DEVELOPMENT OF A RAT CLINICAL FRAILTY INDEX
Bibliographic record
Abstract
There has been a recent focus on the development of pre-clinical models of frailty in mice. A mouse clinical frailty index (FI) was developed based on the concept that frailty can be quantified as the accumulation of deficits in health, as originally shown in humans. Rats are a commonly used model for aging studies, so the current study aimed to develop a FI that measures the accumulation of clinically-evident health-related deficits in rats. Male Fischer 344 rats were aged from 6 to 9 months (n=12), and from 13 to 21 months (n=41). A FI comprised of 27 health-related deficits was developed from a review of the literature and consultation with a veterinarian. Deficits were scored 0 if absent, 0.5 if mild or 1 if severe. A FI score was determined for each rat every 3–4 months, and for the older group mortality was assessed up to 21 months. Mean FI scores significantly increased at each time point for the older rats (13 months, 0.06 ± 0.00; 17 months, 0.13 ± 0.01; 21 months 0.21 ± 0.01; p<0.0001). The rate of deficit accumulation, and the maximum FI score (0.40) were similar to those observed in previous mouse and human FI studies. A high FI score measured at both 17 months (p<0.0001) and 21 months of age (p=0.007) was also associated with decreased probability of survival as assessed with Kaplan-Meier curves. The rat clinical FI has significant value for use in aging and interventional studies, and will contribute to translational research in this field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".