Literature DB >> 29036493

Predicting Remission in Subjects at Clinical High Risk for Psychosis Using Mismatch Negativity.

Minah Kim1, Tak Hyung Lee2, Youngwoo Bryan Yoon2, Tae Young Lee3, Jun Soo Kwon1,2.   

Abstract

Background: The declining transition rate to psychotic disorder and the increasing rate of nonpsychotic poor outcomes among subjects at clinical high risk (CHR) for psychosis have increased the need for biomarkers to predict remission regardless of transition. This study investigated whether mismatch negativity (MMN) predicts the prognosis of CHR individuals during a 6-year follow-up period.
Methods: A total of 47 healthy control (HC) subjects and 48 subjects at CHR for psychosis participated in the MMN assessment. The clinical statuses of the CHR subjects were examined at baseline and regularly for up to 6 years. The CHR subjects were divided into remitter and nonremitter groups, and the baseline MMN amplitudes and latencies were compared across the remitter, nonremitter, and HC groups. Regression analyses were performed to identify the predictive factors of remission, the improvement of attenuated positive symptoms, and functional recovery.
Results: CHR nonremitters showed reduced MMN amplitudes at baseline compared to CHR remitters and HC subjects. A logistic regression analysis revealed that the baseline MMN amplitude at the frontal electrode site was the only significant predictor of remission. In a multiple regression analysis, the MMN amplitude, antipsychotic use, and years of education predicted an improvement in attenuated positive symptoms. The MMN amplitude at baseline predicted functional recovery. Conclusions: These results suggest that MMN is a putative predictor of prognosis regardless of the transition to psychotic disorder in subjects at CHR. Early prognosis prediction and the provision of appropriate interventions based on the initial CHR status might be aided using MMN.

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Year:  2018        PMID: 29036493      PMCID: PMC5890455          DOI: 10.1093/schbul/sbx102

Source DB:  PubMed          Journal:  Schizophr Bull        ISSN: 0586-7614            Impact factor:   9.306


  42 in total

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3.  Individual prediction of long-term outcome in adolescents at ultra-high risk for psychosis: Applying machine learning techniques to brain imaging data.

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4.  Impaired mismatch negativity is associated with current functional status rather than genetic vulnerability to schizophrenia.

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6.  Automatic auditory processing deficits in schizophrenia and clinical high-risk patients: forecasting psychosis risk with mismatch negativity.

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7.  The psychosis threshold in Ultra High Risk (prodromal) research: is it valid?

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9.  Psychosis prediction: stratification of risk estimation with information-processing and premorbid functioning variables.

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10.  Relationship between brain glutamate levels and clinical outcome in individuals at ultra high risk of psychosis.

Authors:  Alice Egerton; James M Stone; Christopher A Chaddock; Gareth J Barker; Ilaria Bonoldi; Rachel M Howard; Kate Merritt; Paul Allen; Oliver D Howes; Robin M Murray; Mary A McLean; David J Lythgoe; Ruth L O'Gorman; Philip K McGuire
Journal:  Neuropsychopharmacology       Date:  2014-06-11       Impact factor: 7.853

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Review 4.  Potential Roles of Redox Dysregulation in the Development of Schizophrenia.

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Review 5.  Forecasting Remission From the Psychosis Risk Syndrome With Mismatch Negativity and P300: Potentials and Pitfalls.

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6.  Thalamocortical dysrhythmia in patients with schizophrenia spectrum disorder and individuals at clinical high risk for psychosis.

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7.  Individualized Prediction of Prodromal Symptom Remission for Youth at Clinical High Risk for Psychosis.

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8.  Counterpoint. Early intervention for psychosis risk syndromes: Minimizing risk and maximizing benefit.

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Journal:  Schizophr Res       Date:  2020-05-10       Impact factor: 4.662

9.  Progressive Impairment of Mismatch Negativity Is Reflective of Underlying Pathophysiological Changes in Patients With First-Episode Psychosis.

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Review 10.  Neuroimaging Markers of Resiliency in Youth at Clinical High Risk for Psychosis: A Qualitative Review.

Authors:  Teresa Vargas; Katherine S F Damme; Arielle Ered; Riley Capizzi; Isabelle Frosch; Lauren M Ellman; Vijay A Mittal
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