Pharmacological interventions for antipsychotic-related sialorrhea: a systematic review and network meta-analysis of randomized trials.

Antipsychotic-induced sialorrhea carries a significant burden, but evidence-based treatment guidance is incomplete, warranting network meta-analysis (NMA) of pharmacological interventions for antipsychotic-related sialorrhea. PubMed Central/PsycInfo/Cochrane Central database/Clinicaltrials.gov/WHO-ICTRP and the Chinese Electronic Journal Database (Qikan.cqvip.com) were searched for published/unpublished RCTs of antipsychotic-induced sialorrhea (any definition) in adults, up to 06/12/2023. We assessed global/local inconsistencies, publication bias, risk of bias (RoB2), and confidence in the evidence, conducting subgroup/sensitivity analyses. Co-primary efficacy outcomes were changes in saliva production (standardized mean difference/SMD) and study-defined response (risk ratios/RRs). The acceptability outcome was all-cause discontinuation (RR). Primary nodes were molecules; the mechanism of action (MoA) was secondary. Thirty-four RCTs entered a systematic review, 33 NMA (n = 1958). All interventions were for clozapine-induced sialorrhea in subjects with mental disorders. Regarding individual agents and response, metoclopramide (RR = 3.11, 95% C.I. = 1.39-6.98), cyproheptadine, (RR = 2.76, 95% C.I. = 2.00-3.82), sulpiride (RR = 2.49, 95% C.I. = 1.65-3.77), propantheline (RR = 2.39, 95% C.I. = 1.97-2.90), diphenhydramine (RR = 2.32, 95% C.I. = 1.88-2.86), benzhexol (RR = 2.32, 95% C.I. = 1.59-3.38), doxepin (RR = 2.30, 95% C.I. = 1.85-2.88), amisulpride (RR = 2.23, 95% C.I. = 1.30-3.81), chlorpheniramine (RR = 2.20, 95% C.I. = 1.67-2.89), amitriptyline (RR = 2.09, 95% C.I. = 1.34-3.26), atropine, (RR = 2.03, 95% C.I. = 1.22-3.38), and astemizole, (RR = 1.70, 95% C.I. = 1.28-2.26) outperformed placebo, but not glycopyrrolate or ipratropium. Across secondary nodes (k = 28, n = 1821), antimuscarinics (RR = 2.26, 95% C.I. = 1.91-2.68), benzamides (RR = 2.23, 95% C.I. = 1.75-3.10), TCAs (RR = 2.23, 95% C.I. = 1.83-2.72), and antihistamines (RR = 2.18, 95% C.I. = 1.83-2.59) outperformed placebo. In head-to-head comparisons, astemizole and ipratropium were outperformed by several interventions. All secondary nodes, except benzamides, outperformed the placebo on the continuous efficacy outcome. For nocturnal sialorrhea, neither benzamides nor atropine outperformed the placebo. Active interventions did not differ significantly from placebo regarding constipation or sleepiness/drowsiness. Low-confidence findings prompt caution in the interpretation of the results. Considering primary nodes' co-primary efficacy outcomes and head-to-head comparisons, efficacy for sialorrhea is most consistent for the following agents, decreasing from metoclopramide through cyproheptadine, sulpiride, propantheline, diphenhydramine, benzhexol, doxepin, amisulpride, chlorpheniramine, to amitriptyline, and atropine (the latter not for nocturnal sialorrhea). Shared decision-making with the patient should guide treatment decisions regarding clozapine-related sialorrhea.

Effects of electroconvulsive therapy on cortical thickness in depression: a systematic review.

OBJECTIVE: Electroconvulsive therapy (ECT) is one of the most studied and validated available treatments for severe or treatment-resistant depression. However, little is known about the neural mechanisms underlying ECT. This systematic review aims to critically review all structural magnetic resonance imaging studies investigating longitudinal cortical thickness (CT) changes after ECT in patients with unipolar or bipolar depression. METHODS: We performed a search on PubMed, Medline, and Embase to identify all available studies published before April 20, 2023. A total of 10 studies were included. RESULTS: The investigations showed widespread increases in CT after ECT in depressed patients, involving mainly the temporal, insular, and frontal regions. In five studies, CT increases in a non-overlapping set of brain areas correlated with the clinical efficacy of ECT. The small sample size, heterogeneity in terms of populations, comorbidities, and ECT protocols, and the lack of a control group in some investigations limit the generalisability of the results. CONCLUSIONS: Our findings support the idea that ECT can increase CT in patients with unipolar and bipolar depression. It remains unclear whether these changes are related to the clinical response. Future larger studies with longer follow-up are warranted to thoroughly address the potential role of CT as a biomarker of clinical response after ECT.

Prediction of medical admissions after psychiatric inpatient hospitalization in bipolar disorder: a retrospective cohort study.

Objective: Bipolar Disorder (BD) is a severe mental illness associated with high rates of general medical comorbidity, reduced life expectancy, and premature mortality. Although BD has been associated with high medical hospitalization, the factors that contribute to this risk remain largely unexplored. We used baseline medical and psychiatric records to develop a supervised machine learning model to predict general medical admissions after discharge from psychiatric hospitalization. Methods: In this retrospective three-year cohort study of 71 patients diagnosed with BD (mean age=52.19 years, females=56.33%), lasso regression models combining medical and psychiatric records, as well as those using them separately, were fitted and their predictive power was estimated using a leave-one-out cross-validation procedure. Results: The proportion of medical admissions in patients with BD was higher compared with age- and sex-matched hospitalizations in the same region (25.4% vs. 8.48%). The lasso model fairly accurately predicted the outcome (area under the curve [AUC]=69.5%, 95%C.I.=55-84.1; sensitivity=61.1%, specificity=75.5%, balanced accuracy=68.3%). Notably, pre-existing cardiovascular, neurological, or osteomuscular diseases collectively accounted for more than 90% of the influence on the model. The accuracy of the model based on medical records was slightly inferior (AUC=68.7%, 95%C.I. = 54.6-82.9), while that of the model based on psychiatric records only was below chance (AUC=61.8%, 95%C.I.=46.2-77.4). Conclusion: Our findings support the need to monitor medical comorbidities during clinical decision-making to tailor and implement effective preventive measures in people with BD. Further research with larger sample sizes and prospective cohorts is warranted to replicate these findings and validate the predictive model.