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Validation and refinement of the clinical staging model in a French cohort of outpatient with schizophrenia (FACE-SZ)
- Source :
- Progress in Neuro-Psychopharmacology and Biological Psychiatry, Progress in Neuro-Psychopharmacology and Biological Psychiatry, 2019, 92, pp.226-234. ⟨10.1016/j.pnpbp.2019.01.003⟩, Progress in Neuro-Psychopharmacology and Biological Psychiatry, Elsevier, 2019, 92, pp.226-234. ⟨10.1016/j.pnpbp.2019.01.003⟩
- Publication Year :
- 2018
-
Abstract
- International audience; 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.Method: Using unsupervised machine-learning algorithm, we classified 770 outpatients into 5 clinical stages, the highest being the most severe. Analyses of (co)variance were performed to compare each stage in regard to socio-demographics factors, clinical characteristics, co-morbidities, ongoing treatment and neuropsychological profiles.Results: The precision of clinical staging can be improved by sub-dividing intermediate stages (II and III). Clinical validators of class IV include the presence of concomitant major depressive episode (42.6% in stage IV versus 3.4% in stage IIa), more severe cognitive profile, lower adherence to medication and prescription of >3 psychotropic medications. Follow-up at one-year showed good stability of each stage.Conclusion: Clinical staging in schizophrenia could be improved by adding clinical elements such as mood symptoms and cognition to severity, relapses and global functioning. In terms of therapeutic strategies, attention needs to be paid on the factors associated with the more stages of schizophrenia such as treatment of comorbid depression, reduction of the number of concomitant psychotropic medications, improvement of treatment adherence, and prescription of cognitive remediation.
- Subjects :
- Adult
Male
Pediatrics
medicine.medical_specialty
[SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology
[SDV.NEU.PC] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behavior
Comorbidity
Neuropsychological Tests
Medication Adherence
Machine Learning
03 medical and health sciences
Young Adult
0302 clinical medicine
Cognition
Outpatients
medicine
Humans
Cognitive Dysfunction
Stage (cooking)
Medical prescription
Major depressive episode
Biological Psychiatry
Pharmacology
Depressive Disorder, Major
[SDV.NEU.PC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behavior
business.industry
[SCCO.NEUR]Cognitive science/Neuroscience
[SCCO.NEUR] Cognitive science/Neuroscience
Neuropsychology
[SDV.NEU.NB] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology
[SDV.NEU.SC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences
medicine.disease
Prognosis
030227 psychiatry
3. Good health
Mood
Clinical staging
Schizophrenia
Cognitive remediation therapy
Cohort
Polypharmacy
Female
Schizophrenic Psychology
France
medicine.symptom
business
[SDV.NEU.SC] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences
Algorithms
Subjects
Details
- ISSN :
- 18784216 and 02785846
- Volume :
- 92
- Database :
- OpenAIRE
- Journal :
- Progress in neuro-psychopharmacologybiological psychiatry
- Accession number :
- edsair.doi.dedup.....9b8a2275169ff9be1c57755b1a5efa41
- Full Text :
- https://doi.org/10.1016/j.pnpbp.2019.01.003⟩