Microbleeds in Alzheimer’s Disease: A Neuropsychological Overview and Meta-Analysis
Bibliographic record
Abstract
The current literature on the role of brain microbleeds (MB) on the neuropsychological outcomes of Alzheimer's disease (AD) is heterogeneous. We therefore meta-analytically examined the neuropsychological literature pertaining to MBs in AD. Using a priori selected criteria, studies with cross-sectional neuropsychological assessment on MBs and AD were reviewed. Six of 122 studies met selection criteria and provided neuropsychological data on either AD with MB and without MB, or in contrast to healthy controls. The global neuropsychological difference between AD with MB and AD without MB based on random effect model was nonsignificant, heterogeneous, and small (Effect Size =-0.155; 95% confidence interval =-0.465 to 0.155; p value =0.326; Heterogenity: Q-value =12.744; degrees of freedom =5; p =0.026; I2 =61%). The contribution of MBs to cognitive deficits in AD remains unclear. Future studies of MB in AD should strive to use standardized neuroimaging techniques with high sensitivity for MB, a common standard for MB definition, and neuropsychological tests sensitive for detecting subtle cognitive impairment.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.026 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".