Evidence map›Paper›PMID 37474824›Full record

ArticleSurgical endoscopy2023

Kinematic data profile and clinical outcomes in robotic inguinal hernia repairs: a pilot study.

Sarah Choksi, Daniel P Bitner, Katherine Carsky, Poppy Addison, Rachel Webman, Robert Andrews, Rebecca Kowalski, Matthew Dawson, Valery Dronsky, Andrew Yee and 2 more

Abstract read
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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 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. 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

12 authors.

Sarah ChoksiIntraoperative Performance Analytics Laboratory (IPAL), Department of Surgery, Lenox Hill Hospital, Northwell Health, 186 E 76th Street, 1st Fl, New York, NY, 10021, USA. Schoksi1@northwell.edu.ORCID http://orcid.org/0009-0004-2549-7647
Daniel P BitnerIntraoperative Performance Analytics Laboratory (IPAL), Department of Surgery, Lenox Hill Hospital, Northwell Health, 186 E 76th Street, 1st Fl, New York, NY, 10021, USA.
Katherine CarskyIntraoperative Performance Analytics Laboratory (IPAL), Department of Surgery, Lenox Hill Hospital, Northwell Health, 186 E 76th Street, 1st Fl, New York, NY, 10021, USA.
Poppy AddisonIntraoperative Performance Analytics Laboratory (IPAL), Department of Surgery, Lenox Hill Hospital, Northwell Health, 186 E 76th Street, 1st Fl, New York, NY, 10021, USA.
Rachel WebmanZucker School of Medicine at Hofstra/Northwell Health, 5000 Hofstra Blvd, Hempstead, NY, 11549, USA.
Robert AndrewsZucker School of Medicine at Hofstra/Northwell Health, 5000 Hofstra Blvd, Hempstead, NY, 11549, USA.
Rebecca KowalskiZucker School of Medicine at Hofstra/Northwell Health, 5000 Hofstra Blvd, Hempstead, NY, 11549, USA.
Matthew DawsonZucker School of Medicine at Hofstra/Northwell Health, 5000 Hofstra Blvd, Hempstead, NY, 11549, USA.
Valery DronskyZucker School of Medicine at Hofstra/Northwell Health, 5000 Hofstra Blvd, Hempstead, NY, 11549, USA.
Andrew YeeIntuitive Surgical, Atlanta, GA, USA.
Anthony JarcIntuitive Surgical, Atlanta, GA, USA.
Filippo FilicoriIntraoperative Performance Analytics Laboratory (IPAL), Department of Surgery, Lenox Hill Hospital, Northwell Health, 186 E 76th Street, 1st Fl, New York, NY, 10021, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSurgical training requires clinical knowledge and technical skills to operate safely and optimize clinical outcomes. Technical skills are hard to measure. The Intuitive Data Recorder (IDR), (Sunnyvale, CA) allows for the measurement of technical skills using objective performance indicators (OPIs) from kinematic event data. Our goal was to determine whether OPIs improve with surgeon experience and whether they are correlated with clinical outcomes for robotic inguinal hernia repair (RIHR).

methodsThe IDR was used to record RIHRs from six surgeons. Data were obtained from 98 inguinal hernia repairs from February 2022 to February 2023. Patients were called on postoperative days 5-10 and asked to take the Carolina Comfort Scale (CCS) survey to evaluate acute clinical outcomes. A Pearson test was run to determine correlations between OPIs from the IDR with a surgeon's yearly RIHR experience and with CCS scores. Linear regression was then run for correlated OPIs.

resultsMultiple OPIs were correlated with surgeon experience. Specifically, for the task of peritoneal flap exploration, we found that 23 OPIs were significantly correlated with surgeons' 1-year RIHR case number. Total angular motion distance of the left arm instrument had a correlation of - 0.238 (95% CI - 0.417, - 0.042) for RIHR yearly case number. Total angular motion distance of right arm instrument was also negatively correlated with RIHR in 1 year with a correlation of - 0.242 (95% CI - 0.420, - 0.046). For clinical outcomes, wrist articulation of the surgeon's console positively correlated with acute sensation scores from the CCS with a correlation of 0.453 (95% CI 0.013, 0.746).

conclusionsThis study defines multiple OPIs that correlate with surgeon experience and with outcomes. Using this knowledge, surgical simulation platforms can be designed to teach patterns to surgical trainees that are associated with increased surgical experience and with improved postoperative outcomes.

Indexed as

Hernia, InguinalLaparoscopyRobotic Surgical ProceduresBiomechanical PhenomenaHerniorrhaphyHumansPilot ProjectsKinematic dataObjective performance indicatorsRobotic inguinal hernia repairSurgeon experience

Identifiers

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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.