Author:
Chen Yuqin,Zhou Dansha,Xiong Mingmei,Xi Xin,Zhang Wenni,Zhang Ruifeng,Chen Lishi,Jiang Qian,Lai Ning,Li Xiang,Luo Jieer,Li Xuanyi,Feng Weici,Gao Chuhui,Chen Jiyuan,Fu Xin,Hong Wei,Jiang Mei,Yang Kai,Lu Wenju,Luo Yiping,Zhang Jun,Cheng Zhe,Liu Chunli,Wang Jian
Abstract
Abstract
Background
Pregnant women with pulmonary hypertension (PH) have higher mortality rates and poor foetal/neonatal outcomes. Tools to assess these risk factors are not well established.
Methods
Predictive and prognostic nomograms were constructed using data from a “Development” cohort of 420 pregnant patients with PH, recorded between January 2009 and December 2018. Logistic regression analysis established models to predict the probability of adverse maternal and foetal/neonatal events and overall survival by Cox analysis. An independent “Validation” cohort comprised data of 273 consecutive patients assessed from January 2019 until May 2022. Nomogram performance was evaluated internally and implemented with online software to increase the ease of use.
Results
Type I respiratory failure, New York Heart Association functional class, N-terminal pro-brain natriuretic peptide $$\ge$$
≥
1400 ng/L, arrhythmia, and eclampsia with pre-existing hypertension were independent risk factors for maternal mortality or heart failure. Type I respiratory failure, arrhythmia, general anaesthesia for caesarean section, New York Heart Association functional class, and N-terminal pro-brain natriuretic peptide $$\ge$$
≥
1400 ng/L were independent predictors of pulmonary hypertension survival during pregnancy. For foetal/neonatal adverse clinical events, type I respiratory failure, arrhythmia, general anaesthesia for caesarean section, parity, platelet count, fibrinogen, and left ventricular systolic diameter were important predictors. Nomogram application for the Development and Validation cohorts showed good discrimination and calibration; decision curve analysis demonstrated their clinical utility.
Conclusions
The nomogram and its online software can be used to analyse individual mortality, heart failure risk, overall survival prediction, and adverse foetal/neonatal clinical events, which may be useful to facilitate early intervention and better survival rates.
Funder
National Natural Science Foundation of China
Guangdong Department of Science and Technology
Basic Science and Application of Guangzhou Science and Technology Plan
Department of Science and Technology of China Grants
Changjiang Scholars, and Innovative Research Team in University
Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program
Guangzhou Basic Research Program Municipal School (Hospital) Joint Funded Foundation and Application Basic Research Project
the Independent Project of State Key Laboratory of Respiratory Disease
the State Key Laboratory of Respiratory Disease, and Guangdong-Hong Kong-Macao Joint Laboratory of Respiratory Infectious Disease
Publisher
Springer Science and Business Media LLC