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Record W3114715148 · doi:10.7759/cureus.12246

Risk of Major Adverse Cardiovascular Events in Patients With Rheumatoid Arthritis

2020· article· en· W3114715148 on OpenAlexaff
Kheraj Mal, Ratan Kumar, Farah Mansoor, Navneet Kaur, Anil Kumar, Sidra Memon, Amber Rizwan

Bibliographic record

VenueCureus · 2020
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsMedicineRheumatoid arthritisInternal medicineOdds ratioArthritisMyocardial infarctionPopulationAdverse effectPhysical therapy

Abstract

fetched live from OpenAlex

Introduction Rheumatoid arthritis is a chronic, inflammatory, and multisystem disease, which, along with the joints, can involve the cardiovascular system. The treatment of rheumatoid arthritis or rheumatoid arthritis itself can lead to atherosclerosis, which is considered one of the major causes by which it can affect the cardiovascular system. In this study, we will assess the risk of cardiovascular events in patients with rheumatoid arthritis as compared to the general population. Method This case-control study was conducted from January 2018 to November 2018. Two-hundred twenty-two (222) patients with diagnosed rheumatoid arthritis were included as cases in the study. Two-hundred eleven (211) patients were included in the study as the control group (patients without rheumatoid arthritis). All the data were recorded in a self-structured questionnaire. Result Participants with rheumatoid arthritis also showed an increased risk of myocardial infarction (MI) by an odds ratio of 2.50 (95% CI; 0.77-8.14). There was also an increased risk of cardiovascular death in participants with rheumatoid arthritis by an odds ratio of 1.99 (0.58-6.71). Conclusion The study suggests that rheumatoid arthritis along with joint inflammation can also affect the cardiovascular system. Hence, a multidisciplinary team of rheumatologists and cardiologists should manage patients suffering from rheumatoid arthritis, which will improve morbidity and mortality in such patients.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.015
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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.

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

Citations10
Published2020
Admission routes1
Has abstractyes

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