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Predictive model for estimating the risk of high-altitude pulmonary edema: a single-centre retrospective outcome-reporting study

Authors :
Ju Huang
Yangzong Suona
Luobu Gesang
Zhuoga Danzeng
Bai Ci
Quzong Zhaxi
Source :
BMJ Open, Vol 13, Iss 11 (2023)
Publication Year :
2023
Publisher :
BMJ Publishing Group, 2023.

Abstract

Objective To develop the first prediction model based on the common clinical symptoms of high-altitude pulmonary edema (HAPE), enabling early identification and an easy-to-execute self-risk prediction tool.Methods A total of 614 patients who consulted People’s Hospital of Tibet Autonomous Region between January 2014 and April 2022 were enrolled. Out of those, 508 patients (416 males and 92 females) were diagnosed with HAPE and 106 were patients without HAPE (33 females and 72 males). They were randomly distributed into training (n=431) and validation (n=182) groups. Univariate and multivariate analysis were used to screen predictors of HAPE selected from the 36 predictors; nomograms were established based on the results of multivariate analysis. The receiver operating characteristic curve (ROC) was developed to obtain the area under the ROC curve (AUC) of the predictive model, and its predictive power was further evaluated by calibrating the curve, while the Decision Curve Analysis (DCA) was developed to evaluate the clinical applicability of the model, which was visualised by nomogram.Results All six predictors were significantly associated with the incidence of HAPE, and two models were classified according to whether the value of SpO2 (percentage of oxygen in the blood) was available in the target population. Both could accurately predict the risk of HAPE. In the validation cohort, the AUC of model 1 was 0.934 with 95% CI (0.848 to 1.000), and model 2 had an AUC of 0.889, 95% CI (0.779 to 0.999). Calibration plots showed that the predicted and actual HAPE probabilities fitted well with internal validation, and the clinical decision curve shows intervention in the risk range of 0.01–0.98, resulting in a net benefit of nearly 99%.Conclusion The recommended prediction model (nomogram) could estimate the risk of HAPE with good precision, high discrimination and possible clinical applications for patients with HAPE. More importantly, it is an easy-to-execute scoring tool for individuals without medical professionals’ support.

Subjects

Subjects :
Medicine

Details

Language :
English
ISSN :
20446055
Volume :
13
Issue :
11
Database :
Directory of Open Access Journals
Journal :
BMJ Open
Publication Type :
Academic Journal
Accession number :
edsdoj.16dadf324344beb8d85e1c4cf2446f
Document Type :
article
Full Text :
https://doi.org/10.1136/bmjopen-2023-074161