Ahmed Mohsen Elsawah, Mosaad Lamey Ghanem, Ahmed Ali Ali, Hatem Khairy, Amr Mohamed Imam, Mohamed Makram, Ramy Omar and Mohamed Sabry Elhadainy
Background: Acute pulmonary embolism (PE) carries substantial risk of hemodynamic compromise, yet existing clinical scores incompletely capture right‑to‑left ventricular interactions. We investigated whether the ratio of pulmonary artery systolic pressure to left ventricular stroke volume (PASP/LVSV), measured within 24 hours of diagnosis, predicts adverse short‑ and mid‑term outcomes in hemodynamically stable PE patients.
Methods: In this prospective, multicenter cohort study, 150 patients with confirmed acute PE underwent standardized transthoracic echocardiography within 24 hours of admission. PASP was estimated from tricuspid regurgitant jet velocity and inferred right atrial pressure, while LVSV was calculated from LV outflow tract area and Doppler velocity time integral. Patients were dichotomized into PASP/LVSV < 1.0 (Group I, n = 72) and ≥ 1.0 (Group II, n = 78). The primary composite endpoint comprised in‑hospital mortality, cardiac arrest, or thrombolytic therapy; secondary endpoints included 90‑day all‑cause mortality and need for ventilatory support.
Results: Group II patients experienced significantly higher rates of the primary composite endpoint (35.9% vs. 12.5%; p < 0.001) and 90‑day mortality or respiratory failure (38.5% vs. 15.3%; p < 0.001). PASP/LVSV demonstrated superior discrimination for the primary outcome (AUC 0.812; sensitivity 91.0%, specificity (47.2%) compared with Bova (0.645) and PESI (0.605) scores (both p < 0.001 vs. PASP/LVSV). In multivariate analysis, PASP/LVSV ≥ 1.0 remained an independent predictor of the primary composite (OR 2.15; 95% CI 1.78-5.02; p < 0.001) and secondary outcomes (OR 1.82; 95% CI 1.18-2.02; p = 0.001).
Conclusion: The PASP/LVSV ratio, reflecting ventriculo‑pulmonary coupling, independently predicts adverse in‑hospital events and 90‑day mortality in stable acute PE. Integrating this echocardiographic marker into early risk stratification may optimize patient management.
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