The ClASsification for Psoriatic ARthritis (CASPAR) Criteria – A Retrospective Feasibility, Sensitivity, and Specificity Study: Table 1.
Bibliographic record
Abstract
OBJECTIVE: To evaluate the sensitivity, specificity, and feasibility of the ClASsification criteria for Psoriatic ARthritis (CASPAR) to retrospectively classify an existing research cohort. METHODS: In total, 480 patient records were reviewed from the Royal National Hospital for Rheumatic Diseases Psoriatic Arthritis (PsA) cohort and for 100 consecutive controls with inflammatory arthritis from a general rheumatology clinic. The CASPAR score was modified for retrospective use; both "inflammation" and "current psoriasis" were recorded as present if they had ever been confirmed in the rheumatology clinic. Sensitivity and specificity of the CASPAR criteria were compared with expert clinical diagnosis. RESULTS: A total of 480 database records were identified. Nine sets of records had been lost or destroyed. The diagnoses had changed in 15 cases, which were transferred to the control arm, leaving 456 patients with an expert diagnosis of PsA. Of 115 controls, 96 had rheumatoid arthritis, 5 osteoarthritis, 3 reactive arthritis, 3 seronegative arthritis, 3 undifferentiated arthralgia, 2 ankylosing spondylitis, 1 spondyloarthritis, and 2 systemic sclerosis. Sensitivity (99.7%) and specificity (99.1%) were both high and equivalent to previous reports. Sensitivity remained high even after inclusion of 7 PsA patients with insufficient data to complete the CASPAR assessment (sensitivity 98.2%, specificity 99.1%). The criteria were found to be easy and practical to apply to case records. CONCLUSION: Our study demonstrates that the feasibility, specificity, and sensitivity of the CASPAR are maintained when adapted for retrospective use to classify an established research cohort.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".