Cardiology

hs-cTnT-gen6 enables efficient MI rule-out with fewer patients labeled as myocardial injury

In 3,346 ED patients with suspected MI, hs-cTnT-gen6 matched gen5 for diagnostic accuracy at presentation (AUC 0.927 vs 0.931). Gen6 classified fewer patients above the upper reference limit than gen5 (35.9% vs 43.5%), potentially reducing downstream myocardial injury labeling. A single gen6 cutoff <6 ng/L ruled out NSTEMI in 30% of patients with 100% sensitivity, irrespective of chest pain onset timing. ESC-style 0/1-hour gen6 criteria ruled out 56.3% with 99.7% sensitivity and ruled in 20.0% with 93.4% specificity. 1

Early aspirin withdrawal after PCI reduces bleeding without excess MI on ticagrelor/prasugrel

This meta-analysis pooled seven RCTs including 27,743 high-risk post-PCI patients on ticagrelor or prasugrel. Transitioning to P2Y12 monotherapy within 3 months reduced clinically relevant bleeding versus continued DAPT (HR 0.55, 95% CI 0.42-0.71). Overall MI rates were not significantly different (HR 1.11, 95% CI 0.91-1.35), and death, stroke, and stent thrombosis were similar. Immediate aspirin noninitiation or in-hospital cessation increased MI (HR 1.41, 95% CI 1.01-1.97), whereas post-discharge discontinuation did not (HR 0.97). 2

Renin-independent aldosterone excess in hypertension shows graded cardiorenal risk, not a binary threshold

This Danish cohort included 12,650 hypertensive adults undergoing renin and aldosterone testing with median 3.6-year follow-up. Higher aldosterone-to-renin ratio, higher aldosterone, and lower renin were each associated with increased rapid eGFR decline and kidney failure risk. Adjusted HRs for rapid kidney decline rose stepwise with ARR categories: 1.27, 1.98, and 2.66 across increasing ARR strata. For kidney failure or ≥40% eGFR decline and MACE, risk increased at higher ARR levels but not at modest ARR elevation. 3

Smartwatch-derived daily peak VO2 predicts heart failure events days to weeks ahead

In TRUE-HF, 217 free-living HF patients wore Apple Watches for a median 94.5 days. A deep learning model estimated daily wearable-based peak VO2, strongly correlating with CPET peak VO2 (r=0.85). Each 10% drop in wearable-derived peak VO2 was associated with a 3.62-fold higher hazard of unplanned healthcare events, occurring about 7.4 days later. In an external All of Us cohort using a reduced-sensor model, similar drops predicted events with HR 1.32 and median 21-day lead time. 4