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Record W4212799121 · doi:10.1093/jcag/gwab049.189

A190 EPIDEMIOLOGY OF MUSCULOSKELETAL MANIFESTATIONS IN PAEDIATRIC INFLAMMATORY BOWEL DISEASE: A SYSTEMATIC REVIEW

2022· review· en· W4212799121 on OpenAlexaff
Asma Amir Ali, M Schmidt, David Piskin, Eileen Crowley, Roberta Berard

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2022
Typereview
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsVictoria HospitalLawson Health Research InstituteWestern University
Fundersnot available
KeywordsMedicineEpidemiologyCritical appraisalObservational studyCINAHLCochrane LibraryInflammatory bowel diseasePopulationDiseaseSystematic reviewMEDLINEInternal medicinePediatricsFamily medicinePhysical therapyAlternative medicinePathologyMeta-analysisPsychiatryPsychological intervention

Abstract

fetched live from OpenAlex

Abstract Background Paediatric inflammatory bowel disease (p-IBD) is a chronic and relapsing gastrointestinal disorder of childhood with associated long-term morbidity. Several extraintestinal manifestations (EIMs) are described, the most common being joint pain and/or inflammation. In 1986, Passo et al. were the first to describe the association of arthritis in p-IBD patients. However, since then, data on the epidemiology, patient and disease factors associated with, treatments for, and outcomes of p-IBD associated musculoskeletal (MSK) disease are not well-established. Aims Our study aims to summarize the literature on the epidemiology of MSK EIMs in p-IBD in the era of biologics. Methods A systematic review of the literature was performed. PubMed, Embase, Cochrane Library, Web of Science Core Collection, and CINAHL databases were searched with relevant keywords. Studies in English published from January 1, 2000 to December 21, 2020 were included. In total, 3893 papers were identified and screening was performed by two independent reviewers (AA, MS). Conflicts were resolved by a third reviewer (EC, RB). Study and population characteristics were recorded. The primary outcomes of interest were MSK symptoms at presentation and their course, method of diagnosis and definitions used for MSK EIMs. Risk of bias assessment was performed using the JBI Critical Appraisal Tools. Results Thirteen studies were included for full review, which were primarily single-centre observational studies with retrospective or cross-sectional design. The method of diagnosis for MSK EIMs varied across the studies, with only 4 studies stating the involvement of a rheumatologist in diagnosis. The definitions also varied, with MSK EIMs such as peripheral arthritis, axial arthritis, enthesopathy, and arthralgia included. Only 7 studies focused on MSK EIMs as their primary outcome, while the remainder reported on all p-IBD associated EIMs. There was a wide range in the prevalence of MSK EIMs from 2–35% (Figure 1). Four studies reported on the therapeutic response of MSK EIMs, and only 3 of those reported on biologic use. Risk of bias demonstrated heterogeneity in the quality of included studies. Conclusions This is the first systematic review of the literature for MSK EIMs in p-IBD. Analysis was limited due to variability in study design and data-reporting methods. Included studies reported prevalence of MSK EIMs, but the ascertainment of MSK EIMs, both method and definition varied with a clear lack in standardization. Our study demonstrates the need for further research of the MSK associations of p-IBD and to explore optimal management to advance care for this group of children. Funding Agencies None

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)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.044
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.007
Bibliometrics0.0200.020
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.040
GPT teacher head0.377
Teacher spread0.338 · 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 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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