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Record W4293553221 · doi:10.1002/ehf2.14040

Practical Management of Frailty in Older Patients with Heart Failure

2022· article· en· W4293553221 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

VenueESC Heart Failure · 2022
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsWestern University
Fundersnot available
KeywordsHeart failureMedicineIntensive care medicineGerontologyManagement of heart failureInternal medicine

Abstract

fetched live from OpenAlex

AIMS: The heart failure (HF) prognosis in older patients remains poor with a high 5-years mortality rate more frequently attributed to noncardiovascular causes. The complex interplay between frailty and heart failure contribute to poor health outcomes of older adults with HF independently of ejection fraction. The aim of this position paper is to propose a practical management of frailty in older patients with heart failure. METHODS: A panel of multidisciplinary experts on behalf the Heart Failure Working Group of the French Society of Cardiology and on behalf French Society of Geriatrics and Gerontology conducted a systematic literature search on the interlink between frailty and HF, met to propose an early frailty screening by non-geriatricians and to propose ways to implement management plan of frailty. Statements were agreed by expert consensus. RESULTS: Clinically relevant aspects of interlink between frailty and HF have been reported to identify the population eligible for screening and the most suitable screening test(s). The frailty screening program proposed focuses on frailty model defined by an accumulation of deficits including geriatric syndromes, comorbidities, for older patients with HF in different settings of care. The management plan of frailty includes optimization of HF pharmacological treatments and non-surgical device treatment as well as optimization of a global patient-centred biopsychosocial blended collaborative care pathway. CONCLUSION: The current manuscript provides practical recommendations on how to screen and optimize frailty management in older patients with heart failure.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.285
Teacher spread0.269 · 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