardiovascular risk, hs-CRP, risk prediction
Beyond Glycemic Control:Decoding Therapeutic and Diagnostic Pathways in Diabetic Neuropathy — A Systematic Review
Diabetic neuropathy (DN) is a common and disabling complication of diabetes mellitus, causing neuropathic pain, sensory loss, autonomic dysfunction, and increased risk of diabetic foot ulceration and amputation. Despite improved glycemic control, DN is frequently underdiagnosed and remains difficult to manage. This systematic review synthesized recent clinical evidence on therapeutic and diagnostic strategies for DN based on a focused set of clinical studies. We conducted a PRISMA 2020–aligned search of PubMed, EMBASE, Cochrane CENTRAL, and Web of Science for randomized controlled trials and analytical observational studies published between January 2020 and March 2025. Eligible studies evaluated pharmacological, metabolic/antioxidant, device-based, rehabilitative, complementary, or diagnostic interventions in adults with DN. Twenty-two studies met inclusion criteria and were summarized narratively due to heterogeneity of interventions and outcomes. The most clinically actionable evidence supported individualized pharmacotherapy and structured sequencing of first-line agents for painful diabetic peripheral neuropathy, with meaningful improvements in pain outcomes. Adjunctive metabolic approaches (e.g., acetyl-L-carnitine, tocotrienol-rich vitamin E) demonstrated modest benefits in pain and neurophysiological measures. Device and rehabilitation strategies improved balance and functional outcomes in selected populations. Diagnostic advances, including point-of-care nerve conduction testing and vascular perfusion indices, showed potential to enable earlier detection and complication risk stratification. Overall, contemporary evidence supports a multimodal approach integrating optimized symptom control with practical screening and risk-focused assessment to reduce DN burden. Keywords: Diabetic Peripheral Neuropathy; Neuropathic Pain; Nerve Conduction; Spinal Cord Stimulation; Diabetic Foot Ulcer; Rehabilitation; Biomarkers; Systematic Review
Diabetic Peripheral Neuropathy; Neuropathic Pain; Nerve Conduction; Spinal Cord Stimulation; Diabetic Foot Ulcer; Rehabilitation; Biomarkers; Systematic Review
Echoes of Silent Decline: Early Clinical Signals Predicting Rapid Progression of Diabetic Kidney Disease in Adults with Type 2 Diabetes
Background: Diabetic kidney disease (DKD) remains a leading cause of chronic kidney disease and end-stage renal failure worldwide. While traditional markers such as estimated glomerular filtration rate (eGFR) and albuminuria guide risk stratification, many patients experience rapid renal decline despite apparently stable early indicators. Objective: To identify subtle early clinical and biochemical signals associated with accelerated DKD progression in adults with type 2 diabetes mellitus (T2DM). Methods: A prospective multicenter cohort study was conducted across four tertiary hospitals in Italy between January 2020 and December 2023. A total of 1,284 adults with T2DM and baseline eGFR ≥60 mL/min/1.73 m² were followed for a median of 36 months. Rapid progression was defined as an annual eGFR decline ≥5 mL/min/1.73 m² or progression to CKD stage ≥3. Multivariable Cox regression and predictive modeling were applied. Results: During follow-up, 312 patients (24.3%) met criteria for rapid DKD progression. Independent predictors included low-grade persistent inflammation (high-sensitivity CRP ≥3 mg/L; HR 1.82, 95% CI 1.41–2.35), nocturnal systolic blood pressure variability >15 mmHg (HR 1.67, p <0.001), and subtle increases in urinary albumin-to-creatinine ratio within the normoalbuminuric range (HR 1.59, p =0.003). A composite early-risk model demonstrated strong discrimination (AUC 0.87), identifying 78.4% of rapid progressors at baseline. Patients in the highest risk quartile showed a threefold higher progression rate (41.6% vs. 13.9%). Conclusion: Early DKD progression is often preceded by quiet yet measurable clinical changes that escape routine assessment. Incorporating inflammatory markers and blood pressure dynamics into early risk models may allow timely intervention and delay irreversible renal decline.
Diabetic kidney disease, early predictors, renal progression, type 2 diabetes, risk stratification
Veiled Signals of the Failing Myocardium: Multimarker Inflammation Trajectories Predicting Silent Heart Failure Progression in High-Risk Adults
Background: Subclinical progression to heart failure often remains undetected until overt decompensation occurs. Inflammatory pathways may provide early signals of myocardial vulnerability, yet their longitudinal predictive value in high-risk adults is insufficiently characterized. Methods: We conducted a prospective cohort study enrolling 1,042 adults aged 45 to 80 years with hypertension or type 2 diabetes but without clinical heart failure at baseline. High-sensitivity C-reactive protein, interleukin-6, and tumor necrosis factor alpha were measured at baseline and annually for three years. The primary outcome was incident heart failure confirmed by echocardiography and clinical criteria. Multivariable Cox models and time-dependent ROC analyses were applied. Results: Over a median follow-up of 38 months, 117 participants developed heart failure, corresponding to an incidence of 11.2 percent. Participants in the highest tertile of a composite inflammation trajectory score had a significantly higher risk compared with the lowest tertile with an adjusted hazard ratio of 2.41 and 95 percent confidence interval 1.63 to 3.56, p < 0.001. Each one standard deviation increase in the trajectory score was associated with a 34 percent higher risk of incident heart failure. The model including clinical covariates alone showed an AUC of 0.71, which improved to 0.81 after adding the inflammatory trajectories, p = 0.002. At a predefined risk threshold, sensitivity was 78 percent and specificity was 73 percent. The association remained consistent across subgroups defined by age, sex, and baseline left ventricular ejection fraction. Conclusion: Longitudinal inflammatory biomarker trajectories provide clinically meaningful early warning signals for silent progression toward heart failure in high-risk adults. Integrating dynamic inflammation profiling into routine risk assessment may enable earlier preventive interventions and more precise cardiovascular risk stratification.
Heart failure, inflammation biomarkers, risk prediction, longitudinal cohort, cardiovascular prevention
Scalpel and Silence: Underreported Surgical-Site Infections in Laparoscopic Appendectomies Across Regional Hospitals
Background: Laparoscopic appendectomy is one of the most common emergency surgeries performed globally. While considered low-risk, surgical-site infections (SSIs) remain a persistent and underreported complication, particularly in decentralized or non-academic hospital settings. Methods: A retrospective cross-sectional study was conducted in five regional Greek hospitals between January 2021 and December 2023. A total of 1,146 laparoscopic appendectomies were reviewed. SSI rates were evaluated using CDC criteria and compared between in-hospital documentation and 30-day post-discharge phone-based surveillance. Risk factors and delay in detection were analyzed using multivariate regression. Results: Official hospital records reported an SSI rate of 3.6% (n = 41), whereas 30-day surveillance identified 7.9% (n = 91) of patients with confirmed or probable SSIs (p < 0.001). Among these, 58.2% were superficial, 32.9% deep incisional, and 8.9% organ-space infections. Key independent predictors included preoperative fever (OR: 2.3, p = 0.002), surgery duration >90 minutes (OR: 1.9, p = 0.01), and lack of antibiotic prophylaxis documentation (OR: 3.6, p < 0.001). Over 61% of SSIs in the undocumented group were treated by general practitioners without hospital readmission, contributing to underreporting. Conclusion: There is a significant gap between documented and actual SSI rates following laparoscopic appendectomy in regional surgical centers. Reliance on inpatient records alone underestimates true postoperative infection rates. Implementing structured 30-day surveillance protocols, even via remote methods, may substantially improve surgical quality monitoring and patient safety.
Surgical-Site Infection, Laparoscopic Appendectomy, Post-Discharge Surveillance, Infection Underreporting, Greece
Blood in the Code: Missed AI Alerts and Hidden Risks in Automated Anemia Management in Diabetic Patients
Background: Artificial intelligence (AI)-driven decision support tools are increasingly integrated into electronic health records (EHRs) for chronic disease management. However, their reliability and sensitivity in detecting complex comorbid conditions, such as anemia in type 2 diabetes mellitus (T2DM), remain underexplored. Methods: A retrospective cohort study analyzed 3,112 adult patients with T2DM managed in primary care and outpatient clinics across the NHS in England between January 2021 and June 2023. AI-based alerts for anemia screening were reviewed and compared to manual laboratory data audits. Primary outcomes included sensitivity of AI detection, prevalence of missed cases, and impact on clinical outcomes (referrals, hemoglobin trends, and hospitalization). Results: Of 3,112 patients, 724 (23.2%) had anemia based on WHO criteria. The AI system successfully flagged 63.8% of cases (n = 462), while 36.2% (n = 262) were missed. Among missed cases, 44.7% had Hb <10 g/dL, and 18.3% required transfusion within 6 months. Hospitalization for anemia-related complications was significantly higher in the missed group (9.9% vs 3.2%, p < 0.001). Notably, iron studies and B12 levels were omitted in 68.7% of unflagged cases. Systematic review revealed that the algorithm failed to integrate multi-source lab inputs and excluded microcytic indicators in 29% of false negatives. Conclusion: AI-based alert systems show promise in managing chronic disease comorbidities but are currently insufficient in reliably detecting anemia in diabetic patients. This study highlights critical blind spots in algorithm logic and data integration. Until these are resolved, clinicians must maintain active vigilance and not rely solely on automated alerts for patient safety.
Anemia, Diabetes Mellitus, Artificial Intelligence, Clinical Decision Support, Missed Alerts
The Unseen Curve: Tracking Hidden Growth Faltering in Post-COVID Preschool Children
*]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" tabindex="-1" data-turn-id="request-685f27d8-e998-8010-be95-0e02a425f489-4" data-testid="conversation-turn-56" data-scroll-anchor="true" data-turn="assistant"> Background: Although most children recover well from COVID-19, the pandemic’s indirect effects on child nutrition, physical activity, and growth remain under-investigated—especially in preschoolers during critical development windows. Methods: A prospective cohort study was conducted between August 2022 and February 2024, involving 642 preschool children (ages 3–5 years) from five urban and rural regions in China. Children with PCR-confirmed COVID-19 were followed for 12 months and compared to age- and sex-matched controls without prior infection. Anthropometric data (height, weight, BMI), nutritional intake (3-day dietary logs), and serum growth-related biomarkers (IGF-1, vitamin D) were collected at baseline, 6 months, and 12 months. Results: At 12 months, 26.5% of post-COVID children showed a ≥10 percentile drop in height-for-age Z-score compared to 8.2% in the control group (p < 0.001). Mean IGF-1 levels were significantly lower in the post-COVID group (107.4 ± 22.1 ng/mL vs 123.8 ± 19.5 ng/mL, p < 0.001). Reduced appetite and decreased physical activity were reported by caregivers in 41.3% and 57.8% of post-COVID children respectively. Rural children had higher risk of growth faltering (RR: 2.8; 95% CI: 1.9–4.3). No significant difference in weight-for-height or BMI was observed, suggesting selective linear growth impact. Conclusion: Subclinical growth faltering may be a delayed consequence of COVID-19 in preschool children, particularly in vulnerable populations. Routine post-infection nutritional screening and community-based interventions could help mitigate long-term developmental impacts. Growth monitoring should be expanded to include COVID-19 recovery as a recognized risk factor in early childhood.
Pediatric Growth, COVID-19 Sequelae, IGF-1, Preschool Children, Linear Growth Dela
Cutting Through Silence: Hidden Incidence and Risk Predictors of Peripheral Nerve Injuries in Elective Abdominal Surgeries
Background: Peripheral nerve injuries (PNIs) are a rare but potentially debilitating complication of abdominal surgeries. Despite low reported incidence, emerging data suggests these events are frequently underdiagnosed due to delayed presentation and non-specific symptoms. Methods: A retrospective cohort study was conducted across four German surgical centers between January 2021 and December 2023. Medical records of 2,214 adult patients who underwent elective open or laparoscopic abdominal surgery were reviewed. PNIs were defined as new postoperative sensorimotor deficits persisting beyond 6 weeks, confirmed via clinical and electrophysiological assessment. Results: Peripheral nerve injury was identified in 63 patients (2.8%). The majority involved the lateral femoral cutaneous nerve (41.3%) and iliohypogastric nerve (33.4%). Laparoscopic procedures accounted for 61.9% of PNIs, despite shorter average operative time. Multivariate regression revealed BMI >30 kg/m² (OR: 2.2, p = 0.003), surgery duration >3 hours (OR: 2.6, p < 0.001), and Trendelenburg positioning >30 minutes (OR: 3.1, p = 0.001) as significant predictors. Only 19% of PNIs were documented prior to discharge; 44% were diagnosed after 30 days via outpatient follow-up. Conclusion: Peripheral nerve injuries following abdominal surgeries are more frequent than traditionally reported, with many cases missed during routine inpatient assessment. High BMI, prolonged procedures, and certain surgical positions significantly increase risk. Postoperative follow-up protocols should incorporate neurologic screening to allow early recognition and rehabilitation. Raising surgical awareness about PNI risk may reduce long-term patient morbidity.
Peripheral Nerve Injury, Abdominal Surgery, Surgical Complications, Elective Surgery, Germany
Silent Resistance: Rising Antimicrobial Non-Response in Community-Acquired Pediatric UTIs in Europe
Background: Community-acquired urinary tract infections (CA-UTIs) in children are becoming increasingly resistant to empirical antibiotics. The trend is subtle but alarming, with major implications for outpatient treatment policies and resistance containment. Methods: A multicenter observational study was conducted in four regions across France from March 2022 to January 2024. A total of 1,036 pediatric patients (age range: 6 months to 12 years) with CA-UTIs were enrolled. Midstream urine samples were collected prior to treatment, and culture sensitivity testing was performed. Primary outcome was resistance to first-line empiric antibiotics (amoxicillin-clavulanate, trimethoprim-sulfamethoxazole, and cefuroxime). Results: Overall, 43.7% of isolates were resistant to at least one first-line agent. Resistance was highest to trimethoprim-sulfamethoxazole (38.9%), followed by amoxicillin-clavulanate (26.3%), and cefuroxime (14.6%). Extended-spectrum beta-lactamase (ESBL)-producing E. coli was detected in 11.8% of cases. Children with recent antibiotic exposure (within 3 months) had a 2.3-fold increased likelihood of resistant infection (p < 0.001). Hospitalization was required in 17.5% of resistant cases versus 6.1% of sensitive cases (p = 0.004). Treatment failure occurred in 9.2% of initial prescriptions, with subsequent switch to broader-spectrum agents. Conclusion: The rate of antibiotic resistance in pediatric CA-UTIs is significantly higher than previously estimated, particularly for commonly prescribed oral agents. These findings call for immediate revision of empiric prescribing guidelines in pediatric primary care. Surveillance systems and antibiotic stewardship in outpatient settings are urgently needed to curb rising resistance trends.
Pediatric UTI, Antimicrobial Resistance, Empiric Treatment, ESBL, France
Veins of Fire: Uncovering the Hidden Burden of Undiagnosed Venous Thromboembolism in Type 2 Diabetic Patients
Background: Venous thromboembolism (VTE) is a major yet underdiagnosed complication in patients with type 2 diabetes mellitus (T2DM), often overshadowed by more commonly monitored cardiovascular events. This study explores the hidden prevalence, risk predictors, and clinical outcomes of undiagnosed VTE in asymptomatic T2DM patients. Methods: A multicenter cross-sectional screening study was conducted across four Italian endocrinology clinics between April 2022 and April 2024. A total of 824 T2DM patients (mean age 61.7 ± 10.3 years; 52.1% male; average HbA1c 8.2%) without prior VTE diagnosis or current anticoagulation therapy were included. All participants underwent Doppler ultrasound of the lower limbs and D-dimer testing. Results: Silent VTE (mostly distal deep vein thrombosis) was identified in 11.9% of participants (n=98), with 73.5% being completely asymptomatic. Among them, 63% had abnormal D-dimer levels (>500 ng/mL). Significant predictors included BMI >30 kg/m² (OR: 2.4; p < 0.001), sedentary lifestyle (OR: 1.9; p = 0.004), and poor glycemic control (HbA1c >9%) (OR: 1.8; p = 0.03). Only 14% of patients with positive findings were previously suspected to have thrombosis by their treating physicians. At 6-month follow-up, 7.1% of those with undiagnosed VTE experienced clinical progression requiring hospitalization. Conclusion: Undetected VTE in patients with T2DM is more common than expected, potentially compromising long-term vascular outcomes. Proactive screening using non-invasive tools may offer a cost-effective strategy to mitigate future complications. These findings call for updated VTE risk assessment protocols in diabetes management guidelines.
Type 2 Diabetes, Venous Thromboembolism, Undiagnosed DVT, Doppler Ultrasound, Hypercoagulability
Pattern of Clinical Presentation of Sudanese SLE Patients with Positive Antiphospholipid Antibodies Attending the Rheumatology Clinic at Merowe Hospital, 2024
Systemic lupus erythematosus is a chronic autoimmune disease with multisystem involvement, and antiphospholipid antibodies are frequently associated with thrombotic and obstetric complications that may worsen disease course. This analytical cross-sectional hospital-based study was conducted at Marawy Medical City (north Sudan) during August to December 2024 to assess the pattern of clinical presentation among Sudanese systemic lupus erythematosus patients with antiphospholipid antibodies and to explore associations between demographic factors and clinical patterns. Data were collected using a structured pre-tested interviewer-administered questionnaire and analyzed using SPSS. The study included adult and adolescent systemic lupus erythematosus patients (including pregnant patients) who had at least one positive antiphospholipid antibody. The findings showed that neurological and musculoskeletal symptoms were frequently reported, moderate-to-severe symptom activity was common, and thrombotic and obstetric complications consistent with antiphospholipid syndrome occurred in a subset of patients. Sun exposure, infections, physical activity, and stress were commonly reported triggers. A statistically significant association was identified between younger age group and skin manifestations, while other demographic variables showed no significant associations with clinical pattern. These findings support the importance of routine antiphospholipid antibody assessment and structured clinical surveillance to improve risk stratification and early recognition of severe antiphospholipid-related complications in systemic lupus erythematosus.
Serum Uric Acid as an Inflammatory Marker in Adult Sudanese Patients with Systemic Autoimmune Rheumatic Diseases (Khartoum Rheumatology Clinics, 2022–2023)
Backgroung Systemic autoimmune rheumatic diseases (SARDs) are chronic inflammatory disorders affecting the musculoskeletal system and multiple organs. Inflammation is usually assessed using erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP), but serum uric acid (UA) may also reflect systemic inflammation beyond gout-related pathology. Objective: To determine the frequency of hyperuricemia among adult Sudanese patients with SARDs and evaluate its relationship with ESR and CRP. Methods: A descriptive cross-sectional study was conducted in rheumatology clinics in Khartoum State, Sudan (August 2022–March 2023). Adults with systemic rheumatic diseases (n=130) were enrolled. Clinical and laboratory data (ESR, CRP, UA) were extracted from questionnaires and medical records. Associations were tested using chi-square and t-tests, and correlations were assessed using Pearson’s correlation (p<0.05). Results: Participants were predominantly female (59.2%), and 80.6% were aged 18–65 years. SLE (39.5%) and RA (31.5%) were the most frequent diagnoses, followed by undifferentiated connective tissue disease (15.3%) and ankylosing spondylitis (6.1%). ESR was elevated in 93% and CRP was positive in 34%. Serum UA was elevated in 61% of patients. High ESR was associated with SLE (p≈0.04), while high CRP was associated with SLE (p≈0.01) and ankylosing spondylitis (p≈0.03). In SLE, UA correlated with ESR and CRP (p<0.005 each). In RA, UA and CRP were elevated (p=0.002) and UA correlated with CRP. UA also correlated with CRP in undifferentiated connective tissue disease (p<0.001). Conclusion: Hyperuricemia was common among Sudanese adults with SARDs and showed significant relationships with conventional inflammatory markers in key subgroups. UA is an inexpensive, widely available test that may complement ESR and CRP for inflammation assessment in resource-limited settings; larger multicenter studies are warranted to confirm clinical applicability.
Serum uric acid, Hyperuricemia, Systemic autoimmune rheumatic diseases, Erythrocyte sedimentation rate (ESR), C-reactive protein (CRP)
Pulmonary Manifestation among Patients with Systemic Lupus Erythematosus (SLE) in Khartoum State 2022
Background: Systemic lupus erythematosus (SLE) is a chronic, multisystem autoimmune inflammatory disease that predominantly affects young women. Pulmonary involvement is variably reported across studies and ranges from mild pleural disease to interstitial lung disease (ILD), with pleural effusion and pulmonary fibrosis among the commonly described abnormalities. Objective: To determine the prevalence and pattern of lung manifestations among patients with SLE. Methods: A multicenter, observational, descriptive cross-sectional study was conducted in rheumatology clinics in Khartoum State, Sudan, during 2022. All patients diagnosed with SLE according to the 2019 classification criteria were included. Data were collected, cleaned, and analyzed using SPSS version 25.0. Results: The study included 53 patients with SLE, with a mean age of 39.3 ± 12.6 years and a male-to-female ratio of 1:52. Approximately half of participants (27, 50.9%) had been diagnosed with SLE for 1–5 years. The most frequent presenting symptoms were fever (14, 26.4%), cough (14, 26.4%), shortness of breath (10, 18.9%), and chest pain (7, 13.2%). Symptom duration of less than one year was reported by 26 patients (49.1%). Common comorbidities included hypertension (9, 17%), heart disease (3, 5.7%), and diabetes mellitus (2, 3.8%). Laboratory findings showed ANA positivity in 52 patients (98.1%); anti–dsDNA positivity in 23 (43.4%); elevated CRP in 12 (22.6%); elevated ESR in 33 (62.3%); low complement C3 in 8 (15.1%); and low complement C4 in 11 (20.8%). On chest X-ray, pleural effusion was noted in 2 (3.8%), lung fibrosis in 1 (1.9%), and reticulonodular shadowing in 1 (1.9%). On chest CT, ILD/pulmonary fibrosis was the most frequent finding (10, 18.9%), followed by pleural effusion (4, 7.5%); pulmonary nodule (1, 1.9%); nonspecific findings (1, 1.9%); ascites (1, 1.9%); and patchy consolidation (1, 1.9%). Echocardiography was normal in 9 patients (17%); ischemic heart disease was identified in 2 (3.8%); diastolic dysfunction in 1 (1.9%); mild aortic and tricuspid regurgitation in 1 (1.9%); and pulmonary hypertension in 1 (1.9%). Regarding treatment, most participants received hydroxychloroquine (47, 88.7%), followed by azathioprine (15, 28.3%), mycophenolate mofetil/Cellcept (11, 20.8%), prednisone (10, 18.9%), and leflunomide (1, 1.9%). Conclusion: Pulmonary manifestations among Sudanese patients with SLE were clinically relevant and should not be overlooked, particularly ILD/pulmonary fibrosis and pleural effusion. These findings support strengthening screening, early detection, and targeted prevention and management policies for high-risk SLE patients in Sudan.
Systemic lupus erythematosus, Pulmonary manifestations, Interstitial lung disease, Pulmonary fibrosis, Pleural effusion
Association Between Periodontitis andRheumatoid Arthritis in Haj Alsafi TeachingHospital, Khartoum State, Sudan2022-2023
Periodontitis is a chronic inflammatory disease that leads to progressive destruction of the supporting structures of the teeth and has been increasingly linked to systemic inflammatory conditions. Rheumatoid arthritis is a chronic autoimmune disorder characterized by persistent synovitis, systemic inflammation, and progressive joint damage, and growing evidence suggests a biological and clinical overlap between these two conditions. This hospital-based cross-sectional study aimed to assess the association between periodontitis and rheumatoid arthritis among adults attending Haj Alsafi Teaching Hospital, Khartoum State, Sudan, during 2022–2023. Adult patients with clinically diagnosed periodontitis were evaluated using structured clinical assessment, laboratory inflammatory and rheumatological markers, and radiological investigations. The analysis focused on describing the prevalence of musculoskeletal manifestations suggestive of rheumatoid arthritis and examining their relationship with the severity of periodontal disease. The findings indicated that a substantial proportion of patients with periodontitis exhibited musculoskeletal symptoms consistent with rheumatoid arthritis, and increasing periodontal severity was associated with higher inflammatory and immunological markers. These results support the concept of a clinically relevant link between periodontal inflammation and systemic rheumatologic involvement and highlight the importance of integrated screening approaches in routine clinical practice. Key words: Periodontitis, Rheumatoid arthritis, Anti-CCP antibodies, Rheumatoid factor, C-reactive protein
Periodontitis, Rheumatoid arthritis, Anti-CCP antibodies, Rheumatoid factor, C-reactive protein
Whispering Pixels: Ultrasound Radiomics for Thyroid Nodule Malignancy in Iodine-Deficient Regions
Background: Diagnostic imaging of thyroid nodules in iodine-deficient regions is challenging because benign hyperplastic nodules may mimic malignancy. Conventional TI-RADS scoring has limited sensitivity in such contexts. Radiomics, through advanced quantitative texture analysis, can identify subtle imaging features associated with cancer that are invisible to the human eye. Objective: To assess the diagnostic performance of an ultrasound radiomics model compared with TI-RADS and evaluate its added value for detecting thyroid malignancy in iodine-deficient populations. Methods: A prospective observational study was conducted between 2022 and 2024 at three hospitals located in known iodine-deficient areas. A total of 1,028 nodules in 876 consecutive patients (mean age 47 ± 11 years, 72% female) were analyzed. Each patient underwent high-resolution ultrasound imaging followed by histopathological confirmation. Radiomic features, including first-order statistics, texture, and wavelet-based parameters, were extracted and processed using a LASSO-based selection method. Logistic regression and random-forest models were trained and validated with 10-fold cross-validation. Results: Malignancy was confirmed in 22.9% of nodules. The conventional TI-RADS achieved an area under the curve (AUC) of 0.81, whereas the radiomics model reached 0.90. When combined with TI-RADS scores, the integrated model achieved an AUC of 0.93 (95% CI 0.91–0.95), sensitivity 88%, and specificity 85%. The most important predictors were high gray-level entropy (odds ratio 2.7) and irregular margin compactness (odds ratio 2.1). The combined model improved net reclassification by 18% compared to TI-RADS alone. Conclusion: Ultrasound radiomics substantially enhances the accuracy of thyroid cancer risk prediction in iodine-deficient areas. Integrating radiomics with existing scoring systems may improve early diagnosis and reduce unnecessary biopsies.
Thyroid nodule, Radiomics, Ultrasound, Cancer risk, Iodine deficiency
Echoes in the Data: Phenotyping HFpEF with EHR–Echocardiography Fusion and Machine Learning
Abstract Background: Heart failure with preserved ejection fraction (HFpEF) represents over 50% of all heart failure hospitalizations, yet its clinical heterogeneity hinders targeted therapy. Combining electronic health record (EHR) data with advanced echocardiographic parameters through machine learning may help identify prognostic phenotypes for early intervention. Objective: To develop and validate a machine-learning model integrating clinical and echocardiographic data for phenotyping HFpEF and predicting one-year readmission or death. Methods: This multicenter retrospective study included 4,012 adults (mean age 67 ± 10 years; 58% female) with ejection fraction ≥ 50% and NT-proBNP ≥ 125 pg/mL across three tertiary hospitals between 2019 and 2024. A total of 42 variables were extracted, including demographics, laboratory results (creatinine, hemoglobin, HbA1c), comorbidities, medications, and echocardiographic metrics (E/e′ ratio, GLS, LA volume index). Gaussian mixture clustering identified phenotypes, and Cox proportional-hazards models evaluated one-year outcomes. Results: Three distinct phenotypes were identified. Cluster 1 (Metabolic-Atrial) included 34% of the cohort and was characterized by obesity (BMI ≥ 30 kg/m²), frequent atrial fibrillation, and intermediate GLS (–18.5%), with a 12-month event rate of 10.8%. Cluster 2 (Renal-Congestive) represented 28% of patients, marked by eGFR < 45 mL/min and the highest NT-proBNP levels (median 1830 pg/mL), showing a 12-month event rate of 23.6%. Cluster 3 (Fibrotic-Stiff) accounted for 38% of cases, defined by a high left atrial volume index (>40 mL/m²) and diastolic dysfunction grade ≥ 2, with an event rate of 15.1%. The integrated model achieved a C-index of 0.82 (95% CI 0.80–0.84), outperforming the conventional H2FPEF score (0.71). Independent predictors of poor outcome included E/e′ > 14 (HR 1.9, p < 0.001), GLS ≥ –16% (HR 1.6, p = 0.01), and eGFR < 45 (HR 2.2, p = 0.002). Conclusion: The fusion of EHR and echocardiographic data using machine learning reveals reproducible HFpEF phenotypes with distinct risk patterns. This approach supports personalized prognostication and individualized treatment strategies in cardiometabolic patients.