OBJECTIVE:Current clinical guidelines for non-ST-segment elevation myocardial infarction (NSTEMI) emphasize the duration of dual antiplatelet therapy (DAPT) based on scores such as the Predicting Bleeding Complications in Patients Undergoing Stent Implantation and Subsequent Dual Antiplatelet Therapy (PRECISE-DAPT) score and the Dual Antiplatelet Therapy (DAPT) score. However, these anatomical and clinical models often overlook the "inflammatory gap,' namely the contribution of systemic inflammation to both thrombotic and hemorrhagic risk. Although traditional models focus primarily on anatomical complexity, systemic inflammation may serve as a silent driver of adverse outcomes. We aimed to evaluate, using an artificial intelligence (AI)-enhanced approach, the incremental prognostic value of the inflammation-based Modified Glasgow Prognostic Score (mGPS) over a 36-month follow-up period, with particular emphasis on capturing non-linear interactions between biological markers and long-term outcomes. METHOD:This study included 456 NSTEMI patients who underwent percutaneous coronary intervention (PCI). mGPS, DAPT, and PRECISE-DAPT scores were calculated for all patients. Prognostic performance was assessed using a Gradient Boosting Machine (GBM)-based machine learning (ML) framework. Analyses focused on improvements in the concordance index (C-index), Net Reclassification Index (NRI), and Integrated Discrimination Improvement (IDI), as well as three-year mortality assessed using Cox proportional hazards modeling to identify residual inflammatory risk. Model calibration was evaluated using the Brier score. RESULTS:At 36 months, mGPS emerged as the strongest independent predictor of mortality. Compared with patients with mGPS 0, those with mGPS 2 demonstrated a 6.18-fold higher risk of mortality (hazard ratio 6.18; 95% confidence interval 2.95-12.94; P < 0.001). Observed mortality rates increased markedly from 3.2% in the mGPS 0 group to 57.1% in the mGPS 2 group (P < 0.001). While mGPS was not significantly associated with the ischemic DAPT score (P = 0.349), it was strongly associated with high bleeding risk (PRECISE-DAPT ≥ 25), with all patients in the mGPS 2 category classified as high bleeding risk (P < 0.001). Incorporation of mGPS into the baseline AI model significantly improved discriminative performance, increasing the C-index from 0.72 to 0.81 (P = 0.008). Additionally, the model correctly reclassified 46% of patients (NRI 0.46, P < 0.001) and demonstrated significant predictive improvement (IDI 0.08, P = 0.004) compared with traditional scoring systems. CONCLUSION:Systemic inflammation, as quantified by mGPS, is a critical biological modifier of cardiovascular risk that may help bridge the "inflammatory gap" in current scoring systems. AI-driven integration of mGPS into conventional clinical scores significantly improves 36-month prognostic reclassification. mGPS appears to function as a biological recalibrator, identifying high-risk individuals who may be misclassified by conventional scoring systems. These findings suggest that mGPS-guided personalized antiplatelet strategies-particularly early DAPT de-escalation in patients with elevated mGPS-may help reduce the high mortality and bleeding risk observed in this vulnerable population by addressing biological fragility in addition to anatomical risk.
OBJECTIVE:Despite advances in prostacyclin therapy, pulmonary hypertension (PH) continues to impair patients' quality of life (QoL). This study aimed to identify the clinical and psychological factors associated with QoL in patients receiving prostacyclin therapy. METHOD:This cross-sectional study was conducted between July 2023 and September 2024 and included 58 patients with PH receiving prostacyclin therapy. Data were collected using a structured questionnaire assessing sociodemographic and disease-related characteristics. Symptom severity, anxiety, depression, and QoL were evaluated using the Pulmonary Arterial Hypertension Symptom Scale (PAHSS), the Hospital Anxiety and Depression Scale (HADS), and the EmPHasis-10 Questionnaire. RESULTS:The mean age of the patients was 48.89 +- 16.17 years, and 69% were female. Overall, 69% had at least one chronic comorbidity, 19% required continuous oxygen therapy, and the mean disease duration was 7.45 +- 6.84 years. The average duration of prostacyclin therapy was 28.03 +- 34.21 months. Mean scores were 71.52 +- 36.40 for PAHSS, 8.70 +- 5.23 for HADS-Anxiety, 7.82 +- 5.32 for HADS-Depression, and 30.05 +- 14.92 for EmPHasis-10. EmPHasis-10 scores showed moderate correlations with PAHSS, HADS-Anxiety, HADS-Depression, and 6-minute walk test (6MWT) scores. In multivariate analysis, age, PAHSS score, anxiety, depression, and vomiting explained 80% of the variance in EmPHasis-10 scores. CONCLUSION:QoL was substantially impaired in patients with PH receiving prostacyclin therapy and was influenced by age, symptom severity, anxiety, depression, and vomiting.
OBJECTIVE:Iron deficiency is the leading cause of anemia in childhood and may induce cardiovascular adaptations, including increased heart rate, elevated cardiac output, plasma volume expansion, and myocardial remodeling. Beyond hematologic consequences, reduced iron availability may also affect myocardial structure and function. This study aimed to assess biventricular function in children with iron deficiency anemia using two-dimensional speckle-tracking echocardiography. METHOD:This prospective case-control study included pre- and post-treatment evaluations. Forty children with iron deficiency anemia and 29 healthy controls were enrolled. Of the 40 patients, 24 were re-evaluated after treatment. Tissue Doppler imaging was used to measure myocardial velocities, isovolumic contraction time, isovolumic relaxation time, and ejection time at the interventricular septum and the basal segments of both ventricles. Speckle-tracking echocardiography was used to assess left ventricular longitudinal strain (LS) and strain rate, left ventricular circumferential strain and strain rate, as well as right ventricular global longitudinal strain and strain rate. RESULTS:Left and right ventricular LS values improved following treatment, indicating recovery of myocardial function. Tissue Doppler parameters also demonstrated improvement in both systolic and diastolic function. CONCLUSION:Although significant improvement was observed after treatment, some echocardiographic parameters did not fully normalize, suggesting that subtle myocardial alterations may persist. These findings should be interpreted with caution due to the relatively small sample size and the predominance of mild-to-moderate anemia in the study population. Children with iron deficiency anemia may benefit from longer-term follow-up and post-treatment evaluation.
Cardiovascular disease (CVD) continues to claim more lives than any other condition worldwide. Traditional clinic visits capture only brief snapshots of health, leaving many opportunities for prevention and early intervention unmet. Wearable technologies now extend cardiovascular care into daily life, delivering continuous physiologic and behavioral data that could transform how we detect, treat, and ultimately prevent CVD. This review highlights how wearable devices, ranging from consumer-grade wristbands to advanced sensor-embedded textiles, are reshaping cardiovascular medicine. We discuss mechanical, optical, and electrochemical sensing modalities and their applications across the spectrum of care: risk assessment, arrhythmia and ischemia detection, heart failure monitoring, and cardiac rehabilitation. When paired with artificial intelligence, these devices generate predictive insights that anticipate clinical deterioration before symptoms appear. Landmark studies demonstrate real-world potential, but persistent challenges, including measurement accuracy, patient adherence, data overload, and limited integration into health systems, temper their current impact. Equally important, gaps in affordability and digital literacy risk widening disparities in cardiovascular outcomes if not urgently addressed. Wearables are moving cardiovascular medicine beyond the hospital and into the home, offering an unprecedented opportunity to shift from reactive treatment to proactive, personalized, and equitable care. Advances in multimodal sensing, artificial intelligence, and seamless health system integration could position wearables as cornerstone tools in the fight against CVD, provided that innovation is matched with rigorous validation, thoughtful regulation, and a commitment to health equity.
