Microstructural brain abnormalities in medication-free patients with major depressive disorder: a systematic review and meta-analysis of diffusion tensor imaging
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Multiple meta-analyses of diffusion tensor imaging (DTI) studies have reported impaired white matter integrity in patients with major depressive disorder (MDD). However, owing to inclusion of medicated patients in these studies, it is difficult to conclude whether these reported alterations are associated with MDD or confounded by medication effects. A meta-analysis of DTI studies on medication-free (medication-naive and medication washout) patients with MDD would therefore be necessary to disentangle MDD-specific effects. METHODS: We analyzed white matter alterations between medication-free patients with MDD and healthy controls using anisotropic effect size-signed differential mapping (AES-SDM). We used DTI query software for fibre tracking. RESULTS: Both pooled and subgroup meta-analyses in medication washout patients showed robust fractional anisotropy (FA) reductions in white matter of the right cerebellum hemispheric lobule, body of the corpus callosum (CC) and bilateral superior longitudinal fasciculus III (SLF III), whereas FA reductions in the genu of the CC and right anterior thalamic projections were seen in only medication-naive patients. Fibre tracking showed that the main tracts with observed FA reductions included the right cerebellar tracts, body of the CC, bilateral SLF III and arcuate fascicle. LIMITATIONS: The analytic techniques, patient characteristics and clinical variables of the included studies were heterogeneous; we could not exclude the effects of nondrug therapies owing to a lack of data. CONCLUSION: By excluding the confounding influences of current medication status, findings from the present study may provide a better understanding of the underlying neuropathology of MDD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 it