Comparison of Naturalistic Treatment Outcomes with the Standard 38-Minute Protocol vs. Shortened (“Dash”) Protocol: A NeuroStar® Registry Database Study
Bibliographic record
Abstract
Background: Optimized Transcranial magnetic stimulation (TMS) protocols for major depressive disorder (MDD) are needed to improve patient convenience and access. The FDA-approved NeuroStar protocol initially required 38 minutes per session (based on 4-second trains and 26-second inter-train-intervals (ITIs)). In 2017, a new (“Dash”) protocol with shorter (11- to 25-second) ITIs was approved, reducing total session times to as short as 19 minutes. We compared naturalistic treatment outcomes for Standard and Shortened “Dash” TMS protocols. Methods: NeuroStar registry data from 103 practice sites represent 7,759 patients. N=5,010 selected for this analysis (intent-to-treat (ITT) sample) had primary MDD diagnoses, age ≥18, baseline PHQ-9 ≥10, and at least one PHQ-9 assessment after treatments began. N=613 received Standard protocol TMS and n=1,493 were treated with Dash. “Completers” (N=3,814) were those who received ≥20 sessions and had a PHQ-9 at end of their acute course. Results: Overall response rate was 57.7% (65.0% for completers) and remission (PHQ-9<5) rate 27.9% (31.7% for completers). No difference was detected between Standard and Dash protocols in longitudinal, mixed-model analyses of PHQ-9 scores. Logistic regression models with/without covariates (e.g., age, motor threshold) did not reveal an effect of protocol on response or remission. PHQ-9 improvement and number of treatments administered were equivalent for both protocols. Conclusions: These large TMS registry outcomes are consistent with other naturalistic data. No efficacy differences were found between Standard and Dash protocols, providing support for use of the quicker protocol in standard clinical practice. Limitations include lack of randomized assignment to protocol group. This study was supported by Neuronetics Inc.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".