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Record W2015718619 · doi:10.1016/j.ejheart.2008.01.014

Acute Heart Failure in the Emergency Department: Short and Long-Term Outcomes of Elderly Patients with Heart Failure

2008· article· en· W2015718619 on OpenAlexaffabout
Justin A. Ezekowitz, Jeffrey A. Bakal, Padma Kaul, Cynthia M. Westerhout, Paul W. Armstrong

Bibliographic record

VenueEuropean Journal of Heart Failure · 2008
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsCanadian VIGOUR CentreUniversity of Alberta
Fundersnot available
KeywordsMedicineEmergency departmentHeart failureCohortPopulationEmergency medicineRetrospective cohort studyCohort studyInternal medicinePediatrics

Abstract

fetched live from OpenAlex

AIMS: Previous epidemiologic studies of acute heart failure (AHF) have involved patients admitted to hospital and fail to account for that unknown proportion discharged directly from the emergency department (ED). We examined discharge rates, and whether outcomes, including mortality, differed based on admission status in AHF. METHODS AND RESULTS: This population-based cohort included all patients > or =65 years presenting to an Alberta ED with HF (ICD9-CM 428.x; 1998 to 2001). Patients were either not admitted (Not-ADM) or directly admitted to hospital (ADM) and followed for one-year. Of 10,415 AHF patients evaluated in the ED, 35% were Not-ADM whereas 65% were ADM. Thirty days after ED presentation the rates of death, re-ED or initial/re-hospitalisation were 3.3%, 44% and 19% for Not-ADM, and 10.9%, 33% and 21% for the ADM patients, respectively (all p<0.0001). At one-year, the rates of death, re-ED or initial/re-hospitalisation were 20%, 82% and 58% for Not-ADM, and 34%, 72% and 60% for ADM, respectively (all p<0.0001). CONCLUSIONS: One third of AHF patients were not immediately admitted after an ED visit but most present again to the ED, two-thirds were hospitalised and 20% died within the first year. Our findings provide new impetus to undertake risk assessment and treatment strategies in the ED for AHF.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.016
GPT teacher head0.257
Teacher spread0.241 · 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.

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

Citations120
Published2008
Admission routes2
Has abstractyes

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