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Record W2147087132 · doi:10.1093/ageing/afn013

Lessons learned from a multidisciplinary heart failure clinic for older women: a randomised controlled trial

2008· article· en· W2147087132 on OpenAlexaff
Nahid Azad, Frank Molnar, Anna Byszewski

Bibliographic record

VenueAge and Ageing · 2008
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsÉlisabeth Bruyère HospitalOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineRandomized controlled trialHeart failureMultidisciplinary approachPhysical therapyPopulationOutpatient clinicClinical trialIntervention (counseling)GerontologyInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: many heart failure disease management programs are primarily conducted in the male population. An approach incorporating disciplines such as physiotherapy, occupational therapy, social work, dietary and pharmacy in a standardized clinical pathway merits further investigation in older women with HF. METHODS: in this randomized controlled trial, female patients in the intervention group received the multidisciplinary clinical pathway consisting of a series of 12 visits over a 6-week period in an outpatient clinic. RESULTS: ninety-one community dwelling female patients aged 63 to 89 were randomized. Comparison of change between the two groups from baseline in the Minnesota Living with Heart Failure Questionnaire score did not show a difference (P<0.470). There was also no difference between the two groups in functional outcome as measured by change from baseline by the Physical Self-Maintenance Scale (P<0.321). The treatment group had significantly more hospitalizations, and cardiologist visits during the study period (P < 0.0001). CONCLUSION: It is feasible to conduct a randomized study in a frail community-based older female population and to test a complex multidisciplinary pathway. Future studies should provide insight into the optimal intensity and duration of heart failure management programs with optimal targeting.

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)0.000
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.331
Teacher spread0.275 · 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 designRandomized trial
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

Citations48
Published2008
Admission routes1
Has abstractyes

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