Prognostic value of 8F-Florbetapir scan: a 36-month follow up analysis using ADNI data
Bibliographic record
Abstract
Background: The Alzheimer’s Disease Neuroimaging Initiative (ADNI) provides an opportunity to investigate the relationship between β-Amyloid neuropathology and patients’ long-term cognitive function change. We examined baseline 18F-florbetapir PET amyloid imaging status and 36-months’ change from baseline in cognitive performance in subjects with mild cognitive impairment (MCI). Method: The study included all ADNI subjects who underwent PET-imaging with 18F-florbetapir and had a clinical diagnosis of MCI at the visit closest to florbetapir imaging. β-Amyloid deposition was measured by florbetapir standard uptake value ratio (SUVR), and dichotomized as Aβ+(SUVR>1.1) or Aβ–(SUVR≤1.1). Cognitive scores, including ADAS11, MMSE and CDR sum of boxes (CDR-SB), were evaluated for up to 36 months. Results: Of 478 MCI-subjects who had at least one florbetapir scan, 153 had a cognitive evaluation at 36-month follow-up. Of those, 79 were Aβ– and 74 Aβ+. At 36-months, the Aβ+ vs. Aβ– group scores changed from baseline (LS means 4.03 vs. 0.26 for ADAS11; -2.61 vs.-0.40 for MMSE; 1.53 vs. -0.11 for CDR-SB [p< 0.0001 all comparisons]). Generalised estimating equation analysis on clinically significant cognitive change showed a marginal Odds Ratio=2.18 (95% CI: 1.47–3.21) for Aβ+ vs. Aβ– groups. Conclusion: MCI subjects with higher β-Amyloid deposition had greater deterioration in cognitive function over 36 months while subjects with no β-Amyloid accumulation tended to be stable.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".