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Record W4388637909 · doi:10.1002/ejhf.3090

Association of Neighbourhood-Level Material Deprivation with Adverse Outcomes and Processes of Care Among Patients with Heart Failure in a Single-Payer Healthcare System: A Population-Based Cohort Study

2023· article· en· W4388637909 on OpenAlexafffund
David Bobrowski, Andrew Dorovenis, Husam Abdel‐Qadir, Candace D. McNaughton, Rea Alonzo, Jiming Fang, Peter C. Austin, Jacob A. Udell, Cynthia A. Jackevicius, David A. Alter, Clare Atzema, R. Sacha Bhatia, Gillian L. Booth, Andrew C.T. Ha, Sharon Johnston, Irfan A. Dhalla, Moira K. Kapral, Harlan M. Krumholz, Idan Roifman, Harindra C. Wijeysundera, Dennis T. Ko, Karen Tu, Heather J. Ross, Michael J. Schull, Douglas S. Lee

Bibliographic record

VenueEuropean Journal of Heart Failure · 2023
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsInstitut du Savoir MontfortUniversity of OttawaSt. Michael's HospitalHealth Sciences CentreNorth York General HospitalSunnybrook Health Science CentreInstitute for Clinical Evaluative SciencesUniversity of TorontoUniversity Health NetworkMontfort HospitalWomen's College Hospital
FundersMinistry of Long-Term CareInstitute of Circulatory and Respiratory HealthCanadian Institutes of Health ResearchOntario Ministry of Health and Long-Term CareInstitute for Clinical Evaluative Sciences
KeywordsMedicineHazard ratioInterquartile rangeConfidence intervalProportional hazards modelHeart failurePopulationCohort studyInternal medicineDemographyEmergency medicineEnvironmental health

Abstract

fetched live from OpenAlex

AIM: We studied the association between neighbourhood material deprivation, a metric estimating inability to attain basic material needs, with outcomes and processes of care among incident heart failure patients in a universal healthcare system. METHODS AND RESULTS: In a population-based retrospective study (2007-2019), we examined the association of material deprivation with 1-year all-cause mortality, cause-specific hospitalization, and 90-day processes of care. Using cause-specific hazards regression, we quantified the relative rate of events after multiple covariate adjustment, stratifying by age ≤65 or ≥66 years. Among 395 763 patients (median age 76 [interquartile range 66-84] years, 47% women), there was significant interaction between age and deprivation quintile for mortality/hospitalization outcomes (p ≤ 0.001). Younger residents (age ≤65 years) of the most versus least deprived neighbourhoods had higher hazards of all-cause death (hazard ratio [HR] 1.19, 95% confidence interval [CI] 1.10-1.29]) and cardiovascular hospitalization (HR 1.29 [95% CI 1.19-1.39]). Older individuals (≥66 years) in the most deprived neighbourhoods had significantly higher hazard of death (HR 1.11 [95% CI 1.08-1.14]) and cardiovascular hospitalization (HR 1.13 [95% CI 1.09-1.18]) compared to the least deprived. The magnitude of the association between deprivation and outcomes was amplified in the younger compared to the older age group. More deprived individuals in both age groups had a lower hazard of cardiology visits and advanced cardiac imaging (all p < 0.001), while the most deprived of younger ages were less likely to undergo implantable cardioverter-defibrillator/cardiac resynchronization therapy-pacemaker implantation (p = 0.023), compared to the least deprived. CONCLUSION: Patients with newly-diagnosed heart failure residing in the most deprived neighbourhoods had worse outcomes and reduced access to care than those less deprived.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.234
Teacher spread0.223 · 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

Citations12
Published2023
Admission routes2
Has abstractyes

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