Predicting Major Complications After Pancreatic Surgery
Author Information
Author(s): Wang Jiaqi, Xu Kangjing, Zhou Changsheng, Wang Xinbo, Zuo Junbo, Zeng Chenghao, Zhou Pinwen, Gao Xuejin, Zhang Li, Wang Xinying
Primary Institution: Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University
Hypothesis
This study aimed to construct and validate a model for predicting postoperative major complications in patients after pancreaticoduodenectomy.
Conclusion
The model based on clinical and CT indices demonstrates good predictive performance and clinical benefit for major complications in patients undergoing pancreaticoduodenectomy.
Supporting Evidence
- Major complications occurred in 13.3% of patients after pancreaticoduodenectomy.
- The nomogram identified high visceral adipose volume, high systemic inflammation response index, high triglyceride glucose-body mass index, low prognostic nutritional index, and CA199 ≥ 37 as independent risk factors for major complications.
- The C-index of the model was 0.854, indicating excellent discrimination.
- The calibration curve showed satisfactory concordance between predictions and actual observations.
- The decision curve analysis indicated substantial clinical utility of the nomogram.
Takeaway
Doctors can use a special chart to help predict if patients will have big problems after surgery for pancreatic cancer, which can help them take better care of the patients.
Methodology
The study collected clinical data from 360 patients who underwent pancreaticoduodenectomy and used LASSO multivariate logistic regression analysis to construct a predictive model.
Potential Biases
Inherent bias due to the retrospective nature of the study.
Limitations
The study was retrospective and had a small sample size, which may introduce bias.
Participant Demographics
The cohort included 173 males (48.1%) and 187 females (51.9%) with a median age of 61.0 years.
Statistical Information
P-Value
p<0.05
Confidence Interval
[0.800–0.907]
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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