Purpose: To investigate the predictive value of the Prognostic Nutrition Index (PNI) in major complications after esophagectomy for esophageal cancer and to develop a Nomogram risk prediction model.

Method: The clinical data of 386 patients who underwent radical esophageal cancer surgery from May 2019 to March 2022 were retrospectively analyzed. Logistic regression analysis was performed to screen independent risk factors associated with major postoperative complications. A nomogram risk prediction model for major postoperative complications was developed based on the predictors, and the clinical utility of the model was assessed by decision curve analysis(DCA).

Result: In this study logistic univariate regression analysis found that age, preoperative radiotherapy, American Society of Anesthesiologists physical status (ASA score), length of surgery, and PNI may be associated with the development of major postoperative complications. logistic multifactorial analysis showed that the above risk factors were independent risk factors for the development of major postoperative complications in esophageal cancer. Nomogram was developed by incorporating the above risk factors with ASA classification. The calibration curves showed that the model had a good agreement. The decision curves showed that the model has good clinical application.

Conclusion: Individualized nomograms based on PNI combined with clinical indicators can be used to predict major complications in the early postoperative period and help to enhance perioperative management.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10311701PMC
http://dx.doi.org/10.1186/s12893-023-02090-8DOI Listing

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