Bibliographic record
Abstract
This article refers to 'Prevalence and prognostic impact of the coexistence of multiple frailty domains in elderly patients with heart failure: the FRAGILE-HF cohort study' by Y. Matsue et al., published in this issue on pages 2112-2119.Heart failure (HF) illustrates a complex set of pathophysiologic processes with multiple aetiologies that affect cardiac structures and function and whole-body systems, which ultimately lead to a poor prognosis.Patients with HF, in addition, become progressively burdened with more health problems of old age as they live longer.However, old (chronologic) age is not synonymous with poor aging as even patients with HF may expect to live in relatively good health with appropriate treatment.1 Understanding the heterogeneity in baseline non-cardiac health status, which consists of a constellation of health deficits, often go unmeasured and underrecognized that need to be incorporated in the identification, prognostication, and management strategies for HF patients.Frailty is a state which illustrates the variability in risk to poor health outcomes of people similar in age due to health deficits, whether subclinical or clinical, that accumulate over their lifetime.2 Patients with high degrees of frailty cannot physically, cognitively and/or socially cope with stressors, such as acute hospitalizations for HF. 3 The failure to cope with these stressors result in declination in functional reserve across multiple organ systems.Patients with cardiovascular disease who are frail have a worse disease prognosis.4 Similarly, cardiovascular disease can also potentiate a faster progression of frailty.5 Frailty may also be as detrimental as cardiovascular disease risk factors for predicting hospitalization and mortality risk.6 Collectively, it is important to understand frailty in patients with cardiovascular disease, such as HF.In this issue of the Journal, Matsue and colleagues 7 study the impact of a holistic definition of frailty that encompasses the interaction of physical, social and cognitive domains, as described by others, 8 in older patients with HF (with reduced or preserved ejection fraction) in the multicentre FRAGILE-HF study (n = 1180).Eligible patients were recruited at 15 participating (university and non-university teaching) hospitals in Japan, they were hospitalized for HF, were at least 65 years of age (median age 81; 57% male) and The opinions expressed in this article are not necessarily those of the Editors of the European Journal of Heart Failure or of the European Society of Cardiology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".