系统评价术前和术中结直肠吻合口漏预测评分（ALPS）。

Systematic review of preoperative and intraoperative colorectal Anastomotic Leak Prediction Scores (ALPS).

机构信息

Blizard Institute, Queen Mary University of London, London, UK

Institute of Population Health Sciences, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

出版信息

BMJ Open. 2023 Jul 18;13(7):e073085. doi: 10.1136/bmjopen-2023-073085.

DOI:10.1136/bmjopen-2023-073085

PMID:37463818

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10357690/

Abstract

OBJECTIVE

To systematically review preoperative and intraoperative Anastomotic Leak Prediction Scores (ALPS) and validation studies to evaluate performance and utility in surgical decision-making. Anastomotic leak (AL) is the most feared complication of colorectal surgery. Individualised leak risk could guide anastomosis and/or diverting stoma.

METHODS

Systematic search of Ovid MEDLINE and Embase databases, 30 October 2020, identified existing ALPS and validation studies. All records including >1 risk factor, used to develop new, or to validate existing models for preoperative or intraoperative use to predict colorectal AL, were selected. Data extraction followed CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies guidelines. Models were assessed for applicability for surgical decision-making and risk of bias using Prediction model Risk Of Bias ASsessment Tool.

RESULTS

34 studies were identified containing 31 individual ALPS (12 colonic/colorectal, 19 rectal) and 6 papers with validation studies only. Development dataset patient populations were heterogeneous in terms of numbers, indication for surgery, urgency and stoma inclusion. Heterogeneity precluded meta-analysis. Definitions and timeframe for AL were available in only 22 and 11 ALPS, respectively. 26/31 studies used some form of multivariable logistic regression in their modelling. Models included 3-33 individual predictors. 27/31 studies reported model discrimination performance but just 18/31 reported calibration. 15/31 ALPS were reported with external validation, 9/31 with internal validation alone and 4 published without any validation. 27/31 ALPS and every validation study were scored high risk of bias in model analysis.

CONCLUSIONS

Poor reporting practices and methodological shortcomings limit wider adoption of published ALPS. Several models appear to perform well in discriminating patients at highest AL risk but all raise concerns over risk of bias, and nearly all over wider applicability. Large-scale, precisely reported external validation studies are required.

PROSPERO REGISTRATION NUMBER

CRD42020164804.

摘要

目的

系统回顾术前和术中吻合口漏预测评分（ALPS）和验证研究，以评估其在手术决策中的性能和实用性。吻合口漏（AL）是结直肠手术最可怕的并发症。个体化漏风险可指导吻合术和/或转流造口术。

方法

系统检索 Ovid MEDLINE 和 Embase 数据库，于 2020 年 10 月 30 日，确定了现有的 ALPS 和验证研究。所有记录均包含>1 个危险因素，用于开发新的或验证现有的用于预测结直肠 AL 的模型，包括术前或术中使用的模型，均被选中。数据提取遵循预测模型验证研究关键评价和数据提取清单指南。使用预测模型风险偏倚评估工具评估模型在手术决策中的适用性和偏倚风险。

结果

共确定了 34 项研究，其中包含 31 个单独的 ALPS（12 个结肠/结直肠，19 个直肠）和 6 篇仅包含验证研究的论文。开发数据集患者人群在数量、手术指征、紧急程度和造口纳入方面存在异质性。异质性排除了荟萃分析。仅 22 项和 11 项 ALPS 分别提供了吻合口漏的定义和时间范围。31 项研究中的 26 项采用某种形式的多变量逻辑回归进行建模。模型包含 3-33 个个体预测因子。31 项研究中有 27 项报告了模型的判别性能，但只有 18 项报告了校准。31 项 ALPS 中有 15 项报告了外部验证，31 项中有 9 项仅报告了内部验证，4 项发表时没有任何验证。31 项 ALPS 和每一项验证研究在模型分析中均被评为高偏倚风险。