Evidence map›Paper›PMID 35325433›Full record

ArticleJournal of robotic surgery2023

The robotic learning curve for a newly appointed colorectal surgeon.

Sabah Uddin Saqib, Muhammad Zeeshan Raza, Charles Evans, Adeel Ahmad Bajwa

Abstract read
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In one paragraph

Article in Journal of robotic surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 5 pooled it
1.4field-weighted citation impact, top 18% 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

14 citing papers in PubMed, 5 syntheses or guidelines pooled it, 14 citations in OpenAlex.

  1. Pooled it
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  5. Learning Curve in Robotic Colorectal Surgery.JSLS : Journal of the Society of Laparoendoscopic Surgeons
    Pooled it
  6. Review
  7. Immersive robotic colorectal training in the United Kingdom is safe and efficient.Annals of the Royal College of Surgeons of England · 2025
    Article
  8. Review
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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

4 authors at 1 institution in 1 country.

Sabah Uddin SaqibClinical Fellow Colorectal Surgery, University Hospital Coventry, Coventry, UK. Sabah.saqib@uhcw.nhs.uk.ORCID http://orcid.org/0000-0002-1103-181X
Muhammad Zeeshan RazaRobotic Research Fellow in Robotic Colorectal Surgery, University Hospital Coventry, Coventry, UK.
Charles EvansConsultant Colorectal Surgeon, University Hospital Coventry, Coventry, UK.
Adeel Ahmad BajwaConsultant Colorectal Surgeon, University Hospital Coventry, Coventry, UK.
University Hospital Coventry · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robotic colorectal surgery allows for better ergonomics, superior retraction, and fine movements in the narrow anatomy of the pelvis. Recent years have seen the uptake of robotic surgery in all pelvic surgeries specifically in low rectal malignancies. However, the learning curve of robotic surgery in this cohort is unclear as established training pathways are not formalized. This study looks at the experience and learning curve of a single laparoscopic trained surgeon in performing safe and effective resections, mainly for low rectal and anal malignancies using the da Vinci robotic system by evaluating metrics related to surgical process and patient outcome. A serial retrospective review of the robotic colorectal surgery database, in the University Hospital Coventry and Warwickshire (UHCW), was undertaken. All 48 consecutive cases, performed by a recently qualified colorectal surgeon, were included in our study. The surgical process was evaluated using both console and total operative time recorded in each case along with the adequacy of resections performed; in addition, patient-related outcomes including intraoperative and postoperative complications were analyzed to assess differences in the learning curve. Forty eight sequential recto-sigmoid resections were included in the study performed by a single surgeon. The cases were divided into four cohorts in chronological order with comparable demographics, tumour stage, location, and complexity of the operation (mean age 65, male 79%, and female 29%). The results showed that the mean console time dropped from 3 to 2.5 h, while total operative time dropped from 6 h to 5.5 h as the surgeon became more experienced; however, this was not found to be statistically significant. In addition, no significant difference in pathological staging was seen over the study period. No major intra-op and post-op complications were observed and no 30-day mortality was recorded. Moreover, after 30 cases, the learning curve developed the plateau phase, suggesting the gain of maximum proficiency of skills required for robotic colorectal resections. The learning curve in robotic rectal surgery is short and flattens early; complication rates are low during the learning curve and continue to decrease with time. This shows that with proper training and proctoring, new colorectal surgeons can be trained in a short time to perform elective colorectal pelvic resections.

Indexed as

LaparoscopyRectal NeoplasmsRoboticsRobotic Surgical ProceduresSurgeonsAgedFemaleHumansLearning CurveMaleRetrospective StudiesColorectal cancerDa VinciLearning curveRobotic surgery

Identifiers

PMID35325433
OpenAlexW4220939948

What OpenQuestion holds

Textmetadata
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.