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Background <p>Postoperative hypoxemia (PH) is the most common postoperative pulmonary complication (PPC) of bariatric surgery. However, clinically validated tools and tests are lacking to predict the risk of hypoxemia after bariatric surgery in patients with obesity. Therefore, this study developed and validated a nomogram model for predicting the probability of hypoxemia within 24&#xa0;h after laparoscopic sleeve gastrectomy (LSG) in patients with obesity.</p> Methods <p>The prediction model was based on a retrospective study of 195 patients with obesity who underwent LSG between January 2018 and December 2023 at Shanghai Tenth People’s Hospital. Multivariate logistic regression analysis was performed to identify independent predictors of postoperative hypoxemia. Model performance was evaluated using receiver operating characteristic curves, calibration curves, clinical decision curve analysis, and clinical impact curves. This prediction model was internally validated with bootstrap resampling and further externally validated in 105 patients who underwent LSG at Beijing Friendship Hospital and The Third People’s Hospital of Chengdu.</p> Results <p>The nomogram prediction model included preoperative body mass index (BMI), platelet count (PLT), fibrinogen level (FIB), and the triglyceride-glucose (TyG) index. This prediction model demonstrated favorable discrimination, calibration, and clinical validity in both the training and validation sets. We published the nomogram online as a simple and useful calculator.</p> Conclusions <p>The prediction model accurately predicted the risk of postoperative hypoxemia in patients with obesity and may help professionals identify high-risk patients early and make informed clinical decisions.</p> Trial registration: NCT04548232

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Development and External Validation of a Prediction Model for Hypoxemia After Laparoscopic Sleeve Gastrectomy in Patients with Obesity: a Multicenter Retrospective Study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月24日

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  • Junwei Guo,
  • Peirong Tian,
  • Jiahui Yu,
  • Guanda Lu,
  • Kelibinuer Mutailipu,
  • Xin Wen,
  • Xingchun Wang,
  • Hui You,
  • Culing Zhu,
  • Liesheng Lu,
  • Yue Wang,
  • Shen Qu,
  • Haibing Chen,
  • Yugang Zhuang,
  • Le Bu

摘要

Background

Postoperative hypoxemia (PH) is the most common postoperative pulmonary complication (PPC) of bariatric surgery. However, clinically validated tools and tests are lacking to predict the risk of hypoxemia after bariatric surgery in patients with obesity. Therefore, this study developed and validated a nomogram model for predicting the probability of hypoxemia within 24 h after laparoscopic sleeve gastrectomy (LSG) in patients with obesity.

Methods

The prediction model was based on a retrospective study of 195 patients with obesity who underwent LSG between January 2018 and December 2023 at Shanghai Tenth People’s Hospital. Multivariate logistic regression analysis was performed to identify independent predictors of postoperative hypoxemia. Model performance was evaluated using receiver operating characteristic curves, calibration curves, clinical decision curve analysis, and clinical impact curves. This prediction model was internally validated with bootstrap resampling and further externally validated in 105 patients who underwent LSG at Beijing Friendship Hospital and The Third People’s Hospital of Chengdu.

Results

The nomogram prediction model included preoperative body mass index (BMI), platelet count (PLT), fibrinogen level (FIB), and the triglyceride-glucose (TyG) index. This prediction model demonstrated favorable discrimination, calibration, and clinical validity in both the training and validation sets. We published the nomogram online as a simple and useful calculator.

Conclusions

The prediction model accurately predicted the risk of postoperative hypoxemia in patients with obesity and may help professionals identify high-risk patients early and make informed clinical decisions.

Trial registration: NCT04548232