scholarly journals Identification of Risk Factors to Predict the Occurrences of Relapses in Individuals with Schizophrenia Spectrum Disorder in Iran

2021 ◽  
Vol 18 (2) ◽  
pp. 546
Author(s):  
Omran Davarinejad ◽  
Tahereh Mohammadi Majd ◽  
Farzaneh Golmohammadi ◽  
Payam Mohammadi ◽  
Farnaz Radmehr ◽  
...  
Keyword(s):  
Risk Factors ◽  
Suicide Attempts ◽  
Disease Onset ◽  
Sudden Onset ◽  
Spectrum Disorder ◽  
Therapeutic Interventions ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
History Of ◽  
Log Normal

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.

Patterns of neuropsychological deficit in cases of schizophrenia spectrum disorder with and without a family history of psychosis

1994 ◽  
Vol 54 (1) ◽  
pp. 37-49 ◽  
Author(s):  
Frederic J. Sautter ◽  
Barbara E. McDermott ◽  
John Cornwell ◽  
F. William Black ◽  
Alicia Borges ◽  
...  
Keyword(s):  
Family History ◽  
Spectrum Disorder ◽  
Schizophrenia Spectrum Disorder ◽  
Neuropsychological Deficit ◽  
Schizophrenia Spectrum ◽  
History Of

Benzodiazepine use among older adults with schizophrenia spectrum disorder: prevalence and associated factors in a multicenter study

2019 ◽  
Vol 32 (4) ◽  
pp. 441-451 ◽  
Author(s):  
Jean-Pierre Schuster ◽  
Nicolas Hoertel ◽  
Armin von Gunten ◽  
Anne-Sophie Seigneurie ◽  
Frédéric Limosin ◽  
...  
Keyword(s):  
Older Patients ◽  
Therapeutic Strategy ◽  
Psychiatric Service ◽  
Spectrum Disorder ◽  
Group Differences ◽  
Short Term ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Benzodiazepine Use ◽  
History Of

ABSTRACTObjectives:Data on psychotropic medications of older patients with schizophrenia spectrum disorder are scarce. Specifically, information about the use of benzodiazepines among older patients with schizophrenia spectrum disorder is very limited. Because benzodiazepine use in older patients has been associated with many disabling side effects, its use in actual practice must be described and questioned. This study aimed at exploring the prevalence of benzodiazepine use and the clinical factors associated with such use among older patients with schizophrenia spectrum disorder.Methods/Design:Data from the Cohort of individuals with Schizophrenia Aged 55 years or more (CSA) were used to examine the prevalence of benzodiazepine use among older patients with schizophrenia spectrum disorder. Demographic and clinical characteristics associated with benzodiazepine prescription were also explored.Results:The prevalence of benzodiazepine use was 29.8% of older patients with schizophrenia spectrum disorder. These patients were significantly more likely to have medical comorbidities, cognitive and social functioning impairments, to report a lifetime history of suicide attempt, to be institutionalized, and to have been hospitalized in a psychiatric service in the past year compared to those without a benzodiazepine prescription (all p<0.05). There were no between-group differences in schizophrenia severity and psychiatric comorbidity.Conclusions:Although it can be hypothesized that benzodiazepine prescription is part of a short-term therapeutic strategy toward patients with more severe trouble or comorbid disorders, our results suggest a strong link between benzodiazepine prescription and a particularly vulnerable subpopulation of older patients with schizophrenia spectrum disorder.

scholarly journals Cognitive motor impairments and brain structure in schizophrenia spectrum disorder patients with a history of catatonia

2020 ◽  
Vol 222 ◽  
pp. 335-341 ◽  
Author(s):  
Derek J. Dean ◽  
Neil Woodward ◽  
Sebastian Walther ◽  
Maureen McHugo ◽  
Kristan Armstrong ◽  
...  
Keyword(s):  
Brain Structure ◽  
Spectrum Disorder ◽  
Motor Impairments ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
History Of

scholarly journals Psychotic-like experiences in the general population: characterizing a high-risk group for psychosis

2010 ◽  
Vol 41 (1) ◽  
pp. 1-6 ◽  
Author(s):  
I. Kelleher ◽  
M. Cannon
Keyword(s):  
Risk Factors ◽  
General Population ◽  
High Risk Group ◽  
Spectrum Disorder ◽  
Psychotic Symptoms ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Related Risk ◽  
Increased Risk ◽  
Social Environmental

Recent research shows that psychotic symptoms, or psychotic-like experiences (PLEs), are reported not only by psychosis patients but also by healthy members of the general population. Healthy individuals who report these symptoms are considered to represent a non-clinical psychosis phenotype, and have been demonstrated to be at increased risk of schizophrenia-spectrum disorder. Converging research now shows that this non-clinical psychosis phenotype is familial, heritable and covaries with familial schizophrenia-spectrum disorder. A review of the research also shows that the non-clinical phenotype is associated extensively with schizophrenia-related risk factors, including social, environmental, substance use, obstetric, developmental, anatomical, motor, cognitive, linguistic, intellectual and psychopathological risk factors. The criterion and construct validity of the non-clinical psychosis phenotype with schizophrenia demonstrates that it is a valid population in which to study the aetiology of psychosis. Furthermore, it suggests shared genetic variation between the clinical and non-clinical phenotypes. Much remains to be learned about psychosis by broadening the scope of research to include the non-clinical psychosis phenotype.

scholarly journals Rates and Risk Factors for Suicide Ideas among Schizophrenia Patients in Indonesia

2019 ◽  
Vol 7 (16) ◽  
pp. 2579-2582
Author(s):  
Nurmiati Amir ◽  
Ronald Antoni ◽  
Asmarahadi Asmarahadi ◽  
Prianto Djatmiko ◽  
Siti Khalimah ◽  
...  
Keyword(s):  
Risk Factors ◽  
Family History ◽  
Suicide Attempts ◽  
Clinical Symptoms ◽  
Demographic Data ◽  
Disease Onset ◽  
Multivariate Logistic Regression Analysis ◽  
High Rate ◽  
Factors Associated ◽  
History Of

BACKGROUND: Schizophrenia is associated with a high rate of suicide. AIM: Our study was aimed to identify the rates of suicide ideas in patients with schizophrenia as well as the risk factors associated with suicide ideas. METHODS: As many as 1130 subjects were evaluated using the Indonesian version of Diagnosis Interview for Psychosis (DIP) to establish the diagnosis of schizophrenia. Subjects aged 18-65 years. The risk factors were socio-demographic data, mental disorder history in the family, clinical symptoms and clinical course of schizophrenia. Risk factors that have the strongest correlation with suicide ideas were analysed using multivariate logistic regression analysis. RESULTS: About 6.1% of subjects reported suicide ideas in their life. The age of disease onset (p = 0.006), family history of schizophrenia (p = 0.013), poor concentration (p = 0.032), loss of enjoyment (p = 0.000), guilty feeling (p = 0.000), family history of mental illness (p = 0.000), nihilistic delusion (p = 0.001) and alcohol abuse (p = 0.000) were significantly associated with suicide ideas. CONCLUSION: Suicide idea is quite common in people with schizophrenia. Evaluation and management of risk factors associated with suicide ideas should be performed to prevent suicide attempts or death. Suicide ideas and risk factors can become clinical parameters in the instrument of suicide prevention.

scholarly journals Acoustic speech markers for schizophrenia-spectrum disorders: a diagnostic and symptom-recognition tool

2021 ◽  
pp. 1-11
Author(s):  
J. N. de Boer ◽  
A. E. Voppel ◽  
S. G. Brederoo ◽  
H. G. Schnack ◽  
K. P. Truong ◽  
...  
Keyword(s):  
Negative Symptoms ◽  
Structured Interview ◽  
Diagnostic Value ◽  
Spectrum Disorder ◽  
Psychotic Symptoms ◽  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum Disorder ◽  
Speech Technology ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders

Abstract Background Clinicians routinely use impressions of speech as an element of mental status examination. In schizophrenia-spectrum disorders, descriptions of speech are used to assess the severity of psychotic symptoms. In the current study, we assessed the diagnostic value of acoustic speech parameters in schizophrenia-spectrum disorders, as well as its value in recognizing positive and negative symptoms. Methods Speech was obtained from 142 patients with a schizophrenia-spectrum disorder and 142 matched controls during a semi-structured interview on neutral topics. Patients were categorized as having predominantly positive or negative symptoms using the Positive and Negative Syndrome Scale (PANSS). Acoustic parameters were extracted with OpenSMILE, employing the extended Geneva Acoustic Minimalistic Parameter Set, which includes standardized analyses of pitch (F0), speech quality and pauses. Speech parameters were fed into a random forest algorithm with leave-ten-out cross-validation to assess their value for a schizophrenia-spectrum diagnosis, and PANSS subtype recognition. Results The machine-learning speech classifier attained an accuracy of 86.2% in classifying patients with a schizophrenia-spectrum disorder and controls on speech parameters alone. Patients with predominantly positive v. negative symptoms could be classified with an accuracy of 74.2%. Conclusions Our results show that automatically extracted speech parameters can be used to accurately classify patients with a schizophrenia-spectrum disorder and healthy controls, as well as differentiate between patients with predominantly positive v. negatives symptoms. Thus, the field of speech technology has provided a standardized, powerful tool that has high potential for clinical applications in diagnosis and differentiation, given its ease of comparison and replication across samples.

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