The importance of disease associations and concomitant therapy for the long-term management of psoriasis patients
Bibliographic record
Abstract
It is well established that several inflammatory-type conditions, such as arthritis, diabetes, cardiovascular disease, and irritable bowel disease exist comorbidly and at an increased incidence in patients with psoriasis. Psoriasis and other associated diseases are thought to share common inflammatory pathways. Conditions such as these, with similar pathogenic mechanisms involving cytokine dysregulation, are referred to as immune-mediated inflammatory diseases (IMIDs). Considerable evidence for the genetic basis of comorbidities in psoriasis exists. The WHO has reported that the occurrence of chronic diseases, including IMIDs, are a rising global burden. In addition, conditions linked with psoriasis have been associated with increasing rates of considerable morbidity and mortality. The presence of comorbid conditions in psoriasis patients has important implications for clinical management. QoL, direct health care expenditures and pharmacokinetics of concomitant therapies are impacted by the presence of comorbid conditions. For example, methotrexate is contraindicated in hepatic impairment, while patients on cyclosporin should be monitored for kidney function. In addition, some agents, such as beta blockers, lithium, synthetic antimalarial drugs, NSAIDs and tetracycline antibiotics, have been implicated in the initiation or exacerbation of psoriasis. Consequently, collaboration between physicians in different specialties is essential to ensuring that psoriasis treatment benefits the patient without exacerbating associated conditions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".