Amyloid-beta- associated clinical decline occurs only in the presence of elevated p-tau
Bibliographic record
Abstract
Objective\n To elucidate the relationship between the two hallmark proteins of Alzheimer's disease (AD), amyloid-β (Aβ) and tau, and clinical decline over time among cognitively normal older individuals.\n\n Design\n A longitudinal cohort of clinically and cognitively normal older individuals assessed with baseline lumbar puncture and longitudinal clinical assessments.\n\n Setting\n Research centers across the United States and Canada.\n\n Patients\n We examined one hundred seven participants with a Clinical Dementia Rating (CDR) of 0 at baseline examination.\n\n Main Outcome Measures\n Using linear mixed effects models, we investigated the relationship between CSF p-tau181p, CSF Aβ1-42 and clinical decline as assessed using longitudinal change in global CDR, CDR-Sum of Boxes (CDR-SB), and the Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog).\n\n Results\n We found a significant relationship between decreased CSF Aβ1-42 and longitudinal change in global CDR, CDR-SB, and ADAS-cog in individuals with elevated CSF p-tau181p. In the absence of CSF p-tau181p, the effect of CSF Aβ1-42 on longitudinal clinical decline was not significantly different from zero.\n\n Conclusions\n In cognitively normal older individuals, Aβ-associated clinical decline over a mean of three years may occur only in the presence of ongoing, “downstream” neurodegeneration.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".