Predictive Capacity of Pulmonary Function Tests for Acute Mountain Sickness

Introduction

Exposure to hypobaric hypoxia can cause acute mountain sickness (AMS), a distressing and often debilitating malady defined by headache in combination with additional symptoms commonly encountered on rapid ascent higher than 2,500 m (8,202 ft) (Roach et al., 1993, 2018).

Risk stratification and prediction models aim at identifying those at risk of developing AMS to reduce morbidity, mortality, and potentially avoid the burden of high-altitude rescue. Various physiologic measurements have been investigated to predict AMS, including hypoxic ventilatory response (Richalet et al., 1988, 2012; Bartsch et al., 2002; Burtscher et al., 2004), 6-minute walk test (Lazio et al., 2010; Shea et al., 2016), arterial oxygen saturation (Burtscher et al., 2004, 2019; Chen et al., 2012; Richalet et al., 2012; Guo et al., 2014), and heart rate variability (Huang et al., 2010; Mellor et al., 2018; Sutherland et al., 2017) without clear support regarding their utility.

Researchers have explored the relationship between the high-altitude hypobaric hypoxia and changes in pulmonary function tests (PFTs) via spirometry, an attractive modality given its simplicity and noninvasive potential insight into the pulmonary effects of high altitude and pathophysiology of AMS (Luks and Hopkins, 2014). The majority of studies report decreases in forced vital capacity (FVC) (Anholm et al., 1979; Pollard et al., 1996; Hashimoto et al., 1997; Mason et al., 2000; Senn et al., 2006), and increases in peak expiratory flow (PEF) (Gautier et al., 1982; Pollard et al., 1996; Cogo et al., 1997; Mason et al., 2000; Deboeck et al., 2005), with variable changes in forced expiratory volume in one second (FEV₁) on ascent to high altitude (Selland et al., 1993; Hashimoto et al., 1997; Mason et al., 2000; Cremona et al., 2002). However, other high-altitude studies, including the largest PFT study to date, have found no changes at high altitude with FVC (Cremona et al., 2002; Dehnert et al., 2010), and even transient increases in FVC (Sharma and Brown, 2007).

Though some data suggest a relationship between spirometry and AMS (Anholm et al., 1979; Selland et al., 1993; Cremona et al., 2002), a few have formally assessed their relationship. Limited data support negative correlations between AMS and PEF (Pollard et al., 1996), as well as between FEV₁ and FVC (Song et al., 2013). Comparisons of these studies are limited due to varying methodologies, nonstandardized ascent profiles, equipment inaccuracies, and varying definitions of AMS. As such, there is no clear consensus on both the impact of high altitude on lung function measurements (Dehnert et al., 2010; Swenson, 2011; Luks and Hopkins, 2014), and their association with AMS (Mason et al., 2000; Dehnert et al., 2010). The role of the lungs in the hypoxia-driven process of AMS remains controversial, as it is unknown whether the decreased arterial oxygen saturation and observed pulmonary vascular changes act as a driver of altitude illness or downstream casualty (Swenson, 2014; Mairbaurl et al., 2019).

Although a review of the literature reveals an actively ongoing, decade-long discussion regarding spirometric changes at altitude, it also reveals a knowledge gap in the association between spirometry and AMS and the need for larger studies with a systematic AMS definition and standardized ascent profile. Thus, the objectives of this study were to extend prior findings of changes in pulmonary function on ascent to high altitude and association with AMS, and to determine the predictive capacity of pulmonary spirometry for the development of AMS.

Materials and Methods

Results

One hundred three participants were analyzed with well-matched comparisons of baseline demographics (Table 1) (Lipman et al., 2018). The cumulative incidence of AMS was 75 (73%) participants, with an incidence of severe AMS of 48 (47%) and mean cumulative LLQ of 4.3 ± 3.1. Acetazolamide reduced AMS by 30% compared with budesonide and 20% versus placebo (Lipman et al., 2018). When PFT was analyzed by drug arm and placebo at high altitude, there were no significant differences (Appendix Tables A1 and A2), allowing them to be combined into a single cohort for analysis (Kanaan et al., 2015; Alsup et al., 2019).

Mean spirometry values are presented in Table 2. No statistically significant changes were found between mean spirometry values at low altitude baseline, evening of, and morning after ascent (Table 3). In addition, there were no statistically significant associations between changes in mean PFT values with incidence of AMS or severe AMS (Table 4).

Correlogram analysis investigating the relationship between low-altitude spirometry values and high-altitude LLQ scores demonstrated statistically significant slight negative correlations with PEF > FVC > FEV₁ the evening of ascent but not the next morning (Fig. 1). When high-altitude spirometry was correlated with LLQ scores, analysis found similar relationships the evening of ascent, which were diminished the next morning at peak altitude (Fig. 2). Prediction modeling for low-altitude PFT to predict eventual AMS yielded 65%–73% accuracy, with an ROC range of 0.51–0.65 between statistical models.

OPEN IN VIEWER

FIG. 1.

Correlogram of PFTs at baseline low altitude with LLQ scores the evening of and morning after ascent. Strikethrough indicates insignificant values with alpha = 0.05 as marker of significance,* highlighted pertinent values. A, low altitude baseline; B1, evening of ascent to high altitude; B2, morning after ascent to high altitude; FEF_25–75, mean forced expiratory flow between 25% and 75% of the forced vital capacity; FEV₁, forced expiratory volume in one second; FVC, forced vital capacity; LLQ, Lake Louise Questionnaire; PEF, peak expiratory flow; PFT, pulmonary function test.

OPEN IN VIEWER

FIG. 2.

Correlogram of PFTs at evening of ascent with LLQ scores the evening of and morning after ascent. Strikethrough indicates insignificant values with alpha = 0.05 as marker of significance, * highlighted pertinent values. B1, evening of ascent to high altitude; B2, morning after ascent to high altitude.

Discussion

This was the largest study to date to investigate the relationship between PFTs and AMS defined by LLQ criteria. Despite the high incidence of AMS and severe AMS encountered, we did not find a significant association of disease with spirometric changes, consistent with previous investigations (Mason et al., 2000; Dehnert et al., 2010). Though slight negative correlations were found between baseline spirometry and AMS symptom severity reflected in raw LLQ scores the evening of ascent, this relationship diminished the morning after ascent and did not translate into clinically significant AMS. This weak correlation between severity of symptoms per LLQ score and decreased PFT is similar to prior observations (Anholm et al., 1979; Selland et al., 1993), but as the prior research did not systematically quantify AMS symptoms, direct comparisons are challenging.

Our observed lack of any statistically significant association of AMS with PFT changes contrasts a similar-sized military manuscript (Zhou et al., 2004), but any insights into methodological differences are limited due to its unavailability. Though larger sample sizes have been studied (Cremona et al., 2002), the largest study with comparative AMS definitions and spirometry did not analyze PFT outcomes per AMS incidence or severity (Zheng et al., 2014). They too examined oral and inhaled chemoprophylactic AMS medications, and similarly found no significant impact of medicines versus placebo on PFT other than Δ FVC in one arm. However, the authors' primary pharmacologic outcomes were subsequently unverifiable (Berger et al., 2017; Lipman et al., 2018). Likewise, we did not find significant changes in PFT on ascent in either drug, nor when limiting the analysis to just the placebo group, which further supports our conclusions. With a weak predictive accuracy of all pulmonary testing variables, our results support that PFT is a poor predictor of AMS.

In the decade-old body of spirometry literature, many studies, though methodologically sound, involved relatively small populations (Gautier et al., 1982; Selland et al., 1993; Hashimoto et al., 1997; Sharma and Brown, 2007), making definitive associations between spirometry and AMS difficult to demonstrate. Though debated (Swenson, 2011), spirometric derangement at altitude may suggest the presence of sub-clinical interstitial pulmonary edema which has been demonstrated at high altitude (Welsh et al., 1993; Cremona et al., 2002; Alsup et al., 2019), and postulated to be associated with higher rates of AMS (Cremona et al., 2002). Pulmonary edema in AMS is supported by lung ultrasound findings and pulmonary oxygen diffusion changes (Ge et al., 1997; Alsup et al., 2019). However, the statistical significance of these ultrasound changes (from the same cohort) was very slight (Alsup et al., 2019), which could reasonably correspond to a lack of observed significant associations between PFT and AMS.

Changes in PFT on ascent to high altitude would ideally be examined through a mechanistic lens; however, the causative physiology is poorly understood and proposed theories for observed changes have been historically conflicted. Early literature postulated that cold-induced broncho-constriction may have contributed to decreased FVC, though this was largely disproven with bronchodilators (Hashimoto et al., 1997). It was proposed that sub-diaphragmatic gas expansion from hypobaria or hypoxia-driven respiratory muscle fatigue contributes to decreases in FVC (Rahn and Hammond, 1952; Finkelstein et al., 1965; Deboeck et al., 2005), although both theories have been opposed (Tenney et al., 1953; Sharma and Brown, 2007). The largest high-altitude PFT cohort failed to demonstrate significant changes in FVC on ascent (Cremona et al., 2002); however, the next largest study published nearly a decade later produced contrary results, further complicating consensus (Zheng et al., 2014).

Contributing to the heterogeneity and limiting comparisons are methodological discrepancies in the peak altitude reached, speed of ascent, length of high-altitude exposure and consequential extended time course of spirometry measurements, lack of AMS as primary outcome, and a myriad of uncontrollable environmental variables in the case of field studies—all of which may contribute to pulmonary function at high altitude. As such, spirometry is unlikely to advance our understanding of AMS.

Conclusions

Spirometry did not demonstrate statistically significant changes on ascent to high altitude, nor with the development of AMS or severe AMS. Low-altitude spirometry was not a useful predictor for the development of AMS and should not be recommended for risk stratification of potential disease.