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Record W4402667013 · doi:10.1097/ju.0000000000004242

A Patient-Prioritized Research Agenda for Clinical Trials in Kidney Stone Disease

2024· article· en· W4402667013 on OpenAlexaff
Jonathan S. Ellison, Kathryn E. Flynn, Katherine Sheridan, Samantha Siodlarz, Jodi Antonelli, Christopher E. Bayne, Hunter Beck, Christina B. Ching, Pankaj Dangle, Casey A. Dauw, Carley Davis, Kim Hollander, Dirk Lange, Kristi Ouimet, Carswell Ouimet, Amy Pan, Kristina L. Penniston, Charles D. Scales, Nayan Shah, Ryan Spiardi, Necole M. Streeper, Kristin Whitmore, Mike Witt, Liyun Zhang, Gregory E. Tasian

Bibliographic record

VenueThe Journal of Urology · 2024
Typearticle
Languageen
FieldMedicine
TopicKidney Stones and Urolithiasis Treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineClinical trialIntensive care medicineKidney diseaseKidney stonesSurgeryInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: To ensure that research on kidney stones provides meaningful impact for the kidney stone community, patients and caregivers should be engaged as stakeholders in clinical trial design, starting at study inception. This project aimed to elicit, refine, and prioritize research ideas from kidney stone stakeholders to develop a patient-centered research agenda for clinical trials. MATERIALS AND METHODS: The Kidney Stone Engagement Core, a group of patients, caregivers, advocates, clinicians, and researchers, executed an iterative process of surveys and focus groups to elicit and refine research themes, which were then translated into research questions. A separate group of patients, caregivers, and clinicians prioritized these questions through parallel modified Delphi and crowdsourced digital platforms. A research agenda was developed by the Kidney Stone Engagement Core based on the highest rated questions during a hybrid virtual/in-person capstone session. RESULTS: A total of 70 individuals (57 patients and caregivers, 13 researchers and clinicians) participated in the elicitation, 20 individuals (15 patients and caregivers, 5 researchers and clinicians) participated in refinement, and an additional 80 individuals (81 patients and caregivers, 9 researchers and clinicians) participated in prioritization. Key novel themes emerged from elicitation and refinement: ureteral stents, genetic evaluation, shared surgical decision-making, key subgroups, cumulative disease burden, genetic evaluation, and psychosocial support. Stakeholders generated 6 proposed trials from these themes focused on surveillance, surgical intervention, and medical prevention. CONCLUSIONS: Patients and caregivers valued comparative effectiveness kidney stone research that focused on individualized care, shared decision-making, and improvement of patient-reported experiences. This process provided actionable recommendations for future patient-centered clinical trials within kidney stone disease.

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)0.599
metaresearch head score (Gemma)0.443
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.599
Threshold uncertainty score0.495

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5990.443
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0050.004
Science and technology studies0.0200.024
Scholarly communication0.0310.031
Open science0.0070.042
Research integrity0.0240.033
Insufficient payload (model declined to judge)0.0090.003

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 head0.307
GPT teacher head0.540
Teacher spread0.233 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2024
Admission routes1
Has abstractyes

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