Cerebral microbleeds on 7 Tesla MRI in preclinical Alzheimer’s disease: The Medea‐7T study
Bibliographic record
Abstract
Abstract Background Subjective cognitive decline is increasingly being viewed as an early cognitive marker of preclinical Alzheimer’s disease (AD). Studies have recommended including AD biomarkers to increase the specificity of subjective cognitive decline, because of its etiological heterogeneity. We studied the prevalence and burden of cerebral microbleeds in persons with normal cognition, subjective memory impairment, cognitive impairment, and a clinical diagnosis mild cognitive impairment (MCI) or AD. Methods Data are from 386 participants (68±9 years, 30% women) included in the Medea‐7T cohort, a diverse cohort of persons with normal cognition, patients with a history of vascular disease, and memory clinic patients. A 7T brain MRI was performed in all participants. Four cognitive stages were defined: 1) normal cognition (n=196); 2) subjective memory impairment (n=78); 3) cognitive impairment (defined as <1.5 SD below age, sex, and education adjusted Z‐scores in any cognitive domain within the study sample) (n=57); 4) MCI/AD diagnosed according to international criteria (n=36). CMBs were visually rated on 7T MRI according to established criteria. Age‐ and sex‐adjusted log‐binomial regression was performed to examine the association between the cognitive stages and presence of CMBs (yes vs. no). Results Overall microbleed prevalence was 61%, with estimates per cognitive stage: normal cognitive function 60%, SCD 73%, cognitive impairment 55%, MCI and AD 47% (Figure 1). Age‐ and sex‐adjusted log‐binomial regression showed that—compared with the normal group—differences in microbleed prevalence were not statistically significant. Nonetheless, SCD showed an increased risk of CMBs (RR=1.18; 95% CI, 0.99‐1.41; p=0.06), whereas MCI/AD showed a decreased risk (RR=0.68; 95% CI, 0.45‐1.02; p=0.06), both approaching statistical significance. Conclusion In this study, cerebral microbleeds on 7T MRI were highly prevalent in older persons with normal cognition, subjective memory impairment, and MCI/AD. Differences observed between groups may reflect differences in underlying dominant etiology.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".