Al‐Soleiti, Majd

Background: Lithium is a mainstay treatment for bipolar disorder, but its narrow therapeutic index and susceptibility to pharmacokinetic interactions make appropriate monitoring crucial. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs), such as semaglutide, are increasingly prescribed for type 2 diabetes and weight management. Scarce evidence exists on the potential interaction between semaglutide and lithium. Methods: We present 3 cases involving patients on stable lithium regimens who were initiated on semaglutide, reviewing potential mechanisms underlying the interaction between them. Findings: In 2 cases, lithium levels increased significantly, leading to toxicity despite stable renal function and no changes in concurrent medications. In the third case, preemptive reductions in lithium dosage mitigated toxicity, although lithium levels remained higher than anticipated. Mechanistic hypotheses that might contribute to semaglutide-associated elevated lithium levels include altered kidney function, dehydration from reduced oral intake, vomiting, or diarrhea, and delayed gastric emptying. Conclusions: To our knowledge, this is one of the first documented case series describing a potential interaction between semaglutide and lithium in the medical literature. These cases underscore the importance of vigilant monitoring when combining lithium with semaglutide, and potentially other GLP-1 RAs. Baseline renal function, hydration status, and lithium levels should be assessed before initiating semaglutide, and lithium levels should be monitored more frequently during therapy. Clinicians prescribing semaglutide to patients on lithium should exercise caution, monitor for signs of toxicity, and provide appropriate patient education. Further research is needed to elucidate the mechanisms of this potential interaction and its clinical significance.

Background: Invasive and non-invasive neuromodulation in psychiatry represents a burgeoning field that leverages advanced neuromodulation techniques to address substance use disorders (SUDs). Aims: This narrative review synthesizes findings from multiple reviews to evaluate the efficacy of neuromodulation in treating SUDs. Methods: A comprehensive literature search was conducted between December 2024 and April 2025, focusing on systematic reviews and meta-analyses that examined various neuromodulation modalities, including repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), and deep brain stimulation (DBS). The selected reviews were analyzed to identify common themes, outcomes, and gaps in the current understanding of these treatments for SUDs. Results: 11 reviews met the final inclusion criteria; 5 focused on non-invasive neuromodulation (rTMS, tDCS) and 6 on invasive neuromodulation (DBS). Non-invasive neurostimulation was associated with modest improvements in craving and cognitive dysfunction in individuals with SUDs. Similarly, invasive neuromodulation (DBS), through high-frequency stimulation of the bilateral nucleus accumbens, appeared to reduce cravings and improve comorbid psychiatric symptoms in both preclinical and human studies. Importantly, small sample sizes, heterogeneity in targets and stimulation protocols, and short follow-up periods significantly limit the generalizability of current findings from both non-invasive and invasive neuromodulation studies. Conclusions: As novel and more effective therapies for the treatment of SUD are desperately needed, procedural interventional psychiatry holds promise. However, despite encouraging results, existing evidence is still preliminary, and larger, rigorously designed studies are warranted to further establish the safety and efficacy of neuromodulatory interventions for SUD treatment.

Background: Bipolar disorder (BD) involves significant mood and energy shifts reflected in speech patterns. Detecting these patterns is crucial for diagnosis and monitoring, currently assessed subjectively. Advances in natural language processing offer opportunities to objectively analyze them. Aims: To (i) correlate speech features with manic-depressive symptom severity in BD, (ii) develop predictive models for diagnostic and treatment outcomes, and (iii) determine the most relevant speech features and tasks for these analyses. Methods: This naturalistic, observational study involved longitudinal audio recordings of BD patients at euthymia, during acute manic/depressive phases, and after-response. Patients participated in clinical evaluations, cognitive tasks, standard text readings, and storytelling. After automatic diarization and transcription, speech features, including acoustics, content, formal aspects, and emotionality, will be extracted. Statistical analyses will (i) correlate speech features with clinical scales, (ii) use lasso logistic regression to develop predictive models, and (iii) identify relevant speech features. Results: Audio recordings from 76 patients (24 manic, 21 depressed, 31 euthymic) were collected. The mean age was 46.0 ± 14.4 years, with 63.2% female. The mean YMRS score for manic patients was 22.9 ± 7.1, reducing to 5.3 ± 5.3 post-response. Depressed patients had a mean HDRS-17 score of 17.1 ± 4.4, decreasing to 3.3 ± 2.8 post-response. Euthymic patients had mean YMRS and HDRS-17 scores of 0.97 ± 1.4 and 3.9 ± 2.9, respectively. Following data pre-processing, including noise reduction and feature extraction, comprehensive statistical analyses will be conducted to explore correlations and develop predictive models. Conclusions: Automated speech analysis in BD could provide objective markers for psychopathological alterations, improving diagnosis, monitoring, and response prediction. This technology could identify subtle alterations, signaling early signs of relapse. Establishing standardized protocols is crucial for creating a global speech cohort, fostering collaboration, and advancing BD understanding.