ArticleBMJ open2023
Predictive model for estimating the risk of high-altitude pulmonary edema: a single-centre retrospective outcome-reporting study.
Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Development and validation of nomogram for predicting neurogenic pulmonary edema in hypertensive intracerebral hemorrhage.Frontiers in cardiovascular medicine · 2026Article
- Clinical characteristic and prognosis of adult inpatients with high altitude pulmonary edema: a multi-central, retrospective study in plateau of China from 2012 to 2022.BMC pulmonary medicine · 2025Article
- A machine learning-based severity stratification tool for high altitude pulmonary edema.BMC medical informatics and decision making · 2025Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo 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.
methodsA 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.
resultsAll six predictors were significantly associated with the incidence of HAPE, and two models were classified according to whether the value of SpO
conclusionThe 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.
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