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Abstract 4140382: Does pain predict physical function, cognitive function, activities of daily living, or health-related quality life among adults with heart failure?

2024· article· en· W4404363778 on OpenAlexaboutno aff
A Smith, Miyeon Jung, Susan J. Pressler

Bibliographic record

VenueCirculation · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHeart failureQuality of life (healthcare)CognitionActivities of daily livingGerontologyPhysical therapyHealth related quality of lifePhysical activityPhysical medicine and rehabilitationCardiologyInternal medicinePsychiatryDiseaseNursing

Abstract

fetched live from OpenAlex

Introduction: Although an estimated 54% of patients with heart failure (HF) and chronic pain report high symptom-associated distress, it is unclear whether pain predicts reduced physical function, cognitive function, independent activities of daily living (IADL) or health-related quality of life (HRQL) over time. The aims were to evaluate baseline pain presence as a predictor of physical function, cognitive function, IADL, and HRQL at baseline, 10 weeks, 4 months, and 8 months after baseline. Methods: In a retrospective longitudinal secondary analysis, data were analyzed from 237 participants with HF enrolled in the Cognitive Intervention to Improve Memory in Heart Failure Patients study. Pain presence was measured with the Health Utilities Index Mark-3 Questionnaire (HUI-3), physical function was measured by the Timed Up and Go (TUG), cognitive function was measured with the Montreal Cognitive Assessment (MoCA), IADL was measured by the Everyday Problems Test (EPT), and HRQL was measured by the Minnesota Living with Heart Failure Questionnaire (LHFQ). Descriptive statistics, independent t-tests, and linear mixed models were used to achieve the aims while controlling for gender. Results: The demographics were mean age 66.31 ± 12.02 years, gender 46% men, 54% women, race 13.5% Black, 85.7% White, 0.8% Other, NYHA class I: 9.7% II: 37.6% III: 52.7%, average LVEF: 48.9%. A total of 160 (67.51%) reported pain. In independent t-tests, patients with pain experienced significantly longer (i.e., worse) TUG scores at all timepoints except 10 weeks, and significantly higher (i.e., worse) LHFQ scores at all timepoints (see Table 1). However, in linear mixed models, pain at baseline did not predict TUG scores (F = 1.239, p = .298), MoCA scores (F = 0.148, p = .931), EPT scores, (F = 0.522, p = .668), or LHFQ scores (F = 0.364, p = .779) over time – see Table 1. Conclusions: Patients with HF and pain experienced significantly worse LHFQ and TUG scores at multiple timepoints. However, pain did not significantly predict cognitive function, physical function, IADL, or HRQL over time. Future prospective studies are needed to examine other outcomes associated with pain in this population and utilize more robust pain instruments.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.301
Teacher spread0.283 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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