预测食管切除术后吻合口漏患者的死亡率:利用tentle -食管研究数据建立预测模型

Sander Ubels, Bastiaan Klarenbeek, Moniek Verstegen, Stefan Bouwense, Ewen A Griffiths, Frans van Workum, Camiel Rosman, Gerjon Hannink
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引用次数: 0

摘要

吻合口漏是食管切除术后常见但严重的并发症,超过10%的吻合口漏患者死亡。已知AL患者的不同预后因素,但缺乏预测AL后死亡率的工具。本研究旨在建立食管切除术后AL患者术后死亡率的预测模型。tentle - esophagus是一项国际回顾性队列研究,纳入了1509例食管切除术后AL患者。主要终点为术后90天死亡率。选择先前确定的死亡率预后因素作为预测因素:与患者相关(如合并症、工作状态)和与漏相关的预测因素(如白细胞计数、胃管总体状况)。使用多变量逻辑回归建立预测模型,并使用自举法进行内部验证。1509例AL患者中,90天死亡率为11.7%。预测模型中包含16个预测因子。经内部验证,模型性能良好,c-index为0.79(95%置信区间为0.75 ~ 0.83)。内部验证模型对死亡率的预测与观察到的90天死亡率非常吻合。该预测模型被纳入一个供个人使用的在线工具,可在https://www.tentaclestudy.com/prediction-model上找到。建立的预测模型结合了患者相关因素和泄漏相关因素,能够准确预测食管切除术后AL患者的术后死亡率。该模型对临床医生在对患者及其家属进行咨询时很有用,并可能有助于在诊断AL时识别高风险患者。在未来,该工具可以指导临床决策;然而,工具的外部验证是必要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Predicting mortality in patients with anastomotic leak after esophagectomy: development of a prediction model using data from the TENTACLE-Esophagus study.

Predicting mortality in patients with anastomotic leak after esophagectomy: development of a prediction model using data from the TENTACLE-Esophagus study.

Predicting mortality in patients with anastomotic leak after esophagectomy: development of a prediction model using data from the TENTACLE-Esophagus study.

Anastomotic leak (AL) is a common but severe complication after esophagectomy, and over 10% of patients with AL suffer mortality. Different prognostic factors in patients with AL are known, but a tool to predict mortality after AL is lacking. This study aimed to develop a prediction model for postoperative mortality in patients with AL after esophagectomy. TENTACLE-Esophagus is an international retrospective cohort study, which included 1509 patients with AL after esophagectomy. The primary outcome was 90-day postoperative mortality. Previously identified prognostic factors for mortality were selected as predictors: patient-related (e.g. comorbidity, performance status) and leak-related predictors (e.g. leucocyte count, overall gastric conduit condition). The prediction model was developed using multivariable logistic regression and validated internally using bootstrapping. Among the 1509 patients with AL, 90-day mortality was 11.7%. Sixteen predictors were included in the prediction model. The model showed good performance after internal validation: the c-index was 0.79 (95% confidence interval 0.75-0.83). Predictions for mortality by the internally validated model aligned well with observed 90-day mortality rates. The prediction model was incorporated in an online tool for individual use and can be found at: https://www.tentaclestudy.com/prediction-model. The developed prediction model combines patient-related and leak-related factors to accurately predict postoperative mortality in patients with AL after esophagectomy. The model is useful for clinicians during counselling of patients and their families and may aid identification of high-risk patients at diagnosis of AL. In the future, the tool may guide clinical decision-making; however, external validation of the tool is warranted.

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