ArticleBMC cardiovascular disorders2022
Risk prediction in pulmonary hypertension due to chronic heart failure: incremental prognostic value of pulmonary hemodynamics.
Article in BMC cardiovascular disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02164526 (National, Prospective, Multicenter,Observational Registry Study on Pulmonary Hypertension Due to Left Heart Disease in China), which is not on this map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
National, Prospective, Multicenter,Observational Registry Study on Pulmonary Hypertension Due to Left Heart Disease in China
Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
- Deep Convolutional Generative Adversarial Network for Improved Cardiac Image Classification in Heart Disease Diagnosis.Journal of imaging informatics in medicine · 2025Article
- Relaxin mimetic in pulmonary hypertension associated with left heart disease: Design and rationale of Re-PHIRE.ESC heart failure · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 9 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere 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.
methodsConsecutive 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.
resultsA 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
conclusionIn PH-LHD, pulmonary hemodynamics can provide incremental prognostic value for risk prediction. CLINICAL
trial registrationNCT02164526 at https://clinicaltrials.gov .
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.