Diagnostic Delay in Psoriatic Arthritis: A Population-based Study
Bibliographic record
Abstract
OBJECTIVE: To examine demographic and clinical characteristics associated with diagnostic delay in psoriatic arthritis (PsA). METHODS: We characterized a retrospective, population-based cohort of incident adult (≥ 18 yrs) patients with PsA from Olmsted County, Minnesota, from 2000-2017. All patients met the classification criteria. Diagnostic delay was defined as the time from any patient-reported PsA-related joint symptom to a physician diagnosis of PsA. Factors associated with delay in PsA diagnosis were identified through logistic regression models. RESULTS: Of the 164 incident PsA cases from 2000 to 2017, 162 had a physician or rheumatologist diagnosis. Mean (SD) age was 41.5 (12.6) years and 46% were female. Median time from symptom onset to physician diagnosis was 2.5 years (IQR 0.5-7.3). By 6 months, 38 (23%) received a diagnosis of PsA, 56 (35%) by 1 year, and 73 (45%) by 2 years after symptom onset. No significant trend in diagnostic delay was observed over calendar time. Earlier age at onset of PsA symptoms, higher BMI, and enthesitis were associated with a diagnostic delay of > 2 years, whereas sebopsoriasis was associated with a lower likelihood of delay. CONCLUSION: In our study, more than half of PsA patients had a diagnostic delay of > 2 years, and no significant improvement in time to diagnosis was noted between 2000 and 2017. Patients with younger age at PsA symptom onset, higher BMI, or enthesitis before diagnosis were more likely to have a diagnostic delay of > 2 years, whereas patients with sebopsoriasis were less likely to have a diagnostic delay.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".