Clustering analysis of acute mountain sickness susceptibility among young adults during rapid ascent using...

Acute mountain sickness (AMS) compromises health and work efficiency after rapid ascent. This study aimed to explore a low-altitude-data-based method for classifying AMS-susceptible young adults. Forty-four low-altitude residents (18-31 years) completed a step test at 50 m. Measurements included maximal oxygen uptake (V̇O₂max), peripheral oxygen saturation at rest (re_SpO₂), exercise (ex_SpO₂), and recovery (rec_SpO₂), heart rate at rest (re_HR), exercise (ex_HR), and recovery (rec_HR), and step index. Participants ascended to 3650 m within 6 h, and AMS was assessed using the 2018 Lake Louise Score (LLS). Associations with LLS were examined before k-means clustering. Neither re_SpO₂ nor re_HR was significantly correlated with LLS, whereas non-resting-state variables (V̇O₂max, ex_SpO₂, rec_SpO₂, ex_HR, rec_HR, and step index) were. Clustering using V̇O₂max, ex_SpO₂, rec_SpO₂, and step index showed strong structure (silhouette coefficient = 0.767) and 93.18% agreement with LLS. Step index and ex_SpO₂ showed the greatest between-cluster separation, followed by rec_SpO₂ and V̇O₂max. Exercise- and recovery-phase variables from a low-altitude step test may classify AMS susceptibility in young adults via unsupervised learning. Evaluated after rapid ascent to 3650 m, this noninvasive, low-cost, and practical approach shows potential for pre-ascent AMS susceptibility screening in healthy young adults.