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Record W4248095883 · doi:10.2310/7750.2009.00024

Psoriasis Comorbidities

2009· review· en· W4248095883 on OpenAlexaffabout
Lyn Guenther, Wayne Gulliver

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2009
Typereview
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsMemorial University of NewfoundlandGuenther Dermatology Research Centre
FundersAbbott Laboratories
KeywordsMedicinePsoriasisPsoriatic arthritisComorbidityDepression (economics)Diabetes mellitusMetabolic syndromeDiseaseAnxietyHyperlipidemiaIntensive care medicineDermatologyObesityInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Psoriasis has been associated with a number of behavioral and systemic comorbidities, including psoriatic arthritis, anxiety, depression, obesity, hypertension, diabetes mellitus, hyperlipidemia, metabolic syndrome, smoking, cardiovascular disease, alcoholism, Crohn's disease, lymphoma, and multiple sclerosis. Many of these conditions have a similar immunologic pathogeneses. Canadian and international studies have not only confirmed the presence of these comorbidities but also have demonstrated that patients with psoriasis have a significantly reduced life span. Given that patients with psoriasis are often unaware of their comorbidities, they should be screened for these conditions and treated if required by their dermatologist and/or primary care physician. It is important to keep in mind that the comorbidities and drugs used to treat them have an impact on the choice of antipsoriatic treatment. In addition, comorbidities often preclude the use of traditional systemic agents. Recent studies have demonstrated that patients with preexisting comorbidities can be safely and effectively treated with biologic therapy. Furthermore, literature is evolving to suggest that better control of psoriasis might decrease cardiovascular mortality and prolong life.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.900
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.305
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations77
Published2009
Admission routes2
Has abstractyes

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