Evidence map›Paper›PMID 37212917›Full record

ArticleInternational journal of colorectal disease2023

Prediction model of anastomotic leakage after anterior resection for rectal cancer-based on nomogram and multivariate analysis with 1995 patients.

Ruiqi Li, Jiajie Zhou, Shuai Zhao, Qiannan Sun, Daorong Wang

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Article in International journal of colorectal disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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3 · Its place in the literature

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14 citing papers in PubMed, 15 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Ruiqi LiNorthern Jiangsu People's Hospital Affiliated to Medical School of Nanjing University, Yangzhou, 225001, China.
Jiajie ZhouNorthern Jiangsu People's Hospital Affiliated to Medical School of Nanjing University, Yangzhou, 225001, China.
Shuai ZhaoNorthern Jiangsu People's Hospital Affiliated to Medical School of Nanjing University, Yangzhou, 225001, China.
Qiannan SunNorthern Jiangsu People's Hospital, Yangzhou, China.
Daorong WangNorthern Jiangsu People's Hospital Affiliated to Medical School of Nanjing University, Yangzhou, 225001, China. wdaorong666@sina.com.
Northern Jiangsu People's Hospital · CNNanjing University · CNYangzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPostoperative anastomotic leakage for rectal cancer shows higher morbidity with grievous concomitant symptoms. Accurate assessment of the incidence of anastomotic leakage, multivariate analysis, and establishment of a scientific prediction model can be useful to dispose of its possible severe clinical consequences.

methodsThis retrospective study collected 1995 consecutive patients who underwent anterior resection of rectal cancer with primary anastomosis at Northern Jiangsu People's Hospital between January 2016 and June 2022. Independent risk factors associated with anastomotic leakage were analyzed by univariate and multivariate logistic regression. The chosen independent risk factors were used to construct a nomogram risk prediction model whose availability was evaluated by using a bootstrapped-concordance index and calibration plots with R software.

resultsA total of 1995 patients who underwent anterior resection for rectal cancer were included while 120 patients were diagnosed with anastomotic leakage, an incidence of 6.0%. Univariate analysis and its concomitant multivariate cox regression analysis indicated that independent risk factors associated with anastomotic leakage included male gender (odds ratio (OR) = 2.873), diabetes (OR = 2.480), neoadjuvant therapy (OR = 5.283), tumor's distance from the anus verge < 5 cm (OR = 5.824), tumor size ≥ 5 cm (OR = 4.888), and the blood lose > 50 mL (OR = 9.606).We established a nomogram prediction model with proper applicability (concordance index, 0.83) and the calibration curve to justify its predictive ability that the predicted occurrence probability keeps a high degree of consistency with the actual occurrence probability. Meanwhile, the area under the receiver operating characteristic (ROC) curve was 0.83.

conclusionsThe characteristics of patients and tumor surgery-related conditions can affect the incidence of anastomotic leakage. However, whether the surgical method will affect morbidity is still controversial. Our nomogram can be seen as an effective instrument to predict anastomotic leakage after anterior resection for rectal cancer precisely.

Indexed as

Anastomotic LeakRectal NeoplasmsAnastomosis, SurgicalHumansMaleMultivariate AnalysisNomogramsRetrospective StudiesRisk FactorsAnastomotic leakageNomogram prediction modelRectal cancerRisk factor

Identifiers

PMID37212917
OpenAlexW4377220657

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.