Increased Incidence of Critical Illness in Psoriasis
Bibliographic record
Abstract
BACKGROUND: Psoriasis is associated with an increased risk of comorbid disease. Despite the recognition of increased morbidity in psoriasis, the effects on health care utilisation remain incompletely understood. Little is known about the risk of intensive care unit (ICU) admission in persons with psoriasis. OBJECTIVE: To compare the incidence of ICU admission and post-ICU mortality rates in a psoriasis population compared with a matched population without psoriasis. METHODS: Using population-based administrative data from Manitoba, Canada, we identified 40 930 prevalent cases of psoriasis and an age-, sex-, and geographically matched cohort from the general population (n = 150 210). We compared the incidence of ICU admission between populations using incidence rates and Cox regression models adjusted for age, sex, socioeconomic status, and comorbidity and compared mortality after ICU admission. RESULTS: Among incident psoriasis cases (n = 30 150), the cumulative 10-year incidence of ICU admission was 5.6% (95% confidence interval [CI], 5.3%-5.8%), 21% higher than in the matched cohort (incidence rate ratio, 1.21; 95% CI, 1.15-1.27). In the prevalent psoriasis cohort, crude mortality in the ICU was 11.5% (95% CI, 9.9%-13.0%), 32% higher than observed in the matched population admitted to the ICU (8.7%; 95% CI, 8.3%-9.1%). Mortality rates after ICU admission remained elevated at all time points in the psoriasis cohort compared with the matched cohort. CONCLUSION: Psoriasis is associated with an increased risk for ICU admission and with an increased risk of mortality post-ICU admission.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".