Mortality trends in a Cohort of Canadian Psoriatic Arthritis Patients
Bibliographic record
Abstract
Methods: We reviewed retrospectively the charts of psoriatic arthritis patients who died from 1995-2010.We included 13 deceased patients with a psoriatic arthritis di-agnosis and compared them with 140 patients living with psoriatic arthritis that at-tend the same clinic. The population was derived from a single academic rheumatol-ogist’s practice in St. John’s, Newfoundland, Canada. Patients are seen at six-month intervals with a history and physical exam performed at each visit. Laboratory data was collected at each visit. Diagnosis of psoriatic arthritis is based on the CASPAR Classifcation and Diagnostic Criteria for Psoriatic Arthritis. Results: The mean age of the 13 deceased patients was 62.9 years. Of these, 38.5% were female and 85.7% had an erythrocyte sedimentation rate greater than 15 mm/hour vs. 36.4% of patients living with psoriatic arthritis. Of deceased patients, 16%had dystrophic nail changes of vs. 59.6% of living patients. Health Assessment Questionnaire was found to show a signifcantly greater loss in function in deceasedpatients. (1.39 vs. 0.70, p= 0.002). Almost half of the deceased patients had used Prednisone (46.2%) as opposed to 11.2% of living patients. Conclusions: We realize that this study employs a small sample size. Increased ESR and Health Assessment Questionnaire score were found to be associated with mor-tality in psoriatic arthritis patients. Dystrophic nail changes were found to be pro-tective for psoriatic arthritis 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".