Plasma biomarkers distinguish Boston Criteria 2.0 cerebral amyloid angiopathy from healthy controls
Bibliographic record
Abstract
Abstract INTRODUCTION Cerebral amyloid angiopathy (CAA) is characterized by the deposition of beta‐amyloid (Aβ) in small vessels leading to hemorrhagic stroke and dementia. This study examined whether plasma Aβ 42/40 , phosphorylated‐tau (p‐tau), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) differ in CAA and their potential to discriminate Boston Criteria 2.0 probable CAA from healthy controls. METHODS Plasma Aβ 42/40 , p‐tau‐181, NfL, and GFAP were quantified using single molecule array (Simoa) and Aβ 42/40 was also independently quantified using immunoprecipitation liquid chromatography mass‐spectrometry (IPMS). RESULTS Forty‐five participants with CAA and 47 healthy controls had available plasma. Aβ 42/40 ratios were significantly lower in CAA than healthy controls. While p‐tau‐181 and NfL were elevated in CAA, GFAP was similar. A combination of Aβ 42/40 (Simoa), p‐tau‐181, and NfL resulted in an area under the curve of 0.90 (95% confidence interval: 0.80, 0.95). DISCUSSION Plasma Aβ 42/40 , p‐tau‐181, and NfL differ in those with CAA and together can discriminate CAA from healthy controls. Highlights Participants with CAA had reduced plasma Aβ 42/40 ratios compared to controls. Plasma p‐tau‐181 and NfL concentrations are elevated in CAA compared to controls. Plasma GFAP was similar in CAA and controls. Together, plasma Aβ 42/40 , p‐tau‐181, and NfL had excellent discriminability for CAA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".