Biological Variation of Resting Ventilation and its Diagnostic Accuracy for Acute Mountain Sickness at Altitude

Abstract

Individuals who develop acute mountain sickness (AMS) upon exposure to high altitude (HA) exhibit differential responses in resting measures of minute ventilation (VE) and end-tidal partial pressure of carbon dioxide (PETCO2). PURPOSE: To determine the biological variation and diagnostic potential of ventilatory parameters in association with AMS. METHODS: We performed a retrospective analysis via the Mountain Medicine Database of 22 studies completed by the U.S. Army Research Institute of Environmental Medicine (N = 424). First, we determined the biological variation of resting measures of ventilation and defined the accompanying static and dynamic thresholds that indicate a significant deviation from normal at sea level (SL). Second, the diagnostic accuracy of ventilatory measures for AMS development was assessed at HA (4300 m). RESULTS: Resting measures of ventilation demonstrated substantial variability within (range 0.4 - 7.7%) and between (range 1.0 - 24.5%) subjects. Based on the index of individuality (II), end-tidal partial pressure of oxygen (PETO2) and respiratory exchange ratio (RER) may be useful in the static assessment of physiological deviations from normal (II = 0.57 and 0.60, respectively) at HA. Based on the index of heterogeneity (IH), PETO2 and peripheral oxygen saturation (SpO2) may be useful in the dynamic assessment of deviations from normal (IH = 1.91 and 0.41, respectively) at HA. RER and SpO2 showed significant diagnostic accuracy in the static assessment of AMS (sensitivity/specificity = 53/86 and 24/96, respectively). Ventilatory efficiency for oxygen (VE/VO2), RER, and SpO2 showed significant diagnostic accuracy in the dynamic assessment of AMS (sensitivity/specificity = 72/54, 53/74, and 25/98, respectively). Among all measures, RER showed the greatest Youden’s Index, a value indicative of the combined sensitivity and specificity of a given predictor (static: 39, dynamic: 28). CONCLUSION: Many resting ventilation measures do not demonstrate potential for AMS prediction. However, the few measures identified as potential predictors of AMS following SL biological variation analysis also demonstrated the greatest diagnostic power for AMS at HA. RER shows particular promise as a potential AMS prediction tool. DISCLAIMER: Author views not official US Army or DOD policy.