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Record W2794002476 · doi:10.1177/1062860618754702

The Impact of a Transition of Care Program on Acute Myocardial Infarction Readmission Rates

2018· article· en· W2794002476 on OpenAlex
Jeffrey A. Marbach, Drew Johnson, Juergen Kloo, Amit Vira, Scott W. Keith, Walter K. Kraft, Natalie Margules, David J. Whellan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Medical Quality · 2018
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineMyocardial infarctionLogistic regressionOdds ratioOddsEmergency medicineAcute carePropensity score matchingHospital readmissionConditional logistic regressionTransitional careHospital dischargeInternal medicineIntensive care medicineHealth care

Abstract

fetched live from OpenAlex

Hospital discharge is a high-risk time period, and acute myocardial infarction (AMI) patients often have early readmissions. The authors hypothesized that a multifaceted AMI care coordination program would reduce early hospital readmission rates. The outcomes of patients receiving care coordination (n = 304) were compared to patients receiving standard care (n = 192). Multivariable analyses of the outcomes were conducted by conditional logistic regression of propensity score matched sets. The primary outcome-hospital readmission within 30 days of discharge-occurred in 18% of standard care patients and 11.8% of care coordination patients. Patients receiving care coordination demonstrated a 48% reduction in odds of readmission within 30 days (odds ratio = 0.52; P = .04; 95% CI = 0.28-0.97). These results are the first to demonstrate that inclusion in an AMI-specific care coordination program is associated with a significantly lower risk of 30-day hospital readmission.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.976
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.434
Teacher spread0.412 · 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