Effect of hippocampal and amygdala volumes on clinical outcomes in major depression: a 3-year prospective magnetic resonance imaging study
Bibliographic record
Abstract
OBJECTIVE: According to the stress-toxicity hypothesis of depression, hippocampal volumes may diminish as the disease progresses. We sought to examine the changes in hippocampal and amygdala volumes at baseline and at 3 years after an acute depressive episode, and the impact of reduced hippocampal volumes on the outcome. METHODS: In a prospective, longitudinal study, we examined the hippocampus and amygdala of 30 inpatients with major depression from the Department of Psychiatry and Psychotherapy and 30 healthy participants from the community (control group) using high-resolution magnetic resonance images at baseline and after 3 years. Psychopathology was assessed at baseline, weekly during the inpatient phase and then after 1, 2 and 3 years. RESULTS: During the 3-year follow-up period, neither hippocampal nor amygdala volumes changed significantly among patients or participants in the control group. However, in the subgroup of patients who took antidepressants over the full 3 years, the left hippocampal volumes increased significantly. Patients with small hippocampal volumes and previous depressive episodes had a worse clinical outcome compared with patients with large hippocampal volumes and previous depressive episodes. CONCLUSION: Overall, our results suggest that a relatively small hippocampal volume may be a vulnerability factor for a bad treatment response in major depression. Subtle changes in hippocampal volumes may be detectable during continuous antidepressant therapy. Such changes may be the result of neuroplastic processes.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".