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Record W3167606689 · doi:10.1093/ecco-jcc/jjab076.243

P116 Development of a new patient-reported outcome measure for patients with complex cryptoglandular fistulas

2021· article· en· W3167606689 on OpenAlexaff
Jeffrey D. McCurdy, Patrick Crooks, Chad Gwaltney, Robert Krupnick, Kathy-Ann Cadogan, Santiago González, Chitra Karki

Bibliographic record

VenueJournal of Crohn s and Colitis · 2021
Typearticle
Languageen
FieldMedicine
TopicAnorectal Disease Treatments and Outcomes
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsDebriefingEmbarrassmentPatient-reported outcomeAnal fistulaQuality of life (healthcare)MedicinePromPhysical therapyPsychologyClinical psychologySurgeryFistulaPsychotherapistNursing

Abstract

fetched live from OpenAlex

Abstract Background Complex cryptoglandular fistulas (CCF) arise from infected anal glands and are often associated with substantial morbidity and healthcare utilization. Standarized patient-reported outcome measures (PROMs) for CCF are lacking. Thus, we aimed to develop a disease-specific PROM to assess the burden of symptoms and their impact on daily life in patients with CCF. Methods To develop a conceptual model, a targeted literature review was conducted to identify symptoms and impacts on daily life associated with CCF. Existing PROMs relating to anal fistulas were also sought. Semi-structured interviews with colorectal surgeons (n=5) assessed clinical perspectives on patient experience of CCF. A draft item pool was developed based on the refined conceptual model and using the Quality of Life in Patients with Anal Fistula Questionnaire as a reference. The tool was refined through concept elicitation interviews on the symptoms and impacts of CCF, and cognitive debriefing on the interpretation, understanding and response to each item. Interviews were conducted until concept saturation was achieved and patient feedback suggested no further refinements were required. Results The literature review identified discharge, pain, faecal incontinence and bleeding as the most prevalent symptoms, and embarrassment as the most prevalent impact on daily life. Results from surgeon interviews were then used to revise the initial conceptual model. Twenty US adults (60% female; mean age, 49 years) with clinically confirmed CCF participated in interviews (four waves of n=5). Patients identified 10 salient symptoms and 11 salient impacts on daily life (salient defined as mention by ≥50% of patients and mean disturbance rating ≥5 on a 10-point scale). The final conceptual model included the main symptoms and treatment-related effects, and impacts on daily life. The draft item pool was refined, resulting in a final PROM consisting of 14 items (covering frequency and severity) relating to symptom domains – discharge, incontinence, pain, irritation, odour, abscess – and 6 items relating to health-related quality of life domains – functional, physical, psychological, social health. The PROM features a 7-day recall period, with responses mostly given on a 5-point verbal rating scale. Cognitive debriefing confirmed that the PROM was clear, easy to understand and relevant to patients’ experiences. Conclusion The 20-item CCF questionnaire (CCFQ-20) is a new PROM that has been developed and tested for content validity, following expert guidance and regulatory best practices. It addresses a comprehensive set of salient symptoms and impacts experienced by patients with CCF. Psychometric testing is required to fully evaluate this PROM. Sponsor: Takeda Pharmaceuticals USA, Inc.

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)0.017
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.043
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0040.003
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.035
GPT teacher head0.281
Teacher spread0.246 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2021
Admission routes1
Has abstractyes

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