Age modulates the predictive value of self-reported sleepiness for all-cause mortality risk: insights from a comprehensive national database of veterans.

Abstract

Excessive daytime sleepiness (EDS) is prevalent and overwhelmingly stems from disturbed sleep. We hypothesized that age modulates the association between EDS and increased all-cause mortality. We utilized the Veterans' Health Administration data from 1999-2022. We enrolled participants with sleep related ICD9/10 codes or sleep services. A natural language processing (NLP) pipeline was developed and validated to extract the Epworth Sleepiness Scale (ESS) as a self-reported tool to measure EDS from physician progress notes. The NLP's accuracy was assessed through manual annotation of 470 notes. Participants were categorized into Normal-ESS, n-ESS, (ESS 0-10) and high-ESS, h-ESS, (ESS 11-24). We created three age groups: < 50 years; 50 to < 65 years; and ≥ 65 years. The adjusted odds ratio (aOR) of mortality was calculated for age, BMI, sex, race, ethnicity, and the Charlson Comorbidity Index (CCI), using n-ESS as the reference. Subsequently, we conducted age stratified analysis. The first ESS records were extracted from 423,087 veterans with a mean age of 54.8 (±14.6), mean BMI of 32.6 (±6.2), and 90.5% male. The aOR across all ages was 17% higher (1.15,1.19) in the h-ESS category. The aORs only became statistically significant for individuals aged ≥ 50 years in the h-ESS compared to the n-ESS category (< 50 years: 1.02 [0.96,1.08], 50 to < 65 years 1.13[1.10,1.16]; ≥ 65 years: 1.25 [1.21-1.28]). High ESS, predicted increased mortality only in participants aged 50 and older. Further research is required to identify this differential behavior in relation to age.