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Record W2117227819 · doi:10.1136/thoraxjnl-2011-201454

Comparing the American and European diagnostic guidelines for cystic fibrosis: same disease, different language?

2012· article· en· W2117227819 on OpenAlexafffund
Chee Y. Ooi, Annie Dupuis, Lynda Ellis, Keith Jarvi, Sheelagh Martin, Tanja Gonska, Ruslan Dorfman, Paul Kortan, Melinda Solomon, Elizabeth Tullis, Peter R. Durie

Bibliographic record

VenueThorax · 2012
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsSt. Michael's HospitalMount Sinai HospitalSickKids FoundationUniversity of TorontoPublic Health OntarioHospital for Sick ChildrenInstitute for Clinical Evaluative Sciences
FundersCanadian Institutes of Health Research
KeywordsConcordanceMedicineCystic fibrosisGuidelineObstructive azoospermiaGenotypingInternal medicineDiseaseSweat testPediatricsPathologyAzoospermiaGenotype

Abstract

fetched live from OpenAlex

BACKGROUND: The American and European cystic fibrosis (CF) guidelines recommend different diagnostic criteria. This study assessed diagnostic concordance between these recommendations. METHODS: Subjects with single organ manifestations suggestive of CF (chronic sinopulmonary disease (RESP), chronic/recurrent pancreatitis (PANC) or obstructive azoospermia (AZOOSP)) were prospectively evaluated by sweat test, nasal potential difference and genotyping. Concordance in diagnostic outcomes between the two algorithms was measured using observed agreement and κ statistics. RESULTS: A total of 208 subjects were evaluated. Observed agreement was 84.8% and level of agreement was excellent (κ=0.87) between the American and European recommendations. The RESP phenotype was associated with the highest degree of concordance (observed agreement ≥90%, κ=0.92) compared with the PANC (observed agreement 86%, κ=0.65) and AZOOSP (observed agreement 80%, κ=0.87) phenotypes. Incorporation of nasal potential difference into the American algorithm failed to improve the overall degree of concordance (good agreement level; κ=0.75); the level of agreement was unchanged in RESP and PANC subjects, but reduced in AZOOSP subjects (from excellent to good). Extensive genotyping had limited clinical utility in the diagnosis of CF in both algorithms. CONCLUSIONS: Despite inconsistencies between the American and European diagnostic recommendations, concordance in diagnostic outcomes among subjects presenting with single organ manifestations of CF was good to excellent. These diagnostic guidelines provide guidance and promote rigorous evaluation for the diagnosis of CF but neither guideline should be regarded as dogma.

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)0.000
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation 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 score0.181
Threshold uncertainty score0.677

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
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 head0.066
GPT teacher head0.388
Teacher spread0.322 · 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 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".

Quick stats

Citations50
Published2012
Admission routes2
Has abstractyes

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