AUTHOR=Zeng Yanxi , Zhakeer Gulinigeer , Li Bingyu , Yu Qing , Niu Mingyuan , Maimaitiaili Nuerbiyemu , Mi Ma , Deji Zhuoga , Zhuang Jianhui , Peng Wenhui TITLE=A novel clinical prediction scoring system of high-altitude pulmonary hypertension JOURNAL=Frontiers in Cardiovascular Medicine VOLUME=10 YEAR=2024 URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2023.1290895 DOI=10.3389/fcvm.2023.1290895 ISSN=2297-055X ABSTRACT=Background

High-altitude pulmonary hypertension (HAPH) is a common disease in regions of high altitude where performing right heart catheterization (RHC) is challenging. The development of a diagnostic scoring system is crucial for effective disease screening.

Methods

A total of 148 individuals were included in a retrospective analysis, and an additional 42 residents were prospectively enrolled. We conducted a multivariable analysis to identify independent predictors of HAPH. Subsequently, we devised a prediction score based on the retrospective training set to anticipate the occurrence and severity of HAPH. This scoring system was further subjected to validation in the prospective cohort, in which all participants underwent RHC.

Results

This scoring system, referred to as the GENTH score model (Glycated hemoglobin [OR = 4.5], Echocardiography sign [OR = 9.1], New York Heart Association-functional class [OR = 12.5], Total bilirubin [OR = 3.3], and Hematocrit [OR = 3.6]), incorporated five independent risk factors and demonstrated strong predictive accuracy. In the training set, the area under the curve (AUC) values for predicting the occurrence and severity of HAPH were 0.851 and 0.832, respectively, while in the validation set, they were 0.841 and 0.893. In the validation set, GENTH score model cutoff values of ≤18 or >18 points were established for excluding or confirming HAPH, and a threshold of >30 points indicated severe HAPH.

Conclusions

The GENTH score model, combining laboratory and echocardiography indicators, represents an effective tool for distinguishing potential HAPH patients and identifying those with severe HAPH. This scoring system improves the clinical screening of HAPH diseases and offers valuable insights into disease diagnosis and management.