Neural connectivity biotypes: predictors of clinical outcomes and improvement patterns of iTBS treatment in adolescents and young adults with depression
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Bibliographic record
Abstract
Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation (iTBS) and hinders the identification of predictive factors. This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression. Aim This study aimed to identify default mode network (DMN)‐based connectivity patterns associated with varying iTBS treatment outcomes in depression. Methods Data from a randomised controlled trial of iTBS in depression (n=82) were analysed using a data‐driven approach to classify homogeneous subgroups based on the DMN. Connectivity subgroups were compared on depressive symptoms and cognitive function at pretreatment and post‐treatment. Furthermore, the predictive significance of baseline inflammatory cytokines on post‐treatment outcomes was evaluated. Results Two distinct subgroups were identified. Subgroup 1 exhibited high heterogeneity and greater centrality in the posterior cingulate cortex and retrosplenial cortex, while subgroup 2 showed more homogeneous connectivity patterns and greater centrality in the temporoparietal junction and posterior inferior parietal lobule. No main effect for subgroup, treatment or subgroup×treatment interaction was revealed in the improvement of depressive symptoms. A significant subgroup×treatment interaction related to symbol coding improvement was detected (F=5.22, p=0.026). Within subgroup 1, the active group showed significantly greater improvement in symbol coding compared with the sham group (t=2.30, p=0.028), while baseline levels of interleukin‐6 and C‐reactive protein emerged as significant indicators for predicting improvements in symbolic coding (R 2 =0.35, RMSE (root‐mean‐square error)=5.72, p=0.013). Subgroup 2 showed no significant findings in terms of cognitive improvement or inflammatory cytokines predictions. Conclusions Data‐driven network analyses offer valuable insights into iTBS treatment outcomes in depression, providing clues for predicting cognitive improvements from an inflammatory perspective. Trial registration number ChiCTR2100042346.
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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 | 0.000 |
| 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) | 0.000 | 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