A nomogram model to predict postoperative delirium in esophageal cancer patients undergoing esophagectomy
Abstract Background Postoperative delirium (POD) after esophagectomy is one of the most serious complications for cases with esophageal cancer (EC). This study determined to obtain predictive factors for POD and develop a nomogram model to predict the occurrence of POD among EC patients. Methods LAS...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | BMC Cancer |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12885-025-14478-1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Abstract Background Postoperative delirium (POD) after esophagectomy is one of the most serious complications for cases with esophageal cancer (EC). This study determined to obtain predictive factors for POD and develop a nomogram model to predict the occurrence of POD among EC patients. Methods LASSO and multivariate logistic regression analyses were utilized to identify potential predictive factors. A nomogram model was developed based on the results of multivariate logistic regression analysis. Results Totally, 924 EC patients undergoing esophagectomy were included, and 157 (16.99%) patients developed POD. Results of LASSO and multivariate logistic analyses showed that age > 70 years, use of penehyclidine hydrochloride, open surgery, preoperative lymphocyte ≤ 1.45*109/L, preoperative albumin ≤ 43.6 g/L, preoperative prognostic nutritional index (PNI) ≤ 50.9, preoperative neutrophil-to-lymphocyte ratio (NLR) > 2.33, preoperative platelet-to-white cell ratio (PWR) ≤ 34.97, and postoperative PNI ≤ 39.40 were independent risk factors for POD. This nomogram model showed a good predictive ability with a C-index value of 0.832 (95% CI: 0.797–0.867). The calibration curve suggested that the predicted results of this nomogram model were in concordance with the actual results. The decision curve analysis (DCA) of this nomogram indicated that there were net benefits for predicting POD. Conclusion This nomogram model helps clinicians to predict the occurrence of POD in patients with EC. |
|---|---|
| ISSN: | 1471-2407 |