Development of a Nomogram Using Lipid Profiles and Ultrasonic Thyroid Features as Potential Predictors of Postoperative Nausea and Vomiting After Thyroid Lobectomy
Year: 2025
Type: article
Study design: Observational Study
Abstract: AIM: This study aims to evaluate the predictive performance of preoperative blood lipid profiles combined with thyroid ultrasound features for postoperative nausea and vomiting (PONV) after thyroid lobectomy, and to develop a nomogram for individualized risk assessment. METHODS: This retrospective study included 269 patients who underwent thyroid lobectomy for nodular thyroid disease at the People's Hospital of Pingyang between January 2022 and December 2024. Study participants were divided into non-PONV (n = 102) and PONV (n = 167) groups. Preoperative clinical details, thyroid ultrasound parameters, and lipid profiles were compared between the two groups. Statistically significant variables (p < 0.05) from the univariate analysis were included in the multivariate logistic regression to identify independent risk predictors. A nomogram was constructed and internally validated using bootstrap resamples (1000 iterations). RESULTS: Multivariate analysis identified Apfel score, thyroid volume, maximum nodule diameter, presence of diffuse changes, total cholesterol (TC), high-density lipoprotein cholesterol (HDL), and low-density lipoprotein cholesterol (LDL) as independent risk predictors of PONV. The nomogram showed favorable discriminative performance with an area under the receiver operating characteristic curve of 0.804 (95% CI: 0.749-0.859) and a bias-corrected area under the curve (AUC) of 0.794 (95% CI: 0.737-0.850) after bootstrap validation. Additionally, the model demonstrated favorable calibration and superior clinical utility, as assessed using the decision curve analysis. CONCLUSIONS: Multivariate analysis identified that preoperative blood lipid profiles and thyroid ultrasound features are independently associated with PONV. Incorporating these indicators along with established clinical risk factors into a nomogram enables accurate individualized prediction and may support targeted prophylactic interventions.
Source: Annali Italiani di Chirurgia
DOI: 10.62713/aic.4393
Authors: Xicai Zhang, Weiwei Yu, Yingying Wang
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4417178799
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