Why the study?
While reduced right ventricular–pulmonary arterial coupling (TAPSE/PASP ratio) predicts worse outcomes in heart failure, its relationship with tolerance to GDMT optimization after an acute heart failure hospitalization remained unclear.
Does admission TAPSE/PASP ratio correlate with the degree of Guideline-Directed Medical Therapy optimization achieved at discharge in patients hospitalized for acute heart failure?
Cohort (n=79)
Does admission TAPSE/PASP ratio correlate with the degree of Guideline-Directed Medical Therapy optimization achieved at discharge in patients hospitalized for acute heart failure?
Early assessment of right ventricular-pulmonary arterial coupling via the TAPSE/PASP ratio at ICU admission identifies acute heart failure patients with reduced tolerance to GDMT titration prior to discharge.
Admission TAPSE/PASP was associated with GDMT optimization at discharge in acute HF; hypothesis-generating for RV-PA coupling in titration decisions.
Purpose Right ventricular–pulmonary arterial coupling, expressed by the TAPSE/PASP ratio, reflects RV adaptation to pulmonary afterload. While reduced coupling predicts worse outcomes in heart failure (1-3), its relationship with tolerance to Guideline-Directed Medical Therapy (GDMT) after an acute heart failure (AHF) event remains unclear. The purpose of this study is to evaluate, in patients hospitalized for AHF, whether TAPSE/PASP measured at admission correlates with (i) clinical, echocardiographic, and hemodynamic parameters, and (ii) the degree of GDMT optimization achieved at discharge after clinical stabilization. Methods A cohort of 79 consecutive AHF patients were retrospectively analyzed. TAPSE/PASP was measured within 6 hours of ICU admission, with repeat clinical and echocardiographic evaluations performed before discharge. Patients were categorized into TAPSE/PASP tertiles: T1 < 0.38 mm/mmHg, T2 = 0.38–0.50 mm/mmHg, T3 > 0.50 mm/mmHg. Continuous and categorical variables were compared using Kruskal–Wallis and χ²/Fisher tests, respectively. Spearman’s correlation assessed associations between TAPSE/PASP, clinical/hemodynamic variables (e.g., systolic BP, LVEF, stroke volume), and the Therapy Optimization Score (0–4), representing the number of GDMT classes prescribed at discharge (RAAS blockade, β-blocker, MRA, SGLT2i). Results Median [95% CI] TAPSE/PASP was 0.44 [0.36–0.52]. Lower TAPSE/PASP values correlated with older age (ρ = –0.435, p < 0.001), whereas higher values correlated positively with LVEF (ρ = +0.269, p = 0.017), stroke volume (ρ = +0.392, p < 0.001), and Therapy Optimization Score (ρ = +0.340, p = 0.002). Across tertiles, therapy intensity progressively increased (median score: T1 = 2, T2 = 3, T3 = 3; p = 0.0095). The use of RAAS blockade, MRA, and SGLT2i rose stepwise across tertiles (RAAS: 56.7% → 65.2% → 73.1%; MRA: 52.2% → 73.9% → 76.9%; SGLT2i: 34.8% → 34.8% → 57.7%), while β-blocker use remained uniformly high (≈91–96%). Conclusion In patients admitted for AHF, a lower TAPSE/PASP ratio was associated with reduced tolerance to GDMT optimization during hospitalization and once clinically stabilized after an AHF episode, whereas preserved RV–PA coupling (>0.50 mm/mmHg) was linked to greater therapeutic implementation. Early TAPSE/PASP evaluation at admission for AHF episode may serve as a practical tool to stratify patients and guide a more accelerated GDMT titration strategy during hospitalization for acute heart failure.
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Caputo et al. (2026) conducted a cohort in Acute heart failure (n=79). Higher admission TAPSE/PASP ratio (>0.50 mm/mmHg, T3) vs. Lower admission TAPSE/PASP ratio (<0.38 mm/mmHg, T1; 0.38-0.50 mm/mmHg, T2) was evaluated on Therapy Optimization Score (0–4), representing the number of GDMT classes prescribed at discharge (RAAS blockade, β-blocker, MRA, SGLT2i) (ρ = +0.340, p=0.002).
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