Characteristics and correlation of gray matter volume and somatic symptoms in adolescent patients with depressive disorder
Bibliographic record
Abstract
Background Adolescent patients with depressive disorders commonly exhibit somatic symptoms, which have a significant negative impact on their treatment and prognosis. Despite this, specific brain imaging characteristics of these symptoms have been poorly studied. Methods The Hamilton Depression Rating scale (HAMD-17), Children’s Functional Somatization scale (CSI), and Toronto Alexithymia scale (TAS) were used to evaluate the clinical symptoms of adolescent depression. We analyzed the correlation between brain gray matter volume (GMV) and clinical symptoms in adolescent patients with depression and somatic symptoms. Results The depression subgroups with and without functional somatic symptoms (FSS) had higher scores on the HAMD-17, CSI, and TAS than the normal control group. The group with FSS had higher HAMD-17, CSI, and TAS scores than the depression group without FSS ( p < 0.05). CSI and TAS scores were positively correlated ( r = 0.378, p < 0.05). The GMV of the right supplementary motor area was higher in the depression groups with and without FSSs than in the normal control group, and the GMV was higher in the group without FSS than in the group with FSS ( F = 29.394, p < 0.05). The GMV of the right supplementary motor area was negatively correlated with CSI in the depressed group with FSS ( r = −0.376, p < 0.05). In the group with depression exhibiting FSS, CSI scores were positively correlated with GMV of the middle occipital gyrus ( pr = 0.665, p = 0.0001), and TAS scores were positively correlated with GMV of the caudate nucleus ( pr = 0.551, p = 0.001). Conclusion Somatic symptoms of adolescent depressive disorder are associated with alexithymia; moreover, somatic symptoms and alexithymia in adolescent patients with depressive disorders are correlated with GMV changes in different brain regions.
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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 | 0.000 | 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".