ArticleSurgery open science2023
Length of intraabdominal measurement of bowel (LIMB).
Article in Surgery open science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Development of an artificial intelligence based virtual tool for measuring distances during image-guided surgery.Surgical endoscopy · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Laparoscopic Roux-en-Y gastric bypass (RYGB) is one of the most commonly performed bariatric surgeries. The steep associated learning curve is dependent on the training facility, laparoscopic experience, and overall procedural volume. William Beaumont Army Medical Center (WBAMC) has been accredited as a bariatric center of excellence and trains resident surgeons in the performance of RYGB. Objective: This study aimed to investigate the accuracy and precision of a bariatric center of excellence's training of surgical residents in terms of laparoscopic measurements of simulated small bowel. This will act as a surrogate for how well surgical residents learn to run the small bowel during bariatric procedures and how their accuracy and precision change over time in training. Setting: This study took place at William Beaumont Army Medical Center, a bariatric center of excellence and training institution. Methods: Participants included surgical residents from WBAMC. Participants used a laparoscopic trainer and two bowel graspers to measure both a collapsing garden hose (simulated bowel) and a nylon rope (control material) to 75 cm (cm) and 125 cm (cm), three times each, with recordings of time required to do so, actual distance measured, and technique used. Results: Fifteen residents participated in the study. Residents displayed accuracy of 21.6 %. 33%of residents were precise for the 75 cm measurement, and 53 % of residents were precise for the 125-cm measurement. PGY-4 residents were the most accurate while PGY-3 residents were the most precise. There were no statistical differences between junior (PGY 1-4) and senior residents (PGY 5-6) in accuracy or precision in the measurement of 75-cm or 125-cm. No statistical differences were found measuring the hose versus rope in accuracy nor precision. PGY-4 residents completed the task in the least amount of time while PGY-2 residents took the longest to complete each task. Conclusions: In general, residents are neither precise nor accurate in measurements of simulated bowel lengths, and experience does not contribute to either. Time in residency correlates with laparoscopic speed but not with accuracy nor precision. Extrapolating this data to attending surgeons suggests that estimated lengths of small bowel that are 'run' or measured during laparoscopic cases are neither accurate nor precise. More investigation must be performed in this area.
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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.