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September 5, 2025Open Access

Climbing Smarter: A Predictive Model for Acute Mountain Sickness Risk at High Altitudes

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Field study identifies demographic and physiological predictors of acute mountain sickness risk, suggesting enhanced preventive strategies.

The predictive model effectively estimates acute mountain sickness risk using key physiological and demographic factors.
Logistic regression analysis indicated strong discriminatory performance with an AUROC of 0.83 and robust internal validation.
Key predictors included low arterial oxygen saturation, low diastolic blood pressure, and limited high-altitude experience.
Findings highlight the importance of assessing risk factors to improve preventive strategies in high-altitude environments.

Landivar et al. (2025) studied this question.

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Field study identifies demographic and physiological predictors of acute mountain sickness risk, suggesting enhanced preventive strategies.