Identification of Risk Factors to Predict the Occurrences of Relapses in Individuals with Schizophrenia Spectrum Disorder in Iran.
predictions
relapse
schizophrenia spectrum disorder
treatment adherence
Journal
International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455
Informations de publication
Date de publication:
11 01 2021
11 01 2021
Historique:
received:
16
11
2020
revised:
29
12
2020
accepted:
31
12
2020
entrez:
14
1
2021
pubmed:
15
1
2021
medline:
19
3
2021
Statut:
epublish
Résumé
Schizophrenia Spectrum Disorder (SSD) is a chronic psychiatric disorder with a modest treatment outcome. In addition, relapses are commonplace. Here, we sought to identify factors that predict relapse latency and frequency. To this end, we retrospectively analyzed data for individuals with SSD. Medical records of 401 individuals with SSD were analyzed (mean age: 25.51 years; 63.6% males) covering a five-year period. Univariate and multivariate Penalized Likelihood Models with Shared Log-Normal Frailty were used to determine the correlation between discharge time and relapse and to identify risk factors. A total of 683 relapses were observed in males, and 422 relapses in females. The Relapse Hazard Ratio (RHR) decreased with age (RHR = 0.99, CI: (0.98-0.998)) and with participants' adherence to pharmacological treatment (HR = 0.71, CI: 0.58-0.86). In contrast, RHR increased with a history of suicide attempts (HR = 1.32, CI: 1.09-1.60), and a gradual compared to a sudden onset of disease (HR = 1.45, CI: 1.02-2.05). Gender was not predictive. Data indicate that preventive and therapeutic interventions may be particularly important for individuals who are younger at disease onset, have a history of suicide attempts, have experienced a gradual onset of disease, and have difficulties adhering to medication.
Identifiants
pubmed: 33440817
pii: ijerph18020546
doi: 10.3390/ijerph18020546
pmc: PMC7827717
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
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