RESUMO
BACKGROUND: The burden of asymptomatic left ventricular dysfunction (LVD) is greater than that of heart failure; however, a cost-effective tool for asymptomatic LVD screening has not been well validated. We aimed to prospectively validate an artificial intelligence (AI)-enabled electrocardiography (ECG) algorithm for asymptomatic LVD detection and evaluate its cost-effectiveness for opportunistic screening. METHODS: In this prospective observational study, patients undergoing ECG at outpatient clinics or health check-ups were enrolled in 2 hospitals in Taiwan. Patients were stratified into LVD (left ventricular ejection fraction ≤ 40%) risk groups according to a previously developed ECG algorithm. The performance of AI-ECG was used to conduct a cost-effectiveness analysis of LVD screening compared with no screening. Incremental cost-effectiveness ratio (ICER) and sensitivity analyses were used to examine the cost-effectiveness and robustness of the results. RESULTS: Among the 29,137 patients, the algorithm demonstrated areas under the receiver operating characteristic curves of 0.984 and 0.945 for detecting LVD within 28 days in the 2 hospital cohorts. For patients not initially scheduled for ECG, the algorithm predicted future echocardiograms (high-risk, 46.2%; medium-risk, 31.4%; low-risk, 14.6%) and LVD (high-risk, 26.2%; medium-risk, 3.4%; low-risk, 0.1%) at 12 months. Opportunistic screening with AI-ECG could result in a negative ICER of -$7,439 for patients aged 65 years, with consistent cost-savings across age groups and particularly in men. Approximately 91.5% of the cases were found to be cost-effective at the willingness-to-pay threshold of $30,000 in the probabilistic analysis. CONCLUSIONS: The use of AI-ECG for asymptomatic LVD risk stratification is promising, and opportunistic screening in outpatient clinics has the potential to reduce costs.
RESUMO
BACKGROUND: Brain-derived neurotrophic factor (BDNF) is associated with sympathetic activation. However, the effects of BDNF on diabetic nephropathy are unknown. The aim of this study was to assess the estimated glomerular filtration rates (eGFRs) and changes in serum BDNF levels in type 2 diabetic subjects treated with antihypertensive medications. METHODS: In this randomized, double-blind clinical trial, type 2 diabetic subjects with hypertension were assigned to either the benazepril/amlodipine or valsartan/hydrochlorothiazide treatment groups for a 16-week period. The post hoc analyses were based on increased or decreased serum BDNF levels. RESULTS: Of the 153 enrolled subjects, the changes in eGFR were significantly and inversely correlated with those in BDNF in the 76 subjects treated with valsartan/hydrochlorothiazide (r = -0.264, P = 0.021) but not in the 77 subjects treated with benazepril/amlodipine (r = -0.025, P = 0.862). The 45 subjects with increased BDNF following valsartan/hydrochlorothiazide treatment exhibited a significantly reduced eGFR (-8.8 ± 14.9 mL/min/1.73 m(2); P < 0.001). Multivariate regression analysis revealed that increased serum BDNF represents an independent factor for reduced eGFR (95% confidence interval between -0.887 and -0.076, P = 0.020). CONCLUSIONS: Increased serum BDNF is associated with reduced eGFR in type 2 diabetic subjects treated with valsartan/hydrochlorothiazide but not with amlodipine/benazepril.