Key result
Novel nomogram using BMI, PDW, and TyG index predicts obstructive sleep apnea with ~0.81 AUC.
Why the study?
Polysomnography is resource-intensive and not always readily accessible for diagnosing obstructive sleep apnea, prompting the need for individualized risk stratification tools.
Does a nomogram incorporating platelet distribution width and the triglyceride-glucose index accurately predict the risk of obstructive sleep apnea in adults referred for polysomnography?
Cohort (n=1,328)
No
Does a nomogram incorporating platelet distribution width and the triglyceride-glucose index accurately predict the risk of obstructive sleep apnea in adults referred for polysomnography?
Effect estimate: AUC 0.806 (95% CI 0.750-0.862)
A novel nomogram combining routine clinical variables with platelet distribution width and the triglyceride-glucose index provides acceptable discrimination for predicting obstructive sleep apnea in high-risk patients referred for sleep evaluation.
OSA associated with higher odds in retrospective data; leaves open causal role and need for prospective confirmation.
Liyong Shi,1,* Lianshun Lin,1,* Tanwei Liu,1,* Xiali Wang,2 Jing Cheng,3 Miaoxiang Chen,1 Qidong Chen,1 Fanbin Zhong,1 Linlin Chen,4 Xiaoyang Chen1,5,6 1Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Fujian Medical University, The Second Clinical College of Fujian Medical University, Quanzhou, Fujian, 362000, Peopleâs Republic of China; 2Science and Technology Center, Quanzhou Medical College, Quanzhou, Fujian, 362000, Peopleâs Republic of China; 3School of Clinical Medicine, Quanzhou Medical College, Quanzhou, Fujian, 362000, Peopleâs Republic of China; 4School of Pharmacy, Key Laboratory of Marine Natural Medicine and Biopharmaceuticals, Quanzhou Medical College, Quanzhou, Fujian, 362000, Peopleâs Republic of China; 5Key Laboratory of Sleep Medicine (The Second Affiliated Hospital, Fujian Medical University), Fujian Province University, Quanzhou, Fujian, 362000, Peopleâs Republic of China; 6NHC Key Laboratory of Etiological Epidemiology of Chronic Diseases with High Incidence in Fujian-Taiwan Area (Co-Construction), Fujian Medical University, Fuzhou, Fujian, 350122, Peopleâs Republic of China*These authors contributed equally to this workCorrespondence: Linlin Chen, Science and Technology Center, Quanzhou Medical College, Quanzhou, Fujian, 362000, Peopleâs Republic of China, Email cll@qzmc.edu.cn Xiaoyang Chen, Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Fujian Medical University, The Second Clinical College of Fujian Medical University, Quanzhou, Fujian, 362000, Peopleâs Republic of China, Email ccxxyy008@fjmu.edu.cnPurpose: Obstructive sleep apnea (OSA) is a prevalent systemic disorder linked to cardiovascular and metabolic consequences. However, polysomnography (PSG), the diagnostic gold standard, is resource-intensive and not always readily accessible. This study aimed to develop an exploratory nomogram incorporating platelet distribution width (PDW) and the triglyceride-glucose (TyG) index for individualized OSA risk stratification among adults referred for PSG evaluation.Patients and Methods: A retrospective analysis of 1328 consecutive adults who underwent PSG, with participants randomly divided into a training cohort (70%) for model development and a validation cohort (30%) for internal validation. Candidate predictors were evaluated using multivariable logistic regression, and LASSO logistic regression was additionally performed as a sensitivity analysis for variable selection. A predictive nomogram was constructed based on clinically relevant and statistically supported predictors, and its performance was evaluated using the area under the curve (AUC), calibration, and decision curve analysis.Results: Univariate logistic regression showed that age, sex, BMI, hypertension, PDW, and TyG index were associated with OSA. In multivariable analysis, older age (OR = 1.035, 95% CI: 1.016â 1.054, P < 0.001), male sex (OR = 2.990, 95% CI: 1.723â 5.189, P < 0.001), higher BMI (OR = 1.240, 95% CI: 1.149â 1.339, P < 0.001), elevated PDW (OR = 1.152, 95% CI: 1.025â 1.294, P = 0.017), and higher TyG index (OR = 1.710, 95% CI: 1.107â 2.642, P = 0.016) were included as predictors in the final nomogram. LASSO logistic regression supported the relevance of PDW and the TyG index, as both were retained under the lambda.min and lambda.1se criteria. The nomogram incorporating age, sex, BMI, PDW, and TyG index achieved an AUC of 0.806 in the training cohort and 0.751 in the validation cohort. Calibration curves showed consistency between predicted and observed OSA probabilities, and decision curve analysis indicated a higher net benefit than the treat-all and treat-none strategies across the evaluated threshold probability range.Conclusion: This exploratory nomogram, incorporating readily available clinical variables together with PDW and the TyG index, may help stratify OSA risk among adults referred for PSG evaluation. Further external validation is required before its use can be recommended in broader screening settings.
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Shi et al. (2026) conducted a cohort in Obstructive Sleep Apnea (n=1,328). Nomogram incorporating platelet distribution width (PDW) and triglyceride-glucose (TyG) index was evaluated on Discriminative performance (AUC) for predicting Obstructive Sleep Apnea in the training cohort (AUC 0.806, 95% CI 0.750-0.862). A novel nomogram incorporating age, sex, BMI, platelet distribution width, and the triglyceride-glucose index demonstrated good discrimination for predicting obstructive sleep apnea, achieving an AUC of 0.806.
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