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Record W4391161395 · doi:10.1093/ecco-jcc/jjad212.1307

P1177 Perceptions of patients with Inflammatory Bowel Disease and first degree relatives on prediction and prevention of disease

2024· article· en· W4391161395 on OpenAlexaff
Ángeles Palomo Bravo, S G Christensen, Mette Julsgaard, Iago Rodríguez–Lago, Daniel Ginard, H G Sørensen, Gionata Fiorino, Anthony Buisson, Nina Stemmer, Natália Sousa Freitas Queiroz, Antoni Ribas, Viviana Parra-Izquierdo, Corey A. Siegel, Kenneth Croitoiru, Elizabeth A. Spencer, Inga Peter, J F Colombel, Manasi Agrawal, Ryan C. Ungaro, Catarina Fidalgo, B Morão, J Torres

Bibliographic record

VenueJournal of Crohn s and Colitis · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicinePsychological interventionDiseaseInflammatory bowel diseaseColonoscopyCrohn's diseaseFamily historyFamily medicineInternal medicineColorectal cancerCancerPsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Significant advances have been made in understanding the preclinical stages of IBD, and in identifying risk factors and biomarkers to predict IBD onset. With the use of predictive testing to identify patients at risk of developing the disease, it would be possible to intervene and try to mitigate that risk. However, the feasibility of such strategy, would depend on whether individuals at risk of developing IBD would be willing to undergo predictive testing and preventive interventions. Methods A Redcap® electronic survey, available in five languages, was disseminated by clinicians and patient’s associations to patients with IBD, first-degree relatives (FDRs) of those with IBD, parents with IBD and healthy children at risk (based on family history), and healthy couples with multiple children including one with IBD. Participants were asked to express their concerns regarding their own or offspring’s risk of developing IBD and acceptable predictive testing and preventive interventions. Results 817 individuals (75% women, mean age of 41±12 years) living in 28 different countries participated. The majority were parents with IBD of healthy at-risk children (59%). Among individuals with IBD, 50% had Crohn's disease, 55% were on biologic treatment, 25% had undergone surgery, and 62% reported a significant impact on their quality of life. Overall 85% expressed willingness for predictive testing, favoring minimally-invasive methods. Half of participants would agree to cross-sectional imaging and 38% would accept a colonoscopy. The main benefits recognized with predictive testing were the possibility of starting preventive interventions to minimize the risk of developing IBD (74%) and obtaining an earlier diagnosis (63%). Anxiety from a positive result was a concern (57%). A total of 98% would accept preventive interventions. The most accepted were quitting smoking (64%), physical exercise (81%), dietary modification/supplementation (86%/71%) and probiotics (79%); with the optimal duration of the intervention to last up to one year (33%). Participants deemed a risk of minor adverse events up to 10% acceptable, with 33% tolerating a higher risk if disease risk was reduced by 75%. Half agreed that costs should be supported entirely or shared (39%) with the government. Conclusion In this international survey of patients with IBD or parents of children at-risk of developing IBD, minimally-invasive predictive testing would be well accepted as well as non-pharmacological and highly effective preventive interventions.

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)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.005
GPT teacher head0.221
Teacher spread0.215 · 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 designQualitative
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

Citations3
Published2024
Admission routes1
Has abstractyes

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