Cardiovascular differences between sham and active iTBS related to treatment response in MDD
Bibliographic record
Abstract
BACKGROUND: Heart rate in MDD is often dysregulated, expressed in overall higher heart rates (HR) and lower heart rate variability (HRV). Interestingly, HR decelerations have been reported after stimulation of the DLPFC using rTMS, suggesting connectivity between the DLPFC and the heart. Recently, a new form of rTMS called theta burst stimulation (TBS) has been developed. One form of TBS, intermittent TBS (iTBS), delivers 600 pulses in just 3 min. OBJECTIVE: To determine whether iTBS aimed at the DLPFC also affects HR, blood pressure and HRV, and whether these cardiac responses at baseline are associated with treatment response. METHODS: ECG and blood pressure were recorded during both sham and active iTBS in 15 MDD patients, over 30 sessions. RESULTS: We found a significantly larger HR deceleration for active iTBS, compared to sham, within the first minute of stimulation. Also, a trend towards an association between HR deceleration and treatment response was found, explaining 26% of the variance. Furthermore, several measures of heart rate variability were significantly higher during iTBS stimulation over sessions, compared to sham. Both systolic and diastolic blood pressure, were lower during active iTBS. CONCLUSION: Active iTBS applied to the DLPFC is able to transsynaptically modulate the autonomic nervous system, in particular the parasympathetic branch, similar to what has been found for conventional rTMS methods. Furthermore, data suggest that the larger the autonomic changes induced at baseline, the better the clinical response after 30 sessions of iTBS.
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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".