Wearable devices simultaneously capture multiple cardiovascular and behavioral domains, including autonomic function, physical activity, sedentary behavior, sleep and rhythm. Integrating these data may provide a more comprehensive representation of cardiovascular risk than any single wearable parameter. Objective: To evaluate the relationship of multimodal wearable-derived digital biomarkers with cardiovascular-risk status and assess the discriminatory performance of a composite digital-biomarker score for identifying individuals at high cardiovascular risk. Materials and Methods: A total of 150 adults aged 30–70 years without established cardiovascular disease underwent conventional cardiovascular-risk assessment and 7–14 days of wearable monitoring. Digital biomarkers included resting heart rate, HRV, daily step count, active minutes, sedentary time, sleep duration, sleep efficiency and rhythm abnormalities. Correlations with conventional cardiovascular-risk score were assessed. Receiver-operating-characteristic analysis compared individual wearable parameters with an exploratory composite digital-biomarker score. Results: Mean daily steps decreased from 8,426 ± 2,315 in low-risk participants to 5,018 ± 1,876 in high-risk participants (p<0.001), while sedentary time increased from 7.1 ± 1.5 to 9.4 ± 1.7 hours/day (p<0.001). Mean sleep duration declined from 7.21 ± 0.78 to 6.12 ± 0.94 hours/night and sleep efficiency from 87.6 ± 5.8% to 77.8 ± 7.3% (both p<0.001). Irregular-rhythm notifications occurred in 13 participants (8.7%), rising from 2.9% in low-risk participants to 20.0% in high-risk participants (p=0.01). The composite score achieved an AUC of 0.86 (95% CI 0.79–0.92), sensitivity 83.3% and specificity 79.2%, exceeding the performance of individual biomarkers. Conclusion: Multimodal wearable-derived physiological and behavioral biomarkers demonstrated significant associations with conventional cardiovascular risk. Integration of multiple wearable domains into a composite score improved discrimination of high cardiovascular risk and may provide a useful adjunct to conventional risk assessment.

Cardiovascular risk assessment traditionally depends on demographic, clinical and biochemical measurements obtained during episodic healthcare encounters. Wearable sensors enable longitudinal assessment of heart rate and heart-rate variability (HRV), potentially providing complementary information regarding autonomic cardiovascular regulation. Objective: To assess the association of wearable-derived resting heart rate and HRV indices with conventional cardiovascular-risk categories among adults without previously established cardiovascular disease. Materials and Methods: This hospital-based prospective observational analytical study included 150 adults aged 30–70 years. Participants underwent conventional cardiovascular-risk assessment including history, anthropometry, blood pressure, resting 12-lead electrocardiography, glycaemic assessment and lipid profile. A validated wrist-worn wearable device was used for at least seven days, with a target monitoring duration of 14 days. Resting heart rate, night-time nadir heart rate, standard deviation of normal-to-normal intervals (SDNN), root mean square of successive differences (RMSSD) and LF/HF ratio were analysed. Participants were classified as low-, moderate- or high-cardiovascular-risk. Results: Of 150 participants, 68 were low risk, 52 moderate risk and 30 high risks. Mean resting heart rate increased from 67.3 ± 6.8 bpm in the low-risk group to 72.5 ± 7.4 bpm in the moderate-risk group and 78.1 ± 8.3 bpm in the high-risk group (p<0.001). SDNN decreased from 52.8 ± 13.4 ms to 43.6 ± 11.7 ms and 34.9 ± 10.5 ms, respectively (p<0.001), while RMSSD decreased from 45.3 ± 12.6 ms to 35.8 ± 10.3 ms and 27.4 ± 8.9 ms (p<0.001). RMSSD demonstrated the strongest correlation with cardiovascular-risk score (r=−0.49, p<0.001), followed by SDNN (r=−0.46, p<0.001). RMSSD showed an AUC of 0.78 for identifying participants in the high-risk category. Conclusion: Higher cardiovascular risk was associated with increased resting and night-time heart rate, reduced HRV and a higher LF/HF ratio. Wearable-derived HRV, particularly RMSSD, may provide useful adjunctive information for early cardiovascular-risk assessment.

Patients labelled as statin-intolerant are frequently moved directly to non-statin therapies despite evidence that many can tolerate a modified statin regimen following structured reassessment. Evidence regarding the effectiveness, persistence and affordability of alternative therapies in real-world Indian practice remains limited. Objective: To assess the outcomes of systematic evaluation and statin rechallenge and to evaluate LDL-C reduction, goal attainment, safety, adherence, persistence and treatment cost among patients requiring alternative lipid-lowering therapy. Materials and Methods: Patients with suspected or labelled statin intolerance entered a structured diagnostic pathway incorporating symptom characterization, investigation and correction of secondary causes, supervised dechallenge and rechallenge when clinically appropriate. Patients with confirmed complete or partial intolerance received alternative therapy selected by their treating physician. Lipid parameters, adverse effects, adherence, treatment satisfaction, persistence and out-of-pocket expenditure were assessed prospectively over 12 months. Results: A total of 247 patients entered the structured evaluation pathway. A potentially contributory secondary cause was identified in 68 (27.5%), including vitamin D deficiency in 15.8%, drug interactions in 9.7% and hypothyroidism in 4.9%. Rechallenge was undertaken in 185 patients; 106 (57.3%) tolerated a statin and 79 (42.7%) developed recurrent symptoms. Across the complete evaluation cohort, 42.9% were ultimately returned to statin therapy. Among 88 confirmed statin-intolerant participants completing 12 months of alternative therapy, mean LDL-C decreased from 139.2±31.4 to 103.6±29.8 mg/dL, corresponding to a 25.6% reduction (p<0.001). Goal attainment increased from 4.5% to 38.6%. LDL-C reductions were 18.5% with ezetimibe monotherapy, 32.2% with ezetimibe plus low-dose/intermittent statin, 32.0% with bempedoic acid±ezetimibe and 55.7% with PCSK9 monoclonal antibody therapy. Twelve-month persistence ranged from 81.6% with ezetimibe to 55.6% with PCSK9 therapy. Median monthly out-of-pocket expenditure ranged from ₹185 to ₹18,200. Conclusion: Systematic reassessment restored statin therapy in a substantial proportion of patients labelled intolerant. Alternative therapies produced meaningful LDL-C reductions, but most patients remained above target and long-term persistence was strongly influenced by affordability.