MétaCan
Menu
Back to cohort
Record W1997087920 · doi:10.1016/s1474-5151(09)60036-0

FAMP7 A New Clinical Care Paradigm Improves Cardiac Rehabilitation Enrollment In Post Myocardial Infarction Patients: Targeting the Care Gap following Hospital Discharge

2009· article· en· W1997087920 on OpenAlexaff
K Parker, Trina Hauer, Ross Arena, Debra Lundberg, David Goodhart, Sourabh Aġġarwal, Mouhieddin Traboulsi

Bibliographic record

VenueEuropean Journal of Cardiovascular Nursing · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsLibin Cardiovascular Institute of AlbertaAlberta Health Services
Fundersnot available
KeywordsMedicineRehabilitationMyocardial infarctionHospital dischargeIntensive care medicinePatient dischargeHospital careEmergency medicineCardiologyInternal medicinePhysical therapyMEDLINEHealth care

Abstract

fetched live from OpenAlex

Initiation of secondary prevention programming (i.e. cardiac rehabilitation) among myocardial infarction (MI) survivors significantly reduces subsequent disease-related events. Unfortunately, less than half of these individuals participate in cardiac rehabilitation (CR). Barriers, such as non-standardized CR referral processes, delayed timing of program delivery, and communication gaps between health care settings, in accessing CR programming are cited as primary factors for suboptimal participation rates in this form of secondary prevention. Purpose: To develop and implement a clinical model that will augment the rate of MI survivors successful transitioning between acute inpatient care and outpatient CR services. Methods: A construct of the cardiac patient journey was developed through a collaboration with acute and community based cardiac care settings by triangulating information from three principle data sources: 1) a patient needs assessment survey collected as part of an early follow-up clinical pilot project in a ST elevation myocardial infarction (STEMI) population; 2) a process review of hospital based CR referral and discharge teaching practices; 3) a process review of CR based referral and patient program scheduling activities. Information collected from this four-point analysis was then used to develop a health services transition care model.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.004
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 head0.010
GPT teacher head0.298
Teacher spread0.288 · 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 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

Citations1
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of Cardiovascular NursingSame topicCardiac Health and Mental HealthFrench-language works237,207