Background: Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, with over 75% of deaths occurring in low- and middle-income countries, where conventional risk models often demonstrate poor calibration and limited generalizability. Objective: This study aimed to develop an interpretable, pharmacotherapy-informed machine learning model for cardiovascular risk prediction using national electronic health record (EHR) data from Jordan. Methods: A retrospective cohort study was conducted using approximately 600,000 individuals from the national Hakeem EHR system (2018-2022). Demographic, clinical, blood pressure, laboratory, and medication data were integrated to construct three datasets reflecting varying levels of feature completeness. Multiple machine learning models were benchmarked, followed by optimization, hybrid modeling, and probability calibration. Model interpretability was assessed using SHAP analysis. Results: The national cohort demonstrated a high cardiometabolic burden, with prevalence of hypertension (50.2%), hyperlipidemia (54.9%), and diabetes (47.9%). Antihypertensive and lipid-lowering therapies were more frequently used among CVD patients (56.9% and 49.6%, respectively). Treatment patterns were dominated by amlodipine (19.9%) and atorvastatin (74.4%). The final calibrated seed-bagged gradient boosting model achieved robust performance (ROC-AUC 0.844; PR-AUC 0.813) with consistent generalization across datasets. Key predictors included antihyperlipidemic therapy, systolic blood pressure variability, age, and sex. Conclusions: This study presents JoRisk, a calibrated and interpretable machine learning framework that integrates pharmacotherapy and clinical data for short-term cardiovascular risk prediction. The model demonstrates strong performance using routinely available EHR variables and offers a scalable decision-support tool for risk stratification in resource-constrained healthcare systems.

Background: Osteoporosis is increasingly understood as a complex population health condition shaped by interacting behavioral, metabolic, pharmacological, and healthcare system determinants rather than isolated skeletal risk factors. However, comparative studies integrating these dimensions across distinct healthcare and sociocultural settings remain scarce. We aimed to characterize cross-national differences in osteoporosis-related risk clustering between Romanian and Tunisian adults using an integrative multidimensional framework. Methods: We performed a comparative cross-sectional analysis of harmonized data from two pharmacy-based studies conducted in Romania and Tunisia, including adults aged ≥ 40 years (n = 349). Osteoporosis-related knowledge, lifestyle and metabolic risk factors, pharmacological exposures, preventive behaviors, and treatment patterns were assessed. Multivariable regression and mediation analyses were used to identify independent predictors of screening uptake and to evaluate the relationship between knowledge and preventive behavior. An exploratory cumulative preventive deficit score was used to estimate overall preventive burden within the pharmacy-based study sample. Results: Romanian participants demonstrated significantly higher osteoporosis knowledge than Tunisian participants (8.90 ± 2.20 vs. 7.83 ± 2.99; p < 0.001); however, knowledge was not independently associated with Dual-Energy X-ray Absorptiometry (DXA) uptake and did not mediate country-related differences in screening behavior. Compared with the Romanian cohort, the Tunisian cohort exhibited lower DXA screening rates (11.2% vs. 22.8%; p = 0.005), lower vitamin D supplementation (11.9% vs. 38.6%; p < 0.001), greater sedentary behavior, and a significantly higher cumulative preventive deficit burden (3.39 ± 1.08 vs. 2.77 ± 1.26; p < 0.001). Medication-related osteoporosis risk was also greater in Tunisia, particularly due to markedly higher corticosteroid exposure (7.5% vs. 0.5%; p = 0.002). Despite this less favorable preventive profile, the treatment gap among participants with diagnosed osteoporosis was significantly lower in Tunisia than in Romania (4.8% vs. 42.9%; p = 0.003). Conclusions: Distinct but convergent osteoporosis-related risk patterns were identified across the two populations, suggesting that osteoporosis vulnerability emerges through context-specific clustering of behavioral, pharmacological, and healthcare-access determinants rather than through isolated risk factors alone. The dissociation between knowledge and preventive behavior highlights the limited impact of awareness-based strategies when structural barriers remain unaddressed. These findings support a shift toward integrated, population-tailored osteoporosis prevention models that incorporate healthcare-system, medication-related, and behavioral determinants, in addition to conventional educational approaches.

Cardiovascular disease remains a leading cause of mortality despite major advances in lipid lowering and risk-factor control, highlighting the importance of residual cardiovascular risk. Inflammation is a central driver of atherosclerosis, while obesity promotes chronic low-grade inflammation, adipose tissue dysfunction, ectopic fat accumulation, and vascular injury. This narrative review focuses on obesity-associated inflammation as an upstream contributor to residual atherosclerotic risk and evaluates whether incretin-based therapies modify this pathway through weight loss, metabolic improvement, and additional inflammatory or vascular mechanisms. Data from mechanistic studies, biomarker analyses, vascular imaging studies, and cardiovascular outcome trials are reviewed. Anti-inflammatory trials support inflammation as a modifiable therapeutic pathway, although clinical benefit depends on the therapeutic target, timing, and patient selection. Glucagon-like peptide-1 receptor agonists reduce inflammatory and oxidative stress biomarkers and show anti-atherosclerotic effects in experimental models, but human vascular imaging data remain inconclusive. Cardiovascular outcome trials establish benefit with several GLP-1 receptor agonists, including semaglutide in selected patients with overweight or obesity without diabetes. However, direct human evidence for receptor-mediated anti-inflammatory or anti-atherosclerotic effects remains limited, and the relative contributions of weight loss, metabolic improvement, and additional mechanisms remain uncertain.

With the growing of the global population aging, the comorbidity of cardiovascular disease (CVD) and Alzheimer's disease (AD) has gradually become a major contributor to global disease burden, with the two diseases exhibiting interacting pathological characteristics. This review summarizes the mechanisms underlying CVD-AD comorbidity, including cerebral hypoperfusion and protein aggregation, oxidative stress and inflammation, as well as metabolic disorders and genetic factors. We also assess the value of blood biomarkers in this comorbidity, such as p-tau217, NT-proBNP, NfL, GFAP, and miRNAs. We then review the role of exercise in ameliorating this comorbidity, integrating its potential mechanisms into five aspects: repairing cerebral hypoperfusion and endothelial injury, accelerating Aβ clearance and inhibiting Tau protein hyperphosphorylation, reducing inflammation, protecting neuronal structure and the blood-brain barrier, and improving metabolic disorder. We also analyze in detail the relationship between exercise targets and blood biomarkers. Finally, we discussed the impact and application of different exercise modalities in this comorbidity, concluding with suitable exercise prescriptions and relevant safety considerations for each modality, further organized the mainstream pharmacological and nutritional intervention strategies for CVD-AD comorbidity, and objectively explored their potential interactions when combined with exercise interventions. Future research should integrate multi-omics technologies and gradually refine clinical data on comorbidity, with the aim of developing more targeted, personalized exercise prescriptions for patients with comorbidities, thereby providing scientific theoretical guidance for early risk prevention and disease management in patients with co-occurring CVD and AD.

Headache is a common complaint in children and may indicate early hypertension (HT), an emerging concern in pediatrics. Children with primary headache (PH) may exhibit elevated blood pressure (BP) load or impaired nocturnal dipping despite normal office BP. This study aimed to evaluate the utility of ambulatory blood pressure monitoring (ABPM) in children with PH.

A case-control study was conducted including 37 children aged 8-17 years diagnosed with PH according to the International Classification of Headache Disorders (ICHD-3) criteria, all with office BP below the 95th percentile. Thirty-seven age- and sex-matched healthy subjects served as controls. Demographic, office BP, and ABPM parameters were compared between groups.

Of the PH group, 81% (n = 30) had migraines and 19% (n = 7) had tension-type headache. No significant differences were found between groups regarding age, BMI SDS, or office systolic BP SDS. However, ABPM revealed significantly higher total, daytime, and nocturnal systolic BP, and increased nocturnal systolic and diastolic BP loads in the PH group (all p < 0.05). No differences were noted between headache subtypes.

Children with PH may exhibit increased BP loads and disrupted BP patterns despite normal office measurements. ABPM appears to be a useful tool for accurately detecting subtle BP alterations in this population.

Inflammation and thrombosis influence short-term outcomes after primary percutaneous coronary intervention (PCI) for acute ST-segment elevation myocardial infarction (STEMI). The platelet-to-lymphocyte ratio (PLR) is an inexpensive marker that may support bedside risk stratification.

To assess whether pre-PCI and post-PCI PLR predict in-hospital outcomes and 90-day all-cause mortality in STEMI patients undergoing primary PCI in Palestine.

This retrospective cohort study included STEMI patients referred for primary PCI at An-Najah National University Hospital. Of 413 eligible patients, 118 were excluded for incomplete records, leaving 295 patients for analysis. PLR was measured before and after PCI and dichotomized using ROC-derived cutoffs: pre-PCI PLR < 21.68 versus ≥ 21.68 and post-PCI PLR < 14.85 versus ≥ 14.85. Outcomes were compared between groups, and multivariable logistic regression was used to assess independent associations.

Elevated pre-PCI PLR was associated with greater in-hospital clinical instability and remained independently associated with the composite in-hospital clinical endpoint, both per 10-unit increase (OR 1.41, 95% CI 1.13-1.74; p = 0.002) and using the cutoff ≥ 21.68 (OR 2.90, 95% CI 1.55-5.44; p < 0.001). However, pre-PCI PLR was not independently associated with heart failure or 90-day mortality. Post-PCI PLR showed stronger prognostic value and was independently associated with composite in-hospital events, heart failure, and 90-day mortality, both as a continuous variable and using the cutoff ≥ 14.85.

Post-PCI PLR demonstrated stronger prognostic value than pre-PCI PLR and may serve as a simple, low-cost adjunctive marker for short-term risk stratification after primary PCI in STEMI patients.

Early diagnosis of acute myocarditis (AMC) is crucial due to its rapid progression and high mortality rate. Initial symptoms such as fever, abdominal pain, and vomiting are nonspecific and pose challenges for clinicians in distinguishing AMC from acute gastroenteritis (AGE).

We retrospectively reviewed the clinical characteristics of seven patients with AMC who were hospitalized at our institution between April 2011 and March 2022. We compared these findings with those of 19 patients with AGE.

The common initial symptoms of patients with AMC included fever, vomiting, abdominal pain, appetite loss, nausea, and fatigue, which did not differ significantly from those in patients with AGE. However, the percentage of diarrhea was significantly lower, whereas the detection rates of tachypnea, tachycardia, gallop rhythms, or cardiomegaly on radiography were higher in the patients with AMC than in those with AGE, respectively. Additionally, patients with AMC exhibited significantly higher serum lactate dehydrogenase (LDH) levels than those with AGE (p = 0.006). LDH demonstrated 71% sensitivity and 100% specificity (area under the curve, 0.857) for predicting AMC when a cutoff value of 459 U/L was used.

Preliminary findings suggest that LDH may serve as a trigger for suspicion of AMC in the pediatric population. Furthermore, combining LDH results with physical examination and chest radiographic findings could be useful for early diagnosis.

To evaluate the effect of 12-week Mavacamten on left ventricular function in obstructive hypertrophic cardiomyopathy (oHCM) using myocardial work analysis, and explore its role in myocardial energy metabolism.

Thirty-five oHCM patients and 35 matched healthy controls were enroled. Patients received Mavacamten for 12 weeks. At baseline and post-treatment, we measured LVOT gradient, LVEF, GLS, myocardial work parameters [GWI, GCW, GWW, GWE], mitral regurgitation severity, and SAM.

Myocardial work parameters showed good reproducibility (ICCs > 0.75). After 12 weeks, resting and provoked LVOT gradients significantly decreased (both p < 0.001). Proportions of moderate/severe mitral regurgitation and SAM reduced. GWI, GCW, and GWW decreased (p < 0.001), while GWE increased (p < 0.001). NT-proBNP decreased and NYHA functional class improved (p < 0.001). LVEF, GLS, and left atrial diameter showed no significant changes. Compared with controls, baseline oHCM patients had lower GWI, GCW, GWE and higher GWW (all p < 0.001). After treatment, GWE remained lower than controls (p < 0.001), and GWW remained higher (p < 0.001).

Twelve-week Mavacamten reduces LVOT obstruction in oHCM, accompanied by decreased GWI and increased GWE, while preserving systolic function and improving symptoms. Myocardial work parameters may serve as novel non-invasive references for treatment evaluation.

Complete atrioventricular block after mechanical tricuspid valve replacement represents a challenging pacing scenario because transvalvular right ventricular lead placement is contraindicated. We report a 51-year-old woman with mechanical mitral and tricuspid valves who presented with syncope and complete AV block due to late epicardial lead dysfunction. Transient restoration of capture during transthoracic echocardiography suggested dynamic lead-myocardial contact or intermittent lead continuity. Coronary sinus pacing was attempted but abandoned because of intolerable diaphragmatic stimulation. The patient later deteriorated and died from septic shock. This case highlights the limitations of available pacing strategies after mechanical tricuspid valve replacement.

The incidence of distal femur fractures (DFF) has shown a continuous annual increase. Preoperative deep vein thrombosis (DVT) of the lower limbs in DFF patients is associated with unfavorable clinical outcomes. Inflammation has been recognized as an essential contributor to thrombus formation, drawing increasing research attention in recent years.

This study aimed to construct a predictive model utilizing inflammatory blood indicators to estimate the preoperative risk of DVT in patients with DFF.

A retrospective analysis was performed on 493 eligible patients treated for DFF, admitted to a single-center, between January 2022 and September 2025. Clinical baseline characteristics and laboratory parameters were collected. Independent risk factors for preoperative lower limb DVT were identified through univariate and multivariate binary logistic regression analyses. The predictive model was established using R 4.2.0, with patients randomly allocated to training and validation cohorts in a 7:3 ratio. Receiver operating characteristic (ROC) curves and corresponding areas under the curve (AUC) were computed for internal validation. Model performance was further assessed using calibration curves (CC) and decision curve analysis (DCA) in both cohorts.

A total of 493 eligible patients were analyzed, comprising 205 cases with DVT and 288 without DVT. Univariate and multivariate binary logistic regression identified neutrophil- to-lymphocyte (NLR) (OR = 0.86, 95% confidence interval (CI) [0.774-0.95], P = 0.004), lymphocyte-to-monocyte ratio (LMR) (OR = 1.545, 95% CI [1.3-1.851], P = 0.000), white blood cell count (OR = 1.245, 95% CI [1.152-1.353], P = 0.000), neutrophil count (OR = 1.563, 95% CI [1.398-1.766], P = 0.000), lymphocyte count (OR = 0.151, 95% CI [0.077-0.285], P = 0.000), and eosinophil count (OR = 2.343, 95% CI [0.657-8.447], P = 0.19) as independent variables associated with preoperative lower limb DVT in DFF patients. Incorporating age with these indicators, a predictive model was developed. The ROC analysis demonstrated AUC values of 0.926 and 0.939 in the training and validation cohorts, respectively.

Among the preoperative inflammatory indicators evaluated, NLR, LMR, white blood cell count, neutrophil count, lymphocyte count, and eosinophil count were identified as independent determinants of preoperative lower limb DVT in patients with DFF. The predictive model constructed based on independent risk factors has excellent predictive efficacy and clinical application value.