Prediction of acute mountain sickness occurring at 4554 m using overnight pulse oximetry from lower altitude: A pilot...

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.