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Abstract 16821: Impact of Patient Transfers on Outcome Evaluations Following Acute Myocardial Infarction

2014· article· en· W2244047448 on OpenAlexaffabout
Melissa Pak, Mona Izadnegahdar, May K. Lee, Min Gao, Karin H. Humphries

Bibliographic record

VenueCirculation · 2014
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsProvidence Health CareUniversity of British Columbia
Fundersnot available
KeywordsMedicineMyocardial infarctionLogistic regressionMortality rateDemographyEmergency medicineAcute carePediatricsHealth careInternal medicine

Abstract

fetched live from OpenAlex

Introduction: Patients hospitalized for an AMI are commonly transferred to tertiary care facilities to receive advanced procedures. In the United States, transferred patients are often excluded from outcome evaluations due to limitations in ascertaining outcomes. In Canada, centralized administrative and clinical databases allow for linkage of outcomes across institutions. This study evaluated the influence of excluding transferred AMI patients on estimates of age and sex-specific 30-day mortality rates over a 10-year period. Methods: All incident AMI hospitalizations (ICD-9: 410 and ICD-10: I21, I22) to acute care hospitals in British Columbia from 2000 to 2009 were identified through the Discharge Abstract Database and linked to mortality through the Vital Statistics registry. A transfer was identified as a discharge from the index AMI admission hospital to another hospital. Thirty-day mortality was defined as any death within 30 days of the index hospitalization. A logistic regression model was used to compare transfer rate by age (20-55, 56-64, 65-74 and ≥ 75 years), sex and admission year. Thirty-day mortality rates by sex and age were calculated with and without transferred patients. Results: Of the 67,444 AMI hospitalizations identified, 38.6% involved at least one transfer. Overall, younger patients were more likely to be transferred. Transfer rates increased over time in all age groups but with different slopes (p = 0.02) regardless of sex, and differed significantly between sexes only in those ≥ 75 (p < 0.001; Fig. A). Thirty-day mortality rates were overestimated in each age-sex category when transferred patients were excluded, compared to rates that included all patients, irrespective of transfer status (Fig. B). Conclusions: The rate of patient transfers post AMI has increased over time. Excluding transferred patients results in overestimates of 30-day mortality, and thus impacts outcome assessments. This impact is expected to increase over time.

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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)0.012
metaresearch head score (Gemma)0.064
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 score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.064
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.063
GPT teacher head0.458
Teacher spread0.395 · 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
Published2014
Admission routes2
Has abstractyes

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