Clinical characteristics and outcomes of patients with COVID‐19 and psoriasis
Bibliographic record
Abstract
To summarize the clinical characteristics and explore the role of treatment types in outcomes among psoriasis patients with coronavirus disease 2019 (COVID-19). The principal summary measures were pooled prevalence and risk ratio (RR) with 95% confidential interval (CI). R statistic software was used for all the analysis. A total of 19 studies including 4073 psoriasis patients with COVID-19 were eligible for the meta-analysis. The overall hospitalization rate is about 20.2% (95% CI: 12.7%-28.7%), and changed to be 18.0% (95% CI: 9.9%-27.6%) or 14.1% (95% CI: 5.9%-24.6%) after systemic or biologic treatment. Moreover, the overall fatality rate is 1.5% (95% CI: 0.4%-3.0%), and turned to be 0.7% (95% CI: 0%-2.0%) or 0.5% (95% CI: 0%-2.2%) after systemic or biologic therapy. Notably, a lower hospitalization RR was found in patients receiving biologic therapy than those receiving other treatments (RR = 0.62, 95% CI: 0.42-0.94). The results were consistent after sensitivity analysis and trim-and-fill analysis. Systemic, especially biologic therapy could lessen the clinical severity in psoriasis patients with COVID-19. Our finding will help to guide current recommendations and provide a reference for clinical decision-making.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.010 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".