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Record W2510393272 · doi:10.1159/000446664

International Multi-Specialty Delphi Survey: Identification of Diagnostic Criteria for Hepatic and Renal Cyst Infection

2016· article· en· W2510393272 on OpenAlexaff
Marten A. Lantinga, Alexander J.m. Darding, Ruud G.L. de Sévaux, Ahsan Alam, Chantal P. Bleeker‐Rovers, Mickaël Bobot, Émilie Cornec-Le Gall, Tom J.G. Gevers, Ziad Hassoun, Esther Meijer, Michal Mrug, Frederik Nevens, Luiz F. Onuchic, York Pei, Giorgina Barbara Piccoli, Yves Pirson, Gopala K. Rangan, Roser Torrá, Folkert W. Visser, François Jouret, Nada Kanaan, Wim J.G. Oyen, Tatsuya Suwabe, Vicente E. Torres, Joost P.H. Drenth

Bibliographic record

Venue˜The œNephron journals/Nephron journals · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsUniversity of TorontoMcGill University Health Centre
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesRadboud Universitair Medisch Centrum
KeywordsMedicineSpecialtyInternal medicineHelpfulnessCystFamily medicineDelphi methodGastroenterologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Cyst infection is one of the complications of autosomal dominant polycystic kidney disease and polycystic liver disease. The diagnosis is typically made on a mix of clinical, laboratory and imaging abnormalities but the importance of individual items is uncertain. We aimed to perform a Delphi survey amongst physicians to achieve consensus on diagnostic criteria. METHODS: We retrieved diagnostic items from the literature and conducted physician and patient interviews. All items were combined to create the online questionnaire. Participants rated each item during 3 consecutive rounds. Items were rated for diagnostic helpfulness for hepatic and renal cyst infection on a 9-point scale with anchors, from extremely unimportant (n = 1) to extremely important (n = 9). We determined consensus with the disagreement index. The median rating of each item was calculated and categorized into inappropriate (≤3.4), uncertain (3.5-6.4) or appropriate (≥6.5). By combining all items that reached an appropriate consensus rating, we developed a diagnostic algorithm based on expert consensus. RESULTS: We invited 58 physicians to participate in the survey. In total, 35 (60%) responded to round 1 of which 91% (n = 32) and 86% (n = 30) responded to round 2 and 3, respectively. The final panel included 23 nephrologists, 5 hepatologists, a nuclear medicine specialist and an infectious disease physician from 11 countries (male 67%, mean age 47 ± 11 years, median clinical experience 21 years). The panel rated the diagnostic helpfulness of 59 potential items. Ultimately, 22 hepatic and 26 renal items were rated appropriate, including positive blood cultures and fluorodeoxyglucose positron-emission CT imaging. Ultrasonography and absence of intracystic bleeding were amongst those deemed uncertain or inappropriate. Subsequently, by combining items rated appropriate, we developed a clinical tool to diagnose hepatic and renal cyst infection. CONCLUSIONS: We identified diagnostic items for hepatic and renal cyst infection and developed an expert-based diagnostic algorithm, which may aid physicians in the diagnostic work-up. A prospective study is necessary to validate this algorithm.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.332
Teacher spread0.298 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations19
Published2016
Admission routes1
Has abstractyes

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