Reconsidering AHI as an Indicator of Sleep Apnea Severity: Insights from Mining Large, Longitudinal Sleep Datasets

Nhung Hoang, Zilu Liang, Zilu Liang

2025

Abstract

Sleep apnea remains a key area of sleep research, with the Apnea-Hypopnea Index (AHI) widely used to assess its severity. This study evaluated whether AHI is truly the best indicator of sleep apnea and identified its limitations. Using the Sleep Heart Health Study and Wisconsin Sleep Cohort datasets, which provide large, longitudinal data, we also explored survey data on demographics, physiology, and daily behaviors—often overlooked in polysomnography-based studies. The results indicate that AHI may be a good indicator for mild or moderate sleep apnea, but not necessarily for normal or severe cases. We highlight some trends that can be seen from longitudinal data. Additionally, using contrast set mining method, we identified key risk factors for cardiovascular disease, including age, snoring, and smoking behavior. These results underscore the importance of considering AHI’s limitations and incorporating additional factors for more accurate sleep apnea diagnosis and risk assessment.

Paper Citation

in Harvard Style

Hoang N. and Liang Z. (2025). Reconsidering AHI as an Indicator of Sleep Apnea Severity: Insights from Mining Large, Longitudinal Sleep Datasets. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF; ISBN 978-989-758-731-3, SciTePress, pages 976-983. DOI: 10.5220/0013385500003911

in Bibtex Style

@conference{healthinf25,
author={Nhung Hoang and Zilu Liang},
title={Reconsidering AHI as an Indicator of Sleep Apnea Severity: Insights from Mining Large, Longitudinal Sleep Datasets},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2025},
pages={976-983},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013385500003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF
TI - Reconsidering AHI as an Indicator of Sleep Apnea Severity: Insights from Mining Large, Longitudinal Sleep Datasets
SN - 978-989-758-731-3
AU - Hoang N.
AU - Liang Z.
PY - 2025
SP - 976
EP - 983
DO - 10.5220/0013385500003911
PB - SciTePress