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O8 Performance of the EULAR/ACR 2019 classification criteria for systemic lupus erythematosus in men, ethnicities, and early disease

2020· article· en· W3013401396 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOral Presentations · 2020
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity Health NetworkMount Sinai HospitalUniversity of CalgaryToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineCohortSystemic lupus erythematosusInternal medicineGold standard (test)Ethnic groupDisease

Abstract

fetched live from OpenAlex

<h3>Background</h3> Supported by both the ACR and EULAR, the EULAR/ACR 2019 Classification Criteria for SLE employ positive ANA (ever) as an entry criterion and use a weighted scheme with values ranging from 2 to 10, for a classification cut-off of 10. Criteria items are attributed to SLE only if there is no more likely alternative diagnosis in the individual patients. Items are organized in domains, and only the highest ranking item within a domain is counted. These criteria have been validated in a cohort of 696 SLE patients and 574 non-SLE patients from a total of 21 centers, reaching an overall sensitivity of 96.1% and a specificity of 93.4%. To at least estimate the performance in groups underrepresented in the validation cohort of this transatlantic project, we analyzed this cohort for patient subsets with regard to sex, ethnicity, and disease duration. <h3>Methods</h3> The full EULAR/ACR 2019 classification criteria validation cohort was analyzed for female (n=1,098) and male (n=172) patients, Asian (n=118), Black (n=68), Hispanic (n=124) and White (n=941) patients, and patients with an SLE duration of less than 1 year (n=34), one to less than 3 years (n=196), 3 to less than 5 years (n=157), and 5 or more years (n=879). Sensitivity and specificity were calculated for the EULAR/ACR 2019 criteria, the SLICC 2012 criteria and the ACR 1997 criteria each. <h3>Results</h3> As shown in table 1, most of the point estimates for sensitivity and specificity in subsets lay within the 95% confidence intervals of the sensitivity and specificity of the EULAR/ACR 2019 criteria validation. In particular, sensitivity and specificity for all ethnic groups were within the confidence intervals or even higher. Formally, the sensitivity was slightly lower for male patients, corresponding to a higher specificity, but the male 95% confidence intervals (0.86–0.98 for sensitivity, 0.90–0.99 for specificity) overlapped. While sensitivity appeared independent of disease duration from year 1 on, sensitivity was only 89% in the first year of disease, identical to the SLICC criteria (89%) and numerically higher than the ACR criteria (56%), but all confidence intervals overlapped. <h3>Conclusion</h3> While not all subgroups of SLE patients in the validation cohort are of adequate size to fully explore the sensitivity and specificity of the EULAR/ACR 2019 SLE classification criteria in the respective subsets, the point estimates of sensitivity and specificity suggest that the new criteria perform at least reasonably well in all ethnic groups, in men and in early disease. Nevertheless, sensitivity and specificity should be independently validated in larger groups of Asian, Black and Hispanic patients, male patients and in early 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.

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)0.000
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 score0.113
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.074
GPT teacher head0.350
Teacher spread0.277 · 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