Evidence map›Paper›PMID 29086234›Full record

ArticleInternational journal of computer assisted radiology and surgery2018

Objective assessment of colonoscope manipulation skills in colonoscopy training.

Matthew S Holden, Chang Nancy Wang, Kyle MacNeil, Ben Church, Lawrence Hookey, Gabor Fichtinger, Tamas Ungi

Registry-linked trialAbstract read
PubMed Publisher
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06683326 (Smart-gloves Hand Motion Tracking for Live Endoscopic Submucosal Dissection Training), which is not on this map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 30% 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.

NCT06683326 nanot yet recruitingnot on this mapstarted 2025, after this paper: background citation

Smart-gloves Hand Motion Tracking for Live Endoscopic Submucosal Dissection Training: a Randomized, Comparative Study

TypeinterventionalSponsorCarol Davila University of Medicine and PharmacyRan2025 to 2025Enrolled12ConditionsAnimal ModelArmsROKOKO smart-glove
3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
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

7 authors at 1 institution in 1 country.

Matthew S HoldenLaboratory for Percutaneous Surgery, School of Computing, Queen's University, Kingston, ON, Canada. 72mh@queensu.ca.ORCID http://orcid.org/0000-0002-6031-7208
Chang Nancy WangGastrointestinal Diseases Research Unit, Department of Medicine, Queen's University, Kingston, ON, Canada.
Kyle MacNeilLaboratory for Percutaneous Surgery, School of Computing, Queen's University, Kingston, ON, Canada.
Ben ChurchLaboratory for Percutaneous Surgery, School of Computing, Queen's University, Kingston, ON, Canada.
Lawrence HookeyGastrointestinal Diseases Research Unit, Department of Medicine, Queen's University, Kingston, ON, Canada.
Gabor FichtingerLaboratory for Percutaneous Surgery, School of Computing, Queen's University, Kingston, ON, Canada.
Tamas UngiLaboratory for Percutaneous Surgery, School of Computing, Queen's University, Kingston, ON, Canada.
Queen's University · CA

Funding

Collaborative Health Research Project (NSERC/CIHR) 127797Natural Sciences and Engineering Research Council of Canada (CA) CGSD3-460098-2014
6 · The paper itself

Abstract

objectiveManipulation of the colonoscope is a technical challenge for novice clinicians which is best learned in a simulated environment. It involves the coordination of scope tip steering with scope insertion, using a rotated image as reference. The purpose of this work is to develop and validate a system which objectively assesses colonoscopy technical skills proficiency in an arbitrary training environment, allowing novices to assess their technical proficiency prior to real patient encounters.

methodsWe implemented a motion tracking setup to objectively analyze and assess the way operators perform colonoscopies, including an analysis of wrist and elbow joint motions. Subsequently, we conducted a validation study to verify whether our motion analysis could discriminate novice colonoscopists from experts. Participants navigated a wooden bench-top model using a standard colonoscope while their motions were tracked.

resultsThe developed motion tracking setup allowed colonoscopists of varying levels of proficiency to have their colonoscope manipulation assessed, and was able to be operated by a trained non-technical operator. Novice operators had significantly greater median times (101.5 vs. 31.5 s) and number of hand movements (62.0 vs. 21.5) than experts. Experts, however, spent a significantly greater proportion of time in extreme ranges of wrist and elbow joint motion than novices.

conclusionWe have developed and implemented a hand and joint motion analysis system that is able to discriminate novices from experts based on objective measures of motion. These metrics could, thus, serve as proxies for technical proficiency during training.

Indexed as

Clinical CompetenceColonoscopesColonoscopyComputer SimulationEducational MeasurementHumansColonoscopyMedical educationObjective skill assessmentSimulation-based training

Identifiers

PMID29086234
OpenAlexW2765378388

What OpenQuestion holds

Textmetadata
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.