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Record W2463397294 · doi:10.1177/1203475416658004

Psoriasis Patients Treated With Biologics and Methotrexate Have a Reduced Rate of Myocardial Infarction

2016· article· en· W2463397294 on OpenAlexaff
Wayne Gulliver, Heather M. Young, H. Bachelez, Shane Randell, Susanne Gulliver, Nawaf Al-Mutairi

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedicinePsoriasisMyocardial infarctionMethotrexateIncidence (geometry)ComorbidityPopulationInternal medicinePsoriatic arthritisDermatology

Abstract

fetched live from OpenAlex

Psoriasis is a chronic inflammatory skin condition characterised by the formation of red scaly plaques on the skin. It is an autoimmune disease cause by the dysregulation of cytokines controlling the inflammatory pathways, a mechanism likely contributing to various comorbidities observed in patients with psoriasis. Cardiovascular disease is one comorbidity observed more frequently in the psoriasis patient population. Biologic treatments specifically target the dysregulation of cytokines in the inflammation pathway and have shown to be an effective treatment for moderate to severe psoriasis where other systemic treatments have failed. More recently, biologics have been shown to reduce the incidence of myocardial infarction in patients with psoriasis compared to patients treated with topical agents. In the present study, 4 international psoriasis patient cohorts are combined and analyzed to examine the effect that biologic or methotrexate treatment has on reducing the incidence of myocardial infarction. Both methotrexate and biologic treatments were found to lower the incidence of myocardial infarction in moderate to severe psoriasis patient populations.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.239
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations16
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cutaneous Medicine and SurgerySame topicPsoriasis: Treatment and PathogenesisFrench-language works237,207