Clinical Significance of Brain White Matter Hyperintensities in Young Adults with Psychiatric Illness
Bibliographic record
Abstract
Magnetic resonance imaging (MRI) provides detailed images of brain anatomy, with especially clear definition of gray and white matter structures. Several brain MRI studies have suggested that adults with bipolar disorder (BD) are more likely to have "white matter hyperintensities" (WMH) than adults without BD. The disproportionately greater frequency of these lesions in otherwise physically healthy patients suggests that the illness itself, or treatments used to control the illness, may be risk factors for the development of white matter changes. Similarly, WMH may be an etiological factor for some types of BD. In addition to reviewing the relevant literature, this research study attempted to determine whether lithium treatment is associated with an increased prevalence of WMH in young adults with psychiatric illness. To test this hypothesis, we evaluated over 600 brain MRI scans from inpatients at McLean Hospital, Belmont, Massachusetts. We controlled for possible confounding variables such as age, vascular disease, substance abuse, and markers of illness severity. We found that individuals with BD were no more likely to have WMH than other psychiatric patients. Lithium use was nonsignificantly associated with the presence of WMH. A multivariate regression model for the presence of WMH showed that heart disease, female gender, and multiple psychiatric admissions were significant predictors of WMH. This study does not support previous findings that BD, compared to other psychiatric illnesses, was associated with increased risk of WMH. Lithium use may be subtly associated with WMH. Our results are consistent with previous research that found an association between cardiovascular disease, advanced age, and the presence of WMH, though our analysis appears to be unique in its inclusion of cardiovascular disease as a risk factor in young adults with psychiatric illness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".