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S186 Variation in Colectomy Rates in Ulcerative Colitis

2022· article· en· W4316084546 on OpenAlexaboutno aff
Tamer Zahdeh, Daniel Elias, Ani Nacharian, Blanka Bortely, Avinaash Raja Sager, Sanitha Pulapattassery, Rizwan Alam, Arjun Narayanan, Sameh Elias, Simcha Weissman

Bibliographic record

VenueThe American Journal of Gastroenterology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineColectomyUlcerative colitisMEDLINECohortRandomized controlled trialCohort studyInternal medicineGeneral surgeryDisease

Abstract

fetched live from OpenAlex

Introduction: Data regarding inter-regional colectomy rates in patients with ulcerative colitis (UC) remains largely unknown. Herein, we sought to systematically review the global variation in the rates of colectomy in patients with UC. Methods: A comprehensive search analysis was performed using the electronic databases MEDLINE/PubMed, EMBASE, and Cochrane through May 2020, to identify all full-text, randomized controlled trials (RCTs) and cohort studies pertaining to colectomy rates in adult patients with UC. We followed PRISMA and AMSTAR 2 guidance for conducting our systematic review. Outcomes included continent based demographic data and variation in colectomy rates. All articles were screened for bias using the Newcastle-Ottawa Scale. To identify the region-specific proportion of patients undergoing colectomy, data were plotted and median overall proportions were generated. Results: Our literature search identified 1249 articles, of which 77 studies met inclusion criteria and were eligible for review. The median overall proportion of persons with UC whom underwent a colectomy in studies was 17% (range: 1.6%-71%). Median age at UC diagnosis was scarcely reported and could not be adequately assessed. While the median proportion of persons with UC whom underwent colectomy was 38%, 31%, and 14% in Oceania, North America, and Europe respectively; Africa, Asia, and South America saw median colectomy rates as low as 10%, 8%, and 3%, respectively (Table). Conclusion: Considerable inter-regional differences were observed regarding colectomy rates in patients with UC. As such, the development of homogenous evidence-based guidelines accounting for the geographic differences in managing patients with UC is needed. Additionally, as a paucity of data on colectomy exists outside the North American and European continents, future studies—particularly in less studied locales—are warranted. Table 1. - Continent based Ulcerative Colitis (UC) colectomy rates Region N studies N sample size (median, range) Proportion males (median, range) N colectomy (median, range) Proportion colectomy (median, range) North America 20 429 (26-443,043) 51% (39%-66%) 176 (9-19,208) 31% (4%-58%) Europe 41 474 (30-76,129) 53% (0%-88%) 37 (10-9118) 14% (2%-71%) Asia 10 175.5 (62-1013) 54% (49%-59%) 20 (3-61) 8% (16%-47%) Oceania 3 71 (15-225) 61% (55%-67%) 22 (9-86) 38% (31%-60%) Africa 2 125 (115-135) 45% (44%-47%) 12 (4-20) 10% (3%-17%) South America 1 267 33% 9 3%

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)0.020
metaresearch head score (Gemma)0.087
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.087
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0150.019
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.004
GPT teacher head0.236
Teacher spread0.231 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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