Local Injection for Treating Mood Disorders (LIFT-MOOD): A Pilot Feasibility RCT of Stellate Ganglion Block for Treatment-Resistant Depression
Bibliographic record
Abstract
Background: With nearly one-third of patients with major depressive disorder being resistant to available antidepressants, there is a need to develop new treatments for this population. Stellate ganglion block (SGB) is a procedure used to block sympathetic input to the central autonomic system; it has been administered to treat several conditions, including pain. Recently, indications for SGB have extended and the potential benefits for psychiatric disorders are under investigation. Methods: The Local Injection For Treating Mood Disorders (LIFT-MOOD) study investigated the feasibility of a trial of 2 right-sided injections of bupivacaine 0.5% (7 mL) at the stellate ganglion in participants with treatment-resistant depression (TRD) using a randomized, placebo-controlled, pilot trial. Ten participants were randomized in a 1:1 allocation to receive active treatment or placebo (saline). Primary feasibility outcomes included recruitment rate, withdrawal, adherence, missing data, and adverse events. As a secondary, exploratory objective, we explored the efficacy of SGB in improving symptoms of depression by calculating the change in scores from baseline to follow-up on day 42 for each treatment group. Results: The recruitment rate was reasonable and sufficient, retention and adherence were high, missing data were low, and adverse events were mild and temporary. Both treatment groups demonstrated decreases in Montgomery-Åsberg Depression Rating Scale scores, compared to baseline, by the end of the study. Conclusion: This study supports the feasibility of a confirmatory trial of SGB in participants with TRD. Conclusions regarding efficacy cannot be made based on this preliminary study due to the small number of participants who completed active treatment. Larger-scale randomized controlled trials with long-term follow-ups and alternate sham procedures are needed to assess the efficacy and duration of symptom improvement with the use of SGB in TRD.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".