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Record W4308370081 · doi:10.1056/nejmoa2211680

Trial of an Intervention to Improve Acute Heart Failure Outcomes

2022· article· en· W4308370081 on OpenAlexafffundabout
Douglas S. Lee, Sharon E. Straus, Michael E. Farkouh, Peter C. Austin, Monica Taljaard, Alice Chong, Christine Fahim, Stephanie Poon, Peter Cram, Stuart Smith, Robert S. McKelvie, Liane Porepa, Michael Hartleib, Peter R. Mitoff, Robert M. Iwanochko, Andrea MacDougall, Steven Shadowitz, Howard Abrams, Esam Elbarasi, Jiming Fang, Jacob A. Udell, Michael J. Schull, Susanna Mak, Heather J. Ross

Bibliographic record

VenueNew England Journal of Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsWomen's College HospitalToronto General HospitalToronto Western HospitalOttawa HospitalUniversity Health NetworkHealth Sciences CentreSunnybrook Health Science CentreLondon Health Sciences CentreUniversity of TorontoWestern UniversityUniversity of OttawaThunder Bay Regional Health Sciences CentreSt Joseph's Health CareSouthlake Regional Health CenterWilliam Osler Health SystemTed Rogers Centre for Heart Research
FundersInstitute of Circulatory and Respiratory HealthOntario SPOR SUPPORT Unit
KeywordsHeart failureMedicineIntervention (counseling)Intensive care medicineCardiologyInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Patients with acute heart failure are frequently or systematically hospitalized, often because the risk of adverse events is uncertain and the options for rapid follow-up are inadequate. Whether the use of a strategy to support clinicians in making decisions about discharging or admitting patients, coupled with rapid follow-up in an outpatient clinic, would affect outcomes remains uncertain. METHODS: In a stepped-wedge, cluster-randomized trial conducted in Ontario, Canada, we randomly assigned 10 hospitals to staggered start dates for one-way crossover from the control phase (usual care) to the intervention phase, which involved the use of a point-of-care algorithm to stratify patients with acute heart failure according to the risk of death. During the intervention phase, low-risk patients were discharged early (in ≤3 days) and received standardized outpatient care, and high-risk patients were admitted to the hospital. The coprimary outcomes were a composite of death from any cause or hospitalization for cardiovascular causes within 30 days after presentation and the composite outcome within 20 months. RESULTS: A total of 5452 patients were enrolled in the trial (2972 during the control phase and 2480 during the intervention phase). Within 30 days, death from any cause or hospitalization for cardiovascular causes occurred in 301 patients (12.1%) who were enrolled during the intervention phase and in 430 patients (14.5%) who were enrolled during the control phase (adjusted hazard ratio, 0.88; 95% confidence interval [CI], 0.78 to 0.99; P = 0.04). Within 20 months, the cumulative incidence of primary-outcome events was 54.4% (95% CI, 48.6 to 59.9) among patients who were enrolled during the intervention phase and 56.2% (95% CI, 54.2 to 58.1) among patients who were enrolled during the control phase (adjusted hazard ratio, 0.95; 95% CI, 0.92 to 0.99). Fewer than six deaths or hospitalizations for any cause occurred in low- or intermediate-risk patients before the first outpatient visit within 30 days after discharge. CONCLUSIONS: Among patients with acute heart failure who were seeking emergency care, the use of a hospital-based strategy to support clinical decision making and rapid follow-up led to a lower risk of the composite of death from any cause or hospitalization for cardiovascular causes within 30 days than usual care. (Funded by the Ontario SPOR Support Unit and others; COACH ClinicalTrials.gov number, NCT02674438.).

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score0.955

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)0.0010.000

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 head0.017
GPT teacher head0.320
Teacher spread0.304 · 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 designNot applicable
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

Citations147
Published2022
Admission routes3
Has abstractyes

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