Department of Otolaryngology-Head and Neck Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Yishan Road 600, Shanghai, 200233, China.
Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China.
Sleep Breath. 2020 Dec;24(4):1373-1382. doi: 10.1007/s11325-019-01980-7. Epub 2019 Dec 12.
The purposes of this study were to evaluate the ability of visceral adiposity variables [the lipid accumulation product (LAP), the visceral adiposity index (VAI), and the triglyceride-glucose index (TyG)] in predicting obstructive sleep apnea hypopnea syndrome (OSAHS) and to determine the effect of sex on the prediction.
A total of 5539 subjects admitted to the sleep center for suspected OSAHS were consecutively recruited from 2007 to 2016. Anthropometric measurements, biological indicators, Epworth sleepiness scale score, and polysomnographic variables were collected. Prediction models for diagnosing OSAHS were established in the test group by logistic regression and verified in the validation group by receiver operating characteristic (ROC) curves.
A total of 4703 patients were included in total. LAP and TyG were of moderate diagnostic accuracy for OSAHS, with the diagnostic efficiency differing between men and women. A prediction model was developed that combined visceral adiposity indicators with waist circumstance and the lowest SpO. The sensitivity of those indicators were both 84% in men and women, respectively, and their specificity were both 90%. In addition, the model was confirmed in the validation group with a sensitivity and specificity of 83% and 85% in men and 85% and 84% in women.
LAP and TyG were of moderate efficiency in screening for OSAHS. The prediction model provides a simple and practical screening tool for OSAHS.
本研究旨在评估内脏脂肪变量[脂积聚产物（LAP）、内脏脂肪指数（VAI）和甘油三酯-葡萄糖指数（TyG）]预测阻塞性睡眠呼吸暂停低通气综合征（OSAHS）的能力，并确定性别对预测的影响。
2007 年至 2016 年，连续招募了 5539 名疑似 OSAHS 患者到睡眠中心就诊。收集了人体测量学测量、生物学指标、Epworth 嗜睡量表评分和多导睡眠图变量。通过逻辑回归在测试组中建立了用于诊断 OSAHS 的预测模型，并通过接收者操作特征（ROC）曲线在验证组中进行了验证。
共纳入 4703 例患者。LAP 和 TyG 对 OSAHS 具有中等诊断准确性，其诊断效率在男性和女性之间存在差异。建立了一个结合内脏脂肪指标与腰围和最低 SpO2 的预测模型。这些指标的敏感性在男性和女性中分别为 84%和 84%，特异性均为 90%。此外，该模型在验证组中得到了验证，其在男性中的敏感性和特异性分别为 83%和 85%，在女性中分别为 85%和 84%。
LAP 和 TyG 在筛查 OSAHS 方面具有中等效率。预测模型为 OSAHS 提供了一种简单实用的筛查工具。
