Development of a suspicion index for secondary schizophrenia using the Delphi method

2021 ◽  
pp. 000486742110257
Author(s):  
Olivier Bonnot ◽  
Jose Luis Insua ◽  
Mark Walterfang ◽  
Juan Vincente Torres ◽  
Stefan Armin Kolb
Keyword(s):  
Clinical Practice ◽  
Sensitivity And Specificity ◽  
Delphi Method ◽  
Schizophrenia Spectrum Disorders ◽  
Differential Distribution ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders ◽  
Aids Diagnosis ◽  
Suspicion Index

Aim: The aim of this study was to develop a suspicion index that aids diagnosis of secondary schizophrenia spectrum disorders in regular clinical practice. Method: We used the Delphi method to rate and refine questionnaire items in consecutive rounds. Differences in mean expert responses for schizophrenia spectrum disorders and secondary schizophrenia spectrum disorders populations allowed to define low/middle/high predictive items, which received different weights. Algorithm performance was tested in 198 disease profiles by means of sensitivity and specificity. Results: Twelve experts completed the Delphi process, and consensus was reached in 19/24 (79.2%) items for schizophrenia spectrum disorders and 17/24 (70.8%) for secondary schizophrenia spectrum disorders. We assigned rounded values to each item category according to their predictive potential. A differential distribution of scores was observed between schizophrenia spectrum disorders and secondary schizophrenia spectrum disorders when applying the suspicion index for validation to 198 disease profiles. Sensitivity and specificity analyses allowed to set a >8/10/16 risk prediction score as a threshold to consider medium/high/very high suspicion of secondary schizophrenia spectrum disorders. Conclusion: Our final outcome was the Secondary Schizophrenia Suspicion Index, the first paper-based and reliable algorithm to discriminate secondary schizophrenia spectrum disorders from schizophrenia spectrum disorders with the potential to help improve the detection of secondary schizophrenia spectrum disorder cases in clinical practice.

Sleep and cognition in schizophrenia spectrum disorders: A systematic review protocol.

2020 ◽  
Author(s):  
Sean Carruthers ◽  
Gemma Brunetti ◽  
Susan Rossell
Keyword(s):  
Systematic Review ◽  
Mental Illnesses ◽  
Schizophrenia Spectrum Disorders ◽  
Systematic Review Protocol ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Review Protocol ◽  
Spectrum Disorders ◽  
Sleep And Cognition ◽  
The Relationship

Schizophrenia spectrum disorders are chronic and debilitating mental illnesses characterised by both cognitive impairments and sleep deficits. In this systematic review protocol, we outline an approach to examine the available literature investigating the relationship between sleep and cognition in individuals with schizophrenia spectrum disorder.

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.

Traumatic stress and risk of severe mental illness: A nationwide cohort study

2016 ◽  
Vol 33 (S1) ◽  
pp. S92-S92
Author(s):  
N. Okkels ◽  
B. Trabjerg ◽  
M. Arendt ◽  
C. Bøcker Pedersen
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Mood Disorder ◽  
Posttraumatic Stress ◽  
Traumatic Stress ◽  
Stress Disorder ◽  
Spectrum Disorder ◽  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders

IntroductionA history of traumatic events is prevalent in people with schizophrenia spectrum disorders and mood disorders. However, little is known about their etiological relationship.ObjectivesTo explore whether patients with acute or posttraumatic stress disorder are at higher risk of developing a schizophrenia spectrum disorder or mood disorder.MethodsIn this prospective cohort study using registers covering the entire Danish population, we used the Danish Psychiatric Central Research Register to identify patients with ICD-10 diagnoses of acute traumatic stress disorder and/or posttraumatic stress disorder. From inpatient and outpatient mental hospitals, we identified 4371 diagnoses with more than 18 million years of follow-up. Main outcomes and measures were relative risks (RR) with 95% confidence intervals (95% CI) of schizophrenia, schizophrenia spectrum disorder, bipolar disorder and mood disorder.ResultsThe incidence of traumatic stress disorder (TSD) has increased steadily from 0.6% in 1996 to 6% in 2012, showed a higher incidence in women and an age distribution with a peak-incidence in early adulthood. We found that diagnoses of TSD increase the risk of schizophrenia (RR 5.85, 95% CI 3.59–8.91), schizophrenia spectrum disorder (RR 3.82, 95% CI 2.38–5.75), bipolar disorder (RR 5.83, 95% CI 3.11–9.83) and mood disorder (RR 4.10, 95% CI 3.15–5.22). Risks were high in the first year after diagnosis of TSD and declined going forward in time.ConclusionsOur findings indicate that acute and posttraumatic stress disorder are etiological risk factors for schizophrenia spectrum disorders and mood disorders. If replicated, this may underline treatment of traumatized patients in prevention of severe mental disorder.Disclosure of interestThe authors have not supplied their declaration of competing interest.

The diagnostic boundary between autism spectrum disorder, intellectual developmental disorder and schizophrenia spectrum disorders

2015 ◽  
Vol 9 (5) ◽  
pp. 243-264 ◽  
Author(s):  
Marco O. Bertelli ◽  
Micaela Piva Merli ◽  
Elspeth Bradley ◽  
Roberto Keller ◽  
Niccolò Varrucciu ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Clinical Practice ◽  
Developmental Disorder ◽  
Clinical Presentation ◽  
Autism Spectrum ◽  
Schizophrenia Spectrum Disorders ◽  
Content Type ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders ◽  
Intellectual Developmental Disorder

Purpose – During the last few years the prevalence of autism and Autism Spectrum Disorder (ASD) has increased greatly. A recurring issue is the overlap and boundaries between Intellectual Developmental Disorder (IDD), ASD and Schizophrenia Spectrum Disorders (SSD). In clinical practice with people with IDD, the alternative or adjunctive diagnosis of ASD or SSD is particularly challenging. The purpose of this paper is to define the boundaries and overlapping clinical characteristics of IDD, ASD and SSD; highlight the most relevant differences in clinical presentation; and provide a clinical framework within which to recognize the impact of IDD and ASD in the diagnosis of SSD. Design/methodology/approach – A systematic mapping of the international literature was conducted on the basis of the following questions: first, what are considered to be core and overlapping aspects of IDD, ASD and SSD; second, what are the main issues in clinical practice; and third, can key diagnostic flags be identified to assist in differentiating between the three diagnostic categories? Findings – Crucial clinical aspects for the differentiation resulted to be age of onset, interest towards others, main positive symptoms, and anatomical anomalies of the central nervous system. More robust diagnostic criteria and semeiological references are desirable. Originality/value – The present literature mapping provides a comprehensive description of the most relevant differences in the clinical presentation of ASD and SSD in persons with IDD.

scholarly journals Latent class analysis identified phenotypes in individuals with schizophrenia spectrum disorder who engage in aggressive behaviour towards others

2019 ◽  
Vol 60 ◽  
pp. 86-96 ◽  
Author(s):  
S. Lau ◽  
M.P. Günther ◽  
S. Kling ◽  
J. Kirchebner
Keyword(s):  
Latent Class Analysis ◽  
Aggressive Behaviour ◽  
Latent Class ◽  
Class Analysis ◽  
Schizophrenia Spectrum Disorders ◽  
Case Histories ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Similarities And Differences ◽  
Spectrum Disorders

AbstractPrior research on Hodgins’ (2008) typology of offenders with schizophrenia spectrum disorders (SSD) has revealed inconsistencies in the number of subgroups and the operationalization of the concept. This study addressed these inconsistencies by applying latent class analysis (LCA) based on the most frequently explored variables in prior research. This novel case-centred methodology identified similarities and differences between the subjects contained in the sample instead of the variables explored. The LCA was performed on 71 variables taken from data on a previously unstudied sample of 370 case histories of offenders with SSD in a centre for inpatient forensic therapies in Switzerland. Results were compared with Hodgins’ theoretically postulated patient typologies and confirm three separate homogeneous classes of schizophrenic delinquents. Previous inconsistencies and differences in operationalizations of the typology of offenders with SDD to be found in the literature are discussed.

scholarly journals Upregulation of sICAM-1 and sVCAM-1 Levels in the Cerebrospinal Fluid of Patients with Schizophrenia Spectrum Disorders

2020 ◽  
Author(s):  
Sophie Meixensberger ◽  
Hanna Kuzior ◽  
Bernd Fiebich ◽  
Patrick Süß ◽  
Kimon Runge ◽  
...  
Keyword(s):  
Cell Adhesion ◽  
Adhesion Molecules ◽  
Cell Adhesion Molecules ◽  
Unipolar Depression ◽  
Spectrum Disorder ◽  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders ◽  
Pai 1

Abstract IntroductionImmunological explanatory approaches are becoming increasingly important in schizophrenia research. In this context, the function of the blood–brain barrier (BBB) and the blood–cerebrospinal fluid (CSF) barrier (BCSFB) play an essential role. Different adhesion molecules, such as intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), are key elements in sustaining the integrity of the BBB and BCSFB. The objectives of this study were (1) to compare the levels of different cell adhesion molecules in the CSF of patients with schizophrenia spectrum disorders to those of patients with unipolar depression and (2) to analyze their association with the established markers of the BBB/BCSFB function (total protein and albumin quotient [AQ]).Patients and methodsA total of 40 patients with schizophrenia spectrum disorder and 39 age- and sex-matched control patients with unipolar depression were analyzed. The levels of soluble ICAM-1 (s-ICAM-1), soluble VCAM-1 (s-VCAM-1), and plasminogen activator inhibitor 1 (PAI-1) in the CSF were measured using a magnetic bead multiplexing immunoassay.ResultsThe levels of sICAM-1 (p<0.001), sVCAM-1 (p<0.001), and PAI-1 (p<0.001) in the CSF were significantly higher in patients with schizophrenia spectrum disorder than in patients with unipolar depression. Correlation analyses revealed a significant correlation of protein concentrations with sVCAM-1 levels (r=0.505, p=0.001) and of AQs with the sVCAM-1 (r=0.583, p<0.001) and PAI-1 (r=0.337, p=0.033) levels in patients with schizophrenia.LimitationThe significance of the study is limited by the retrospective research design and by the absence of a healthy control group. The assay used was not previously established for the measurement of CSF.DiscussionResults revealed that sICAM-1 and sVCAM-1 levels in the CSF are higher in patients with schizophrenia spectrum disorder than in patients with depression. These circulating signaling molecules may indicate endothelial dysfunction causing impaired BBB/BCSFB function in patients with schizophrenia spectrum disorders. Consistent with this view, a highly significant correlation of sVCAM-1 with CSF protein and AQs was detected. Upregulation of these cell adhesion molecules might be indicative of a proinflammatory immune response underlying the BBB/BCSFB disturbance in a subgroup of patients with schizophrenia spectrum disorders. Further translational and controlled studies on the role of different cell adhesion molecules in schizophrenia are needed.

scholarly journals Switching antipsychotics: Results of 16-month non-interventional, prospective, observational clinical research of inpatients with schizophrenia spectrum disorders

2017 ◽  
Vol 67 (1) ◽  
pp. 99-112
Author(s):  
Cvetka Bačar Bole ◽  
Mitja Pišlar ◽  
Metka Šen ◽  
Rok Tavčar ◽  
Aleš Mrhar
Keyword(s):  
Clinical Practice ◽  
Psychiatric Hospital ◽  
Adverse Reactions ◽  
Treatment Strategies ◽  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum ◽  
Switching Patterns ◽  
Common Causes ◽  
Spectrum Disorders ◽  
Switching Strategies

AbstractThe study aims to identify prescribing and switching patterns of antipsychotics in clinical practice. A 16-month, prospective study was conducted at the Psychiatric Hospital Idrija, Slovenia. Inpatients (N = 311) with schizophrenia spectrum disorders were observed. The causes for switching antipsychotics and switching strategies were analyzed. Analyzing a total of 3954 prescriptions, the collected data confirmed that treatment strategies in this psychiatric hospital are very complex. It was found that 37 percent of inpatients had at least one switch. Moreover, switches that included three or more antipsychotics were detected. The most common causes for switching antipsychotics were adverse reactions and inefficacy or lack of efficacy. Among switching options, abrupt switch was recorded several times. As some patients are receiving several antipsychotics at the same time, it is possible that unusual switching occurs in clinical practice. It seems that the choice of switching strategy is also affected by the cause and urgency for switching an antipsychotic.

Premorbid cannabis use is associated with more symptoms and poorer functioning in schizophrenia spectrum disorder

2016 ◽  
Vol 46 (15) ◽  
pp. 3127-3136 ◽  
Author(s):  
P. A. Ringen ◽  
R. Nesvåg ◽  
S. Helle ◽  
T. V. Lagerberg ◽  
E. H. Lange ◽  
...  
Keyword(s):  
Substance Use ◽  
Age At Onset ◽  
Cannabis Use ◽  
Spectrum Disorder ◽  
Psychotic Symptoms ◽  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Premorbid Functioning ◽  
Spectrum Disorders

BackgroundCannabis use disorder is associated with an earlier age at onset and a more severe outcome of schizophrenia spectrum disorders. The role of cannabis use before the onset of illness (premorbid cannabis use) has not been fully investigated. We here examined how amount and type of premorbid cannabis use was associated with the later course of illness including current substance use, symptoms and level of functioning in schizophrenia spectrum disorder.MethodWe used a naturalistic sample of patients with DSM-IV schizophrenia spectrum disorders with a comprehensive history of illness and substance use. Data on premorbid substance use was obtained from comprehensive self-report. The relationship to outcome was investigated using regression models that included current substance use and premorbid functioning.ResultsPre-schizophrenia cannabis use was significantly associated with more severe psychotic symptoms and impaired functioning. Higher levels of premorbid cannabis use were associated with higher levels of current psychotic symptoms. These associations were independent of current substance use and premorbid functioning. Early use of cannabis (age <17 years) was associated with earlier age at onset of psychosis, independently of potential confounders.ConclusionsPre-psychosis cannabis use affects illness outcome in schizophrenia spectrum disorders, and is associated with lower age at onset of psychosis. These findings of independent negative effects of premorbid cannabis use in schizophrenia suggest that a limitation of the general use of cannabis may have beneficial health effects.

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