Sex differences in frailty: Comparisons between humans and preclinical models
Bibliographic record
Abstract
Frailty can be viewed as a state of physiological decline that increases susceptibility to adverse health outcomes. This loss of physiological reserve means that even small stressors can lead to disability and death in frail individuals. Frailty can be measured with various clinical tools; the two most popular are the frailty index and the frailty phenotype. Clinical studies have used these tools to show that women are frailer than men even though they have longer lifespans. Still, factors responsible for this frailty-mortality paradox are not well understood. This review highlights evidence for male-female differences in frailty from both the clinical literature and in animal models of frailty. We review evidence for higher frailty levels in female animals as seen in many preclinical models. Mechanisms that may contribute to sex differences in frailty are highlighted. In addition, we review work that suggests frailty may play a role in susceptibility to chronic diseases of aging in a sex-specific fashion. Additional mechanistic studies in preclinical models are needed to understand factors involved in male-female differences in frailty in late life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".