Cognitive Functions Assessment in Psoriasis Patients: A Crosssectional Study in University Hospital
Bibliographic record
Abstract
Background: Psoriasis is not merely an inflammatory skin disease but is commonly associated with systemic inflammation causing medical and psychiatric comorbidities. Objectives: Psoriasis is not merely an inflammatory skin disease but is commonly associated with systemic inflammation causing medical and psychiatric comorbidities. Methods: 100 psoriasis patients, age 80 and sex-matched controls were recruited, dermatological and psychiatric assessments were done, psoriasis severity was assessed using the Psoriasis Area and Severity Index (PASI) score. Montreal Cognitive Assessment-Basic (MoCA-B) was used to assess the different cognitive domains and to screen for any possible MCI. Results: Cognitive functions were significantly worse in patients than in the healthy controls for the total score of MOCA-B (p <0.001), abstraction (p <0.001), delayed recall (p <0.001), visuospatial abilities (p= 0.013), naming (p=0.029) and attention (p <0.001). MCI was detected by the Arabic version of MoCA-B with a cut-off score of 21/22, and it was more in the psoriasis group (16 %) than in the controls (4%). No correlations were observed between disease characteristics (Psoriasis duration in months, PASI, BSA%,) and the MoCA scores in psoriasis patients. Conclusion: Psoriasis patients showed worse cognitive impairment when compared to the controls regardless of the psoriasis severity. Thus, the routine clinical examination of psoriasis patients should include the administration of a brief cognitive screening tool to reach the best management.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".