Characteristics associated with poor COVID-19 outcomes in people with psoriasis, psoriatic arthritis and axial spondyloarthritis: data from the COVID-19 PsoProtect and Global Rheumatology Alliance physician-reported registries
Bibliographic record
Abstract
OBJECTIVES: To investigate factors associated with severe COVID-19 in people with psoriasis (PsO), psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA). METHODS: Demographic data, clinical characteristics and COVID-19 outcome severity of adults with PsO, PsA and axSpA were obtained from two international physician-reported registries. A three-point ordinal COVID-19 severity scale was defined: no hospitalisation, hospitalisation (and no death) and death. ORs were estimated using multivariable ordinal logistic regression. RESULTS: Of 5045 cases, 18.3% had PsO, 45.5% PsA and 36.3% axSpA. Most (83.6%) were not hospitalised, 14.6% were hospitalised and 1.8% died. Older age was non-linearly associated with COVID-19 severity. Male sex (OR 1.54, 95% CI 1.30 to 1.83), cardiovascular, respiratory, renal, metabolic and cancer comorbidities (ORs 1.25-2.89), moderate/high disease activity and/or glucocorticoid use (ORs 1.39-2.23, vs remission/low disease activity and no glucocorticoids) were associated with increased odds of severe COVID-19. Later pandemic time periods (ORs 0.42-0.52, vs until 15 June 2020), PsO (OR 0.49, 95% CI 0.37 to 0.65, vs PsA) and baseline exposure to TNFi, IL17i and IL-23i/IL-12+23i (OR 0.57, 95% CI 0.44 to 0.73; OR 0.62, 95% CI 0.45 to 0.87; OR 0.67, 95% CI 0.45 to 0.98; respectively; vs no disease-modifying antirheumatic drug) were associated with reduced odds of severe COVID-19. CONCLUSION: Older age, male sex, comorbidity burden, higher disease activity and glucocorticoid intake were associated with more severe COVID-19. Later pandemic time periods, PsO and exposure to TNFi, IL17i and IL-23i/IL-12+23i were associated with less severe COVID-19. These findings will enable risk stratification and inform management decisions for patients with PsO, PsA and axSpA during COVID-19 waves or similar future respiratory pandemics.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".