Nature and Science of Sleep (Sep 2024)

A Prediction Nomogram of Severe Obstructive Sleep Apnea in Patients with Obesity Based on the Liver Stiffness and Abdominal Visceral Adipose Tissue Quantification

  • Zhao A,
  • Hao B,
  • Liu S,
  • Qiu X,
  • Ming X,
  • Yang X,
  • Cai J,
  • Li Z,
  • Chen X

Journal volume & issue
Vol. Volume 16
pp. 1515 – 1527

Abstract

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Anbang Zhao,1,2,* Bin Hao,1,2,* Simin Liu,3,* Xiaoyu Qiu,1,2,* Xiaoping Ming,1,2 Xiuping Yang,1,2 Jie Cai,1,2 Zhen Li,4,5 Xiong Chen1,2 1Department of Otorhinolaryngology, Head and Neck Surgery, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of China; 2Sleep Medicine Center, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of China; 3Department of Neurosurgery, Union Hospital Tongji Medical College Huazhong University of Science and Technology, Wuhan, People’s Republic of China; 4Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of China; 5Bariatric and Metabolic Disease Surgery Center, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiong Chen, Department of Otorhinolaryngology, Head and Neck Surgery, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of China, Email [email protected] Zhen Li, Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of China, Email [email protected]: The diagnosis of severe OSA still relies on polysomnography, which causes a strong sense of restraint in patients with obesity. However, better prediction tools for severe OSA applicable to patients with obesity have not been developed.Patients and Methods: Relevant clinical data of 1008 patients with OSA who underwent bariatric surgery in our hospital were collected retrospectively. Patients were divided into training and test cohorts by machine learning. Univariate and multivariate logistic regression analysis was used to screen associations, including liver stiff measurement (LSM) and abdominal visceral tissue (aVAT), and to construct a severe OSA risk prediction nomogram. Then, we evaluated the effectiveness of our model and compared our model with the traditional Epworth Sleepiness Scale (ESS) model. Finally, our associations were used to explore the correlation with other indicators of OSA severity.Results: Our study revealed that age, biological sex, BMI, LSM, aVAT, and LDL were independent risk factors for severe OSA in patients with obesity. A severe OSA risk prediction nomogram constructed by six indicators possessed high AUC (0.845), accuracy (77.6%), and relatively balanced specificity and sensitivity (72.4%, 82.8%). The Hosmer-Lemeshow test (P=0.296, 0.785), calibration curves, and DCA of the training and test cohorts suggested better calibration and more net clinical benefit. Compared with the traditional ESS model, our model had higher AUC (0.829 vs 0.545), sensitivity (78.9% vs 12.2%), PPV (77.9% vs 53.3%), and accuracy (75.4% vs 55.2%). In addition, the associations in our model were independently correlated with other indicators reflecting OSA severity.Conclusion: We provided a simple, cheap, and non-invasive nomogram of severe OSA risk prediction for patients with obesity, which would be helpful for preventing further complications associated with severe OSA.Plain Language Summary: Question: Can we predict severe OSA in patients with obesity by their metabolic complications through some non-invasive examinations?Findings: Compared with traditional questionnaires, we developed and validated a new prediction model, including liver stiffness measurement and abdominal visceral adipose tissue, to screen severe OSA in bariatric surgery candidates through non-invasive examinations, which may contribute to perioperative safety and ultimate weight loss outcomes.Meaning: For patients with obesity who are in hospital because of metabolic disorders, it is necessary for them to be screened for possible severe OSA according to our new prediction nomogram, which is helpful for preventing further complications and perioperative risk associated with severe OSA.Keywords: obstructive sleep apnea, obesity, liver stiffness measurement, visceral adipose tissue, nomogram

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