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Record W3008044694 · doi:10.1093/jcag/gwz047.140

A141 ENDOSCOPIST PROCEDURAL VOLUME AND COLONOSCOPY OUTCOMES: A SYSTEMATIC REVIEW AND META-ANALYSIS

2020· review· en· W3008044694 on OpenAlexaffabout
Nauzer Forbes, Devon J. Boyne, Darren R. Brenner, Matthew Mazurek, Robert J. Hilsden, Yibing Ruan, Robert L. Sutherland, Joy Pader, A M Shaheen, Mubasiru Lamidi, Steven J. Heitman

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2020
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsColonoscopyMedicineOdds ratioMeta-analysisSubgroup analysisConfidence intervalColorectal cancerAdverse effectInternal medicineCancer

Abstract

fetched live from OpenAlex

Abstract Background In addition to monitoring adverse events (AEs) and post-colonoscopy colorectal cancers (PCCRC), several indicators are used to assess the overall quality of colonoscopy performance, including adenoma detection rate (ADR) and cecal intubation rate (CIR). It is unclear whether there is an association between an endoscopist’s annual colonoscopy volumes and ADR, CIR, AEs or PCCRC. Aims We performed a systematic review and meta-analysis to determine whether there is an association between annual colonoscopy volume and colonoscopy quality indicators, or between annual volume and colonoscopy outcomes. Methods A comprehensive electronic search was performed through March of 2019 for any studies assessing the potential association between annual colonoscopy volume and outcomes, or quality indicators, including ADR, CIR, AEs or PCCRC. Pooled odds ratios (OR) were calculated using DerSimonian and Laird random effects models. Subgroup and sensitivity analyses were also performed to assess for any potential methodological or clinical factors associated with outcomes. These included dividing procedural volume into total procedures or screening procedures performed. Results Out of an initial 9,235 studies, 27 were included in our systematic review, representing 11,276,244 colonoscopies performed by over 530 endoscopists. There was no association between procedural volume and ADR (OR 1.00, 95% confidence intervals, CI, 0.98 to 1.02 per additional 100 annual total colonoscopy procedures performed by an endoscopist). CIR was improved with each additional 100 annual colonoscopy procedures (OR 1.17, 95% CI 1.08 to 1.28). There was a trend toward decreased overall adverse events per additional 100 annual procedures that did not meet significance (OR 0.95, 95% CI 0.90 to 1.00), although there was a decreased incidence of colonic perforations with increasing colonoscopy volume. Figure 1 - Forest plots demonstrating the odds of A) detecting an adenoma, B) intubating the cecum, and C) incurring an overall or specific adverse event, per additional 100 annual procedures, for total and screening procedures. Conclusions In this meta-analysis, higher annual colonoscopy volumes correlated with higher CIR, but not with ADR or PCCRC. Trends toward lower AE rates were also demonstrated with higher volumes. All studies included in this review examined endoscopists performing above respective recommended minimum volume thresholds for their health region. Thus, data are lacking on endoscopists performing very low numbers or very high numbers of colonoscopies annually. Future studies should focus on measuring colonoscopy quality metrics and outcomes among these extreme performers to more clearly determine associations between annual volume and colonoscopy outcomes. Funding Agencies Alberta Health Services Digestive Health Strategic Care Network

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.031
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0170.044
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.305
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

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