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Psychosocial factors as predictors of functional status at 1 year in patients with left ventricular dysfunction

2000· article· en· W2128296300 on OpenAlex

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

VenueResearch in Nursing & Health · 2000
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsMontreal Heart InstituteMcGill University
Fundersnot available
KeywordsPsychosocialBiopsychosocial modelMedicineSocioeconomic statusSocial isolationQuality of life (healthcare)Psychological interventionSocial supportPopulationGerontologyPsychologyPsychiatry

Abstract

fetched live from OpenAlex

Chronic heart failure patients often experience significant functional impairments. A better understanding of the biopsychosocial correlates of functional status may lead to interventions that improve quality of life in this population. Social isolation, mood disturbance, low socioeconomic status, and non-White ethnicity were evaluated as possible correlates of impaired functional status in 2,992 U.S. patients with left ventricular ejection fractions (LVEFs) </= 35%. Even after controlling for age and clinical characteristics, all of the psychosocial variables examined were significant predictors of risk for experiencing severe limitations in intermediate and social activities of daily living at 1 year, with adjusted odds ratios in the 1.5-2.0 range. The ability of psychosocial characteristics to predict future functional status was also independent of baseline functional status, comorbid medical conditions, and deterioration in heart failure signs and symptoms over the intervening year. These results suggest that psychosocial factors influence patient functional status even in the later phases of cardiac disease.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.824

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.033
GPT teacher head0.367
Teacher spread0.334 · 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