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

2021 ◽  
Author(s):  
Michelle A Worthington ◽  
Jean Addington ◽  
Carrie E Bearden ◽  
Kristin S Cadenhead ◽  
Barbara A Cornblatt ◽  
...  
Keyword(s):  
High Risk ◽  
Area Under The Curve ◽  
Prodromal Symptom ◽  
Gradient Boosting ◽  
First Episode ◽  
Clinical High Risk ◽  
The North ◽  
Symptom Remission ◽  
Symptomatic Remission ◽  
Individualized Prediction

Abstract The clinical high-risk period before a first episode of psychosis (CHR-P) has been widely studied with the goal of understanding the development of psychosis; however, less attention has been paid to the 75%–80% of CHR-P individuals who do not transition to psychosis. It is an open question whether multivariable models could be developed to predict remission outcomes at the same level of performance and generalizability as those that predict conversion to psychosis. Participants were drawn from the North American Prodrome Longitudinal Study (NAPLS3). An empirically derived set of clinical and demographic predictor variables were selected with elastic net regularization and were included in a gradient boosting machine algorithm to predict prodromal symptom remission. The predictive model was tested in a comparably sized independent sample (NAPLS2). The classification algorithm developed in NAPLS3 achieved an area under the curve of 0.66 (0.60–0.72) with a sensitivity of 0.68 and specificity of 0.53 when tested in an independent external sample (NAPLS2). Overall, future remitters had lower baseline prodromal symptoms than nonremitters. This study is the first to use a data-driven machine-learning approach to assess clinical and demographic predictors of symptomatic remission in individuals who do not convert to psychosis. The predictive power of the models in this study suggest that remission represents a unique clinical phenomenon. Further study is warranted to best understand factors contributing to resilience and recovery from the CHR-P state.

scholarly journals Dysregulation of complement and coagulation pathways: emerging mechanisms in the development of psychosis

2021 ◽  
Author(s):  
Meike Heurich ◽  
Melanie Föcking ◽  
David Mongan ◽  
Gerard Cagney ◽  
David R. Cotter
Keyword(s):  
High Risk ◽  
Psychotic Disorder ◽  
Psychotic Disorders ◽  
Clinical Symptoms ◽  
First Episode Psychosis ◽  
Specific Protein ◽  
First Episode ◽  
Clinical High Risk ◽  
Blood Proteins ◽  
Episode Psychosis

AbstractEarly identification and treatment significantly improve clinical outcomes of psychotic disorders. Recent studies identified protein components of the complement and coagulation systems as key pathways implicated in psychosis. These specific protein alterations are integral to the inflammatory response and can begin years before the onset of clinical symptoms of psychotic disorder. Critically, they have recently been shown to predict the transition from clinical high risk to first-episode psychosis, enabling stratification of individuals who are most likely to transition to psychotic disorder from those who are not. This reinforces the concept that the psychosis spectrum is likely a central nervous system manifestation of systemic changes and highlights the need to investigate plasma proteins as diagnostic or prognostic biomarkers and pathophysiological mediators. In this review, we integrate evidence of alterations in proteins belonging to the complement and coagulation protein systems, including the coagulation, anticoagulation, and fibrinolytic pathways and their dysregulation in psychosis, into a consolidated mechanism that could be integral to the progression and manifestation of psychosis. We consolidate the findings of altered blood proteins relevant for progression to psychotic disorders, using data from longitudinal studies of the general population in addition to clinical high-risk (CHR) individuals transitioning to psychotic disorder. These are compared to markers identified from first-episode psychosis and schizophrenia as well as other psychosis spectrum disorders. We propose the novel hypothesis that altered complement and coagulation plasma levels enhance their pathways’ activating capacities, while low levels observed in key regulatory components contribute to excessive activation observed in patients. This hypothesis will require future testing through a range of experimental paradigms, and if upheld, complement and coagulation pathways or specific proteins could be useful diagnostic or prognostic tools and targets for early intervention and preventive strategies.

Basic symptoms and gray matter volumes of patients at clinical high risk for psychosis

2020 ◽  
pp. 1-9 ◽  
Author(s):  
Daniela Hubl ◽  
Chantal Michel ◽  
Frauke Schultze-Lutter ◽  
Martinus Hauf ◽  
Benno G. Schimmelmann ◽  
...  
Keyword(s):  
High Risk ◽  
Gray Matter ◽  
First Episode ◽  
Clinical High Risk ◽  
Significant Group ◽  
Basic Symptoms ◽  
Conversion Rates ◽  
Episode Psychosis ◽  
Ultra High Risk ◽  
Gray Matter Volumes

Abstract Background Clinical high-risk (CHR) for psychosis is indicated by ultra-high risk (UHR) and basic symptom (BS) criteria; however, conversion rates are highest when both UHR and BS criteria are fulfilled (UHR&BS). While BSs are considered the most immediate expression of neurobiological aberrations underlying the development of psychosis, research on neurobiological correlates of BS is scarce. Methods We investigated gray matter volumes (GMV) of 20 regions of interest (ROI) previously associated with UHR criteria in 90 patients from the Bern early detection service: clinical controls (CC), first-episode psychosis (FEP), UHR, BS and UHR&BS. We expected lowest GMV in FEP and UHR&BS, and highest volume in CC with UHR and BS in-between. Results Significantly, lower GMV was detected in FEP and UHR&BS patients relative to CC with no other significant between-group differences. When ROIs were analyzed separately, seven showed a significant group effect (FDR corrected), with five (inferior parietal, medial orbitofrontal, lateral occipital, middle temporal, precuneus) showing significantly lower GM volume in the FEP and/or UHR&BS groups than in the CC group (Bonferroni corrected). In the CHR group, only COGDIS scores correlated negatively with cortical volumes. Conclusions This is the first study to demonstrate that patients who fulfill both UHR and BS criteria – a population that has been associated with higher conversion rates – exhibit more severe GMV reductions relative to those who satisfy BS or UHR criteria alone. This result was mediated by the BS in the UHR&BS group, as only the severity of BS was linked to GMV reductions.

scholarly journals Prediction of Adverse Events in Stable Non-Variceal Gastrointestinal Bleeding Using Machine Learning

2020 ◽  
Vol 9 (8) ◽  
pp. 2603 ◽  
Author(s):  
Dong-Woo Seo ◽  
Hahn Yi ◽  
Beomhee Park ◽  
Youn-Jung Kim ◽  
Dae Ho Jung ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Risk ◽  
Adverse Events ◽  
Gastrointestinal Bleeding ◽  
Area Under The Curve ◽  
Scoring Systems ◽  
Hemodynamic Instability ◽  
Machine Learning Algorithms ◽  
Gradient Boosting ◽  
Importance Analysis

Clinical risk-scoring systems are important for identifying patients with upper gastrointestinal bleeding (UGIB) who are at a high risk of hemodynamic instability. We developed an algorithm that predicts adverse events in patients with initially stable non-variceal UGIB using machine learning (ML). Using prospective observational registry, 1439 out of 3363 consecutive patients were enrolled. Primary outcomes included adverse events such as mortality, hypotension, and rebleeding within 7 days. Four machine learning algorithms, namely, logistic regression with regularization (LR), random forest classifier (RF), gradient boosting classifier (GB), and voting classifier (VC), were compared with the Glasgow–Blatchford score (GBS) and Rockall scores. The RF model showed the highest accuracies and significant improvement over conventional methods for predicting mortality (area under the curve: RF 0.917 vs. GBS 0.710), but the performance of the VC model was best in hypotension (VC 0.757 vs. GBS 0.668) and rebleeding within 7 days (VC 0.733 vs. GBS 0.694). Clinically significant variables including blood urea nitrogen, albumin, hemoglobin, platelet, prothrombin time, age, and lactate were identified by the global feature importance analysis. These results suggest that ML models will be useful early predictive tools for identifying high-risk patients with initially stable non-variceal UGIB admitted at an emergency department.

Reduced P3a amplitudes in antipsychotic naïve first-episode psychosis patients and individuals at clinical high-risk for psychosis

2013 ◽  
Vol 47 (6) ◽  
pp. 755-761 ◽  
Author(s):  
Alejandra Mondragón-Maya ◽  
Rodolfo Solís-Vivanco ◽  
Pablo León-Ortiz ◽  
Yaneth Rodríguez-Agudelo ◽  
Guillermina Yáñez-Téllez ◽  
...  
Keyword(s):  
High Risk ◽  
First Episode Psychosis ◽  
First Episode ◽  
Clinical High Risk ◽  
Episode Psychosis

scholarly journals O8.4. CORTICAL DOPAMINE RELEASE IN RESPONSE TO A COGNITIVE CHALLENGE: PRELIMINARY RESULTS IN FIRST EPISODE PSYCHOSIS AND CLINICAL HIGH RISK

2019 ◽  
Vol 45 (Supplement_2) ◽  
pp. S184-S184
Author(s):  
Abanti Tagore ◽  
Naren Rao ◽  
Christin Schifani ◽  
Huai-Hsuan Tseng ◽  
Pablo Rusjan ◽  
...  
Keyword(s):  
High Risk ◽  
Dopamine Release ◽  
First Episode Psychosis ◽  
First Episode ◽  
Clinical High Risk ◽  
Preliminary Results ◽  
Episode Psychosis ◽  
Cognitive Challenge

scholarly journals T39. IMPAIRED SENSORIMOTOR GATING USING THE ACOUSTIC PREPULSE INHIBITION PARADIGM IN INDIVIDUALS AT A CLINICAL HIGH RISK FOR PSYCHOSIS

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S246-S246
Author(s):  
Qijing Bo ◽  
Zhen Mao ◽  
Qing Tian ◽  
Weidi Li ◽  
Lei Zhao ◽  
...  
Keyword(s):  
High Risk ◽  
Prepulse Inhibition ◽  
Clinical Characteristics ◽  
Sensorimotor Gating ◽  
Spatial Separation ◽  
Structured Interview ◽  
First Episode ◽  
Clinical High Risk ◽  
Neurocognitive Functions ◽  
First Episode Schizophrenia

Abstract Background Many robust studies on prepulse inhibition (PPI) were conducted in patients with schizophrenia, and, increasingly, evidence has indicated individuals who are at clinical high risk for psychosis (CHR). The specificity of the PPI is insufficient with the classic paradigm. The current study investigated an improved perceived spatial separation PPI (PSSPPI) paradigm in CHR individuals, compared with patients of first-episode schizophrenia (FES) and healthy controls (HC), and the relationship between PPI, demographics, clinical characteristics, and cognitive performance. Methods We included 53 FESs, 55 CHR individuals, and 53 HCs. CHRs were rated on the Structured Interview for Prodromal Syndromes (SIPS). The prepulse inhibition measures of perceived spatial co-location PPI (PSCPPI) and PSSPPI paradigms were applied using 60- and 120-ms lead intervals. The MATRICS Consensus Cognitive Battery (MCCB) was used to assess neurocognitive functions. Results Compared with HC, the CHR group had lower PSSPPI level (ISI=60 ms, P<0.001; ISI=120 ms, P<.001). PSSPPI showed a large effect size (ES) between CHR and HC (ISI=60 ms, ES=0.91; ISI=120 ms, ES=0.98); on PSSPPI using 60-ms lead interval, ES ranged from small to large from CHR to FES. PPI deficits in CHR were unrelated to demographics, clinical characteristics, and cognition. Discussion CHR individuals show a sensorimotor gating deficit similar to FES patients on PSSPPI of the startle response, with greater sensitivity than the classic PPI paradigm. PSSPPI appears a promising objective approach for identifying individuals at clinical high risk for psychosis related to a high risk of transition to schizophrenia.

scholarly journals 117.3 Imaging Microglial Activation in Clinical High Risk for Psychosis and Untreated First-Episode Psychosis: A PET StudyW [18F]FEPPA

2017 ◽  
Vol 43 (suppl_1) ◽  
pp. S64-S64 ◽  
Author(s):  
Romina Mizrahi ◽  
Sina Hafizi ◽  
Cory Gerritsen ◽  
Michael Kiang ◽  
Michael Bargby ◽  
...  
Keyword(s):  
High Risk ◽  
Microglial Activation ◽  
First Episode Psychosis ◽  
First Episode ◽  
Clinical High Risk ◽  
Episode Psychosis

scholarly journals Facial affect recognition in individuals at clinical high risk for psychosis

2008 ◽  
Vol 192 (1) ◽  
pp. 67-68 ◽  
Author(s):  
Jean Addington ◽  
David Penn ◽  
Scott W. Woods ◽  
Donald Addington ◽  
Diana O. Perkins
Keyword(s):  
High Risk ◽  
Facial Affect ◽  
First Episode ◽  
Affect Recognition ◽  
Facial Affect Recognition ◽  
Clinical High Risk ◽  
Identification Task ◽  
Episode Psychosis ◽  
Patient Groups ◽  
Better Than

SummaryFacial affect discrimination and identification were assessed in 86 clinical high-risk individuals and compared with 50 individuals with first-episode psychosis, 53 with multiepisode schizophrenia and 55 non-psychiatric controls. On the identification task the non-psychiatric controls performed significantly better than all other groups, and on discrimination significantly better than both patient groups. Deficits in facial affect recognition appear to be present before the onset of psychosis and may be a vulnerability marker.

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