Epidemiology of Hypertension in Psoriasis: An Analysis of Trends from 2006 to 2023
Bibliographic record
Abstract
Background: Psoriasis and hypertension (HTN) are known to be closely related. However, at present, no study has systematically examined the epidemiology of this disease pattern on a global scale. Methods: We examined six databases from their inception until November 1, 2023 and used the Agency for Healthcare Research and Quality and the Newcastle-Ottawa Scale to assess the quality of observational studies. Data analysis was conducted in R. Meta-regression, sensitivity, and subgroup analyses were used to evaluate interstudy heterogeneity. Egger's test and funnel plots were used to evaluate publication bias. Results: We reviewed 200 studies involving 15,010,888 patients. The overall prevalence of HTN among the patients with psoriasis was 32.22%. Overall, South America had the highest prevalence of hypertension among adult patients with psoriasis (52.36%), the three countries with the highest prevalence were Serbia, Singapore and Brazil. The prevalence of mild and severe psoriasis comorbid with HTN was 31.71% [95% CI: 24.40-40.05%] and 33.19% [95% CI: 27.17-39.81%], respectively. The prevalence of HTN in psoriasis vulgaris was 29.71% [95% CI: 25.10-35.15%], while that in psoriatic arthritis was 34.54% [95% CI: 31.27-38.14%]. Conclusion: Patients with psoriatic arthritis are more predisposed to requiring hypertension risk screening than patients with psoriasis vulgaris. More population-based prospective observational studies are required to elucidate the mechanisms underlying the coexistence of hypertension in patients with psoriasis.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".