Risk factors for hippocampal cavities in a marginally housed population
Bibliographic record
Abstract
Abstract Cavities in the hippocampus are morphological variants of uncertain significance. Aberrant neurodevelopment along with vascular and inflammatory etiologies have been proposed. We sought to characterize these cavities and their potential risk factors in a marginally housed population, with high rates of viral infection, addiction, and mental illness. (1) The volume of hippocampal cavities (HCavs) is greater in this highly multimorbid population compared to the general population. (2) Conventional vascular risk factors such as greater age and systolic blood pressure are associated with higher HCav volume. (3) Nonprescribed substance‐related risk factors such as stimulant use or dependence, and smoking are associated with increased HCav volume independent of vascular risk factors. This is a retrospective analysis of an ongoing prospective study. We analyzed baseline data, including medical history, physical exam, psychiatric diagnosis, and MRI from a total of 375 participants. Hippocampal cavities were defined as spaces isointense to CSF on T1 MRI sequences, bounded on all sides by hippocampal tissue, with a volume of at least 1 mm3. Risk factors were evaluated using negative binomial multiple regression. Stimulant use was reported by 87.3% of participants, with stimulant dependence diagnosed in 83.3% of participants. Prevalence of cavities was 71.6%, with a mean total bilateral HCav volume of 13.89 mm3. On average, a 1 mmHg greater systolic blood pressure was associated with a 2.17% greater total HCav volume (95% CI = [0.57%, 3.79%], p = .0076), while each cigarette smoked per day trended toward a 2.69% greater total HCav volume (95% CI = [−0.87%, 5.54%], p = .058). A diagnosis of stimulant dependence was associated with a 95.6% greater total HCav volume (95% CI = [5.39%, 263.19%], p = .0335). Hypertension and diagnosis of stimulant dependence were associated with a greater total volume of HCav.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".