Objective: This study aimed to identify key clinical predictors for obstructive sleep apnea (OSA) in pilots from routine aeromedical examination data and to assess the predictive value of the Psychomotor Vigilance Task (PVT). Methods: A retrospective 1:1 matched case–control study was conducted, including 37 pilots with polysomnography (PSG)-confirmed OSA and 37 matched non-OSA controls. Data from routine examinations, including anthropometric, biochemical, cardiovascular, and PVT parameters, were analyzed. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select significant predictors from a wide range of variables. These selected factors were then entered into a multivariable logistic regression model to determine their independent predictive value, calculated as odds ratios (ORs). Results: The OSA group had a significantly higher body mass index (BMI; 28.11 ± 2.72 vs 23.93 ± 1.89 kg/m 2 ) and fasting plasma glucose (FPG; 5.29 ± 0.81 vs 4.82 ± 0.41 mmol/L) compared to controls (both P .05). LASSO regression identified six key predictors: BMI, FPG, hyperuricemia, hyperlipidemia, systolic blood pressure (SBP), and high-density lipoprotein (HDL); no PVT parameters were selected by the model. Multivariable logistic regression confirmed BMI (OR = 3.43; 95% CI, 1.97-8.77; P < .001) and FPG (OR = 60.24; 95% CI, 3.45-5052.71; P < .05) as significant independent predictors of OSA. Conclusion: The core predictors for OSA in pilots are primarily indicators of metabolic syndrome, notably BMI and FPG. A framework based on the six physiological factors identified by LASSO regression provides a solid evidence-based foundation for developing an efficient and accurate OSA screening tool. In this study cohort, the PVT, as a measure of cognitive performance, demonstrated limited predictive value and is not recommended as a primary screening tool for OSA in pilots.
Shao et al. (2026) studied this question.