Clinical, Neuroimaging, and Genetic Markers in Cerebral Amyloid Angiopathy-Related Inflammation: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: There are limited data regarding the prevalence of distinct clinical, neuroimaging and genetic markers among patients diagnosed with cerebral amyloid angiopathy–related inflammation (CAA-ri). We sought to determine the prevalence of clinical, radiological, genetic and cerebrospinal fluid biomarker findings in patients with CAA-ri. Methods: A systematic review and meta-analysis of published studies including patients with CAA-ri was conducted to determine the prevalence of clinical, neuroimaging, genetic and cerebrospinal fluid biomarker findings. Subgroup analyses were performed based on (1) prospective or retrospective study design and (2) CAA-ri diagnosis with or without available biopsy. We pooled the prevalence rates using random-effects models and assessed the heterogeneity using Cochran-Q and I 2 -statistics. Results: We identified 4 prospective and 17 retrospective cohort studies comprising 378 patients with CAA-ri (mean age, 71.5 years; women, 52%). The pooled prevalence rates were as follows: cognitive decline at presentation 70% ([95% CI, 54%–84%]; I 2 =82%), focal neurological deficits 55% ([95% CI, 40%–70%]; I 2 =82%), encephalopathy 54% ([95% CI, 39%–68%]; I 2 =43%), seizures 37% ([95% CI, 27%–49%]; I 2 =65%), headache 31% ([95% CI, 22%–42%]; I 2 =58%), T2/fluid-attenuated inversion recovery-hyperintense white matter lesions 98% ([95% CI, 93%–100%]; I 2 =44%), lobar cerebral microbleeds 96% ([95% CI, 92%–99%]; I 2 =25%), gadolinium enhancing lesions 54% ([95% CI, 42%–66%]; I 2 =62%), cortical superficial siderosis 51% ([95% CI, 34%–68%]; I 2 =77%) and lobar macrohemorrhage 40% ([95% CI, 11%–73%]; I 2 =88%). The prevalence rate of the ApoE (Apolipoprotein E) ε4/ε4 genotype was 34% ([95% CI, 17%–53%]; I 2 =76%). Subgroup analyses demonstrated no differences in these prevalence rates based on study design and diagnostic strategy. Conclusions: Cognitive decline was the most common clinical feature. Hyperintense T2/fluid-attenuated inversion recovery white matter lesions and lobar cerebral microbleeds were by far the most prevalent neuroimaging findings. Thirty-four percent of patients with CAA-ri have homozygous ApoE ε4/ε4 genotype and scarce data exist regarding the cerebrospinal fluid biomarkers and its significance in these patients.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.033 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".