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854 – A Logistic Regression Model For Global Functioning In Psychosis
Published online by Cambridge University Press: 15 April 2020
Abstract
In order to improve global functioning in psychotic patients is necessary to know the kind of variables influencing those.
To research that of a clinical and epidemiological variables group which of them are associated to a better outcome in global functioning in patients affected by psychosis.
A total of 73 psychotic patients were included in this study. All of them were evaluated through a battery of tests including GAF and SIX, PANSS, S-GPTS and a comprehensive questionnaire for clinical and epidemiological variables. A binary logistic regression analysis was applied to the data set of global functioning scores divided by the median in two halves: better and worse global functioning. The model included the following variables: positive, negative and general psychopatology PANSS subscales, PANSS subtype, first or second generation antipsychotic, stimulants drugs use, tobacco use, sex, age, onset age, number of psychotic episodes and S-GPTS score.
Treatment with second generation antipsychotics and lesser scoring in S-GPTS scale were associated with a better outcomes in global functioning. We found an association between lesser negative symptoms and lesser number of psychotic episodes with a better functioning which showed a marginal statistical significance.
We raise the question about preferential use of second generation of antipsychotics as opposed to older antipsychotics and the necessity of improving adherence to treatment for breaking the vicious cycle between psychotic episodes and a worse global functioning. Further studies with greater sample are needed to explain these and another questions.
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- Information
- European Psychiatry , Volume 28 , Issue S1: Abstracts of the 21th European Congress of Psychiatry , 2013 , 28-E313
- Copyright
- Copyright © European Psychiatric Association 2013
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