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结直肠手术吻合口漏的评分预测:系统评价。

Score prediction of anastomotic leak in colorectal surgery: a systematic review.

机构信息

Division of Digestive Surgery, University Hospitals of Geneva, Rue Gabrielle-Perret-Gentil 4, 1211, Geneva 14, Switzerland.

Medical School, University of Geneva, Rue Michel-Servet 1, 1205, Geneva, Switzerland.

出版信息

Surg Endosc. 2024 Apr;38(4):1723-1730. doi: 10.1007/s00464-024-10705-1. Epub 2024 Feb 28.

Abstract

OBJECTIVE

Predicting the risk of anastomotic leak (AL) is of importance when defining the optimal surgical strategy in colorectal surgery. Our objective was to perform a systematic review of existing scores in the field.

METHODS

We followed the PRISMA checklist (S1 Checklist). Medline, Cochrane Central and Embase were searched for observational studies reporting on scores predicting AL after the creation of a colorectal anastomosis. Studies reporting only validation of existing scores and/or scores based on post-operative variables were excluded. PRISMA 2020 recommendations were followed. Qualitative analysis was performed.

RESULTS

Eight hundred articles were identified. Seven hundred and ninety-one articles were excluded after title/abstract and full-text screening, leaving nine studies for analysis. Scores notably included the Colon Leakage Score, the modified Colon Leakage Score, the REAL score, www.anastomoticleak.com and the PROCOLE score. Four studies (44.4%) included more than 1.000 patients and one extracted data from existing studies (meta-analysis of risk factors). Scores included the following pre-operative variables: age (44.4%), sex (77.8%), ASA score (66.6%), BMI (33.3%), diabetes (22.2%), respiratory comorbidity (22.2%), cardiovascular comorbidity (11.1%), liver comorbidity (11.1%), weight loss (11.1%), smoking (33.3%), alcohol consumption (33.3%), steroid consumption (33.3%), neo-adjuvant treatment (44.9%), anticoagulation (11.1%), hematocrit concentration (22.2%), total proteins concentration (11.1%), white blood cell count (11.1%), albumin concentration (11.1%), distance from the anal verge (77.8%), number of hospital beds (11.1%), pre-operative bowel preparation (11.1%) and indication for surgery (11.1%). Scores included the following peri-operative variables: emergency surgery (22.2%), surgical approach (22.2%), duration of surgery (66.6%), blood loss/transfusion (55.6%), additional procedure (33.3%), operative complication (22.2%), wound contamination class (1.11%), mechanical anastomosis (1.11%) and experience of the surgeon (11.1%). Five studies (55.6%) reported the area under the curve (AUC) of the scores, and four (44.4%) included a validation set.

CONCLUSION

Existing scores are heterogeneous in the identification of pre-operative variables allowing predicting AL. A majority of scores was established from small cohorts of patients which, considering the low incidence of AL, might lead to miss potential predictors of AL. AUC is seldom reported. We recommend that new scores to predict the risk of AL in colorectal surgery to be based on large cohorts of patients, to include a validation set and to report the AUC.

摘要

目的

在确定结直肠手术的最佳手术策略时,预测吻合口漏(AL)的风险非常重要。我们的目的是对该领域现有的评分进行系统评价。

方法

我们遵循 PRISMA 清单(S1 清单)。在 Medline、Cochrane 中心和 Embase 中搜索了关于创建结直肠吻合术后预测 AL 的评分的观察性研究。仅报告现有评分验证和/或基于术后变量的评分的研究被排除在外。遵循 PRISMA 2020 建议。进行定性分析。

结果

共确定了 800 篇文章。经过标题/摘要和全文筛选,791 篇文章被排除在外,留下 9 篇进行分析。评分包括结肠漏评分、改良结肠漏评分、REAL 评分、www.anastomoticleak.com 和 PROCOLE 评分。四项研究(44.4%)纳入了超过 1000 名患者,一项研究从现有研究中提取数据(危险因素的荟萃分析)。评分包括以下术前变量:年龄(44.4%)、性别(77.8%)、ASA 评分(66.6%)、BMI(33.3%)、糖尿病(22.2%)、呼吸系统合并症(22.2%)、心血管合并症(11.1%)、肝合并症(11.1%)、体重减轻(11.1%)、吸烟(33.3%)、饮酒(33.3%)、类固醇使用(33.3%)、新辅助治疗(44.9%)、抗凝(11.1%)、红细胞压积浓度(22.2%)、总蛋白浓度(11.1%)、白细胞计数(11.1%)、白蛋白浓度(11.1%)、肛缘距离(77.8%)、医院床位数量(11.1%)、术前肠道准备(11.1%)和手术指征(11.1%)。评分包括以下围手术期变量:急诊手术(22.2%)、手术途径(22.2%)、手术持续时间(66.6%)、失血量/输血(55.6%)、附加手术(33.3%)、手术并发症(22.2%)、伤口污染程度(1.11%)、机械吻合(1.11%)和外科医生经验(11.1%)。五项研究(55.6%)报告了评分的曲线下面积(AUC),四项研究(44.4%)包括验证集。

结论

现有的评分在识别允许预测 AL 的术前变量方面存在差异。大多数评分都是从小样本患者中建立的,考虑到 AL 的低发生率,这可能会导致潜在的 AL 预测因素被遗漏。AUC 很少被报道。我们建议新的评分来预测结直肠手术中 AL 的风险,基于大量患者,包括验证集,并报告 AUC。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8e6/10978556/8657c5aeae66/464_2024_10705_Fig1_HTML.jpg

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