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Record W3082087942 · doi:10.1177/2054358120948294

A Provincial Survey of the Contemporary Management of Autosomal Dominant Polycystic Kidney Disease

2020· article· en· W3082087942 on OpenAlexaffabout
Tae Won Yi, Adeera Levin, Micheli Bevilacqua, Mark Canney

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineAutosomal dominant polycystic kidney diseaseTolvaptanPolycystic kidney diseaseDiseaseKidney diseaseBlood pressureNephrologyInternal medicineFamily medicineIntensive care medicineHeart failure

Abstract

fetched live from OpenAlex

BACKGROUND: Recent years have witnessed an encouraging expansion of knowledge and management tools in the care of patients with autosomal dominant polycystic kidney disease (ADPKD), including measurement of total kidney volume as a biomarker of disease progression, stringent blood pressure targets to slow cyst growth, and targeted treatments such as tolvaptan. OBJECTIVES: We sought to evaluate clinicians' familiarity with, and usage of, novel evidence-based management tools for ADPKD. DESIGN: On-line survey. SETTING: British Columbia, Canada. PARTICIPANTS: Nephrologists in academic and community practice (excluding clinicians who practice exclusively in transplantation). MEASUREMENTS: Participants answered multiple-choice questions in 6 domains: sources of information, self-identified needs for optimal care delivery, prognostication, imaging tests, blood pressure targets, and use of tolvaptan. METHODS: An online survey was developed and disseminated via email to 65 nephrologists engaged in current clinical practice in British Columbia. RESULTS: A total of 29 nephrologists (45%) completed the questionnaire. The most popular source of information was the primary literature (83% of respondents). While 86% of respondents reported assessing the risk of disease progression before the onset of kidney function decline, most were using traditional metrics such as blood pressure and proteinuria rather than validated prediction tools such as the Mayo Classification. Although 90% of respondents obtained additional imaging after diagnosis in some or all of their ADPKD patients, only 1 in 5 reported being confident in their ability to interpret kidney size. The recommended blood pressure (BP) target of <110/75 mmHg was sought by 17% of respondents. All respondents reported being familiar with the literature regarding tolvaptan; however, only half were confident in their ability to identify suitable patients for treatment. The top 3 needs identified by clinicians were better access to medications (69%), clear management protocols (66%), and easier access to imaging tests (59%). LIMITATIONS: Funding mechanisms for tolvaptan can vary; therefore, clinicians' experience with the drug may not be generalizable. Although the response rate was acceptable, the survey is nonetheless subject to responder bias. CONCLUSION: This survey indicates that there is substantial variability in the usage of, and familiarity with, evidence-based ADPKD management tools among contemporary nephrologists, contributing to incomplete translation of evidence into clinical practice. Providing greater access to tolvaptan or imaging tests is unlikely to improve patient care without enhancing knowledge translation and education. TRIAL REGISTRATION: Not applicable as this was a survey.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.018
GPT teacher head0.245
Teacher spread0.226 · 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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Citations2
Published2020
Admission routes2
Has abstractyes

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