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An empirical staging model for schizophrenia using machine learning
- M.-C. Clara, F. Sánchez-Lasheras, A. García-Fernández, L. González-Blanco, P. A. Sáiz, J. Bobes, M. P. García-Portilla
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- Journal:
- European Psychiatry / Volume 66 / Issue S1 / March 2023
- Published online by Cambridge University Press:
- 19 July 2023, pp. S626-S627
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Introduction
One of the great challenges still to be achieved in schizophrenia is the development of a staging model that reflects the progression of the disorder. The previous models suggested have been developed from a theoretical point of view and do not include objective variables such as biomarkers, physical comorbidities, or self-reported subjective variables (Martinez-Cao et al. Transl Psychiatry 2022; 12(1) 1-11).
ObjectivesDevelop a multidimensional staging model for schizophrenia based on empirical data.
MethodsNaturalistic, cross-sectional study. Sample: 212 stable patients with Schizophrenia (F20). Assessments: ad hoc questionnaire (demographic and clinical information); psychopathology: PANSS, CDS, OSQ, CGI-S; functioning: PSP; cognition: MATRICS; laboratory tests: C-Reactive Protein (CRP), IL-1RA, IL-6, Platelets/Lymphocytes (PLR), Neutrophils/Lymphocytes (NLR), and Monocytes/Lymphocytes (MLR) ratios. Statistical analysis: Variables selection was performed with an ad hoc algorithm developed for this research. The referred algorithm makes use of genetic algorithms (GA) to select those variables that show the best performance for the patients classification according to their global CGI-S. The objective function of the GA maximizes the individuals correct classification of a support vector machines (SVM) model that employs as input variables those given by the GA (Díez-Díaz et al. Mathematics 2021; 9(6) 654). Models performance was assessed with the help of 3-fold cross-validation and these process was repeated 10,000 times for each one of the models assessed.
ResultsMean age(SD): 39.5(13.54); men: 63.5%; secondary education: 59.50%. Most patients in our sample had never been married (74.10%), and more than a third received disability benefits due to schizophrenia (37.70%). The mean length of the disease was 11.98(12.02) years. The best SVM model included the following variables: 1)Clinical: number of hospitalizations, positive, negative, depressive symptoms and general psychopathology; 2)Cognition: speed of processing, visual learning and social cognition; 3)Functioning: PSP total score; 4)Biomarkers: PLR, NLR and MLR. This model was executed again 100,000 times applying again 3-fold cross-validation. In 95% of the algorithm executions more than a 53.52% of the patients were classfied in the right CGI-S category. On average the right classification was of 61.93%. About specificity and sensitivity the average values obtained were of 0.85 and 0.64 respectively.
ConclusionsOur staging model is a robust method that appropriately distributes patients according to the severity of the disorder. Highlights the importance of clinical, functional and cognitive factors to classify patients. Finally, the inflammatory parameters PLR, NLR and MLR have also emerged as potential biomarkers for staging schizophrenia.
Disclosure of InterestNone Declared
Trends in the incidence of hospital-treated suicide attempts during the COVID-19 pandemic in Oviedo, Spain
- J. Fernandez-Fernandez, L. Jiménez-Treviño, E. Seijo-Zazo, F. Sánchez Lasheras, M. P. García-Portilla, P. A. Sáiz, J. Bobes
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- Journal:
- European Psychiatry / Volume 66 / Issue 1 / 2023
- Published online by Cambridge University Press:
- 03 February 2023, e23
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Background
The potential impact of the COVID-19 pandemic on suicidal behavior has generated predictions anticipating an increase in suicidal tendencies. The aim of this research is to study its influence on the incidence of hospital-treated suicide attempts throughout the year 2020 in Oviedo, Spain.
MethodsData were collected on all patients admitted to the emergency department of Central University Hospital of Asturias in Oviedo for attempted suicide during 2020. Incidence rates were calculated for three lockdown periods. Suicide attempt trends in 2020 were compared with a non-COVID-19 year (2009) to avoid seasonal variations bias. Chi-square and Fisher’s exact tests were performed. The influence of COVID-19 incidence in Oviedo was analyzed using Spearman’s correlation coefficient.
ResultsThe cumulative incidence rate of attempted suicide per 100,000 person-years was 136.33 (pre-lockdown), 115.15 (lockdown), and 90.25 (post-lockdown) in adults (over 19 years old), and 43.63 (pre-lockdown), 32.72 (lockdown), and 72.72 (post-lockdown) in adolescents (10–19 years old). No association was found with COVID-19 incidence rates (Spearman’s rho −0.222; p = 0.113). Comparing the years 2020 and 2009, statistically significant differences were observed in adolescents (Fisher’s exact test; p = 0.024), but no differences were observed in adults (chi-square test = 3.0401; p = 0.218).
ConclusionsHospital-treated suicide rates attempted during the COVID-19 outbreak in Oviedo, Spain showed a similar trend compared with a non-COVID-19 year. In contrast, the number of adolescents hospital-treated for attempted suicide increased during lockdown, suggesting more vulnerability to COVID-19 restrictions after the initial lockdown period in this age group.