Predictors of chronic kidney disease in obstructive sleep apnea patients

  • Phunphai Somkearti Department of Medicine, Faculty of Medicine, Sleep Apnea Research Group, Research Center in Back, Neck and Other Joint Pain and Human Performance, Khon Kaen University, Khon Kaen, Thailand.
  • Paiboon Chattakul Department of Medicine, Faculty of Medicine, Sleep Apnea Research Group, Research Center in Back, Neck and Other Joint Pain and Human Performance, Khon Kaen University, Khon Kaen, Thailand.
  • Sittichai Khamsai Department of Medicine, Faculty of Medicine, Sleep Apnea Research Group, Research Center in Back, Neck and Other Joint Pain and Human Performance, Khon Kaen University, Khon Kaen, Thailand.
  • Panita Limpawattana Department of Medicine, Faculty of Medicine, Sleep Apnea Research Group, Research Center in Back, Neck and Other Joint Pain and Human Performance, Khon Kaen University, Khon Kaen, Thailand.
  • Jarin Chindaprasirt Department of Medicine, Faculty of Medicine, Sleep Apnea Research Group, Research Center in Back, Neck and Other Joint Pain and Human Performance, Khon Kaen University, Khon Kaen, Thailand.
  • Verajit Chotmongkol Department of Medicine, Faculty of Medicine, Sleep Apnea Research Group, Research Center in Back, Neck and Other Joint Pain and Human Performance, Khon Kaen University, Khon Kaen, Thailand.
  • Kittisak Sawanyawisuth | kittisak@kku.ac.th Department of Medicine, Faculty of Medicine, Sleep Apnea Research Group, Research Center in Back, Neck and Other Joint Pain and Human Performance, Khon Kaen University, Khon Kaen, Thailand.

Abstract

Introduction: Obstructive sleep apnea (OSA) is a common condition in patients with chronic kidney disease (CKD). It may worsen renal function in CKD patients and is associated with uncontrolled blood pressure. Although OSA is found in up to 80% of CKD patients, there are limited data available on its clinical features in patients with and without CKD. Objective: This study aimed to identify the differences in the clinical characteristics of OSA between CKD and non-CKD OSA patients and determine the clinical predictors for CKD in OSA patients.

Methods: This was a retrospective study conducted at Khon Kaen University's Srinagarind Hospital in Thailand between July and December 2018. The inclusion criteria were diagnosis with OSA via polysomnography and having undergone laboratory tests for CKD. Obstructive sleep apnea is diagnosed according to the apnea-hypopnea index (AHI) as experiencing >5 events/hour, while CKD diagnosed based on the KDOQI guidelines. Eligible patients were divided into two groups: OSA with CKD and OSA without CKD. Predictors of CKD in OSA patients were analyzed using multivariate logistic regression analysis.

Results: During the study period, there were 178 OSA patients who met the study criteria, 88 (49.44%) of whom were in the OSA with CKD group. Both age and body mass index were comparable between OSA patients with CKD and those without (age: 59 and 57 years, respectively; body mass index: 30 and 29 kg/m2, respectively. There were three significant factors that differed between those with and without CKD group including systolic blood pressure (147 vs 135 mmHg), proportion of patients with diabetes (55% vs 34%), and proportion of patients with Mallampati scores of 3-4 (73% vs 39%). There were three independent predictors for OSA in patients with CKD: female sex, high systolic blood pressure, and Mallampati score of 3 or 4, with adjusted odds ratios (95% confidence interval) of 4.624 (1.554, 13.757), 1.060 (1.020, 1.101), and 2.816 (1.356, 5.849), respectively. The Hosmer-Lemeshow chi square statistic of the predictive model was 6.06 (p 0.640). Systolic blood pressure of more than 130 and 150 mmHg resulted in sensitivity of 84.21% and specificity of 81.40%, respectively.

Conclusions: Female sex, high systolic blood pressure, and Mallampati score of 3-4 were suggestive of OSA with CKD. Obstructive sleep apnea patients with one or more of these predictors may have a high risk of CKD.

Downloads

Download data is not yet available.
Published
2020-01-28
Section
Original Research Articles
Keywords:
Predictors, systolic blood pressure, sex
Statistics
Abstract views: 425

PDF: 57
HTML: 12
Share it

PlumX Metrics

PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.

How to Cite
Somkearti, P., Chattakul, P., Khamsai, S., Limpawattana, P., Chindaprasirt, J., Chotmongkol, V., & Sawanyawisuth, K. (2020). Predictors of chronic kidney disease in obstructive sleep apnea patients. Multidisciplinary Respiratory Medicine, 15. https://doi.org/10.4081/mrm.2020.470