Health Management and Economics Research Center, Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
Obes Surg. 2019 Jul;29(7):2276-2286. doi: 10.1007/s11695-019-03849-w.
BACKGROUND/OBJECTIVE: One of the most effective treatments for patients with obesity, albeit with some complications, is obesity surgery. The aim of this study was to develop a clinical decision support system (CDSS) to predict the early complications of one-anastomosis gastric bypass (OAGB) surgery.
SUBJECTS/METHODS: This study was conducted in Tehran, Iran on patients who underwent OAGB surgery in 2011-2014 in five hospitals. Initially, variables affecting the OAGB early complications were identified using the literature review. Patients' data were extracted from an existing database of obesity surgery. Then, different artificial neural networks (ANNs) (multilayer perceptron (MLP) network) were developed and evaluated for prediction of 10-day, 1-month, and 3-month complications.
Factors including age, BMI, smoking status, intra-operative complications, comorbidities, laboratory tests, sonography results, and endoscopy results were considered important factors for predicting early complications of OAGB. A CDSS was developed with these variables. The accuracy, specificity, and sensitivity of the 10-day prediction system in the test data were 98.4%, 98.6%, and 98.3%, respectively. These figures for 1-month system were 96%, 93%, and 98.4% and for the 3-month system were 89.3%, 86.6%, and 91.5%, respectively.
Using the CDSS designed, we could accurately predict the early complications of OAGB surgery.
背景/目的：肥胖手术是治疗肥胖症患者的最有效方法之一，尽管存在一些并发症。本研究旨在开发一种临床决策支持系统（CDSS），以预测单吻合口胃旁路术（OAGB）手术的早期并发症。
受试者/方法：本研究在伊朗德黑兰进行，对 2011 年至 2014 年期间在五家医院接受 OAGB 手术的患者进行研究。首先，通过文献回顾确定了影响 OAGB 早期并发症的变量。从肥胖手术的现有数据库中提取患者数据。然后，开发并评估了不同的人工神经网络（ANNs）（多层感知器（MLP）网络），以预测 10 天、1 个月和 3 个月的并发症。
包括年龄、BMI、吸烟状况、术中并发症、合并症、实验室检查、超声结果和内窥镜结果在内的因素被认为是预测 OAGB 早期并发症的重要因素。利用这些变量开发了一个 CDSS。在测试数据中，10 天预测系统的准确性、特异性和敏感性分别为 98.4%、98.6%和 98.3%。1 个月系统的这些数字分别为 96%、93%和 98.4%，3 个月系统的分别为 89.3%、86.6%和 91.5%。
使用设计的 CDSS，我们可以准确预测 OAGB 手术的早期并发症。
