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Record W4319656519 · doi:10.1111/ans.18223

Prevalence of irritable bowel syndrome and its association with colorectal cancer: a systematic review and meta‐analysis

2023· review· en· W4319656519 on OpenAlexaboutno aff
Dakshitha Praneeth Wickramasinghe, Sohan Anjana Kamburugamuwa, Chrisjit Xavier, Nandadeva Samarasekera, Janindra Warusavitarne

Bibliographic record

VenueANZ Journal of Surgery · 2023
Typereview
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisIrritable bowel syndromeInternal medicineColorectal cancerMEDLINEConstipationPopulationGastroenterologyCancerEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: This study evaluates the risk of colorectal cancer (CRC) in patients with Irritable Bowel Syndrome (IBS). METHODS: A literature search was performed on MEDLINE, EMBASE, SCOPUS, and Google Scholar from inception to 31st January 2020 without any limitations on article type or language for studies reporting data on CRC on patients with IBS. A meta-analysis was performed to estimate the prevalence of CRC among patients with IBS. Data extraction was according to the PRISMA guidelines. The quality of the included studies was assessed according to the Newcastle Ottawa Scale. RESULTS: Twenty-one articles were eligible for data extraction and quantitative analysis. Of them, 11 were included in the meta-analysis (IBS n = 284 366, no-IBS n = 8 390 509). The pooled prevalence of CRC in patients with IBS was 0.96% (95% CI-0.184%-2.344%). The prevalence was lowest in the constipation-predominant IBS (pooled prevalence 1.126%. Patients with IBS-D and IBS-U had an equal pooled prevalence of CRC (2.49%). Eleven studies compared the prevalence of CRC in patients with IBS with a control population. The pooled OR was 2.8 (CI 2.305-3.294). CONCLUSIONS: There was an increased risk of CRC among patients diagnosed with IBS, primarily in the first year after IBS diagnosis. REGISTRATION: The review was registered on PROSPERO (CRD42021236707).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.610
Threshold uncertainty score0.644

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.084
GPT teacher head0.329
Teacher spread0.245 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations7
Published2023
Admission routes1
Has abstractyes

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