B.3 Neuroimaging markers of cerebrovascular disease and cognition in adults with moderate-great complexity congenital heart disease
Bibliographic record
Abstract
Background: Adults with congenital heart disease (ACHD) are at risk for stroke and dementia. We report baseline and Year 1 results from an ongoing study assessing brain health in people with moderate- and great-complexity ACHD. Methods: Participants aged ≥18 undergo baseline and Year-3 brain MRI/MRA and annual cognitive assessment (MoCA, NIH Toolbox-Cognitive Battery (NIH-TB)). Results: Of 93 participants to date, 79 (85%) have completed Year 1 follow-up. At baseline, the great-complexity group had lower MoCA (26.32 vs. 27.38; p=0.04) and NIH-TB scores (total composite 45.63 vs. 52.80; p=0.002) than the moderate-complexity group. Year-1 testing showed numerical improvements across cognitive batteries in both groups. More participants with great-complexity ACHD had white matter hyperintensities (WMH; 72% vs. 55%; p=0.21) and cerebral microbleeds (CMBs; 72% vs. 54%; p=0.17) on baseline neuroimaging, but differences were not significant. Conclusions: Baseline neuroimaging shows a greater-than-expected burden for age of CMB and WMH in the context of previous cardiac surgery. Baseline cognitive performance was worse with great-complexity ACHD. Improved cognitive battery performance across both subgroups at Year-1 suggests a practice effect. Repeat neuroimaging will be performed in Year-3 and cognitive performance is reassessed annually.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".