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Record W4301397459 · doi:10.3389/fpsyt.2022.935491

Repetitive transcranial magnetic stimulation combined with cognitive behavioral therapy treatment in alcohol-dependent patients: A randomized, double-blind sham-controlled multicenter clinical trial

2022· article· en· W4301397459 on OpenAlexaboutno aff
Xiaorui Hu, Tian Zhang, Hongkun Ma, Xuhui Zhou, Hongxuan Wang, Xiaohong Wang, Chang Cheng, Yanfei Li, Ranran Duan, Bo Zhang, Huaizhi Wang, Jia Lu, Chuanyi Kang, Na Zhao, Yingjie Zhang, Lu Tian, Jun Liu, Jingjing Shi, Zhe Wang, Xinxin Zhou, Shuang Zhu, Qingxia Liu, Xuemin Li, Honghui Wang, Mingxuan Nie, Mei Yang, Jianzhong Yang, Yong Chi, Xiaofeng Zhu, Jian Hu, Yanjie Jia, Ying Peng, Lei Liu

Bibliographic record

VenueFrontiers in Psychiatry · 2022
Typearticle
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTranscranial magnetic stimulationDouble blindRandomized controlled trialMedicineBrain stimulationTranscranial direct-current stimulationDeep transcranial magnetic stimulationClinical trialStimulationPhysical medicine and rehabilitationPsychologyInternal medicinePlaceboAlternative medicine

Abstract

fetched live from OpenAlex

Background Alcohol dependence (AD) is a complex addictive disorder with a high relapse rate. Previous studies have shown that both repetitive transcranial magnetic stimulation (rTMS) and cognitive behavioral therapy (CBT) may be effective for AD, and we aim to explore more effective treatment options to reduce relapse rates for AD. Materials and methods A total of 263 AD patients were recruited. They were divided into six groups according to the location and the type of rTMS: left dorsolateral prefrontal cortex (DLPFC), right DLPFC, sham stimulation, and whether they received CBT treatment: with a fixed schedule (C1) and without a fixed plan (C0). There were included in sham rTMS + C0 group (n = 50), sham rTMS + C1 group (n = 37), right rTMS + C0 group (n = 45), right rTMS + C1 group (n = 42), left rTMS + C0 group (n = 49), left rTMS + C1 group (n = 40). We used obsessive compulsive drinking scale (OCDS), visual analogue scale (VAS), alcohol dependence scale (ADS), montreal cognitive assessment (MoCA), generalized anxiety disorder-7 (GAD-7), patient health questionnaire-9 items (PHQ-9), and Pittsburgh sleep quality index (PSQI) to assess alcohol cravings, alcohol dependence, cognition, anxiety, depression, and sleep quality. They were followed up and evaluated for relapse. Results The sham rTMS + C0 group relapse rate was significantly higher than the right rTMS + C1 group (P = 0.006), the left rTMS + C0 group (P = 0.031), the left rTMS + C1 group (P = 0.043). The right rTMS + C0 group showed significantly higher relapse rate compared to the right rTMS + C1 group (P = 0.046). There was no significant difference in relapse rates between other groups. The repeated-measures ANOVA showed an interaction effect between group and time was significant in the rate of patient health questionnaire-9 items (PHQ-9) scale reduction (P = 0.020). Logistic analysis indicated that smoking and alcohol consumption were independent determinants of relapse (P < 0.05). At 24 weeks of follow-up, Kaplan–Meier survival analysis reveal that there is statistically significant relapse rate between six groups (P = 0.025), left rTMS + C1 group has the best treatment effect for alcohol dependent patients. Cox regression analysis confirmed that current smoking, total cholesterol, and total bilirubin (TBIL) level were risk factors of relapse (P < 0.05). Conclusion This study is the first to suggest that the combination of rTMS and CBT may be a potentially effective treatment for reducing relapse.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.064
GPT teacher head0.356
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2022
Admission routes1
Has abstractyes

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