Racial differences in white matter hyperintensity load in aging, MCI, and AD
Bibliographic record
Abstract
Abstract Background Cerebral small vessel disease (CSVD), often measured using white matter hyperintensities (WMHs) is a pathological change to the brain that increases ones’ risk for both age‐related cognitive decline and dementia. Several studies have noted that there is greater risk of CSVD in African Americans than in Caucasians. However, limited research has examined WMHs as a proxy of CSVD in an ethnically diverse sample. The goal of this research was to determine whether WMH load differs between African Americans and Caucasians. Methods Participants for this study were selected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI1, GO, 2, and 3). They were included if they had baseline WMH measurements and a baseline diagnosis. WMHs were segmented using a previously validated automatic technique (Dadar et al., 2018). A total of 91 African Americans and 1846 Caucasians were included in this analysis. To compare samples, 91 Caucasian participants were randomly matched to African Americans based on age, sex, education, and diagnosis. This random selection was completed 1000 times using bootstrap resampling. A linear mixed effects was completed to examine the influence of race on WMH load: WMH ∼ Race + Age + Sex + Education + Diagnosis. The 95% confidence limits of the t‐statistics distributions for the 1000 samples were examined to determine whether the differences were statistically significant. Results The following figure shows the t‐statistic, 95% confidence intervals, and p‐value distributions of the 1000 bootstrapped samples. The 95% confidence intervals are between t=‐3.06 and t=‐0.89 for total WMH load, indicating significance, as the limits do not include 0. Conclusions Accounting for age, sex, education, and diagnostic status, racial differences were observed for total WMH load. That is, African Americans had higher total WMH load than Caucasians. Future research should examine whether these findings are observed longitudinally and if they influence cognition in an ethnically diverse sample.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".