This study investigated to what extent fluvoxamine affects the pharmacokinetics of thioridazine (THD) in schizophrenic patients under steady-state conditions. Concentrations of THD, mesoridazine, and sulforidazine were measured in plasma samples obtained from 10 male inpatients, aged 36 to 78 years, at three different time points: A, during habitual monotherapy with THD at 88 +/-54 mg/day; B, after addition of a low dosage of fluvoxamine (25 mg twice a day) for 1 week; and C, 2 weeks after fluvoxamine discontinuation. After the addition of fluvoxamine, THD concentrations relative to time point A significantly increased approximately threefold from 0.40 to 1.21 micromol/L (225%) (p < 0.002), mesoridazine concentrations increased from 0.65 to 2.0 micromol/L (219%) (p < 0.004), and sulforidazine levels increased from 0.21 to 0.56 micromol/L (258%) (p < 0.004). The THD-mesoridazine and THD-sulforidazine ratios remained unchanged during the study. Mean plasma THD, mesoridazine, and sulforidazine levels decreased at time point C, but despite fluvoxamine discontinuation for 2 weeks, three patients continued to exhibit elevated concentrations of THD and its metabolites. In conclusion, fluvoxamine markedly interferes with the metabolism of THD, probably at the CYP2C19 and/or CYP1A2 enzyme level. Therefore, clinicians should be aware of the potential for a clinical drug interaction between both compounds, and careful monitoring of THD levels is valuable to prevent the accumulation of the drug and resulting toxicity.
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http://dx.doi.org/10.1097/00004714-199912000-00002 | DOI Listing |
Alzheimers Dement
December 2024
Laboratory of Neuroscience (LIM27), Departamento e Instituto de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina da Universidade de São Paulo, São Paulo, São Paulo, Brazil.
Background: Beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) was first identified as the rate limiting enzyme of amyloid-β-peptide (Aβ) production. The catalytic activity of BACE1 favors the generation of Aβ peptides and overproduction and accumulation of Aβ in the brain triggers downstream neurotoxic events that pertain to the amyloid cascade, leading to the formation of neuritic plaques. Furthermore BACE1 acts in the synapse through processing substrates such as APP-like proteins, Neuregulin-1 (Nrg 1), and β2 and β4 subunits of voltage-gated Na+ channels.
View Article and Find Full Text PDFJ Psychopharmacol
January 2025
Psychiatric Research Center, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan.
Objective: Therapeutic drug monitoring (TDM) indicators have been suggested to predict overall outcome responses to olanzapine (OLZ) treatments in terms of efficacy and metabolic syndrome. This study aimed to investigate whether paraoxonase-1 (PON-1) activity can be used to predict schizophrenia patient outcomes.
Methods: Schizophrenic patients ( = 50) aged between 20 and 65 years who received OLZ treatment were recruited, and their Positive and Negative Syndrome Scale scores, PON-1 activity, and olanzapine drug levels normalized by dose (OLZ/D) and its metabolite N-desmethyl-olanzapine (DMO), together with biochemical parameters, were determined.
Neuropsychopharmacol Hung
December 2024
Pszichiátriai és Pszichoterápiás Klinika, Semmelweis Egyetem, Budapest.
Med Health Care Philos
January 2025
Université de Genève, Genève, Switzerland.
This paper seeks to determine the extent to which individuals with borderline personality disorders can be held morally responsible for a particular subset of their actions: disproportionate anger, aggressions and displays of temper. The rationale for focusing on these aspects lies in their widespread acknowledgment in the literature and their plausible primary association with blame directed at BPD patients. BPD individuals are indeed typically perceived as "difficult patients" (Sulzer 2015:82; Bodner et al.
View Article and Find Full Text PDFBrain Behav
January 2025
Computational and Artificial Intelligence Department, Institute of Cognitive Science Studies, Tehran, Iran.
Purpose: The neurobiological heterogeneity present in schizophrenia remains poorly understood. This likely contributes to the limited success of existing treatments and the observed variability in treatment responses. Our objective was to employ magnetic resonance imaging (MRI) and machine learning (ML) algorithms to improve the classification of schizophrenia and its subtypes.
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