FALLERS AND CORTICAL BRAIN VOLUMES: CROSS-SECTIONAL ANALYSIS IN COGNITIVELY HEALTHY OLDER ADULTS
Bibliographic record
Abstract
Fall is a consequence of gait instability. Cortical and subcortical abnormalities have been associated with gait instability but not yet with fall. This study aims to compare the global and regional brain subvolumes between healthy fallers and non-fallers. A total of 77 healthy older individuals (23 fallers and 54 non-fallers, 69.8 ± 3.5years; 45.5% female) were included in this study using a cross-sectional design. Based on an a priori hypothesis, the following brain subvolumes were quantified from three-dimensional T1-weighted MRI using FreeSurfer: total white matter abnormalities, total white matter, total cortical and subcortical gray matters, hippocampus, motor cortex, somatosensory cortex, premotor cortex, prefrontal cortex and parietal cortex. Age, sex, body mass index, comorbidities, use of psychoactive drugs, far-distance vision, lower-limb proprioception, depressive symptoms and cognitive scores (Mini-Mental State Examination, Frontal Assessment Battery) were used as covariates. Multiple logistic regressions showed that subvolumes of the somatosensory cortex (P<0.042) and the hippocampus (P<0.042) were increased in fallers compared to non-fallers, even after adjustment for clinical and brain characteristics. The greater subvolumes of somatosensory cortex and hippocampus reported in fallers compared to non-fallers suggest a possible brain compensatory mechanism involving spatial navigation and integration of sensory information.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".