Dermatology position paper on the revision of the 1982 ACR criteria for systemic lupus erythematosus
Bibliographic record
Abstract
The 1982 ACR classification criteria have become de facto diagnostic criteria for systemic lupus erythematosus (SLE), but a review of the criteria is necessary to include recent diagnostic tests. The criteria were not developed with the help of dermatologists, and assign too much weight to the skin as one expression of a multiorgan disease. Consequently, patients with skin diseases are classified as SLE based mostly on skin symptoms. We discuss specific problems with each dermatologic criterion, but changes must await a new study. We suggest the following guidelines for such a study, aimed at revision of the criteria. 1) The SLE patient group should be recruited in part by dermatologists. 2) The study should evaluate an appropriate international ethnic/racial mix, including late onset SLE as well as pediatric patients. 3) All patients should have current laboratory and clinical evaluations, as suggested in the paper, to assure the criteria can be up-to-date. This includes anti-SS-A and anti-SS-B antibodies and skin biopsies for suspected cutaneous lupus erythematosus except for nonscarring alopecia and oral ulcers. 4) The study should be based on a series of transparent power calculations. 5) The control groups should represent relevant differential diagnoses in numbers large enough to assess diagnostic problems that might be specific to these differential diagnoses. In order to demonstrate specificity of the criteria with a 95% confidence interval between 90 and 100%, each control group of the above should have at least 73 patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.020 | 0.017 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".