In the course of their missions or training, alpinists, but also mountain combat forces and mountain security services, professional miners, aircrew, aircraft and glider pilots and helicopter crews are regularly exposed to altitude without oxygen supplementation. At altitude, humans are exposed to systemic environmental hypoxia induced by the decrease in barometric pressure (<1,013 hPa) which decreases the inspired partial pressure of oxygen (PIO₂), while the oxygen fraction is constant (equal to approximately 20.9%). Effects of altitude on humans occur gradually and depend on the duration of exposure and the altitude level. From 1,500 m altitude (response threshold), several adaptive responses offset the effects of hypoxia, involving the respiratory and the cardiovascular systems, and the oxygen transport capacity of the blood. Fatigue and cognitive and sensory disorders are usually observed from 2,500 m (threshold of prolonged hypoxia). Above 3,500 m (the threshold for disorders), the effects are not completely compensated and maladaptive responses occur and individuals develop altitude headache or acute altitude illness [Acute Mountain Sickness (AMS)]. The magnitude of effects varies considerably between different physiological systems and exhibits significant inter-individual variability. In addition to comorbidities, the factors of vulnerability are still little known. They can be constitutive (genetic) or circumstantial (sleep deprivation, fatigue, speed of ascent.). In particular, sleep loss, a condition that is often encountered in real-life settings, could have an impact on the physiological and cognitive responses to hypoxia. In this review, we report the current state of knowledge on the impact of sleep loss on responses to environmental hypoxia in humans, with the aim of identifying possible consequences for AMS risk and cognition, as well as the value of behavioral and non-pharmacological countermeasures.

Active ascent to 4,300 m high altitude (HA) accelerated the onset of AMS, confirming previous findings at 3,600 m. Peak AMS symptoms occurred on HA1 in active ascenders and on HA2 in passive ascenders. Unlike at 3,600 m, active ascenders did not recover faster compared with passive ascenders. AMS was likely exaggerated in active ascenders on HA1 due to an ∼7% greater arterial desaturation, increasing hypoxemia during the first 2–3 h at high altitude.

Aircraft pilots face a high mental workload (MW) under environmental constraints induced by high altitude and sometimes sleep restriction (SR). Our aim was to assess the combined effects of hypoxia and sleep restriction on cognitive and physiological responses to different MW levels using the Multi-Attribute Test Battery (MATB)-II with an additional auditory Oddball-like task. Seventeen healthy subjects were subjected in random order to three 12-min periods of increased MW level (low, medium, and high): sleep restriction (SR, 6 h TST), hypoxia (HY, 2 h, F_IO₂ = 13.6%, ~3500 m vs. normoxia, NO, F_IO₂ = 21%). Following each MW level, participants completed the NASA-TLX subjective MW scale. Increasing MW decreases performance on the MATB-II Tracking task (p = 0.001, MW difficulty main effect) and increases NASA-TLX (p = 0.001). In the combined HY/SR condition, MATB-II performance was lower, and the NASA-TLX score was higher compared with the NO/HS condition, while no effect of hypoxia alone was observed. In the accuracy of the auditory task, there is a significant interaction between hypoxia and MW difficulty (F_(2–176) = 3.14, p = 0.04), with lower values at high MW under hypoxic conditions. Breathing rate, pupil size, and amplitude of pupil dilation response (PDR) to auditory stimuli are associated with increased MW. These parameters are the best predictors of increased MW, independently of physiological constraints. Adding ECG, SpO₂, or electrodermal conductance does not improve model performance. In conclusion, hypoxia and sleep restriction have an additive effect on MW. Physiological and electrophysiological responses must be taken into account when designing a MW predictive model and cross-validation.

This study investigates whether a functional single nucleotide polymorphism of HMOX2 (heme oxygenase-2) (rs4786504 T>C) is involved in individual chemosensitivity to acute hypoxia, as assessed by ventilatory responses, in European individuals. These responses were obtained at rest and during submaximal exercise, using a standardized and validated protocol for exposure to acute normobaric hypoxia. Carriers of the ancestral T allele (n = 44) have significantly lower resting and exercise hypoxic ventilatory responses than C/C homozygous carriers (n = 40). In the literature, a hypoxic ventilatory response threshold to exercise has been identified as an independent predictor of severe high altitude-illness (SHAI). Our study shows that carriers of the T allele have a higher risk of SHAI than carriers of the mutated C/C genotype. Secondarily, we were also interested in COMT (rs4680 G > A) polymorphism, which may be indirectly involved in the chemoreflex response through modulation of autonomic nervous system activity. Significant differences are present between COMT genotypes for oxygen saturation and ventilatory responses to hypoxia at rest. In conclusion, this study adds information on genetic factors involved in individual vulnerability to acute hypoxia and supports the critical role of the ≪ O₂ sensor ≫ - heme oxygenase-2 - in the chemosensitivity of carotid bodies in Humans.

Aircraft pilots can be faced with a high mental workload (MW) combined with moderate hypoxia and sleep restriction. We aimed to assess the cross-validation of a machine learning-based MW predictive model under hypoxia and/or sleep restriction. Secondly, we developed a robust predictive model using multimodal physiological parameters to improve the validity across different physiological conditions. Seventeen healthy participants were randomly exposed to three 12-minute periods of increased MW (low, medium, and high) in a 4-condition crossover design: sleep restriction (SR, 6 h TST), hypoxia (HY, 2 h, F_IO₂=13.6%, ∼3500 m) vs. normoxia (NO, F_IO₂=21%). MW levels were designed using the Multi-Attribute Test Battery (MATB)-II with an additional auditory Oddball-like task. Six machine learning classifiers were compared. Features selection (from EEG, ECG, respiratory and eye tracking sensors) was performed using backward Recursive Feature Elimination (RFE). The best models for 1-minute MW levels classification on HSNO were K-Nearest Neighbors (KNN, F1 score = 80.3 ± 8.9%), Support Vector Machine (SVM, 77.8 ± 10.3%) and Random Forest (RF, 75.7 ± 9.1%). Exposure to sleep restriction and/or hypoxia decreased models' performance (F1 <35%). KNN and RF models, in particular those including EEG and eye tracking, trained on All-Conditions performed well across conditions (F1 scores = 77.4 ± 7.8% and 70.7 ± 10.2%). Our results highlight the need for training MW models under different physiological constraints and using multimodal datasets to improve robustness. (NCT05563688).