Association of MRI-measured cerebral ventricular volume with APOE ε4 genotype, cerebrospinal fluid biomarkers (Aβ42 and Tau) and neuropsychological measures in Alzheimer’s disease: A Systematic Review
Bibliographic record
Abstract
Abstract Rationale and Objectives Although neuroimaging studies suggest that the cerebral ventricle is independently associated with APOE ε4, cerebrospinal fluid (CSF) biomarkers, and neuropsychological scores in aging and Alzheimer’s disease (AD), there is no formal synthesis of these findings. We summarized the association of ventricular changes with APOE ε4, CSF biomarkers, and neuropsychological measures. Materials and Methods The Preferred Reporting Items for Systematic reviews and Meta-Analyses guideline was used. PubMed, Scopus, Ovid, Cochrane, and grey literature were searched, and assessment of eligible articles was conducted using the Newcastle-Ottawa Scale. Results 24 studies met the inclusion criteria. Progressive ventricular volume is increased in AD patients at an average volume of 4.4 – 4.7 cm 3 / year compared to average volumes of 2.7 – 2.9 cm 3 / year and 1.1 – 1.4 cm 3 /year for patients with MCI and healthy controls (HCs) respectively. The ventricular volume is estimated to increase by 1.7 cm 3 /year for progression from MCI to AD. APOE ε4 is an independent risk factor for ventricular enlargement in aging and dementia, with AD patients most affected. The combination of CSF Aβ42 with ventricular volume compared to tau is more robust, for tracking the progression of the AD continuum. Further, the combination of ventricular volume with mini-mental state examination (MMSE) scores is the most robust for differentiating AD and MCI from HCs and tracking the progression of the disease. Conclusion The combination of ventricular volume with APOE ε4, CSF Aβ42, and MMSE scores independently may be potentially useful biomarkers for differentiating and tracking the progression of AD.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.011 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".