The aim of the study was to establish a relationship between the clinical efficacy of risperidone (Risp), the biological levels of Risp and its metabolite, 9-hydroxyrisperidone (9-OH-Risp), and the turnover of blood biogenic amines during a long-term treatment (1 year). Risp is one of the newer atypical antipsychotic drugs with potent serotonin (5HT2), moderate D2 and real alpha 1-alpha 2 adrenoreceptor antagonistic effects. The study has been performed in an open setting and included 17 patients, but only 15 were followed-up from 3 to 12 months. Pharmacokinetic analyses were conducted at the same time as clinical evaluations, grading using the Positive and Negative Syndrome Scale (PANSS), the Clinical Global Impressions (CGI), the Global Assessment of Functioning Scale (GAF), the Quality of Life Scale (QLS) and the Extrapyramidal Symptoms Rating Scale (ESRS) and the determinations of plasma and red blood cell (RBC) Risp and 9-OH-Risp, whole blood 5HT and tryptophan (Trp), plasma homovanillic acid (HVA), 5-hydroxyindoleacetic acid (5HIAA) and dihydroxyphenylethyleneglycol (DHPG). The therapeutic drug monitoring needed oral Risp daily dose of 4.5 +/- 2.3 mg (range 2-8) and the stabilized concentrations (ng/ml) at endpoint in plasma and RBC were 10 +/- 8 (range 1-23) and 3.5 +/- 2 (range 1-8) for Risp and 29 +/- 19 (range 8-70) and 11.5 +/- 6.6 (range 2.6-22.5) for 9-OH-Risp, respectively. 9-OH-Risp appears to be the major active metabolite compound at higher concentrations than Risp. Positive linear correlations were found only between plasma and RBC 9-OH-Risp and the daily dose and the score of the GAF. Statistically significant clinical results showed that Risp is a potent antipsychotic agent efficacious both on positive and negative symptoms and on quality of life. Positive symptoms decreased after about the second month and the negative symptoms improved secondly. Patients (n = 8) who responded to Risp were characterized, on the long-term, by a statistically significant decrease of whole blood 5HT and increase of plasma DHPG.
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http://dx.doi.org/10.1016/s0278-5846(02)00218-x | DOI Listing |
Clin Pharmacokinet
January 2025
Facultés de Médecine et de Pharmacie de Lyon, Univ Lyon, Université Claude Bernard Lyon 1, Lyon, France.
Background And Objective: Limited information is available on the pharmacokinetics of rifampicin (RIF) along with that of its active metabolite, 25-deacetylrifampicin (25-dRIF). This study aimed to analyse the pharmacokinetic data of RIF and 25-dRIF collected in adult patients treated for tuberculosis.
Methods: In adult patients receiving 10 mg/kg of RIF as part of a standard regimen for drug-susceptible pulmonary tuberculosis enrolled in the Opti-4TB study, plasma RIF and 25-dRIF concentrations were measured at various occasions.
J Imaging Inform Med
January 2025
Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Eye Disease, Shanghai, 200080, China.
The objectives of this study are to construct a deep convolutional neural network (DCNN) model to diagnose and classify meibomian gland dysfunction (MGD) based on the in vivo confocal microscope (IVCM) images and to evaluate the performance of the DCNN model and its auxiliary significance for clinical diagnosis and treatment. We extracted 6643 IVCM images from the three hospitals' IVCM database as the training set for the DCNN model and 1661 IVCM images from the other two hospitals' IVCM database as the test set to examine the performance of the model. Construction of the DCNN model was performed using DenseNet-169.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
Vision transformer (ViT)and convolutional neural networks (CNNs) each possess distinct strengths in medical imaging: ViT excels in capturing long-range dependencies through self-attention, while CNNs are adept at extracting local features via spatial convolution filters. While ViT may struggle with capturing detailed local spatial information, critical for tasks like anomaly detection in medical imaging, shallow CNNs often fail to effectively abstract global context. This study aims to explore and evaluate hybrid architectures that integrate ViT and CNN to leverage their complementary strengths for enhanced performance in medical vision tasks, such as segmentation, classification, reconstruction, and prediction.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland.
Analysis of the symmetry of the brain hemispheres at the level of individual structures and dominant tissue features has been the subject of research for many years in the context of improving the effectiveness of imaging methods for the diagnosis of brain tumor, stroke, and Alzheimer's disease, among others. One useful approach is to reliably determine the midline of the brain, which allows comparative analysis of the hemispheres and uncovers information on symmetry/asymmetry in the relevant planes of, for example, CT scans. Therefore, an effective method that is robust to various geometric deformations, artifacts, varying noise characteristics, and natural anatomical variability is sought.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Leiden University Medical Center (LUMC), Leiden, the Netherlands.
Rising computed tomography (CT) workloads require more efficient image interpretation methods. Digitally reconstructed radiographs (DRRs), generated from CT data, may enhance workflow efficiency by enabling faster radiological assessments. Various techniques exist for generating DRRs.
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