The relationship between physiological biomarkers, physical function, and fall‐risk among people living with dementia
Bibliographic record
Abstract
Abstract Background People living with dementia (PWD) have upregulated inflammatory pathways, exaggerated metabolic aging, and cellular aging. They also have declines in physical function and heightened fall‐risk. Understanding the physiologic factors that influence physical decline and fall‐risk in PWD is vital to assess and prevent adverse health outcomes, such as future falls. The purpose of this study was to explore the association between physiological biomarkers, physical decline, and fall‐risk in PWD. Method In this cross‐sectional study, we used the baseline data of n=42 PWD in residential care facilities from our pilot randomized controlled trial [NCT05488951]. We assessed fall‐risk with the Morse Fall Scale and pulled fall history in the last 6 months from incident reports in medical charts. Participants completed two 4‐meter usual pace walking trials. We assessed two trials of maximum quadriceps strength on each leg with a portable dynamometer. We drew fasted blood and measured inflammatory biomarkers (Interleukin(IL)‐1b, IL‐6, IL‐8, IL‐10, IL‐12p70, IL‐17A, IL‐18, IL23, IL‐33, chemokine ligand 2, tumor necrosis factor‐a, human interferon (INF)‐a2, INFg), metabolic aging (kynurenine), and cellular aging (telomere length). Separate multiple linear regressions were performed for each biomarker, with gait speed, leg strength, fall history, and the Morse Fall Scale as variables of interest. We controlled for age, sex, and the Montreal Cognitive Assessment in each model. Result Fall history (β=5.61, p=0.03) and older age (β=0.49, p=0.005) were associated with greater INF‐a2 (R2=0.49, p=0.07). Fall history (β=4.93, p=0.07) showed a trend for a relationship with greater IL‐10 (R2=0.50, p=0.04). Older age (β=0.28, p=0.009) and lower MOCA scores (β=‐0.40, p=0.04) were related to greater IL‐12p70 (R2=0.64, p=0.003). Older age (β=9.26, p=0.01), fall history (β=74.42, p=0.04), and poorer leg strength (β=‐7.40, p=0.06) were related to greater kynurenine (R2=0.49, p=0.02). Conclusion Our exploratory findings suggest that there may be a relationship between certain physiological biomarkers (INF‐a2, IL‐10, kynurenine), physical function, and fall history. These inflammatory and metabolic aging biomarkers may play an important role for physical function and fall‐risk in PWD. This preliminary research may have implications for screening and monitoring of physical decline and fall‐risk among PWD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".