Effects of smoking status and MADRS retardation factor on response to low frequency repetitive transcranial magnetic stimulation for depression

Predictive modeling of response to repetitive transcranial magnetic stimulation in treatment-resistant depression

Identifying predictors of treatment response to repetitive transcranial magnetic stimulation (rTMS) remain elusive in treatment-resistant depression (TRD). Leveraging electronic medical records (EMR), this retrospective cohort study applied supervised machine learning (ML) to sociodemographic, clinical, and treatment-related data to predict depressive symptom response (>50% reduction on PHQ-9) and remission (PHQ-9 < 5) following rTMS in 232 patients with TRD (mean age: 54.5, 63.4% women) treated at the University of California, San Diego Interventional Psychiatry Program between 2017 and 2023. ML models were internally validated using nested cross-validation and Shapley values were calculated to quantify contributions of each feature to response prediction. The best-fit models proved reasonably accurate at discriminating treatment responders (Area under the curve (AUC): 0.689 [0.638, 0.740], p < 0.01) and remitters (AUC 0.745 [0.692, 0.797], p < 0.01), though only the response model was well-calibrated. Both models were associated with significant net benefits, indicating their potential utility for clinical decision-making. Shapley values revealed that patients with comorbid anxiety, obesity, concurrent psychiatric medication use, and more chronic TRD were less likely to respond or remit following rTMS. Patients with trauma and former tobacco users were more likely to respond. Furthermore, delivery of intermittent theta burst stimulation and more rTMS sessions were associated with superior outcomes. These findings highlight the potential of ML-guided techniques to guide clinical decision-making for rTMS treatment in patients with TRD to optimize therapeutic outcomes.

Managing substance use in patients receiving therapeutic repetitive transcranial magnetic stimulation: A scoping review

Repetitive Transcranial Magnetic Stimulation (rTMS) is an invaluable treatment option for neuropsychiatric disorders. Co-occurring recreational and nonmedical substance use can be common in those presenting for rTMS treatment, and it is unknown how it may affect the safety and efficacy of rTMS for the treatment of currently approved neuropsychiatric indications. This scoping review aimed to map the literature on humans receiving rTMS and had a history of any type of substance use. The search identified 274 articles providing information on inclusion/exclusion criteria, withdrawal criteria, safety protocols, type of rTMS and treatment parameters, adverse events and effect on primary outcomes that related to substance use. There are neurophysiological effects of substance use on cortical excitability, although the relevance to clinical rTMS practice is unknown. The current literature supports the safety and feasibility of delivering rTMS to those who have co-occurring neuropsychiatric disorder and substance use. However, specific details on how varying degrees of substance use alters the safety, efficacy, and mechanisms of rTMS remains poorly described.

Dynamics of Depressive and Psychomotor Symptoms During Electroconvulsive Therapy in Older Depressive Patients: A Case Series

OBJECTIVE

Electroconvulsive therapy (ECT) is an effective treatment for patients experiencing a major depressive episode, especially older ones. Identification of specific responses within early ECT sessions remains an issue of debate, however. Hence, this pilot study prospectively examined the outcome in terms of depressive signs, symptom by symptom, throughout a course of ECT, concentrating particularly on psychomotor retardation symptoms.

METHODS

Nine patients were clinically evaluated several times during the ECT course, before the first session and then weekly (over 3-6 weeks, according to their evolution), by completing the Montgomery-Åsberg Depression Rating Scale (MADRS), the Mini-Mental State Examination test, and the French Retardation Rating Scale for Depression for assessing the severity of psychomotor retardation.

RESULTS

Nonparametric Friedman tests showed significant positive changes in mood disorders during ECT in older depressive patients (mean, -27.3% of initial MADRS total score). Fast improvement in French Retardation Rating Scale for Depression score was observed at t1 (ie, after 3-4 ECT sessions), whereas a slightly delayed improvement in the MADRS scores was found at t2 (ie, after 5-6 ECT sessions). Moreover, the scores for items linked to the motor component of psychomotor retardation (eg, gait, postural control, fatigability) were the first to significantly decrease during the first 2 weeks of the ECT course compared with the cognitive component.

CONCLUSIONS

Interestingly, participants' concentration on daily functional activities, their interest and fatigability, and their reported state of sadness were the first to progress, representing possible precursor signs of positive patient outcomes after ECT.

Repetitive transcranial magnetic stimulation for smoking cessation: Next steps for translation and implementation into clinical practice

Tobacco smoking is a significant determinant of preventable morbidity and mortality worldwide. It is now possible to modulate the activity of the neurocircuitry associated with nicotine dependence using repetitive Transcranial Magnetic Stimulation (rTMS), a non-invasive neurostimulation approach, which has recently demonstrated efficacy in clinical trials and received regulatory approval in the US and Canada. However there remains a paucity of replication studies and real-world patient effectiveness data as access to this intervention is extremely limited. There are a number of unique challenges related to the delivery of rTMS that need to be addressed prior to widespread adoption and implementation of this treatment modality for smoking cessation. In this paper, we review the accessibility, scientific, technological, economical, and social challenges that remain before this treatment can be translated into clinical practice. By addressing these remaining barriers and scientific challenges with rTMS for smoking cessation and delineating implementation strategies, we can greatly reduce the burden of tobacco-related disease worldwide.

Real world transcranial magnetic stimulation for major depression: A multisite, naturalistic, retrospective study

BACKGROUND

In 2008, the U.S. FDA approved rTMS as a treatment against medication-resistant depression. However, real-world rTMS outcomes remain understudied. This study investigates how rTMS for depression is delivered in routine clinical practice in France, and measures its effectiveness as well as its moderators.

METHODS

Five centers provided retrospective data on patients who were treated with rTMS for treatment-resistant depression from January 2015 to December 2020. Patients were assessed twice using a hetero-questionnaire, with baseline and immediate post-treatment assessments. We conducted univariate analyses to study which factors were significantly associated with rTMS effectiveness. We then included age, gender, and significant factors in a multivariate model.

RESULTS

We collected data from 435 patients with a mean age of 51.27 (14.91): 66 % were female, and 26 % suffered from bipolar depression. Stimulation was delivered using four different stimulation parameters: 1 Hz (7 % of the individuals), 10 Hz (43 %), 20 Hz (12 %), and 50 Hz (intermittent Theta Burst Stimulation, iTBS) (38 %). The mean improvement of depressive symptoms was 33 % (p < 0.001, effect-size: 0.79). Response and remission rates were of 31 % and 22.8 %, respectively. In the multivariate analysis, improvement in depressive symptoms was associated with higher baseline symptoms.

CONCLUSION

This is one of the largest studies that investigates, with careful clinician-rated scales by trained psychiatrists, the effect of rTMS in naturalistic settings. Repetitive TMS appears to be effective in routine clinical practice, although its efficacy could be improved by analyzing predictors of response, as well as personalized targeting of specific brain areas.

Precision non-implantable neuromodulation therapies: a perspective for the depressed brain

Current first-line treatments for major depressive disorder (MDD) include pharmacotherapy and cognitive-behavioral therapy. However, one-third of depressed patients do not achieve remission after multiple medication trials, and psychotherapy can be costly and time-consuming. Although non-implantable neuromodulation (NIN) techniques such as transcranial magnetic stimulation, transcranial direct current stimulation, electroconvulsive therapy, and magnetic seizure therapy are gaining momentum for treating MDD, the efficacy of non-convulsive techniques is still modest, whereas use of convulsive modalities is limited by their cognitive side effects. In this context, we propose that NIN techniques could benefit from a precision-oriented approach. In this review, we discuss the challenges and opportunities in implementing such a framework, focusing on enhancing NIN effects via a combination of individualized cognitive interventions, using closed-loop approaches, identifying multimodal biomarkers, using computer electric field modeling to guide targeting and quantify dosage, and using machine learning algorithms to integrate data collected at multiple biological levels and identify clinical responders. Though promising, this framework is currently limited, as previous studies have employed small samples and did not sufficiently explore pathophysiological mechanisms associated with NIN response and side effects. Moreover, cost-effectiveness analyses have not been performed. Nevertheless, further advancements in clinical trials of NIN could shift the field toward a more “precision-oriented” practice.