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Prevention strategies in clinical high-risks states for psychotic disorders: weighing up costs and benefits
ABSTRACT: Today, the indicated prevention of psychosis prior to its first episode is mainly based on clinical high-risk of psychosis (CHR) criteria, namely ultra-high risk criteria and basic symptom criteria. These are associated with conversion-to-psychosis rates of about 30% within three years. Th...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Cambridge University Press
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10417624/ http://dx.doi.org/10.1192/j.eurpsy.2023.118 |
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author | Schultze-Lutter, F. |
author_facet | Schultze-Lutter, F. |
author_sort | Schultze-Lutter, F. |
collection | PubMed |
description | ABSTRACT: Today, the indicated prevention of psychosis prior to its first episode is mainly based on clinical high-risk of psychosis (CHR) criteria, namely ultra-high risk criteria and basic symptom criteria. These are associated with conversion-to-psychosis rates of about 30% within three years. Thus, many patients meeting CHR criteria will not progress to psychosis over a medium-term period, and the cost-benefit evaluation of CHR states is always complicated by the largely unknown individual psychosis risk of CHR patients. In consequence, for the lesser risk of adverse events, treatment recommendations commonly favour non-pharmacological strategies, in particular cognitive-behavioural psychotherapy. Yet, individual risk estimation in identified CHR patients is increasingly done with help of machine learning algorithms, which might help to identify CHR patients who would greatly benefit from an additional pharmacological intervention with low-dose antipsychotics. The presentation will discuss the evidence-base of such a multistep, machine learning informed prevention strategy. DISCLOSURE OF INTEREST: None Declared |
format | Online Article Text |
id | pubmed-10417624 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-104176242023-08-12 Prevention strategies in clinical high-risks states for psychotic disorders: weighing up costs and benefits Schultze-Lutter, F. Eur Psychiatry Abstract ABSTRACT: Today, the indicated prevention of psychosis prior to its first episode is mainly based on clinical high-risk of psychosis (CHR) criteria, namely ultra-high risk criteria and basic symptom criteria. These are associated with conversion-to-psychosis rates of about 30% within three years. Thus, many patients meeting CHR criteria will not progress to psychosis over a medium-term period, and the cost-benefit evaluation of CHR states is always complicated by the largely unknown individual psychosis risk of CHR patients. In consequence, for the lesser risk of adverse events, treatment recommendations commonly favour non-pharmacological strategies, in particular cognitive-behavioural psychotherapy. Yet, individual risk estimation in identified CHR patients is increasingly done with help of machine learning algorithms, which might help to identify CHR patients who would greatly benefit from an additional pharmacological intervention with low-dose antipsychotics. The presentation will discuss the evidence-base of such a multistep, machine learning informed prevention strategy. DISCLOSURE OF INTEREST: None Declared Cambridge University Press 2023-07-19 /pmc/articles/PMC10417624/ http://dx.doi.org/10.1192/j.eurpsy.2023.118 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Abstract Schultze-Lutter, F. Prevention strategies in clinical high-risks states for psychotic disorders: weighing up costs and benefits |
title | Prevention strategies in clinical high-risks states for psychotic disorders: weighing up costs and benefits |
title_full | Prevention strategies in clinical high-risks states for psychotic disorders: weighing up costs and benefits |
title_fullStr | Prevention strategies in clinical high-risks states for psychotic disorders: weighing up costs and benefits |
title_full_unstemmed | Prevention strategies in clinical high-risks states for psychotic disorders: weighing up costs and benefits |
title_short | Prevention strategies in clinical high-risks states for psychotic disorders: weighing up costs and benefits |
title_sort | prevention strategies in clinical high-risks states for psychotic disorders: weighing up costs and benefits |
topic | Abstract |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10417624/ http://dx.doi.org/10.1192/j.eurpsy.2023.118 |
work_keys_str_mv | AT schultzelutterf preventionstrategiesinclinicalhighrisksstatesforpsychoticdisordersweighingupcostsandbenefits |