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Record W4388462407 · doi:10.1002/acr.25270

Evaluation of the Diagnostic Performance of American College of Rheumatology, EULAR, and National Institute for Health and Clinical Excellence Criteria Against Clinically Relevant Knee Osteoarthritis: Data From the CHECK Cohort

2023· article· en· W4388462407 on OpenAlexfundno aff
Qiuke Wang, J. Runhaar, M. Kloppenburg, Maarten Boers, J. W. J. Bijlsma, Sita Bierma‐Zeinstra

Bibliographic record

VenueArthritis Care & Research · 2023
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersChina Scholarship CouncilArthritis SocietyKiniksa PharmaceuticalsGlaxoSmithKlineDutch Arthritis SocietyPfizer
KeywordsMedicineNiceOsteoarthritisCohortRheumatologyInternal medicinePhysical therapyMedical diagnosisPathologyAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Our objective was to evaluate the diagnostic performance of the EULAR, American College of Rheumatology (ACR), and National Institute for Health and Care Excellence (NICE) criteria by using clinical experts' diagnosis of clinically relevant knee osteoarthritis (OA) as the outcome of interest. METHODS: In a previous study, we recruited clinical experts to evaluate longitudinal (5-, 8-, and 10-year follow-up) clinical and radiographic data of symptomatic knees from the Cohort Hip and Cohort Knee (CHECK) study for the presence or absence of clinically relevant OA. In the current study, ACR, EULAR, and NICE criteria were applied to the same 5-, 8-, and 10-year follow-up data; then a knee was diagnosed with OA if fulfilling the criteria at one of the three time points (F1), two of the time points (F2), or at all three time points (F3). Using clinically relevant OA as the reference standard, the sensitivity, specificity, and positive and negative predictive values for the three criteria were assessed. RESULTS: A total of 539 participants for a total of 833 examined knees were included. Thirty-six percent of knees were diagnosed with clinically relevant OA by experts. Sixty-seven percent to 74% of the knees received the same diagnosis (OA or non-OA) by the three criteria sets for the different definitions (F1 to F3). EULAR consistently (F1 through F3) had the highest specificity, and NICE consistently had the highest sensitivity. CONCLUSION: The diagnoses only moderately overlapped among the three criteria sets. The EULAR criteria seemed to be more suitable for study enrollment (when aimed at recruiting clinically relevant OA knees), given the highest specificities. The NICE criteria, given the highest sensitivities, could be more useful for an initial diagnosis in clinical practice.

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)0.014
metaresearch head score (Gemma)0.029
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 score0.014
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.128
GPT teacher head0.450
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 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".

Quick stats

Citations29
Published2023
Admission routes1
Has abstractyes

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