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Record W4206978172 · doi:10.1093/ecco-jcc/jjab232.643

P516 Discrete choice experiment to examine patient preferences for surgical interventions in patients with Crohn’s perianal fistulas: results from a global burden of illness study

2022· article· en· W4206978172 on OpenAlexaffabout
Chitra Karki, AmitaUmesh Athavale, Gary Hantsbarger, K Lee, Snježana Miličević, Milos Perovic, Leanne Raven, M Sajak-Szczerba, Phil Tozer

Bibliographic record

VenueJournal of Crohn s and Colitis · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsCrohn's and Colitis Canada
Fundersnot available
KeywordsMedicineCohortPsychological interventionQuality of life (healthcare)Crohn's diseaseInternal medicineCohort studyDiseasePhysical therapyPsychiatryNursing

Abstract

fetched live from OpenAlex

Abstract Background Perianal fistulas (PAF) are a common complication of Crohn’s disease (CD) and patients with Crohn’s perianal fistulas (CPF) experience low health-related quality of life and a higher burden of symptoms than patients with CD without PAF (non-PAF CD). Treatment options for PAF, including medical and surgical interventions, are associated with high rates of relapse or failure. This global study assessed the burden of illness in patients with CPF compared with patients with non-PAF CD. Here, we present data on patient satisfaction with currently available PAF treatments and the attributes that drive treatment choice for patients with CPF. Methods This cross-sectional study was conducted in seven countries (France, Germany, Spain, UK, Canada, Australia and Japan) in patients aged ≥21 and ≤90 years with self-reported physician-diagnosed CD. Patients were classified as non-PAF CD (cohort 1) or CPF without PAF-related surgery (cohort 2) or CPF with PAF-related surgery (cohort 3). Using a web-enabled questionnaire, patient satisfaction with current PAF treatment options was recorded using a 1–9 scale and relative treatment attribute preferences were assessed via a discrete choice experiment (DCE) that included six attributes (Figure 1). Patients evaluated two treatment profiles at a time (“choice tasks”) to identify their most preferred treatment of the choices available. Data were analysed using descriptive statistics. Results A total of 929 patients were recruited, 620 with non-PAF CD and 309 with CPF. Of those with CPF (cohort 2, n=174; cohort 3, n=135), 68% were male, 65% were aged 21–40 years and 83% were currently taking CD-related medication. The median number of PAF was the same in cohorts 2 and 3 (both 2.0), although cohort 3 had a higher proportion of patients with active PAF (119/135 [88%]) compared with cohort 2 (136/174 [78%]; p =0.022). In cohort 3, 105/135 (78%) patients had ≥3 PAF-related procedures/surgeries, and ≥1 and >3 post-operative complications were experienced by 117/135 (87%) and 34/135 (25%) patients, respectively. Mean satisfaction scores were moderate for the majority of PAF treatment options and similar in both cohorts (range 6.2–6.9), although cohort 3 had significantly less satisfaction with long-term seton placement than cohort 2 (6.2 vs 6.7, respectively; p =0.035). Among the tested attributes, post-operative discomfort and fistula healing rate were the most important attributes influencing treatment choice (Figure 1). Conclusion In this study, patients with CPF had moderate satisfaction with PAF treatment options, regardless of surgical intervention. The DCE demonstrated that patients preferred interventions with better healing rates and lower post-operative discomfort compared to other attributes tested.

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)0.008
metaresearch head score (Gemma)0.009
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.150
GPT teacher head0.391
Teacher spread0.240 · 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".

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Citations1
Published2022
Admission routes2
Has abstractyes

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