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Record W4224036526 · doi:10.1093/crocol/otac014

Yoga in Patients With Inflammatory Bowel Disease: A Narrative Review

2022· review· en· W4224036526 on OpenAlexaff
Sandeep Kaur, Adrijana D’Silva, Abdel Aziz Shaheen, Maitreyi Raman

Bibliographic record

VenueCrohn s & Colitis 360 · 2022
Typereview
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineQuality of life (healthcare)PsychosocialAnxietyPsychological interventionRandomized controlled trialInflammatory bowel diseaseDepression (economics)Physical therapyIntervention (counseling)DiseaseAlternative medicineIrritable bowel syndromeCrohn's diseaseClinical trialIntensive care medicinePsychiatryInternal medicineNursing

Abstract

fetched live from OpenAlex

Despite advancements in the treatment of inflammatory bowel disease (IBD), the global prevalence of IBD is increasing. Patients with IBD often experience a high psychosocial burden, worsening their IBD symptoms and increasing relapse, hospitalization rates, and healthcare costs, which impairs their quality of life (QoL). Evidence suggests that mind-body intervention in many chronic illnesses is effective in improving symptoms and QoL. Yoga is the most frequently used mind-body practice globally. Meta-analyses of randomized clinical trials and prospective studies have highlighted that yoga improves symptoms and QoL of patients with IBD; however, recommendations about indications for yoga as well as dose and frequency of yoga are lacking. The present narrative review aims to describe the available evidence regarding the effects of yoga on common patient-reported outcome measures in IBD, including depression, anxiety, stress, and QoL. Physicians can hence promote yoga interventions in their discussions with patients to help control these IBD-related outcome measures.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.039
GPT teacher head0.343
Teacher spread0.305 · 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 designNot applicable
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

Citations6
Published2022
Admission routes1
Has abstractyes

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