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Rural-Urban Disparities in the Management and Outcomes of Atrial Fibrillation in Emergency Departments in Canada

2025· article· en· W4415208880 on OpenAlexaffabout
Mohammed Shurrab, Andrew C.T. Ha, Jason G. Andrade, Christopher C. Cheung, Guy Amit, Allan C. Skanes, Girish M. Nair, Feng Qiu, Olivia Haldenby, Paul Angaran, Damian Redfearn, Ratika Parkash, Jeff S. Healey, Dennis T. Ko

Bibliographic record

VenueCirculation Cardiovascular Quality and Outcomes · 2025
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsSunnybrook Health Science CentreSt. Michael's HospitalHealth Sciences NorthLondon Health Sciences CentrePopulation Health Research InstituteQueen Elizabeth II Health Sciences CentreBC Innovation CouncilNOSM UniversityUniversity of British ColumbiaHamilton Health SciencesUniversity Health NetworkKingston Health Sciences CentreUniversity of OttawaQueen's UniversityInstitute of Health Services and Policy Research
Fundersnot available
KeywordsAtrial fibrillationPsychological interventionEmergency departmentHealth careRural areaMEDLINEManagement of atrial fibrillationDisease management

Abstract

fetched live from OpenAlex

BACKGROUND: In a universal health care system, geographic disparities in atrial fibrillation (AF) outcomes remain poorly understood. This study aimed to evaluate rural-urban differences in clinical outcomes among patients presenting to the emergency department (ED) with AF. METHODS: We conducted a population-based retrospective cohort study of all adults (aged ≥18 years) presenting to an ED in Ontario, Canada, with a primary diagnosis of AF between April 1, 2012, and March 31, 2022. Rural residence was defined as living in a community with a population of ≤10 000. The primary outcome was a composite of all-cause mortality or hospital admission within 1 year; secondary outcomes included the individual components of the primary outcome and all-cause ED visits. Comparisons were adjusted for demographics and baseline comorbidities using inverse probability of treatment weighting. Cox regression was used for end points that included death. RESULTS: Among 104 195 eligible patients, 16 860 (16.2%) resided in rural communities. After inverse probability of treatment weighting, baseline characteristics were well balanced (standardized differences <0.1) as the mean age was 69.4 years in rural and urban groups; 47.2% were women in the rural group versus 47.1% in the urban group. Within 1 year, patients with AF presenting to the ED in rural Ontario had higher rate of all-cause mortality or admission compared with the urban group (34.6% versus 33.5%; hazard ratio, 1.04 [95% CI, 1.01-1.07]), driven primarily by increased hospital admission rates (31.3% versus 29.7%; hazard ratio, 1.06 [95% CI, 1.03-1.09]). ED visit rates were higher in rural patients (63.8% versus 55.3%; hazard ratio, 1.27 [95% CI, 1.25-1.30]), while mortality was similar (9.8% versus 9.9%; hazard ratio, 1.00 [95% CI, 0.95-1.04]). CONCLUSIONS: Despite universal health care coverage, rural-urban disparities in AF outcomes persist. Rural patients with AF had higher acute care utilization compared with urban patients. System interventions are needed to address inequities for rural 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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.043
GPT teacher head0.321
Teacher spread0.278 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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