Abstract 48: Factors Associated With Motor Performance in Patients With Mild Cognitive Impairment and Cerebral Small Vessel Disease: Data From the VMCI-Tuscany study
Bibliographic record
Abstract
Background and purpose: Neuroimaging correlates of cerebral small vessel disease (SVD) are frequently detected in elderly subjects and are clinically associated with cognitive and gait dysfunction. Our aim was to evaluate clinical and neuroimaging factors associated with motor performance in a cohort of patients with mild cognitive impairment (MCI) and cerebral small vessel disease (SVD). Methods: the VMCI Tuscany Study is an ongoing, longitudinal, multicenter, observational study aimed at investigating predictors of transition from vascular MCI to dementia. Inclusion criteria were: 1) MCI (Winblad et al. criteria), and 2) evidence on MRI of moderate to severe degrees of white matter hyperintensities [(WMH), modified Fazekas scale]. Centralized visual assessment also included: number of lacunar infarcts, microbleeds, cortical atrophy, and medial temporal lobe atrophy on MRI. All patients underwent clinical and functional evaluation. Quantitative tests of gait and balance included the Short Physical Performance Battery (SPPB; range: 0 [poor] to 12 [normal]). Results: Out of the 145 patients enrolled (mean age 74.6±6.7, 55% males, 52% with severe WMH), mean SPPB score was 8.5±2.5, and Montreal Cognitive Assessment test (MoCA) 20.0±4.9. MoCA significantly correlated with SPPB (Spearman coefficient 0.204, p=0.014). The association also remained significant in the multivariate linear regression model (standardized coefficient 0.111, p=0.009), entering MoCA together with age, and neuroimaging variables. Among these latter, global atrophy retained a significant association (standardized coefficient -0.273, p=0.002). Conclusion: in our cohort of MCI patients with moderate to severe WMH, motor performance was associated with cognitive performance. Among MRI features, cortical atrophy seem to have a primary role, in line with the recent view that regards cortical atrophy as one of the neuroimaging correlates of SVD. Study funded by Tuscany Region.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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".