Abstract
Abstract
Acute mountain sickness (AMS) affects many individuals ascending to high altitude annually, carrying potential morbidity and mortality risks (e.g., high‐altitude cerebral oedema). The objective of this pilot study was to record overnight pulse oximetry during ascent to 4554 m and determine whether: (1) extracted overnight biomarkers had any relationship to AMS; and (2) AMS at 4554 m could be predicted by oximetry biomarkers using classification models trained/validated on overnight data from lower altitudes. Twenty lowlanders (five females, 36.8 ± 18.5 years old) completed a 4 day ascent to 4554 m, where AMS status was determined by clinical examination. Oximetry was recorded continuously each night, with >40 biomarkers extracted and compared between AMS and non‐AMS. Exploratory classification models (5‐fold cross‐validation) were tested for nightly data with a systematic approach to feature selection. Model performances were evaluated based on predictions of AMS at 4554 m. A significant effect of ascent was observed for many overnight biomarkers; however, no effect of AMS status was evident, nor were any differences observed between AMS and non‐AMS for any overnight biomarkers during ascent. AMS at 4554 m was most accurately predicted from overnight recordings collected at 2600 m (accuracy, 100%; true positive rate, 100%) and 3647 m (accuracy, 80%; true positive rate, 90.9%) using
k
‐nearest neighbour and support vector machine classification models. Biomarkers were extracted from overnight oximetry recordings, with limited differences observed between AMS and non‐AMS. In conclusion, AMS at 4554 m can be predicted from overnight oximetry using machine learning; however, these preliminary findings need confirmation in a larger cohort, with additional investigation into the most clinically relevant biomarkers.