Prevalence and Risk Factors of Brain Infarcts and Associations With Cognitive Performance in Tenants of Marginal Housing
Bibliographic record
Abstract
Background Homeless and vulnerably housed individuals are at increased risk for multimorbidity compared with the general population. We assessed prevalence of brain infarcts on neuroimaging and associations with vascular risk factors and cognitive performance in a prospective study of residents living in marginal housing. Methods and Results Two hundred twenty‐eight participants underwent structured clinical interviews, targeted clinical, laboratory, and neuropsychological assessments, and magnetic resonance imaging with T 1 , T 2 ‐fluid‐attenuated inversion recovery and susceptibility‐weighted images. Subjects underwent cognitive testing to assess premorbid IQ , verbal learning and memory, inhibition, sustained attention, mental flexibility, and decision making. In this sample (mean age 44.0 years [ SD 9.4], 77% male), prevalence of conventional vascular risk factors was lower than in the general population apart from tobacco use (94%). Ten‐year Framingham risk for any cardiovascular event was 11.4%±9.2%. Brain infarcts were present in 25/228 (11%). All were ischemic (40% cortical, 56% lacunar, 4% both). Participants with infarcts were older than those without (48.9±9.4 versus 43.4±9.2, P =0.006). In a multivariable regression analysis, only age remained a significant predictor of brain infarcts (odds ratio 1.08, 95% CI 1.02–1.14, P =0.004). After controlling for age and education, the presence of infarct was a significant predictor of impaired decision making on the Iowa Gambling Task of decision making (β −28.2, 95% CI −42.7 to −14.1, P <0.001). Conclusions Prevalence of infarcts on neuroimaging in this disadvantaged, community‐dwelling cohort was much higher than expected for age and was associated with impaired decision making. Further research is needed to identify individuals at highest risk who may benefit from targeted preventative strategies.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".