Literature DB >> 29367043

Conversion is a risk factor for postoperative anastomotic leak in rectal cancer patients - A retrospective cohort study.

Xuan-Hui Liu1, Xian-Rui Wu1, Chi Zhou1, Xiao-Bin Zheng1, Jia Ke1, Hua-Shan Liu1, Tuo Hu1, Yu-Feng Chen1, Xiao-Wen He1, Xiao-Sheng He1, Yong-le Chen1, Yi-Feng Zou1, Jian-Ping Wang1, Xiao-Jian Wu2, Ping Lan3.   

Abstract

AIM: The impact of conversion from laparoscopic surgery to laparotomy on the development of anastomotic leak (AL) in rectal cancer patients following laparoscopic low anterior resection (LAR) with total mesorectal excision (TME) has not been evaluated. The aim of this study was to evaluate the impact of conversion on the risk of AL and develop a prediction nomogram for postoperative AL.
METHODS: All rectal cancer patients following laparoscopic LAR with TME from January 2010 to October 2014 were enrolled in the primary cohort. Comparisons of the postoperative anastomotic leak incidence rate between converted patients and non-converted patients were performed using both univariate and multivariate logistic regression analyses. The result of multivariable analysis was used to develop the predicting model and the performance of nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. An independent validation cohort containing 200 patients from November 2014 to October 2015 was assessed.
RESULTS: Of all patients enrolled (n=646), 592 (91.6%) patients underwent totally laparoscopic surgery, and 54 (8.4%) were converted from laparoscopic surgery to laparotomy. Converted group patients were more likely to have a higher body mass index (BMI), prolonged length of stay (LOS), increased overall postoperative complication rates and advanced clinical T stage (T3 or T4), pathological N stage (N1 or N2) and pathological TNM stage (III or IV). The percentage of patients who had preoperative radiotherapy for rectal cancer was higher in non-converted patients. Patients who underwent conversion to laparotomy (n=10, 18.5%) were more likely to suffer from postoperative AL than those undergoing totally laparoscopic surgery (n=38, 6.4%) (P=0.004). Multivariate logistic regression analyses confirmed the association between conversion and postoperative AL (Odds ratio [OR], 95% confidence interval [CI]: 2.71 [1.31-5.63], P=0.007). Conversion, gender, and clinical N stage incorporated in the individualized prediction nomogram showed good discrimination, with a C-index of 0.697 (C-index, 0.621 and 0.772 through internal validation), and good calibration. In the validation cohort, the main results were consistent with the findings of the primary cohort, with a C-index of 0.670 (C-index, 0.562 and 0.777 through internal validation). Decision curve analysis demonstrated that the prediction nomogram was clinically useful.
CONCLUSION: Conversion during laparoscopic LAR was found to be associated with an increased risk for the postoperative AL in RC patients. A nomogram model incorporating conversion, gender and patient's clinical N stage seems to offers a useful tool for predicting postoperative AL in these patients.
Copyright © 2018. Published by Elsevier Ltd.

Entities:  

Keywords:  Anastomotic leak; Conversion to laparotomy; Laparoscopic surgery; Prediction nomogram; Primary anastomosis; Rectal cancer; Risk factor

Mesh:

Year:  2018        PMID: 29367043     DOI: 10.1016/j.ijsu.2018.01.024

Source DB:  PubMed          Journal:  Int J Surg        ISSN: 1743-9159            Impact factor:   6.071


  3 in total

1.  Converting laparoscopic colectomies to open is associated with similar outcomes as a planned open approach among Crohn's disease patients.

Authors:  Rebecca Sahyoun; Brian D Lo; George Q Zhang; Miloslawa Stem; Chady Atallah; Peter A Najjar; Jonathan E Efron; Bashar Safar
Journal:  Int J Colorectal Dis       Date:  2021-10-05       Impact factor: 2.571

2.  Machine learning-based random forest predicts anastomotic leakage after anterior resection for rectal cancer.

Authors:  Rongbo Wen; Kuo Zheng; Qihang Zhang; Leqi Zhou; Qizhi Liu; Guanyu Yu; Xianhua Gao; Liqiang Hao; Zheng Lou; Wei Zhang
Journal:  J Gastrointest Oncol       Date:  2021-06

3.  A Predicting Nomogram for Mortality in Patients With COVID-19.

Authors:  Deng Pan; Dandan Cheng; Yiwei Cao; Chuan Hu; Fenglin Zou; Wencheng Yu; Tao Xu
Journal:  Front Public Health       Date:  2020-08-11
  3 in total

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