Development and internal validation of a prediction model for early anastomotic leak after minimally invasive esophagectomy: a prospective cohort study

Background Anastomotic leak (AL) remains a complication after minimally invasive esophagectomy (MIE), affecting 10–20% of patients and increasing morbidity and mortality. Although local conduit perfusion and systemic nutritional status are central to anastomotic healing, no validated bedside tool integrates quantitative early endoscopic findings with systemic indicators to predict postoperative AL.Methods This prospective single-center cohort study enrolled 583 patients who underwent MIE at Tangdu Hospital. Standardized endoscopy within 72 h quantified gastric conduit ischemic length, and postoperative serum albumin was measured. Multivariable logistic regression and receiver operating characteristic (ROC) analysis identified independent predictors and optimal cutoffs to develop a risk-stratification system. A Lasso-regularized logistic regression (Lasso LR) model was developed and internally validated (7:3 split), with performance assessed by area under the curve (AUC), calibration curves, and decision curve analysis. Associations with ECCG-defined AL severity were also assessed.Results Gastric conduit ischemic length ≥3.5 cm (OR 3.361, p = 0.043) and postoperative serum albumin <31.75 g/L (OR 0.886, p < 0.001) were independent predictors. The Lasso LR model achieved an internal validation AUC of 0.727 (95% CI: 0.641–0.810). The risk-stratification system yielded AL rates of 11.00%, 22.73%, and 73.68% across low-, medium-, and high-risk groups (p < 0.001). Both predictors correlated with ECCG severity. A nomogram and web-based calculators were developed for bedside use.Conclusion Quantitative gastric conduit ischemic length and postoperative serum albumin enabled individualized AL risk assessment within 72 h after MIE. By integrating local perfusion and systemic healing capacity, the model and digital tools provide a framework for early targeted postoperative management.Trial registration Chinese Clinical Trial Registry, ChiCTR2100054550. Registered December 19, 2021, https://www.chictr.org.cn/.

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Journal
Annals of Medicine
Published
2026-09-12
DOI
https://doi.org/10.1080/07853890.2026.2726636
Primary Topic
Esophageal Cancer Research and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Development and internal validation of a prediction model for early anastomotic leak after minimally invasive esophagectomy: a prospective cohort study

Feng Zhi-bo, Menghua Xue, Yao Ma, Yu-Quan Bai et al.
Annals of Medicine
Esophageal Cancer Research and Treatment
article

Development and internal validation of a prediction model for early anastomotic leak after minimally invasive esophagectomy: a prospective cohort study

Feng Zhi-bo, Menghua Xue, Yao Ma, Yu-Quan Bai, Jinbo Zhao, Fan Gao, He Xu, Xuan-Feng Ren, Pei-Long Bao
article en

Abstract

Background Anastomotic leak (AL) remains a complication after minimally invasive esophagectomy (MIE), affecting 10–20% of patients and increasing morbidity and mortality. Although local conduit perfusion and systemic nutritional status are central to anastomotic healing, no validated bedside tool integrates quantitative early endoscopic findings with systemic indicators to predict postoperative AL.Methods This prospective single-center cohort study enrolled 583 patients who underwent MIE at Tangdu Hospital. Standardized endoscopy within 72 h quantified gastric conduit ischemic length, and postoperative serum albumin was measured. Multivariable logistic regression and receiver operating characteristic (ROC) analysis identified independent predictors and optimal cutoffs to develop a risk-stratification system. A Lasso-regularized logistic regression (Lasso LR) model was developed and internally validated (7:3 split), with performance assessed by area under the curve (AUC), calibration curves, and decision curve analysis. Associations with ECCG-defined AL severity were also assessed.Results Gastric conduit ischemic length ≥3.5 cm (OR 3.361, p = 0.043) and postoperative serum albumin <31.75 g/L (OR 0.886, p < 0.001) were independent predictors. The Lasso LR model achieved an internal validation AUC of 0.727 (95% CI: 0.641–0.810). The risk-stratification system yielded AL rates of 11.00%, 22.73%, and 73.68% across low-, medium-, and high-risk groups (p < 0.001). Both predictors correlated with ECCG severity. A nomogram and web-based calculators were developed for bedside use.Conclusion Quantitative gastric conduit ischemic length and postoperative serum albumin enabled individualized AL risk assessment within 72 h after MIE. By integrating local perfusion and systemic healing capacity, the model and digital tools provide a framework for early targeted postoperative management.Trial registration Chinese Clinical Trial Registry, ChiCTR2100054550. Registered December 19, 2021, https://www.chictr.org.cn/.

Annals of MedicineVol. 58(1)
Northwest University (US), Air Force Medical University (CN)
National Natural Science Foundation of China
Zero hunger
Openalex Percentile: Top 8%
Esophageal Cancer Research and Treatment
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