Objective: To compare the clinical symptomatology in patients with Early-Onset Schizophrenia (EOS, N = 176), especially the subgroup Very Early Onset Schizophrenia (VEOS) and Adult Onset Schizophrenia (AOS, N = 551).
Method: In a large French multicentric sample, 727 stable schizophrenia patients, classified by age at onset of the disorder, were assessed using standardized and extensive clinical and neuropsychological batteries: AOS with onset ≥ 18 years and EOS with onset < 18 years (including 22 VEOS < 13 years).
Results: The importance of better diagnosing EOS group, and in particularly VEOS, appeared in a longer DUP Duration of Untreated Psychosis (respectively, 2.
Eur Arch Psychiatry Clin Neurosci
August 2019
Psychosocial Interventions (PIs) have shown positive effects on clinical and functional outcomes of schizophrenia (SZ) in randomized controlled trials. However their effectiveness and accessibility remain unclear to date in "real world" schizophrenia. The objectives of the present study were (i) to assess the proportion of SZ outpatients who benefited from PIs between 2010 and 2015 in France after an Expert Center Intervention in a national multicentric non-selected community-dwelling sample; (ii) to assess PIs' effectiveness at 1-year follow-up.
View Article and Find Full Text PDFBackground: Extrapyramidal side effects (EPS) have been identified as a complication of antipsychotic treatment. Previous meta-analyses have investigated EPS prevalence and risk factors in randomized clinical trials with highly selected patients, but studies in real-world schizophrenia are missing.
Objective: To examine the prevalence and clinical correlates associated with EPS in a nonselected national multicenter sample of stabilized patients with schizophrenia.
Prog Neuropsychopharmacol Biol Psychiatry
June 2019
Objective: Existing staging models have not been fully validated. Thus, after classifying patients with schizophrenia according to the staging model proposed by McGorry et al. (2010), we explored the validity of this staging model and its stability after one-year of follow-up.
View Article and Find Full Text PDFProg Neuropsychopharmacol Biol Psychiatry
June 2019
Background: Predicting psychotic relapse is one of the major challenges in the daily care of schizophrenia.
Objectives: To determine the predictors of psychotic relapse and follow-up withdrawal in a non-selected national sample of stabilized community-dwelling SZ subjects with a machine learning approach.
Methods: Participants were consecutively included in the network of the FondaMental Expert Centers for Schizophrenia and received a thorough clinical and cognitive assessment, including recording of current treatment.