The implications of frailty in older adults with epilepsy
Bibliographic record
Abstract
Older adults constitute a large proportion of people with epilepsy (PWE) due to the changing demographics worldwide and epilepsy's natural history. Aging-related pathophysiological changes lower the tolerance and increase our vulnerability to stressors, which manifests as frailty. Frailty is closely associated with adverse health outcomes. This narrative review examines the interplay between frailty and epilepsy, especially in older adults, emphasizing its clinical implications, including its role in managing PWE. Mechanistically, frailty develops through complex interactions among molecular and cellular damage, including genomic instability, mitochondrial dysfunction, and hormonal changes. These contribute to systemic muscle mass, bone density, and organ function decline. The concept of frailty has evolved from a primarily physical syndrome to include social, psychological, and cognitive dimensions. The "phenotypic frailty" model, which focuses on physical performance, and the "deficit accumulation" model, which quantifies health deficits, provide frameworks for understanding and assessing frailty. PWE are potentially more prone to developing frailty due to a higher prevalence of risk factors predisposing to frailty. These include, but are not limited to, polypharmacy, higher comorbidity, low exercise level, social isolation, low vitamin D, and osteoporosis. We lack commercial biomarkers to measure frailty but can diagnose it using self- or healthcare provider-administered frailty scales. Recent attempts to develop a PWE-specific frailty scale are promising. Unlike chronological age, frailty is reversible, so its management using multidisciplinary care teams should be strongly considered. Frailty can affect antiseizure medication (ASM) tolerance secondary to its impact on pharmacokinetics and pharmacodynamics. While frailty's effect on seizure control efficacy of ASM is poorly understood, its undoubted association with overall poor outcomes, including epilepsy surgery, behooves us to consider its presence and implication while treating older PWE. Incorporation of frailty measures in future research is essential to improve our understanding of frailty's role in PWE health. PLAIN LANGUAGE SUMMARY: Frailty is the declining state of the human body. People with epilepsy are more prone to it. It should be factored into their management.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".