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Record W2612176626 · doi:10.1016/j.jchf.2017.03.012

Associations Between Short or Long Length of Stay and 30-Day Readmission and Mortality in Hospitalized Patients With Heart Failure

2017· article· en· W2612176626 on OpenAlexafffundabout
Maneesh Sud, Bing Yu, Harindra C. Wijeysundera, Peter C. Austin, Dennis T. Ko, Juarez R. Braga, Peter Cram, John A. Spertus, Michaël Domanski, Douglas S. Lee

Bibliographic record

VenueJACC Heart Failure · 2017
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsSinai Health SystemSunnybrook Health Science CentreToronto General HospitalUniversity Health NetworkUniversity of TorontoHealth Sciences CentreInstitute for Clinical Evaluative Sciences
FundersCanadian Institutes of Health Research
KeywordsMedicineHazard ratioHeart failureConfidence intervalInternal medicineMortality rateCohort studyPopulationContinuous variableCardiologyEmergency medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: This study sought to examine the associations between heart failure (HF)-related hospital length of stay and 30-day readmissions and HF hospital length of stay and mortality rates. BACKGROUND: Although reducing HF readmission and mortality rates are health care priorities, how HF-related hospital length of stay affects these outcomes is not fully known. METHODS: A population-level, multicenter cohort study of 58,230 patients with HF (age >65 years) was conducted in Ontario, Canada between April 1, 2003 and March 31, 2012. RESULTS: When length of stay was modeled as continuous variable, its association with the rate of cardiovascular readmission was nonlinear (p < 0.001 for nonlinearity) and U-shaped. When analyzed as a categorical variable, there was a higher rate of cardiovascular readmission for short (1 to 2 days; adjusted hazard ratio [HR]: 1.12; 95% confidence interval [CI]: 1.04 to 1.21; p = 0.003) and long (9 to 14 days; HR: 1.11; 95% CI: 1.04 to 1.19; p = 0.002) lengths of stay as compared with 5 to 6 days (reference). Hospital readmissions for HF demonstrated a similar nonlinear (p = 0.005 for nonlinearity) U-shaped relationship with increased rates for short (HR: 1.15; 95% CI: 1.04 to 1.27; p = 0.006) and long (HR: 1.14; 95% CI: 1.04 to 1.25; p = 0.004) lengths of stay. Noncardiovascular readmissions demonstrated increased rates with long (HR: 1.17; 95% CI: 1.07 to 1.29; p < 0.001) and decreased rates with short (HR: 0.87; 95% CI: 0.79 to 0.96; p = 0.006) lengths of stay (p = 0.53 for nonlinearity). The 30-day mortality risk was highest after a long length of stay (HR: 1.28; 95% CI: 1.14 to 1.43; p < 0.001). CONCLUSIONS: A short length of stay after hospitalization for HF is associated with increased rates of cardiovascular and HF readmissions but lower rates of noncardiovascular readmissions. A long length of stay is associated with increased rates of all types of readmission and mortality.

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)0.005
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 score0.063
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.024
GPT teacher head0.308
Teacher spread0.284 · 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

Citations133
Published2017
Admission routes3
Has abstractyes

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