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Record W4390638606 · doi:10.1093/eurjcn/zvad126

Why isn’t frailty being assessed on an ongoing basis within the cardiac setting?

2024· letter· en· W4390638606 on OpenAlexaffabout
Suzanne Fredericks

Bibliographic record

VenueEuropean Journal of Cardiovascular Nursing · 2024
Typeletter
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMedicineMetropolitan areaGerontologyNursing homesLibrary scienceFamily medicineNursingPathology

Abstract

fetched live from OpenAlex

This invited commentary refers to ‘Association between walking speed early after admission and all-cause death and/or re-admission in patients with acute decompensated heart failure,’ by K. Nozaki et al. https://doi.org/10.1093/eurjcn/zvad092 What is it about screening and assessing for frailty that scares us? Is it that we don’t know how to do it? Or that we just don’t feel it is a relevant part of the care we should be providing to our clients over the age of 65? In an article published in the European Journal of Cardiovascular Nursing, the authors investigated the associations between walking speed early after admission and clinical events in patients with acute decompensated heart failure (ADHF).1 They found faster walking speed within 4 days after admission was associated with favourable clinical outcomes in patients with ADHF. The results suggest that measuring walking speed in acute phase is useful for earlier risk stratification. The authors suggest that frailty is a potential mechanism of action that may account for walking speed. This is indeed a correct assumption, as there have been significant evidence that, as the authors have rightly stated, indicate decreased walking speed is a typical index of frailty, and frailty as a chronic condition has been associated with poor prognosis in specific populations. However, within Nozaki et al.’s study,1 frailty data were not analysed. Thus, this begs the question that if the authors knew of the impact of frailty, then why were frailty outcomes not assessed? In fact, Nozaki et al. did collect the standardized methodology for assessing walking speed to ensure reproducibility, but they did not analyse it from a frailty perspective. This standardized methodology consisted of a walking speed of ≥0.9 m/s which rules out the presence of frailty, while a walking speed of ≤0.8 m/s doubles the probability of a diagnosis of frailty. Adults over the age of 65 years diagnosed with cardiovascular disease such as heart failure (HF) usually have other chronic conditions that are responsible for major functional decline that include multimorbid conditions, polypharmacy, and geriatric syndromes inclusive of delirium, dementia, and depression. These conditions can lead to an overall state of reduced physiological reserve in multiple organ systems resulting in frailty.2 Evidence indicates early diagnosis of frailty in primary care should be an important first step when caring for patients over the age of 65 because of its high prevalence. Within the HF population, it is recommended that frailty be assessed at each stage of the HF trajectory.3 As well, potential treatments should be used to delay or even reverse frailty in its early stages.4 Thus, during any initial interactions with clients over the age of 65, clinicians should always consider the individual’s degree of frailty which can impact on walking speed and physical function such as HF outcomes. Since frailty is a predictor of adverse outcomes, inclusive of mortality, it is important to be aware of frailty when proposing treatment interventions.5 In addition to evaluating the degree of frailty, potential reversible risk factors for frailty should also be assessed. These reversible risk factors include malnutrition, dehydration, reduced daily physical activity, presence of chronic disease resulting in loss of muscle mass, dementia and/or cognitive dysfunction, lack of social supports, and loneliness.3 Finally, within the HF population, frailty can negatively impact on symptom presentation, as well as the management of disease progression.3 Wleklik et al.3 suggest when caring for frail patients living with HF an individualized approach to care should be designed that consists of strategies aimed at reversible risk factors and somatic and mental health symptoms.3 As well, the use of a comprehensive discharge plan that includes risk counselling during invasive therapeutic procedures and the delivery of care practice from a patient-centred care approach should also be considered. Collectively, these strategies should be implemented on an ongoing basis when engaging with adults over 65 years of age, who have been diagnosed with a cardiovascular disease such as HF.

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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)0.003
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.019
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.049
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0190.024
Insufficient payload (model declined to judge)0.0100.007

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 head0.022
GPT teacher head0.270
Teacher spread0.248 · 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 designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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Same venueEuropean Journal of Cardiovascular NursingSame topicFrailty in Older AdultsFrench-language works237,207