The Use of Repetitive Transcranial Magnetic Stimulations for the Treatment of Bipolar Disorder: A Scoping Review
Bibliographic record
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive neuromodulation technique that involves the application of magnetic pulses on hyperactive or hypoactive cortical brain areas. rTMS is considered a high therapeutic tool in many neuropsychiatric conditions. Despite its wide and continuous usage for the treatment of psychiatric disorders, information about the use of rTMS in bipolar disorders is limited and not well-established in the literature. Objectives: This scoping review aims to explore the literature available regarding the application of rTMS for the management of bipolar disorders, to garner evidence in support of it uses in the management of bipolar disorders, and for recommendations on future clinical and research work. Method: We electronically conducted a data search in five research databases (MEDLINE, CINAHL, Psych INFO, SCOPUS, and EMBASE) using all identified keywords across all the databases to identify evidence-based studies. Articles were included if they were published randomized control designs aimed at the use of rTMS in the management of bipolar disorders. Overall, nine studies were eligible for this review. The search results are up to date as of the final date of data search—20 December 2020. Only full-text published articles written in English were reviewed. Review articles on treatment with rTMS for conditions either than bipolar disorders were excluded. Conclusion: The application of rTMS intervention for bipolar disorders looks promising despite the diversity of its outcomes and its clinical significance. However, to be able to draw a definite conclusion on the clinical effectiveness of the technique, more randomized controlled studies with well-defined stimulation parameters need to be conducted with large sample sizes in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".