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1601 No increased risk of arrhythmia among patients with systemic lupus erythematosus or rheumatoid arthritis using hydroxychloroquine

2022· article· en· W4313532323 on OpenAlexaffabout
J. Antonio Aviña‐Zubieta, Md. Rashedul Hoque, Na Lü, Narsis Daftarian, Hui Xie

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsSimon Fraser UniversityResearch CanadaUniversity of British Columbia
Fundersnot available
KeywordsMedicineHydroxychloroquineRheumatoid arthritisAtrial fibrillationInternal medicineHazard ratioProportional hazards modelRheumatologyPropensity score matchingDiseaseConfidence interval

Abstract

fetched live from OpenAlex

Background Hydroxychloroquine (HCQ) is a cornerstone medication for the treatment and management of systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and other autoimmune rheumatic diseases. Previous studies have found an association between HCQ use and risk of arrhythmias, however the evidence is limited by small sample sizes and selected populations; additionally, findings have been contradictory. We assessed the risk of arrhythmias among new users of HCQ in newly diagnosed SLE and RA patients. Methods We used administrative health databases from the entire province of British Columbia, Canada covering January 1997 to March 2015 to identify all patients who met the following criteria: 1) incident SLE or RA; 2) no arrhythmic events or use of anti-arrhythmic medications; and 3) no HCQ use prior to the disease index date. Eligible individuals were separated into HCQ initiator and HCQ non-initiator groups, matched 1:1 by propensity scores using baseline confounders of demographics including presence of SLE or RA disease and duration of disease prior to the index date, comorbidities, other medications, and healthcare utilization. Matching was done within the same calendar year to account for a potential secular trend in HCQ use and risk of arrhythmia. The outcomes assessed were any new arrhythmias, atrial fibrillation, abnormal electrocardiogram including prolonged QT syndrome and conduction disorder, and other unspecified arrhythmias during follow-up. Cox proportional hazard models with death as a competing event were used to assess the association of HCQ initiation and the outcomes. Results We identified 11,518 HCQ initiators (863 SLE and 10,655 RA patients, mean ± SD age 55.9 ± 15.1 years, 76.1% female) and 11,518 HCQ non-initiators (879 SLE and 10,639 RA patients, mean ± SD age 56.0 ± 16.2 years, 76.4% female) after 1:1 propensity score matching. Over the mean follow-up of eight years, there were 1,610 and 1,646 incident arrhythmias in the HCQ initiator and non-initiator groups, respectively. The crude incidence rates of arrhythmia were 17.5, and 18.1 per 1,000 person-years, respectively. Cumulative risk of incident arrhythmia remained similar for both groups. (figure 1). Adjusted hazard ratio (aHR) of incident arrhythmia from the Cox proportional hazard model for HCQ initiators was 0.99 (95% CI: 0.92-1.06) compared to non-initiators (table 1). The corresponding aHRs for HCQ initiators in subtypes of arrhythmia – atrial fibrillation, abnormal electrocardiogram, and other unspecified arrhythmias were 0.95 (95% CI: 0.84-1.06), 1.04 (95% CI: 0.87-1.26), and 0.96 (95% CI: 0.86-1.08), respectively. Conclusions There is no increased risk of any type of arrhythmia among new users of HCQ in SLE and RA patients. We believe the results of this large cohort study will add to the confidence with which HCQ can be used in SLE and RA management.

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)0.002
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 score0.057
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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".

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Citations0
Published2022
Admission routes2
Has abstractyes

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