Evidence map›Paper›PMID 36180753›Full record

ArticleSurgical endoscopy2023

Objective metrics for hand-sewn bowel anastomoses can differentiate novice from expert surgeons.

Ganesh Sankaranarayanan, Lisa M Parker, Aimal Khan, James Dials, Doga Demirel, Tansel Halic, Alyson Crawford, Uwe Kruger, Suvranu De, James W Fleshman

Open access · greenAbstract read
In one paragraph

Article in Surgical endoscopy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.0field-weighted citation impact, top 14% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Validity of a virtual reality-based straight coloanal anastomosis simulator.International journal of computer assisted radiology and surgery · 2025
    Article
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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

10 authors at 6 institutions in 1 country.

Ganesh SankaranarayananDepartment of Surgery, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA. Ganesh.Sankaranarayanan@UTSouthwestern.edu.ORCID http://orcid.org/0000-0003-1556-2797
Lisa M ParkerBaylor University Medical Center, Dallas, TX, USA.
Aimal KhanVanderbilt University Medical Center, Nashville, TN, USA.
James DialsFlorida Polytechnic University, Lakeland, FL, USA.
Doga DemirelFlorida Polytechnic University, Lakeland, FL, USA.
Tansel HalicUniversity of Central Arkansas, Conway, AK, USA.
Alyson CrawfordWestern Surgical Group, Reno, NV, USA.
Uwe KrugerRensselaer Polytechnic Institute, Troy, NY, USA.
Suvranu DeRensselaer Polytechnic Institute, Troy, NY, USA.
James W FleshmanBaylor University Medical Center, Dallas, TX, USA.
Baylor University Medical Center · USFlorida Polytechnic University · USRensselaer Polytechnic Institute · USSouthwestern Medical Center · USUniversity of Central Arkansas · USVanderbilt University Medical Center · US

Funding

Development and validation of a Virtual Colorectal Surgical Trainer (VCoST)R01EB025241 · NIBIB · RENSSELAER POLYTECHNIC INSTITUTE · PI DE, SUVRANU · 2018 to 2022
$2.7M
NIBIB NIH HHS R01 EB025241
6 · The paper itself

Abstract

backgroundAssessing performance automatically in a virtual reality trainer or from recorded videos is advantageous but needs validated objective metrics. The purpose of this study is to obtain expert consensus and validate task-specific metrics developed for assessing performance in double-layered end-to-end anastomosis. MATERIALS AND

methodsSubjects were recruited into expert (PGY 4-5, colorectal surgery residents, and attendings) and novice (PGY 1-3) groups. Weighted average scores of experts for each metric item, completion time, and the total scores computed using global and task-specific metrics were computed for assessment.

resultsA total of 43 expert surgeons rated our task-specific metric items with weighted averages ranging from 3.33 to 4.5 on a 5-point Likert scale. A total of 20 subjects (10 novices and 10 experts) participated in validation study. The novice group completed the task significantly more slowly than the experienced group (37.67 ± 7.09 vs 25.47 ± 7.82 min, p = 0.001). In addition, both the global rating scale (23.47 ± 4.28 vs 28.3 ± 3.85, p = 0.016) and the task-specific metrics showed a significant difference in performance between the two groups (38.77 ± 2.83 vs 42.58 ± 4.56 p = 0.027) following partial least-squares (PLS) regression. Furthermore, PLS regression showed that only two metric items (Stay suture tension and Tool handling) could reliably differentiate the performance between the groups (20.41 ± 2.42 vs 24.28 ± 4.09 vs, p = 0.037).

conclusionsOur study shows that our task-specific metrics have significant discriminant validity and can be used to evaluate the technical skills for this procedure.

Indexed as

SurgeonsVirtual RealityAnastomosis, SurgicalBenchmarkingClinical CompetenceHumansIntestines

Identifiers

PMID36180753
PMCPMC11335072
OpenAlexW4298147872

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.