Predicting severe high-altitude de-acclimatization syndrome from pre-return exposure dose and laboratory indicators: a prospective cohort study of 475 males

Abstract High-altitude de-acclimatization syndrome (HADAs) poses significant health challenges to individuals returning from high-altitude residence, yet its de-acclimatization process of laboratory indicators and the extent to which it can be predicted before descent remain poorly characterized. We conducted a longitudinal cohort study involving 475 participants with repeated assessments at high-altitude residence (T0), 1 month after return to plain area (T1), and 3 months after return to plain area (T2). HADAs was diagnosed using established questionnaire criteria; outcomes were stratified by course (ever, persistent) and by severity. Cochran-Armitage trend tests were used to evaluate dose-response relationships of altitude and residence duration with HADAs incidence and persistence; Mann-Whitney U tests with Benjamini–Hochberg FDR correction were used to compare the 40 laboratory indicators between HADAs and non-HADAs participants; and machine-learning models (LightGBM, XGBoost, Random Forest, SVM, ensemble, TabPFN) were developed under a leakage-free protocol to predict severe HADAs from pre-return (T0) data. Altitude and residence duration showed robust dose-response associations with HADAs incidence and persistence (P for trend < 0.001), with over 85% incidence at altitudes above 5,000 m or residence for more than 18 months. After FDR correction, triglycerides, direct bilirubin and platelet distribution width differed between groups (q = 0.036). For severe HADAs, the TabPFN model achieved a held-out test AUC of 0.784 (95% CI 0.665–0.893). At the Youden-optimal threshold, its sensitivity and specificity were 0.739 and 0.750. Altitude, the altitude × duration interaction and pre-return erythrocyte indices were the dominant predictors. Cumulative exposure dose (altitude and residence duration) is the dominant determinant of HADAs incidence and persistence. Dysregulated lipid and platelet indices were core pathophysiological correlates of the de-acclimatization process. The pre-return model can identify the minority at risk of severe HADAs, supporting targeted monitoring while avoiding indiscriminate labeling in a population with high overall incidence.

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Journal
Scientific Reports
Published
2026-10-04
DOI
https://doi.org/10.1038/s41598-026-73585-6
Primary Topic
High Altitude and Hypoxia
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article
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article

Predicting severe high-altitude de-acclimatization syndrome from pre-return exposure dose and laboratory indicators: a prospective cohort study of 475 males

梁鸿寅, Liyao Shui, Lijun Tang, Mu Yuan et al.
Scientific Reports
High Altitude and Hypoxia
article

Predicting severe high-altitude de-acclimatization syndrome from pre-return exposure dose and laboratory indicators: a prospective cohort study of 475 males

梁鸿寅, Liyao Shui, Lijun Tang, Mu Yuan, Zhu Huang, Yi Wen, Ruohong Liu, Yufan Zhang, Dongxu Liao
article en

Abstract

Abstract High-altitude de-acclimatization syndrome (HADAs) poses significant health challenges to individuals returning from high-altitude residence, yet its de-acclimatization process of laboratory indicators and the extent to which it can be predicted before descent remain poorly characterized. We conducted a longitudinal cohort study involving 475 participants with repeated assessments at high-altitude residence (T0), 1 month after return to plain area (T1), and 3 months after return to plain area (T2). HADAs was diagnosed using established questionnaire criteria; outcomes were stratified by course (ever, persistent) and by severity. Cochran-Armitage trend tests were used to evaluate dose-response relationships of altitude and residence duration with HADAs incidence and persistence; Mann-Whitney U tests with Benjamini–Hochberg FDR correction were used to compare the 40 laboratory indicators between HADAs and non-HADAs participants; and machine-learning models (LightGBM, XGBoost, Random Forest, SVM, ensemble, TabPFN) were developed under a leakage-free protocol to predict severe HADAs from pre-return (T0) data. Altitude and residence duration showed robust dose-response associations with HADAs incidence and persistence (P for trend < 0.001), with over 85% incidence at altitudes above 5,000 m or residence for more than 18 months. After FDR correction, triglycerides, direct bilirubin and platelet distribution width differed between groups (q = 0.036). For severe HADAs, the TabPFN model achieved a held-out test AUC of 0.784 (95% CI 0.665–0.893). At the Youden-optimal threshold, its sensitivity and specificity were 0.739 and 0.750. Altitude, the altitude × duration interaction and pre-return erythrocyte indices were the dominant predictors. Cumulative exposure dose (altitude and residence duration) is the dominant determinant of HADAs incidence and persistence. Dysregulated lipid and platelet indices were core pathophysiological correlates of the de-acclimatization process. The pre-return model can identify the minority at risk of severe HADAs, supporting targeted monitoring while avoiding indiscriminate labeling in a population with high overall incidence.

Scientific Reports
Chengdu Military General Hospital (CN), Southwest Jiaotong University (CN)
Good health and well-being
Openalex Percentile: Top 13%
High Altitude and Hypoxia
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