To study prevalence of hallucinations in patients with Parkinson's disease (PD) during a 1-year period, and identify factors predictive of the onset of hallucinations in patients who were hallucination-free at baseline, 141 unselected outpatients with PD were evaluated prospectively for a set of demographic, clinical, and therapeutic variables and the presence of hallucinations during the previous 3 months. Patient groups were compared with nonparametric tests, and logistic regression was applied to significant data. Follow-up data were available for 127 patients. The hallucination prevalence rates (%) at the first and second evaluation were, respectively, 41.7 and 49.6 for hallucinations of all types (NS), 29.1 and 40.2 for minor hallucinations (i.e., presence or passage hallucinations, and illusions) (P = 0.02), 22.8 and 21.2 for formed visual hallucinations (NS), and 8.7 and 8.7 for auditory hallucinations (NS). Hallucinations rarely started or ceased during the study. The most labile forms were minor hallucinations, which developed in 20% of patients and ceased in 9%. During follow-up, 15% of patients started to hallucinate. Three factors, all present at the first evaluation, independently predicted the onset of hallucinations in patients previously free of hallucinations at baseline (odds ratio; 95% confidence interval): severe sleep disturbances (14.3; 2.5-80.9), ocular disorders (9.1; 1.6-52.0), and a high axial motor score (5.7; 1.2-27.4). Hallucinations have a chronic course in most parkinsonian patients. Factors predicting the onset of hallucinations point to a role of extranigral brainstem involvement and a nonspecific, facilitating role of ocular disorders.
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Conscious Cogn
January 2025
Humane Technology Lab, Catholic University of Sacred Heart, Milan, Italy; Applied Technology for Neuro-Psychology Lab., Istituto Auxologico Italiano IRCCS, Milan, Italy. Electronic address:
Psychedelic drugs offer valuable insights into consciousness, but disentangling their causal effects on perceptual and high-level cognition is nontrivial. Technological advances in virtual reality (VR) and machine learning have enabled the immersive simulation of visual hallucinations. However, comprehensive experimental data on how these simulated hallucinations affects high-level human cognition is lacking.
View Article and Find Full Text PDFPatient Educ Couns
January 2025
Wiser Healthcare, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Australia; The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, NSW, Australia.
Objective: This study aimed to assess whether information from AI chatbots on benefits and harms of breast and prostate cancer screening were concordant with evidence-based cancer screening recommendations.
Methods: Seven unique prompts (four breast cancer; three prostate cancer) were presented to ChatGPT in March 2024. A total of 60 criteria (30 breast; 30 prostate) were used to assess the concordance of information.
Genes (Basel)
December 2024
Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.
Background/objectives: Artificial intelligence and large language models like ChatGPT and Google's Gemini are promising tools with remarkable potential to assist healthcare professionals. This study explores ChatGPT and Gemini's potential utility in assisting clinicians during the first evaluation of patients with suspected neurogenetic disorders.
Methods: By analyzing the model's performance in identifying relevant clinical features, suggesting differential diagnoses, and providing insights into possible genetic testing, this research seeks to determine whether these AI tools could serve as a valuable adjunct in neurogenetic assessments.
Adv Sci (Weinh)
January 2025
Computational Science Research Center, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea.
Efficiently extracting data from tables in the scientific literature is pivotal for building large-scale databases. However, the tables reported in materials science papers exist in highly diverse forms; thus, rule-based extractions are an ineffective approach. To overcome this challenge, the study presents MaTableGPT, which is a GPT-based table data extractor from the materials science literature.
View Article and Find Full Text PDFJ ECT
January 2025
Department of Psychiatry, Central Institute of Psychiatry, Kanke, Ranchi, Jharkhand, India.
Background: Resistant auditory verbal hallucination (AVH) remains a disabling symptom in schizophrenia. Transcranial direct current stimulation (tDCS) and its more targeted variant, high-definition tDCS (HD-tDCS), have shown promising results in reducing AVH. We aimed to determine the effects of adjunctive HD-tDCS on various dimensions of AVH in patients with schizophrenia.
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