White Matter Disease Severity of the Brain and Its Association With Geriatric Syndromes
Bibliographic record
Abstract
BACKGROUND AND AIM: White matter disease (WMD) of the brain is considered to be secondary to small vessel ischemia and can be a single unifying risk factor for the development of geriatric syndromes. The aim of our study was to investigate the association of the global and regional severity of WMD in the brain with geriatric syndromes burden. METHODS: In our retrospective study, consecutive outpatient charts from patients seen between January 2010 and June 2011 at University of Alberta Hospital Seniors Clinic were reviewed. Subjects with brain computed tomography (CT) scans were included in the study. Subjects with incomplete information or with diseases that confounded WMD assessment on CT were excluded. White matter disease was quantified on CT using Wahlund scoring. A multiple linear regression analysis was conducted to determine the association of WMD severity with geriatric syndromes burden after controlling for confounding vascular risk factors. RESULTS: Of the 505 subjects, 326 (64.6%) were women. Mean age of the study patients was 79.8 years (SD ± 7.04), prevalence of WMD disease was 79.4%, and mean WMD score was 5.1 (SD ± 4.4). In subjects aged < and > 80 years, the mean number of geriatric syndromes was 2.83 (standard error of the mean [SE] 0.08) and 3.22 (SE 0.08), respectively. In the adjusted regression analysis, there was a significant association between WMD severity, globally (regression coefficient (β) = 0.457, SE 0.155; P = 0.003), as well as WMD in specific regions: frontal (P < 0.001), parieto-occipital (P = 0.004), and infratentorial regions (P = 0.04) with geriatric syndromes burden. The association remains even after correcting for age, sex, and all vascular risk factors. CONCLUSION: In our study, there was a significant association between the severity of global and selected regional WMD of the brain with geriatric syndromes burden, thus raising the possibility of a shared biologic association through vascular pathology of the brain.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".