Recognizable clinical subtypes of obstructive sleep apnea after ischemic stroke: A cluster analysis

Chung Yao Chen*, Chia Ling Chen

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

6 Scopus citations

Abstract

Background and Purpose: Obstructive sleep apnea (OSA) increases risk of stroke recur-rence and mortality in ischemic stroke patients. However, equivocal treatment effects warrant further categorization of post-stroke OSA for risk stratification and individualized treatment planning. Methods: The study recruited 232 ischemic stroke patients with moderate-to-severe OSA admitted for inpatient rehabilitation consecutively. Latent class analysis was performed based on sex, age, smoking, daytime sleepiness, depression, obesity, sedative use, atrial fibrillation, diabetes, dyslipidemia, hypertension, recurrent stroke and dysphagia. The augmentation index, a marker of arterial stiffness, was measured by applanation tonometry. Results: A three-cluster model provided the best fit. Cluster 1 (n=84, 36.2%) was older in age, predominantly female, with the highest hypopnea index and prevalence of atrial fibrillation. Moreover, patients in Cluster 1 had significantly higher augmentation index than those in Cluster 2. Cluster 2 patients (N=80, 34.5%) were of older age, predominantly male, with the highest prevalence of depression, the lowest prevalence of hypertension and had the most normal body mass index (BMI). Additionally, Cluster 2 had less nocturnal hypoxia as compared to Cluster 3. Cluster 3 (n=68, 29.3%) was the youngest in age, predominantly male, with the highest BMI, cumulative risk score, and prevalence of dysli-pidemia of the three clusters. Conclusion: Post-stroke OSA can be categorized into three clinical phenotypes. Patients in Clusters 1 and 3 both had elevated cardiovascular risk and treatment can be based on their distinct characteristics. Patients in Cluster 2 had relatively lower risk of cardiovascular events and the benefits of OSA treatment requires further study.

Original languageEnglish
Pages (from-to)283-290
Number of pages8
JournalNature and Science of Sleep
Volume13
DOIs
StatePublished - 2021

Bibliographical note

Publisher Copyright:
© 2021 Chen and Chen.

Keywords

  • Cluster analysis
  • Ischemic stroke
  • Latent class analysis
  • Obstructive sleep apnea

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