Development and evaluation of a kidney health questionnaire and estimates of chronic kidney disease prevalence in the Cooperative Health Research in South Tyrol (CHRIS) study.

Background: Kidney diseases are a public health burden but are poorly investigated in the general population. In light of inadequate survey tools, we developed a novel questionnaire for use in population-based studies, to retrospectively assess kidney diseases.

Methods: The questionnaire covered general kidney diseases, reduced kidney function, and renal surgeries.

Use of generative artificial intelligence (AI) in psychiatry and mental health care: a systematic review.

Objectives: Tools based on generative artificial intelligence (AI) such as ChatGPT have the potential to transform modern society, including the field of medicine. Due to the prominent role of language in psychiatry, e.g.

A phase 3 randomised double-blind placebo-controlled trial of mirtazapine as a pharmacotherapy for methamphetamine use disorder: a study protocol for the Tina Trial.

Background: There are no approved pharmacotherapies for methamphetamine use disorder. Two preliminary phase 2 randomised controlled trials have found mirtazapine, a tetracyclic antidepressant, to be effective in reducing methamphetamine use. The proposed Tina Trial is the first phase 3 placebo-controlled randomised trial to examine the effectiveness and safety of mirtazapine as an outpatient pharmacotherapy for methamphetamine use disorder.

Machine Learning in Electroconvulsive Therapy: A Systematic Review.

Despite years of research, we are still not able to reliably predict who might benefit from electroconvulsive therapy (ECT) treatment. As we exhaust what is possible using traditional statistical analysis, ECT remains a good candidate for machine learning approaches due to the large data sets with data captured through electroencephalography (EEG) and other objective measures. A systematic review of 6 databases led to the full-text examination of 26 articles using machine learning approaches in examining data predicting response to ECT treatment.