Predicting severe high-altitude de-acclimatization syndrome from pre-return exposure dose and laboratory indicators: a prospective cohort study of 475 males. Download PDF 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 BenjaminiโHochberg 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 solid 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 0.665โ0.893). At the Youden-optimal threshold, its sensitivity and specificity were 0.739 and 0.750.
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