Risk prediction in pulmonary hypertension due to chronic heart failure: incremental prognostic value of pulmonary hemodynamics.

Background: There is no generally accepted comprehensive risk prediction model cooperating risk factors associated with heart failure and pulmonary hemodynamics for patients with pulmonary hypertension due to left heart disease (PH-LHD). We aimed to explore outcome correlates and evaluate incremental prognostic value of pulmonary hemodynamics for risk prediction in PH-LHD.

Methods: Consecutive patients with chronic heart failure undergoing right heart catheterization were prospectively enrolled. The primary endpoint was all-cause mortality. Individual variable selection was performed by machine learning methods. Cox proportional hazards models were conducted to identify the association between variables and mortality. Incremental value of hemodynamics was evaluated based on the Seattle heart failure model (SHFM) and Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) scores.

Results: A total of 276 PH-LHD patients were enrolled, with a median follow-up time of 34.7 months. By L1-penalized regression model and random forest approach, diastolic pressure gradient (DPG) and mixed venous oxygen saturation (SvO) were the hemodynamic predictors most strongly associated with mortality (coefficient: 0.0255 and -0.0176, respectively), with consistent significance after adjusted for SHFM [DPG: HR 1.067, 95% CI 1.024-1.113, P = 0.022; SvO: HR 0.969, 95% CI 0.953-0.985, P = 0.002] or MAGGIC (DPG: HR 1.069, 95% CI 1.026-1.114, P = 0.011; SvO: HR 0.970, 95% CI 0.954-0.986, P = 0.004) scores. The inclusion of DPG and SvO improved risk prediction compared with using SHFM [net classification improvement (NRI): 0.468 (0.161-0.752); integrated discriminatory index (IDI): 0.092 (0.035-0.171); likelihood ratio test: P < 0.001] or MAGGIC [NRI: 0.298 (0.106-0.615); IDI: 0.084 (0.033-0.151); likelihood ratio: P < 0.001] scores alone.

Conclusion: In PH-LHD, pulmonary hemodynamics can provide incremental prognostic value for risk prediction.

Clinical Trial Registration: NCT02164526 at https://clinicaltrials.gov .