Login / Signup

Mortality-risk-based apnea-hypopnea index thresholds for diagnostics of obstructive sleep apnea.

Henri KorkalainenJuha TöyräsSami NikkonenTimo Leppänen
Published in: Journal of sleep research (2019)
The severity of obstructive sleep apnea is clinically assessed mainly using the apnea-hypopnea index. Based on the apnea-hypopnea index, patients are classified into four severity groups: non-obstructive sleep apnea (apnea-hypopnea index < 5); mild (5 ≤ apnea-hypopnea index < 15); moderate (15 ≤ apnea-hypopnea index < 30); and severe obstructive sleep apnea (apnea-hypopnea index ≥ 30). However, these thresholds lack solid clinical and scientific evidence. We hypothesize that the current apnea-hypopnea index thresholds are not optimal despite their global use, and aim to assess this clinical shortcoming by optimizing the thresholds with respect to the risk of all-cause mortality. We analysed ambulatory polygraphic recordings of 1,783 patients with suspected obstructive sleep apnea (mean follow-up 18.3 years). We simulated 79,079 different threshold combinations in 100 randomized subgroups of the population and studied the relative risk of all-cause mortality corresponding to each combination and randomization. The optimal thresholds were chosen according to three criteria: (a) the hazard ratios increase linearly between severity groups towards more severe obstructive sleep apnea; (b) each group includes at least 15% of the study population; (c) group sizes decrease with increasing obstructive sleep apnea severity. The risk of all-cause mortality varied greatly across simulations; the threshold defining non-obstructive sleep apnea group having the largest effect on the hazard ratios. The apnea-hypopnea index threshold combination of 3-9-24 was optimal in most of the subgroups. In conclusion, the assessment of obstructive sleep apnea severity based on the current apnea-hypopnea index thresholds is not optimal. Our novel approach provides methods for optimizing apnea-hypopnea index-based severity classification, and the revised thresholds better differentiate patients into severity groups, ensuring that an increase in the severity corresponds to an increase in the risk of all-cause mortality.
Keyphrases
  • obstructive sleep apnea
  • positive airway pressure
  • sleep apnea
  • newly diagnosed
  • randomized controlled trial
  • machine learning
  • deep learning
  • prognostic factors
  • early onset
  • double blind
  • clinical evaluation