Higher Anxiety Symptoms Predict Progressive Hippocampal Atrophy in the Chronic Stages of Moderate to Severe Traumatic Brain Injury
Bibliographic record
Abstract
BACKGROUND: In the chronic stages of moderate-severe traumatic brain injury (TBI), progressive hippocampal volume loss-continuing well after acute neurological insults have resolved-has now been well documented. Previous research in other populations suggests that elevated anxiety symptoms are associated with compromise to the medial temporal lobes. OBJECTIVE: To examine whether higher anxiety symptoms predict greater hippocampal volume loss in moderate-severe TBI. METHODS: We conducted an analysis of prospectively collected, longitudinal behavioral and magnetic resonance imaging (MRI) data from 5 to 12 to 30 months post-injury. Eighty participants were included in the study, with anxiety symptom and MRI data collected at a minimum of 2 time points. Correlational and bivariate latent difference score (with imputation) analyses were used to examine the relationship of Beck Anxiety Inventory scores with hippocampal volume loss, while controlling for depressive symptoms and total brain volume. RESULTS: Analyses revealed that higher anxiety symptoms at 5 and at 12 months following moderate-severe TBI predicted significant later volume loss in the right hippocampal complex and the right hippocampal head. Right hippocampal volume and volume change did not predict subsequent anxiety scores or anxiety change scores. CONCLUSIONS: These novel findings implicate anxiety symptoms as a possible predictor of progressive hippocampal volume loss in the chronic stages of moderate-severe TBI.
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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 | 0.000 |
| 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 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".