A subgroup of psychiatric patients are at increased risk of committing interpersonal violence, which may lead to placements in forensic-psychiatric institutions. The majority of patients treated in forensic hospitals have had contact with the general psychiatric care system years before being forensically committed due to an offence. Nevertheless, attempts to establish models related to violence prevention in general psychiatry have remained sparse. In the Canton of Zurich, the forensic psychiatric consultation liaison service provides the general psychiatric clinics with access to forensic psychiatric expertise. In this paper, we describe the consultation service's diagnostic and advisory offers and aim to characterize the patient population seen by the service. We compared the three most common diagnostic groups (schizophrenic, affective and personality disorders) regarding reason for consultation, history of violence and substance abuse. In addition, we analyzed content and kind of the recommendations made. From 2013 to 2021, 188 patients in general psychiatric clinics in Zurich have been examined after informed consent. Most patients had a positive history of violence (72.7%) and substance use (66.1%). Almost half of the patients (48.4%) had been diagnosed with schizophrenia or a related disorder.
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http://dx.doi.org/10.1055/a-2182-6606 | DOI Listing |
Kaohsiung J Med Sci
January 2025
Department of Psychiatry, School of Medicine, Kaohsiung Medical University Kaohsiung, Taiwan.
Attention-deficit/hyperactivity disorder (ADHD) is a common psychiatric condition among children and adolescents, often associated with a high risk of psychiatric comorbidities. Currently, ADHD diagnosis relies exclusively on clinical presentation and patient history, underscoring the need for clinically relevant, reliable, and objective biomarkers. Such biomarkers may enable earlier diagnosis and lead to improved treatment outcomes.
View Article and Find Full Text PDFEClinicalMedicine
October 2024
Centre for Psychedelic Research, Division of Psychiatry, Department Brain Sciences, Imperial College London, United Kingdom.
Background: Psilocybin therapy (PT) produces rapid and persistent antidepressant effects in major depressive disorder (MDD). However, the long-term effects of PT have never been compared with gold-standard treatments for MDD such as pharmacotherapy or psychotherapy alone or in combination.
Methods: This is a 6-month follow-up study of a phase 2, double-blind, randomised, controlled trial involving patients with moderate-to-severe MDD.
EClinicalMedicine
December 2024
Department of Neurology, Brain Research Institute, Niigata University, Niigata, Japan.
Background: Therapeutic advancements for the polyglutamine diseases, particularly spinocerebellar degeneration, are eagerly awaited. We evaluated the safety, tolerability, and therapeutic effects of L-arginine, which inhibits the conformational change and aggregation of polyglutamine proteins, in patients with spinocerebellar ataxia type 6 (SCA6).
Methods: A multicenter, randomized, double-blind, placebo-controlled phase 2 trial (clinical trial ID: AJA030-002, registration number: jRCT2031200135) was performed on 40 genetically confirmed SCA6 patients enrolled between September 1, 2020, and September 30, 2021.
Cureus
December 2024
Pharmacy Practice, Ziauddin University, Karachi, PAK.
Background: All recent advances in healthcare, including diagnostics, surveillance, management, and disease prevention, have depended on good-quality research that has brought new information to light. Therefore, in Pakistan, it is important to develop good research skills as, for many years, our physicians have relied on research knowledge from the Western world, which does not necessarily provide solutions to a developing country. Considering the gap in research knowledge among young doctors, the study was planned to compare the research knowledge of postgrad trainees of clinical and basic health sciences (BHS) of private tertiary care hospitals in Karachi.
View Article and Find Full Text PDFEClinicalMedicine
August 2024
Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, United Kingdom.
Background: Predicting dementia early has major implications for clinical management and patient outcomes. Yet, we still lack sensitive tools for stratifying patients early, resulting in patients being undiagnosed or wrongly diagnosed. Despite rapid expansion in machine learning models for dementia prediction, limited model interpretability and generalizability impede translation to the clinic.
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