Faculty, Staff and Student Publications

Publication Date

1-1-2025

Journal

PLoS One

DOI

10.1371/journal.pone.0328214

PMID

40638677

PMCID

PMC12244826

PubMedCentral® Posted Date

7-10-2025

PubMedCentral® Full Text Version

Post-print

Abstract

Objective: To quantitate hypoxemia severity.

Methods: We developed the Weighted Hypoxemia Index to be adapted to different clinical settings by applying 5 steps to the oxygen saturation curve: (1) Identify desaturation/resaturation event [Formula: see text] by setting the upper threshold; (2) Exclude events as artifact by setting a lower threshold; (3) Calculate weighted area for each [Formula: see text] as [Formula: see text]; (4) Calculate a normalization factor [Formula: see text] for each subject; (5) Calculate the Weighted Hypoxemia Index as the summation of all weighted areas multiplied by [Formula: see text]. We assessed the Weighted Hypoxemia Index predictive value for all-cause mortality and cardiovascular mortality using the Sleep Heart Health Study (enrollment 1995-1998, 11.1 years mean follow-up).

Results: We set varying upper thresholds at 92%, 90%, 88%, and 86%, a lower threshold of 50%, calculated area under the curve and area above the curve, with and without a linear weighted factor (duration of each event [Formula: see text]), and used the same normalization factor of total sleep time < 90% divided by total sleep time. After excluding subjects with missing data, we analyzed 4,509 participants (Alive: N = 3,769; All-cause mortality: N = 1,071; cardiovascular mortality: N = 330). Since the Weighted Hypoxemia Index-Area Under the Curve set at upper threshold of 90% (WHI-AUC90) had the best results in predicting all-cause mortality, we then compared it to the Apnea-Hypopnea Index and Total Sleep Time < 90%. WHI-AUC90 showed statistical significance across quintiles for all-cause mortality, but not cardiovascular mortality, in adjusted Cox regression models.

Conclusion: The Weighted Hypoxemia Index offers a versatile and clinically relevant method for quantifying hypoxemia severity, with potential applications to evaluate mechanisms and outcomes across various patient populations.

Keywords

Humans, Hypoxia, Female, Male, Middle Aged, Severity of Illness Index, Oxygen Saturation, Aged, Adult, Cardiovascular Diseases

Published Open-Access

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