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Record W2167545838 · doi:10.2174/1871523011312010009

Biologics and the Cardiovascular System: A Double-Edged Sword

2013· review· en· W2167545838 on OpenAlexaff
C. Roubille, Johanne Martel‐Pelletier, Boulos Haraoui, Jean‐Claude Tardif, Jean‐Pierre Pelletier

Bibliographic record

VenueAnti-Inflammatory & Anti-Allergy Agents in Medicinal Chemistry · 2013
Typereview
Languageen
FieldImmunology and Microbiology
TopicAtherosclerosis and Cardiovascular Diseases
Canadian institutionsUniversité de MontréalHôpital Notre-Dame
Fundersnot available
KeywordsSWORDMedicineCardiologyInternal medicineComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Patients with chronic inflammatory diseases such as rheumatoid arthritis have a higher risk of cardiovascular diseases and related mortality compared to the general population. This risk is first due to classical cardiovascular risk factors but also due to systemic inflammation which is independently involved, causing accelerated atherosclerosis, myocardial infarction, cerebrovascular disease and heart failure (HF). Pro-inflammatory cytokines such as tumor necrosis factor-alpha (TNF-alpha), interleukin (IL)-1 and IL-6 could be major actors on this pathophysiology. Biologics are effective specific treatments in the management of inflammatory rheumatic and systemic diseases. In this review, beneficial and deleterious effects on the heart and vessels of the biologics used in the management of inflammatory arthritis and vasculitides will be discussed, focusing on TNF-alpha, IL-6 and IL-1 blockades, and anti-CD20. Noninflammatory cardiac conditions, such as heart failure, myocardial infarction, and cardiovascular conditions such as atherosclerosis, as well as inflammatory diseases including vasculitides will be discussed.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.002
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 head0.036
GPT teacher head0.267
Teacher spread0.231 · 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

Citations24
Published2013
Admission routes1
Has abstractyes

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