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用于预测肠梗阻手术患者术后严重并发症的机器学习方法

Machine Learning Approaches for the Prediction of Postoperative Major Complications in Patients Undergoing Surgery for Bowel Obstruction.

作者信息

Mazzotta Alessandro D, Burti Elisa, Causio Francesco Andrea, Orlandi Alex, Martinelli Silvia, Longaroni Mattia, Pinciroli Tiziana, Debs Tarek, Costa Gianluca, Miccini Michelangelo, Aurello Paolo, Petrucciani Niccolò

机构信息

Department of Surgery, Vannini General Hospital, Oncological and General Surgery, 00177 Rome, Italy.

The BioRobotics Institute, Sant'Anna School of Advanced Studies, 56127 Pisa, Italy.

出版信息

J Pers Med. 2024 Oct 8;14(10):1043. doi: 10.3390/jpm14101043.

DOI:10.3390/jpm14101043
PMID:39452550
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11508771/
Abstract

BACKGROUND

Performing emergency surgery for bowel obstruction continues to place a significant strain on the healthcare system. Conventional assessment methods for outcomes in bowel obstruction cases often concentrate on isolated factors, and the evaluation of results for individuals with bowel obstruction remains poorly studied. This study aimed to examine the risk factors associated with major postoperative complications.

METHODS

We retrospectively analyzed 99 patients undergoing surgery from 2015 to 2022. We divided the patients into two groups: (1) benign-related obstruction (n = 68) and (2) cancer-related obstruction (n = 31). We used logistic regression, KNN, and XGBOOST. We calculated the receiver operating characteristic curve and accuracy of the model.

RESULTS

Colon obstructions were more frequent in the cancer group ( = 0.005). Operative time, intestinal resection, and stoma were significantly more frequent in the cancer group. Major complications were at 41% for the cancer group vs. 20% in the benign group ( = 0.03). Uni- and multivariate analysis showed that the significant risk factors for major complications were cancer-related obstruction and CRP. The best model was KNN, with an accuracy of 0.82.

CONCLUSIONS

Colonic obstruction is associated with tumor-related blockage. Malignant cancer and an increase in C-reactive protein (CRP) are significant risk factors for patients who have undergone emergency surgery due to major complications. KNN could improve the process of counseling and the perioperative management of patients with intestinal obstruction in emergency settings.

摘要

背景

对肠梗阻进行急诊手术持续给医疗系统带来巨大压力。肠梗阻病例结局的传统评估方法往往集中于孤立因素,对肠梗阻患者结果的评估仍研究不足。本研究旨在探讨与术后主要并发症相关的危险因素。

方法

我们回顾性分析了2015年至2022年接受手术的99例患者。我们将患者分为两组:(1)良性相关梗阻组(n = 68)和(2)癌症相关梗阻组(n = 31)。我们使用了逻辑回归、K近邻算法(KNN)和极端梯度提升算法(XGBOOST)。我们计算了模型的受试者工作特征曲线和准确性。

结果

癌症组结肠梗阻更为常见(P = 0.005)。癌症组手术时间、肠切除和造口术明显更频繁。癌症组主要并发症发生率为41%,而良性组为20%(P = 0.03)。单因素和多因素分析表明,主要并发症的显著危险因素是癌症相关梗阻和C反应蛋白(CRP)。最佳模型是KNN,准确性为0.82。

结论

结肠梗阻与肿瘤相关阻塞有关。恶性肿瘤和C反应蛋白(CRP)升高是因主要并发症接受急诊手术患者的重要危险因素。KNN可以改善急诊情况下肠梗阻患者的咨询过程和围手术期管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1133/11508771/62402c69ecd5/jpm-14-01043-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1133/11508771/af0168541ab9/jpm-14-01043-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1133/11508771/62402c69ecd5/jpm-14-01043-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1133/11508771/af0168541ab9/jpm-14-01043-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1133/11508771/62402c69ecd5/jpm-14-01043-g002.jpg

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