Evidence map›Paper›PMID 26131798›Full record

Observational studyMedicine2015

A Clinical Parameters-Based Model Predicts Anastomotic Leakage After a Laparoscopic Total Mesorectal Excision: A Large Study With Data From China.

Xiang Hu, Yong Cheng

Registry-linked trialOpen access · goldAbstract readObservational Study
In one paragraph

Observational study in Medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03013153 (Low or High Ligation of the Inferior Mesenteric Artery With Apical Lymph Node Dissection in Rectal Cancer Laparoscopic Surgery), which is not on this map. Cited by 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 pooled it
0.3field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03013153 naunknown statusnot on this mapstarted 2016, after this paper: background citation

Low or High Ligation of the Inferior Mesenteric Artery With Apical Lymph Node Dissection in Rectal Cancer Laparoscopic Surgery: A Prospective, Multi-Center, Randomized, Open-Label, Parallel Group, Non-Inferiority Clinical Trial (LAND)

TypeinterventionalSponsorSixth Affiliated Hospital, Sun Yat-sen UniversityRan2016 to 2023Enrolled748ConditionsRectal CancerArmsLow ligation with apical lymph node dissection, High ligation
3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 3 syntheses or guidelines pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Article
  6. Review
  7. Comparison of the efficacy of growth factor collagen and antibiotic collagen on colon anastomosis in  experimental animals with peritonitis.Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology · 2021
    Article
  8. Colorectal anastomosis dehiscence: a call for more detailed morphological classification.Wideochirurgia i inne techniki maloinwazyjne = Videosurgery and other miniinvasive techniques · 2021
    Article
  9. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Xiang HuFrom the Department of General Surgery (Gastrointestinal Surgery), The First Affiliated Hospital of Chongqing Medical University, Chongqing, P.R. China.
Yong Cheng
The Affiliated Yongchuan Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anastomotic leakage after colorectal surgery is a major and life-threatening complication that occurs more frequently than expected. Intraoperative judgment in predicting potential leakage has shown extremely low sensitivity and specificity. The lack of a model for predicting anastomotic leakage might explain this insufficient judgment. We aimed to propose a clinical parameters-based model to predict anastomotic leakage after laparoscopic total mesorectal excision (TME).This study was a retrospective analysis of a prospectively designed colorectal cancer dataset. In total, 1968 patients with a laparoscopic TME were enrolled from November 1, 2010, to March 20, 2014. The independent risk factors for anastomotic leakage were identified, from which the parameters-based model for leakage was developed.Anastomotic leakage was noted in 63 patients (3.2%). Male sex, a low level of anastomosis, intraoperative blood loss, diabetes, the duration time of the surgery, and low temperature were significantly associated by the bivariate analysis and the Cochran-Mantel-Haenszel test with an increased risk. From these factors, the logistic regression model identified the following 4 independent predictors: male sex (risk ratio [RR] = 1.85, 95% confidence interval [CI]: 1.13-4.87), diabetes (RR = 2.08, 95% CI: 1.19-5.8), a lower anastomosis level (RR = 3.41, 95% CI: 1.17-6.71), and a high volume of blood loss (RR = 1.03, 95% CI: 1.01-1.05). The locally weighted scatterplot smoothing regression showed an anastomosis within 5 cm from the anus and intraoperative blood loss of >100 mL as the cutoff values for a significantly increased risk of leakage. Based on these independent factors, a parameters-based model was established by the regression coefficients. The high and low-risk groups were classified according to scores of 3-5 and 0-2, with leakage rates of 8.57% and 1.66%, respectively (P < 0.001).This parameters-based model could predict the risk of anastomotic leakage following laparoscopic rectal cancer. After further validation, this model might facilitate the intraoperative recognition of high-risk patients to perform defunctional stomas.

Indexed as

Anastomotic LeakModels, StatisticalAdultAgedAged, 80 and overAnastomosis, SurgicalCarcinomaChinaDigestive System Surgical ProceduresFemaleHumansLaparoscopyMaleMiddle AgedRectal NeoplasmsRectum

Identifiers

PMID26131798
PMCPMC4504612
OpenAlexW2316988007

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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.