Publications by authors named "Dominic Oliver"

34 Publications

Universal and Selective Interventions to Prevent Poor Mental Health Outcomes in Young People: Systematic Review and Meta-analysis.

Harv Rev Psychiatry 2021 May-Jun 01;29(3):196-215

From the Early Psychosis: Interventions and Clinical-Detection (EPIC) Laboratory, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London (Drs. Salazar de Pablo, De Micheli, Catalan, Verdino, Di Maggio, Radua, Provenzani, Montealegre, Signorini, and Fusar-Poli, and Mr. Oliver); Departments of Child and Adolescent Psychiatry (Dr. Salazar de Pablo) and of Psychosis Studies (Drs. Bonoldi and Baccaredda Boy), Institute of Psychiatry, Psychology & Neuroscience, King's College London; Institute of Psychiatry and Mental Health. Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), CIBERSAM, Madrid (Drs. Salazar de Pablo and Arango); National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London (Drs. De Micheli and Fusar-Poli); Department of Brain and Behavioral Sciences, University of Pavia (Drs. Di Maggio, Provenzani, Ruzzi, Calorio, Nosari, Di Marco, Famularo, Molteni, Filosi, Mensi, Balottin, Politi, and Fusar-Poli); Neurosciences Department, University of Padova (Dr. Solmi); Mental Health Department, Biocruces Bizkaia Health Research Institute, Basurto University Hospital, Facultad de Medicina y Odontología, Campus de Leioa, University of the Basque Country, UPV/EHU, Barakaldo, Bizkaia, Spain (Dr. Catalan); Department of Molecular and Developmental Medicine, Division of Psychiatry, University of Siena (Dr. Verdino); Imaging of Mood- and Anxiety-Related Disorders (IMARD) group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona (Dr. Radua); Department of Clinical Neuroscience, Centre for Psychiatric Research and Education, Karolinska Institutet, Stockholm (Dr. Radua); Scientific Institute for Research, Hospitalization and Healthcare (IRCCS) Mondino Foundation, Child and Adolescent Neuropsychiatric Unit (Dr. Mensi); Department of Paediatrics, Yonsei University College of Medicine, Seoul (Dr. Shin); Zucker Hillside Hospital, Department of Psychiatry, Northwell Health, Glen Oaks, NY (Dr. Correll); Department of Psychiatry and Molecular Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY (Dr. Correll); Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY (Dr. Correll); Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin Berlin (Dr. Correll); OASIS service, South London and Maudsley NHS Foundation Trust, London (Dr. Fusar-Poli).

Background: Much is not known about the efficacy of interventions to prevent poor mental health outcomes in young people by targeting either the general population (universal prevention) or asymptomatic individuals with high risk of developing a mental disorder (selective prevention).

Methods: We conducted a PRISMA/MOOSE-compliant systematic review and meta-analysis of Web of Science to identify studies comparing post-test efficacy (effect size [ES]; Hedges' g) of universal or selective interventions for poor mental health outcomes versus control groups, in samples with mean age <35 years (PROSPERO: CRD42018102143). Measurements included random-effects models, I2 statistics, publication bias, meta-regression, sensitivity analyses, quality assessments, number needed to treat, and population impact number.

Results: 295 articles (447,206 individuals; mean age = 15.4) appraising 17 poor mental health outcomes were included. Compared to control conditions, universal and selective interventions improved (in descending magnitude order) interpersonal violence, general psychological distress, alcohol use, anxiety features, affective symptoms, other emotional and behavioral problems, consequences of alcohol use, posttraumatic stress disorder features, conduct problems, tobacco use, externalizing behaviors, attention-deficit/hyperactivity disorder features, and cannabis use, but not eating-related problems, impaired functioning, internalizing behavior, or sleep-related problems. Psychoeducation had the highest effect size for ADHD features, affective symptoms, and interpersonal violence. Psychotherapy had the highest effect size for anxiety features.

Conclusion: Universal and selective preventive interventions for young individuals are feasible and can improve poor mental health outcomes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/HRP.0000000000000294DOI Listing
May 2021

Third external replication of an individualised transdiagnostic prediction model for the automatic detection of individuals at risk of psychosis using electronic health records.

Schizophr Res 2021 02 5;228:403-409. Epub 2021 Feb 5.

Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom; OASIS Service, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.

Background: Primary indicated prevention is a key target for reducing the incidence and burden of schizophrenia and related psychotic disorders. An individualised, clinically-based transdiagnostic model for the detection of individuals at risk of psychosis has been developed and validated in two large, urban healthcare providers. We tested its external validity in a geographically and demographically different non-urban population.

Method: Retrospective EHR cohort study. All individuals accessing secondary healthcare provided by Oxford Health NHS Foundation Trust between 1st January 2011 and 30th November 2019 and receiving a primary index diagnosis of a non-psychotic or non-organic mental disorder were considered eligible. The previously developed model was applied to this database and its external prognostic accuracy was measured with Harrell's C.

Findings: The study included n = 33,710 eligible individuals, with an average age of 27.7 years (SD = 19.8), mostly white (92.0%) and female (57.3%). The mean follow-up was 1863.9 days (SD = 948.9), with 868 transitions to psychosis and a cumulative incidence of psychosis at 6 years of 2.9% (95%CI: 2.7-3.1). Compared to the urban development database, Oxford Health was characterised by a relevant case mix, lower incidence of psychosis, different distribution of baseline predictors, higher proportion of white females, and a lack of specialised clinical services for at risk individuals. Despite these differences the model retained an adequate prognostic performance (Harrell's C = 0.79, 95%CI: 0.78-0.81), with no major miscalibration.

Interpretation: The transdiagnostic, individualised, clinically-based risk calculator is transportable outside urban healthcare providers. Further research should test transportability of this risk prediction model in an international setting.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.schres.2021.01.005DOI Listing
February 2021

The case for improved transdiagnostic detection of first-episode psychosis: Electronic health record cohort study.

Schizophr Res 2021 02 22;228:547-554. Epub 2020 Nov 22.

Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.

Background: Improving outcomes of a First Episode of Psychosis (FEP) relies on the ability to detect most individuals with emerging psychosis and treat them in specialised Early Intervention (EI) services. Efficacy of current detection strategies is undetermined.

Methods: RECORD-compliant clinical, 6-year, retrospective, transdiagnostic, lifespan-inclusive, Electronic Health Record (EHR) cohort study, representing real-world secondary mental healthcare in South London and Maudsley (SLaM) NHS. All individuals accessing SLaM in the period 2007-2017 and receiving any ICD-10 diagnosis other than persistent psychosis were included. Descriptive statistics, Kaplan-Meier curves, logistic regression, epidemiological incidence of psychosis in the general population were used to address pathways to care and detection power of EI services for FEP.

Results: A total of 106,706 individuals underwent the 6-year follow-up: they were mostly single (72.57%) males (50.51%) of white ethnicity (60.01%), aged on average 32.96 years, with an average Health Of the Nation Outcome Scale score of 11.12 and mostly affected with F40-48 Neurotic/stress-related/somatoform disorders (27.46%). Their transdiagnostic risk of developing a FEP cumulated to 0.072 (95%CI 0.067-0.077) at 6 years. Those individuals who developed a FEP (n = 1841) entered healthcare mostly (79.02%) through inpatient mental health services (29.76%), community mental health services (29.54%) or accident and emergency departments (19.50%); at the time of FEP onset, most of them (46.43%) were under the acute care pathway. Individuals contacting accident and emergency departments had an increased risk of FEP (OR 2.301, 95%CI 2.095-2.534, P < 0.001). The proportion of SLaM FEP cases that were eligible and under the care of EI services was 0.456 at any time. The epidemiological proportion of FEP cases in the sociodemographically-matched general population that was detected by EI service was 0.373.

Conclusions: More than half of individuals who develop a FEP remain undetected by current pathways to care and EI services. Improving detection strategies should become a mainstream area in the future generation of early psychosis research.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.schres.2020.11.031DOI Listing
February 2021

Universal and selective interventions to promote good mental health in young people: Systematic review and meta-analysis.

Eur Neuropsychopharmacol 2020 12 6;41:28-39. Epub 2020 Nov 6.

Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.

Promotion of good mental health in young people is important. Our aim was to evaluate the consistency and magnitude of the efficacy of universal/selective interventions to promote good mental health. A systematic PRISMA/RIGHT-compliant meta-analysis (PROSPERO: CRD42018088708) search of Web of Science until 04/31/2019 identified original studies comparing the efficacy of universal/selective interventions for good mental health vs a control group, in samples with a mean age <35 years. Meta-analytical random-effects model, heterogeneity statistics, assessment of publication bias, study quality and sensitivity analyses investigated the efficacy (Hedges' g=effect size, ES) of universal/selective interventions to promote 14 good mental health outcomes defined a-priori. 276 studies were included (total participants: 159,508, 79,142 interventions and 80,366 controls), mean age=15.0 (SD=7.4); female=56.0%. There was a significant overall improvement in 10/13 good mental health outcome categories that could be meta-analysed: compared to controls, interventions significantly improved (in descending order of magnitude) mental health literacy (ES=0.685, p<0.001), emotions (ES=0.541, p<0.001), self-perceptions and values (ES=0.49, p<0.001), quality of life (ES=0.457, p=0.001), cognitive skills (ES=0.428, p<0.001), social skills (ES=0.371, p<0.001), physical health (ES=0.285, p<0.001), sexual health (ES=0.257, p=0.017), academic/occupational performance (ES=0.211, p<0.001) and attitude towards mental disorders (ES=0.177, p=0.006). Psychoeducation was the most effective intervention for promoting mental health literacy (ES=0.774, p<0.001) and cognitive skills (ES=1.153, p=0.03). Physical therapy, exercise and relaxation were more effective than psychoeducation and psychotherapy for promoting physical health (ES=0.498, p<0.001). In conclusion, several universal/selective interventions can be effective to promote good mental health in young people. Future research should consolidate and extend these findings.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.euroneuro.2020.10.007DOI Listing
December 2020

Transdiagnostic individualized clinically-based risk calculator for the automatic detection of individuals at-risk and the prediction of psychosis: external replication in 2,430,333 US patients.

Transl Psychiatry 2020 10 29;10(1):364. Epub 2020 Oct 29.

Early Psychosis: Interventions and Clinical detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.

The real-world impact of psychosis prevention is reliant on effective strategies for identifying individuals at risk. A transdiagnostic, individualized, clinically-based risk calculator to improve this has been developed and externally validated twice in two different UK healthcare trusts with convincing results. The prognostic performance of this risk calculator outside the UK is unknown. All individuals who accessed primary or secondary health care services belonging to the IBM MarketScan Commercial Database between January 2015 and December 2017, and received a first ICD-10 index diagnosis of nonorganic/nonpsychotic mental disorder, were included. According to the risk calculator, age, gender, ethnicity, age-by-gender, and ICD-10 cluster diagnosis at index date were used to predict development of any ICD-10 nonorganic psychotic disorder. Because patient-level ethnicity data were not available city-level ethnicity proportions were used as proxy. The study included 2,430,333 patients with a mean follow-up of 15.36 months and cumulative incidence of psychosis at two years of 1.43%. There were profound differences compared to the original development UK database in terms of case-mix, psychosis incidence, distribution of baseline predictors (ICD-10 cluster diagnoses), availability of patient-level ethnicity data, follow-up time and availability of specialized clinical services for at-risk individuals. Despite these important differences, the model retained accuracy significantly above chance (Harrell's C = 0.676, 95% CI: 0.672-0.679). To date, this is the largest international external replication of an individualized prognostic model in the field of psychiatry. This risk calculator is transportable on an international scale to improve the automatic detection of individuals at risk of psychosis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41398-020-01032-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596040PMC
October 2020

Using Natural Language Processing on Electronic Health Records to Enhance Detection and Prediction of Psychosis Risk.

Schizophr Bull 2021 03;47(2):405-414

Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.

Background: Using novel data mining methods such as natural language processing (NLP) on electronic health records (EHRs) for screening and detecting individuals at risk for psychosis.

Method: The study included all patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within the South London and Maudsley (SLaM) NHS Foundation Trust between January 1, 2008, and July 28, 2018. Least Absolute Shrinkage and Selection Operator (LASSO)-regularized Cox regression was used to refine and externally validate a refined version of a five-item individualized, transdiagnostic, clinically based risk calculator previously developed (Harrell's C = 0.79) and piloted for implementation. The refined version included 14 additional NLP-predictors: tearfulness, poor appetite, weight loss, insomnia, cannabis, cocaine, guilt, irritability, delusions, hopelessness, disturbed sleep, poor insight, agitation, and paranoia.

Results: A total of 92 151 patients with a first index diagnosis of nonorganic and nonpsychotic mental disorder within the SLaM Trust were included in the derivation (n = 28 297) or external validation (n = 63 854) data sets. Mean age was 33.6 years, 50.7% were women, and 67.0% were of white race/ethnicity. Mean follow-up was 1590 days. The overall 6-year risk of psychosis in secondary mental health care was 3.4 (95% CI, 3.3-3.6). External validation indicated strong performance on unseen data (Harrell's C 0.85, 95% CI 0.84-0.86), an increase of 0.06 from the original model.

Conclusions: Using NLP on EHRs can considerably enhance the prognostic accuracy of psychosis risk calculators. This can help identify patients at risk of psychosis who require assessment and specialized care, facilitating earlier detection and potentially improving patient outcomes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/schbul/sbaa126DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7965059PMC
March 2021

Precuneus and insular hypoactivation during cognitive processing in first-episode psychosis: Systematic review and meta-analysis of fMRI studies.

Rev Psiquiatr Salud Ment (Engl Ed) 2020 Sep 25. Epub 2020 Sep 25.

Research Institute of the Hospital Clínic Universitari of Valencia (INCLIVA), Valencia, Spain; Center for Networking Biomedical Research in Mental Health (CIBERSAM), Spain; Department of Psychiatric, University of Valencia, School of Medicine, Valencia, Spain.

Introduction: The neural correlates of the cognitive dysfunction in first-episode psychosis (FEP) are still unclear. The present review and meta-analysis provide an update of the location of the abnormalities in the fMRI-measured brain response to cognitive processes in individuals with FEP.

Methods: Systematic review and voxel-based meta-analysis of cross-sectional fMRI studies comparing neural responses to cognitive tasks between individuals with FEP and healthy controls (HC) according to PRISMA guidelines.

Results: Twenty-six studies were included, comprising 598 individuals with FEP and 567 HC. Individual studies reported statistically significant hypoactivation in the dorsolateral prefrontal cortex (6 studies), frontal lobe (8 studies), cingulate (6 studies) and insula (5 studies). The meta-analysis showed statistically significant hypoactivation in the left anterior insula, precuneus and bilateral striatum.

Conclusions: While the studies tend to highlight frontal hypoactivation during cognitive tasks in FEP, our meta-analytic results show that the left precuneus and insula primarily display aberrant activation in FEP that may be associated with salience attribution to external stimuli and related to deficits in perception and regulation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.rpsm.2020.08.001DOI Listing
September 2020

Lower speech connectedness linked to incidence of psychosis in people at clinical high risk.

Schizophr Res 2021 02 18;228:493-501. Epub 2020 Sep 18.

Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK.

Background: Formal thought disorder is a cardinal feature of psychotic disorders, and is also evident in subtle forms before psychosis onset in individuals at clinical high-risk for psychosis (CHR-P). Assessing speech output or assessing expressive language with speech as the medium at this stage may be particularly useful in predicting later transition to psychosis.

Method: Speech samples were acquired through administration of the Thought and Language Index (TLI) in 24 CHR-P participants, 16 people with first-episode psychosis (FEP) and 13 healthy controls. The CHR-P individuals were then followed clinically for a mean of 7 years (s.d. = 1.5) to determine if they transitioned to psychosis. Non-semantic speech graph analysis was used to assess the connectedness of transcribed speech in all groups.

Results: Speech was significantly more disconnected in the FEP group than in both healthy controls (p < .01) and the CHR-P group (p < .05). Results remained significant when IQ was included as a covariate. Significant correlations were found between speech connectedness measures and scores on the TLI, a manual assessment of formal thought disorder. In the CHR-P group, lower scores on two measures of speech connectedness were associated with subsequent transition to psychosis (8 transitions, 16 non-transitions; p < .05).

Conclusion: These findings support the utility and validity of speech graph analysis methods in characterizing speech connectedness in the early phases of psychosis. This approach has the potential to be developed into an automated, objective and time-efficient way of stratifying individuals at CHR-P according to level of psychosis risk.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.schres.2020.09.002DOI Listing
February 2021

Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice.

Schizophr Bull 2021 03;47(2):284-297

Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, UK.

Background: The impact of precision psychiatry for clinical practice has not been systematically appraised. This study aims to provide a comprehensive review of validated prediction models to estimate the individual risk of being affected with a condition (diagnostic), developing outcomes (prognostic), or responding to treatments (predictive) in mental disorders.

Methods: PRISMA/RIGHT/CHARMS-compliant systematic review of the Web of Science, Cochrane Central Register of Reviews, and Ovid/PsycINFO databases from inception until July 21, 2019 (PROSPERO CRD42019155713) to identify diagnostic/prognostic/predictive prediction studies that reported individualized estimates in psychiatry and that were internally or externally validated or implemented. Random effect meta-regression analyses addressed the impact of several factors on the accuracy of prediction models.

Findings: Literature search identified 584 prediction modeling studies, of which 89 were included. 10.4% of the total studies included prediction models internally validated (n = 61), 4.6% models externally validated (n = 27), and 0.2% (n = 1) models considered for implementation. Across validated prediction modeling studies (n = 88), 18.2% were diagnostic, 68.2% prognostic, and 13.6% predictive. The most frequently investigated condition was psychosis (36.4%), and the most frequently employed predictors clinical (69.5%). Unimodal compared to multimodal models (β = .29, P = .03) and diagnostic compared to prognostic (β = .84, p < .0001) and predictive (β = .87, P = .002) models were associated with increased accuracy.

Interpretation: To date, several validated prediction models are available to support the diagnosis and prognosis of psychiatric conditions, in particular, psychosis, or to predict treatment response. Advancements of knowledge are limited by the lack of implementation research in real-world clinical practice. A new generation of implementation research is required to address this translational gap.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/schbul/sbaa120DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7965077PMC
March 2021

Intranasal oxytocin increases heart-rate variability in men at clinical high risk for psychosis: a proof-of-concept study.

Transl Psychiatry 2020 07 12;10(1):227. Epub 2020 Jul 12.

Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK.

Autonomic nervous system (ANS) dysfunction (i.e., increased sympathetic and/or decreased parasympathetic activity) has been proposed to contribute to psychosis vulnerability. Yet, we still lack directed therapeutic strategies that improve ANS regulation in psychosis or at-risk states. The oxytocin system constitutes a potential therapeutic target, given its role in ANS regulation. However, whether intranasal oxytocin ameliorates autonomic regulation during emerging psychosis is currently unknown. We pooled together two datasets, one of 30 men at clinical high risk for psychosis (CHR-P), and another of 17 healthy men, who had participated in two double-blinded, placebo-controlled, randomised, crossover MRI studies with similar protocols. All participants self-administered 40 IU of intranasal oxytocin or placebo using a nasal spray. We recorded pulse plethysmography during a period of 8 min at about 1 h post dosing and estimated heart rate (HR) and high-frequency HR variability (HF-HRV), an index of cardio-parasympathetic activity. CHR-P and healthy men did not differ at resting HR or HF-HRV under placebo. We found a significant condition × treatment effect for HF-HRV, showing that intranasal oxytocin, compared with placebo, increased HF-HRV in CHR-P but not in healthy men. The main effects of treatment and condition were not significant. In this proof-of-concept study, we show that intranasal oxytocin increases cardio-parasympathetic activity in CHR-P men, highlighting its therapeutic potential to improve autonomic regulation in this clinical group. Our findings support the need for further research on the preventive and therapeutic potential of intranasal oxytocin during emerging psychosis, where we lack effective treatments.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41398-020-00890-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354990PMC
July 2020

Acute oxytocin effects in inferring others' beliefs and social emotions in people at clinical high risk for psychosis.

Transl Psychiatry 2020 06 22;10(1):203. Epub 2020 Jun 22.

Early Psychosis: Interventions and Clinical-detection (EPIC) lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.

Social deficits are key hallmarks of the Clinical High Risk for Psychosis (CHR-P) state and of established psychotic disorders, and contribute to impaired social functioning, indicating a potential target for interventions. However, current treatments do not significantly ameliorate social impairments in CHR-P individuals. Given its critical role in social behaviour and cognition, the oxytocinergic (OT) system is a promising target for novel interventions in CHR-P subjects. In a double-blind, placebo-controlled, crossover design, 30 CHR-P males were studied using functional magnetic resonance imaging (fMRI) on two occasions, once after 40IU self-administered intranasal OT and once after placebo. A modified version of the Sally-Anne task was used to assess brain activation during inferring others' beliefs and social emotions. The Reading the Mind in the Eyes Test was acquired prior to the first scan to test whether OT effects were moderated by baseline social-emotional abilities. OT did not modulate behavioural performances but reduced activation in the bilateral inferior frontal gyrus compared with placebo while inferring others' social emotions. Furthermore, the relationship between brain activation and task performance after OT administration was moderated by baseline social-emotional abilities. While task accuracy during inferring others' social emotion increased with decreasing activation in the left inferior frontal gyrus in CHR-P individuals with low social-emotional abilities, there was no such relationship in CHR-P individuals with high social-emotional abilities. Our findings may suggest that acute OT administration enhances neural efficiency in the inferior frontal gyrus during inferring others' social emotions in those CHR-P subjects with low baseline social-emotional abilities.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41398-020-00885-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7308367PMC
June 2020

Real-world implementation of precision psychiatry: Transdiagnostic risk calculator for the automatic detection of individuals at-risk of psychosis.

Schizophr Res 2021 01 19;227:52-60. Epub 2020 Jun 19.

Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; National Institute for Health Research, Maudesley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom; OASIS Service, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy. Electronic address:

Background: Risk estimation models integrated into Electronic Health Records (EHRs) can deliver innovative approaches in psychiatry, but clinicians' endorsement and their real-world usability are unknown. This study aimed to investigate the real-world feasibility of implementing an individualised, transdiagnostic risk calculator to automatically screen EHRs and detect individuals at-risk for psychosis.

Methods: Feasibility implementation study encompassing an in-vitro phase (March 2018 to May 2018) and in-vivo phase (May 2018 to April 2019). The in-vitro phase addressed implementation barriers and embedded the risk calculator (predictors: age, gender, ethnicity, index cluster diagnosis, age*gender) into the local EHR. The in-vivo phase investigated the real-world feasibility of screening individuals accessing secondary mental healthcare at the South London and Maudsley NHS Trust. The primary outcome was adherence of clinicians to automatic EHR screening, defined by the proportion of clinicians who responded to alerts from the risk calculator, over those contacted.

Results: In-vitro phase: implementation barriers were identified/overcome with clinician and service user engagement, and the calculator was successfully integrated into the local EHR through the CogStack platform. In-vivo phase: 3722 individuals were automatically screened and 115 were detected. Clinician adherence was 74% without outreach and 85% with outreach. One-third of clinicians responded to the first email (37.1%) or phone calls (33.7%). Among those detected, cumulative risk of developing psychosis was 12% at six-month follow-up.

Conclusion: This is the first implementation study suggesting that combining precision psychiatry and EHR methods to improve detection of individuals with emerging psychosis is feasible. Future psychiatric implementation research is urgently needed.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.schres.2020.05.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7875179PMC
January 2021

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack.

J Vis Exp 2020 05 15(159). Epub 2020 May 15.

Early Psychosis: Interventions and Clinical-detection (EPIC) lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London; National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust; OASIS service, South London and Maudsley National Health Service (NHS) Foundation Trust; Department of Brain and Behavioral Sciences, University of Pavia.

Recent studies have shown that an automated, lifespan-inclusive, transdiagnostic, and clinically based, individualized risk calculator provides a powerful system for supporting the early detection of individuals at-risk of psychosis at a large scale, by leveraging electronic health records (EHRs). This risk calculator has been externally validated twice and is undergoing feasibility testing for clinical implementation. Integration of this risk calculator in clinical routine should be facilitated by prospective feasibility studies, which are required to address pragmatic challenges, such as missing data, and the usability of this risk calculator in a real-world and routine clinical setting. Here, we present an approach for a prospective implementation of a real-time psychosis risk detection and alerting service in a real-world EHR system. This method leverages the CogStack platform, which is an open-source, lightweight, and distributed information retrieval and text extraction system. The CogStack platform incorporates a set of services that allow for full-text search of clinical data, lifespan-inclusive, real-time calculation of psychosis risk, early risk-alerting to clinicians, and the visual monitoring of patients over time. Our method includes: 1) ingestion and synchronization of data from multiple sources into the CogStack platform, 2) implementation of a risk calculator, whose algorithm was previously developed and validated, for timely computation of a patient's risk of psychosis, 3) creation of interactive visualizations and dashboards to monitor patients' health status over time, and 4) building automated alerting systems to ensure that clinicians are notified of patients at-risk, so that appropriate actions can be pursued. This is the first ever study that has developed and implemented a similar detection and alerting system in clinical routine for early detection of psychosis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3791/60794DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7272223PMC
May 2020

Psychiatric and neuropsychiatric presentations associated with severe coronavirus infections: a systematic review and meta-analysis with comparison to the COVID-19 pandemic.

Lancet Psychiatry 2020 07 18;7(7):611-627. Epub 2020 May 18.

UCL Institute of Mental Health, University College London, London, UK.

Background: Before the COVID-19 pandemic, coronaviruses caused two noteworthy outbreaks: severe acute respiratory syndrome (SARS), starting in 2002, and Middle East respiratory syndrome (MERS), starting in 2012. We aimed to assess the psychiatric and neuropsychiatric presentations of SARS, MERS, and COVID-19.

Methods: In this systematic review and meta-analysis, MEDLINE, Embase, PsycINFO, and the Cumulative Index to Nursing and Allied Health Literature databases (from their inception until March 18, 2020), and medRxiv, bioRxiv, and PsyArXiv (between Jan 1, 2020, and April 10, 2020) were searched by two independent researchers for all English-language studies or preprints reporting data on the psychiatric and neuropsychiatric presentations of individuals with suspected or laboratory-confirmed coronavirus infection (SARS coronavirus, MERS coronavirus, or SARS coronavirus 2). We excluded studies limited to neurological complications without specified neuropsychiatric presentations and those investigating the indirect effects of coronavirus infections on the mental health of people who are not infected, such as those mediated through physical distancing measures such as self-isolation or quarantine. Outcomes were psychiatric signs or symptoms; symptom severity; diagnoses based on ICD-10, DSM-IV, or the Chinese Classification of Mental Disorders (third edition) or psychometric scales; quality of life; and employment. Both the systematic review and the meta-analysis stratified outcomes across illness stages (acute vs post-illness) for SARS and MERS. We used a random-effects model for the meta-analysis, and the meta-analytical effect size was prevalence for relevant outcomes, I statistics, and assessment of study quality.

Findings: 1963 studies and 87 preprints were identified by the systematic search, of which 65 peer-reviewed studies and seven preprints met inclusion criteria. The number of coronavirus cases of the included studies was 3559, ranging from 1 to 997, and the mean age of participants in studies ranged from 12·2 years (SD 4·1) to 68·0 years (single case report). Studies were from China, Hong Kong, South Korea, Canada, Saudi Arabia, France, Japan, Singapore, the UK, and the USA. Follow-up time for the post-illness studies varied between 60 days and 12 years. The systematic review revealed that during the acute illness, common symptoms among patients admitted to hospital for SARS or MERS included confusion (36 [27·9%; 95% CI 20·5-36·0] of 129 patients), depressed mood (42 [32·6%; 24·7-40·9] of 129), anxiety (46 [35·7%; 27·6-44·2] of 129), impaired memory (44 [34·1%; 26·2-42·5] of 129), and insomnia (54 [41·9%; 22·5-50·5] of 129). Steroid-induced mania and psychosis were reported in 13 (0·7%) of 1744 patients with SARS in the acute stage in one study. In the post-illness stage, depressed mood (35 [10·5%; 95% CI 7·5-14·1] of 332 patients), insomnia (34 [12·1%; 8·6-16·3] of 280), anxiety (21 [12·3%; 7·7-17·7] of 171), irritability (28 [12·8%; 8·7-17·6] of 218), memory impairment (44 [18·9%; 14·1-24·2] of 233), fatigue (61 [19·3%; 15·1-23·9] of 316), and in one study traumatic memories (55 [30·4%; 23·9-37·3] of 181) and sleep disorder (14 [100·0%; 88·0-100·0] of 14) were frequently reported. The meta-analysis indicated that in the post-illness stage the point prevalence of post-traumatic stress disorder was 32·2% (95% CI 23·7-42·0; 121 of 402 cases from four studies), that of depression was 14·9% (12·1-18·2; 77 of 517 cases from five studies), and that of anxiety disorders was 14·8% (11·1-19·4; 42 of 284 cases from three studies). 446 (76·9%; 95% CI 68·1-84·6) of 580 patients from six studies had returned to work at a mean follow-up time of 35·3 months (SD 40·1). When data for patients with COVID-19 were examined (including preprint data), there was evidence for delirium (confusion in 26 [65%] of 40 intensive care unit patients and agitation in 40 [69%] of 58 intensive care unit patients in one study, and altered consciousness in 17 [21%] of 82 patients who subsequently died in another study). At discharge, 15 (33%) of 45 patients with COVID-19 who were assessed had a dysexecutive syndrome in one study. At the time of writing, there were two reports of hypoxic encephalopathy and one report of encephalitis. 68 (94%) of the 72 studies were of either low or medium quality.

Interpretation: If infection with SARS-CoV-2 follows a similar course to that with SARS-CoV or MERS-CoV, most patients should recover without experiencing mental illness. SARS-CoV-2 might cause delirium in a significant proportion of patients in the acute stage. Clinicians should be aware of the possibility of depression, anxiety, fatigue, post-traumatic stress disorder, and rarer neuropsychiatric syndromes in the longer term.

Funding: Wellcome Trust, UK National Institute for Health Research (NIHR), UK Medical Research Council, NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust and University College London.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/S2215-0366(20)30203-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7234781PMC
July 2020

Real-world digital implementation of the Psychosis Polyrisk Score (PPS): A pilot feasibility study.

Schizophr Res 2020 12 24;226:176-183. Epub 2020 Apr 24.

Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; OASIS Service, South London and the Maudsley NHS Foundation Trust, London, United Kingdom; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy. Electronic address:

Background: The Psychosis Polyrisk Score (PPS) is a potential biomarker integrating non-purely genetic risk/protective factors for psychosis that may improve identification of individuals at risk and prediction of their outcomes at the individual subject level. Biomarkers that are easy to administer are direly needed in early psychosis to facilitate clinical implementation. This study digitally implements the PPS and pilots its feasibility of use in the real world.

Methods: The PPS was implemented digitally and prospectively piloted across individuals referred for a CHR-P assessment (n = 16) and healthy controls (n = 66). Distribution of PPS scores was further simulated in the general population.

Results: 98.8% of individuals referred for a CHR-P assessment and healthy controls completed the PPS assessment with only one drop-out. 96.3% of participants completed the assessment in under 15 min. Individuals referred for a CHR-P assessment had high PPS scores (mean = 6.2, SD = 7.23) than healthy controls (mean = -1.79, SD = 6.78, p < 0.001). In simulated general population data, scores were normally distributed ranging from -15 (lowest risk, RR = 0.03) to 39.5 (highest risk, RR = 8912.51).

Discussion: The PPS is a promising biomarker which has been implemented digitally. The PPS can be easily administered to both healthy controls and individuals at potential risk for psychosis on a range of devices. It is feasible to use the PPS in real world settings to assess individuals with emerging mental disorders. The next phase of research should be to include the PPS in large-scale international cohort studies to evaluate its ability to refine the prognostication of outcomes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.schres.2020.04.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7774585PMC
December 2020

Adverse effects of cannabidiol: a systematic review and meta-analysis of randomized clinical trials.

Neuropsychopharmacology 2020 10 8;45(11):1799-1806. Epub 2020 Apr 8.

King's College London, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, London, UK.

Cannabidiol (CBD) is being investigated as a treatment for several medical disorders but there is uncertainty about its safety. We conducted the first systematic review and meta-analysis of the adverse effects of CBD across all medical indications. Double-blind randomized placebo-controlled clinical trials lasting ≥7 days were included. Twelve trials contributed data from 803 participants to the meta-analysis. Compared with placebo, CBD was associated with an increased likelihood of withdrawal for any reason (OR 2.61, 95% CI: 1.38-4.96) or due to adverse events (OR 2.65, 95% CI: 1.04-6.80), any serious adverse event (OR 2.30, 95% CI: 1.18-4.48), serious adverse events related to abnormal liver function tests (OR 11.19, 95% CI: 2.09-60.02) or pneumonia (OR 5.37, 95% CI: 1.17-24.65), any adverse event (OR 1.55, 95% CI: 1.03-2.33), adverse events due to decreased appetite (OR 3.56, 95% CI: 1.94-6.53), diarrhoea (OR 2.61, 95% CI: 1.46-4.67), somnolence (OR 2.23, 95% CI: 1.07-4.64) and sedation (OR 4.21, 95% CI: 1.18-15.01). Associations with abnormal liver function tests, somnolence, sedation and pneumonia were limited to childhood epilepsy studies, where CBD may have interacted with other medications such as clobazam and/or sodium valproate. After excluding studies in childhood epilepsy, the only adverse outcome associated with CBD treatment was diarrhoea (OR 5.03, 95% CI: 1.44-17.61). In summary, the available data from clinical trials suggest that CBD is well tolerated and has relatively few serious adverse effects, however interactions with other medications should be monitored carefully. Additional safety data from clinical trials outside of childhood epilepsy syndromes and from studies of over-the-counter CBD products are needed to assess whether the conclusions drawn from clinical trials can be applied more broadly.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41386-020-0667-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7608221PMC
October 2020

Prenatal and perinatal risk and protective factors for psychosis: a systematic review and meta-analysis.

Lancet Psychiatry 2020 05 24;7(5):399-410. Epub 2020 Mar 24.

Early Psychosis: Interventions and Clinical-detection (EPIC) Laboratory, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; National Institute for Health Research Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK; Outreach And Support in South London (OASIS) Service, South London and Maudsley NHS Foundation Trust, London, UK; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy. Electronic address:

Background: Prenatal and perinatal insults are implicated in the aetiopathogenesis of psychotic disorders but the consistency and magnitude of their associations with psychosis have not been updated for nearly two decades. The aim of this systematic review and meta-analysis was to provide a comprehensive and up-to-date synthesis of the evidence on the association between prenatal or perinatal risk and protective factors and psychotic disorders.

Methods: In this systematic review and meta-analysis, we searched the Web of Science database for articles published up to July 20, 2019. We identified cohort and case-control studies examining the association (odds ratio [OR]) between prenatal and perinatal factors and any International Classification of Diseases (ICD) or Diagnostic and Statistical Manual of Mental Disorders (DSM) non-organic psychotic disorder with a healthy comparison group. Other inclusion criteria were enough data available to do the analyses, and non-overlapping datasets. We excluded reviews, meta-analyses, abstracts or conference proceedings, and articles with overlapping datasets. Data were extracted according to EQUATOR and PRISMA guidelines. Extracted variables included first author, publication year, study type, sample size, type of psychotic diagnosis (non-affective psychoses or schizophrenia-spectrum disorders, affective psychoses) and diagnostic instrument (DSM or ICD and version), the risk or protective factor, and measure of association (primary outcome). We did random-effects pairwise meta-analyses, Q statistics, I index, sensitivity analyses, meta-regressions, and assessed study quality and publication bias. The study protocol was registered at PROSPERO, CRD42017079261.

Findings: 152 studies relating to 98 risk or protective factors were eligible for analysis. Significant risk factors were: maternal age younger than 20 years (OR 1·17) and 30-34 years (OR 1·05); paternal age younger than 20 years (OR 1·31) and older than 35 years (OR 1·28); any maternal (OR 4·60) or paternal (OR 2·73) psychopathology; maternal psychosis (OR 7·61) and affective disorder (OR 2·26); three or more pregnancies (OR 1·30); herpes simplex 2 (OR 1·35); maternal infections not otherwise specified (NOS; OR 1·27); suboptimal number of antenatal visits (OR 1·83); winter (OR 1·05) and winter to spring (OR 1·05) season of birth in the northern hemisphere; maternal stress NOS (OR 2·40); famine (OR 1·61); any famine or nutritional deficits in pregnancy (OR 1·40); maternal hypertension (OR 1·40); hypoxia (OR 1·63); ruptured (OR 1·86) and premature rupture (OR 2·29) of membranes; polyhydramnios (OR 3·05); definite obstetric complications NOS (OR 1·83); birthweights of less than 2000 g (OR 1·84), less than 2500 g (OR 1·53), or 2500-2999 g (OR 1·23); birth length less than 49 cm (OR 1·17); small for gestational age (OR 1·40); premature birth (OR 1·35), and congenital malformations (OR 2·35). Significant protective factors were maternal ages 20-24 years (OR 0·93) and 25-29 years (OR 0·92), nulliparity (OR 0·91), and birthweights 3500-3999 g (OR 0·90) or more than 4000 g (OR 0·86). The results were corrected for publication biases; sensitivity and meta-regression analyses confirmed the robustness of these findings for most factors.

Interpretation: Several prenatal and perinatal factors are associated with the later onset of psychosis. The updated knowledge emerging from this study could refine understanding of psychosis pathogenesis, enhance multivariable risk prediction, and inform preventive strategies.

Funding: None.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/S2215-0366(20)30057-2DOI Listing
May 2020

Are You on My Wavelength? Interpersonal Coordination in Dyadic Conversations.

J Nonverbal Behav 2020 15;44(1):63-83. Epub 2019 Oct 15.

1Institute of Cognitive Neuroscience, UCL, Alexandra House, 17 Queen Square, London, WC1N 3AZ UK.

Conversation between two people involves subtle nonverbal coordination in addition to speech. However, the precise parameters and timing of this coordination remain unclear, which limits our ability to theorize about the neural and cognitive mechanisms of social coordination. In particular, it is unclear if conversation is dominated by synchronization (with no time lag), rapid and reactive mimicry (with lags under 1 s) or traditionally observed mimicry (with several seconds lag), each of which demands a different neural mechanism. Here we describe data from high-resolution motion capture of the head movements of pairs of participants (= 31 dyads) engaged in structured conversations. In a pre-registered analysis pathway, we calculated the wavelet coherence of head motion within dyads as a measure of their nonverbal coordination and report two novel results. First, low-frequency coherence (0.2-1.1 Hz) is consistent with traditional observations of mimicry, and modeling shows this behavior is generated by a mechanism with a constant 600 ms lag between leader and follower. This is in line with rapid reactive (rather than predictive or memory-driven) models of mimicry behavior, and could be implemented in mirror neuron systems. Second, we find an unexpected pattern of lower-than-chance coherence between participants, or hypo-coherence, at high frequencies (2.6-6.5 Hz). Exploratory analyses show that this systematic decoupling is driven by fast nodding from the listening member of the dyad, and may be a newly identified social signal. These results provide a step towards the quantification of real-world human behavior in high resolution and provide new insights into the mechanisms of social coordination.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s10919-019-00320-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054373PMC
October 2019

Worldwide implementation of clinical services for the prevention of psychosis: The IEPA early intervention in mental health survey.

Early Interv Psychiatry 2020 12 17;14(6):741-750. Epub 2020 Feb 17.

Early Psychosis: Interventions and Clinical-detection (EPIC) lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.

Background: Clinical research into the Clinical High Risk state for Psychosis (CHR-P) has allowed primary indicated prevention in psychiatry to improve outcomes of psychotic disorders. The strategic component of this approach is the implementation of clinical services to detect and take care of CHR-P individuals, which are recommended by several guidelines. The actual level of implementation of CHR-P services worldwide is not completely clear.

Aim: To assess the global geographical distribution, core characteristics relating to the level of implementation of CHR-P services; to overview of the main barriers that limit their implementation at scale.

Methods: CHR-P services worldwide were invited to complete an online survey. The survey addressed the geographical distribution, general implementation characteristics and implementation barriers.

Results: The survey was completed by 47 CHR-P services offering care to 22 248 CHR-P individuals: Western Europe (51.1%), North America (17.0%), East Asia (17.0%), Australia (6.4%), South America (6.4%) and Africa (2.1%). Their implementation characteristics included heterogeneous clinical settings, assessment instruments and length of care offered. Most CHR-P patients were recruited through mental or physical health services. Preventive interventions included clinical monitoring and crisis management (80.1%), supportive therapy (70.2%) or structured psychotherapy (61.7%), in combination with pharmacological treatment (in 74.5%). Core implementation barriers were staffing and financial constraints, and the recruitment of CHR-P individuals. The dynamic map of CHR-P services has been implemented on the IEPA website: https://iepa.org.au/list-a-service/.

Conclusions: Worldwide primary indicated prevention of psychosis in CHR-P individuals is possible, but the implementation of CHR-P services is heterogeneous and constrained by pragmatic challenges.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1111/eip.12950DOI Listing
December 2020

How experimental cannabinoid studies will inform the standardized THC unit.

Addiction 2020 07 5;115(7):1217-1218. Epub 2020 Feb 5.

King's College London, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, London, UK.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1111/add.14959DOI Listing
July 2020

What Causes the Onset of Psychosis in Individuals at Clinical High Risk? A Meta-analysis of Risk and Protective Factors.

Schizophr Bull 2020 01;46(1):110-120

Early Psychosis: Interventions and Clinical detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

Twenty percent of individuals at clinical high risk for psychosis (CHR-P) develop the disorder within 2 years. Extensive research has explored the factors that differentiate those who develop psychosis and those who do not, but the results are conflicting. The current systematic review and meta-analysis comprehensively addresses the consistency and magnitude of evidence for non-purely genetic risk and protective factors associated with the risk of developing psychosis in CHR-P individuals. Random effects meta-analyses, standardized mean difference (SMD) and odds ratio (OR) were used, in combination with an established stratification of evidence that assesses the association of each factor and the onset of psychotic disorders (from class I, convincing evidence to class IV weak evidence), while controlling for several types of biases. A total of 128 original controlled studies relating to 26 factors were retrieved. No factors showed class I-convincing evidence. Two further factors were associated with class II-highly suggestive evidence: attenuated positive psychotic symptoms (SMD = 0.348, 95% CI: 0.280, 0.415) and global functioning (SMD = -0.291, 95% CI: -0.370, -0.211). There was class III-suggestive evidence for negative psychotic symptoms (SMD = 0.393, 95% CI: 0.317, 0.469). There was either class IV-weak or no evidence for all other factors. Our findings suggest that despite the large number of putative risk factors investigated in the literature, only attenuated positive psychotic symptoms, global functioning, and negative psychotic symptoms show suggestive evidence or greater for association with transition to psychosis. The current findings may inform the refinement of clinical prediction models and precision medicine in this field.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/schbul/sbz039DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6942149PMC
January 2020

Psychosis Polyrisk Score (PPS) for the Detection of Individuals At-Risk and the Prediction of Their Outcomes.

Front Psychiatry 2019 17;10:174. Epub 2019 Apr 17.

Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.

Primary prevention in individuals at Clinical High Risk for psychosis (CHR-P) can ameliorate the course of psychotic disorders. Further advancements of knowledge have been slowed by the standstill of the field, which is mostly attributed to its epidemiological weakness. The latter, in turn, underlies the limited identification power of at-risk individuals and the relatively modest ability of CHR-P interviews to rule-in a state of risk for psychosis. In the first part, this perspective review discusses these limitations and traces a new approach to overcome them. Theoretical concepts to support a Psychosis Polyrisk Score (PPS) integrating genetic and non-genetic risk and protective factors for psychosis are presented. The PPS hinges on recent findings indicating that risk enrichment in CHR-P samples is accounted for by the accumulation of non-genetic factors such as: parental and sociodemographic risk factors, perinatal risk factors, later risk factors, and antecedents. In the second part of this perspective review we present a prototype of a PPS encompassing core predictors beyond genetics. The PPS prototype may be piloted in the next generation of CHR-P research and combined with genetic information to refine the detection of individuals at-risk of psychosis and the prediction of their outcomes, and ultimately advance clinical research in this field.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fpsyt.2019.00174DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478670PMC
April 2019

Real World Implementation of a Transdiagnostic Risk Calculator for the Automatic Detection of Individuals at Risk of Psychosis in Clinical Routine: Study Protocol.

Front Psychiatry 2019 13;10:109. Epub 2019 Mar 13.

National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Service (NHS) Foundation Trust, London, United Kingdom.

Primary indicated prevention in individuals at-risk for psychosis has the potential to improve the outcomes of this disorder. The ability to detect the majority of at-risk individuals is the main barrier toward extending benefits for the lives of many adolescents and young adults. Current detection strategies are highly inefficient. Only 5% (standalone specialized early detection services) to 12% (youth mental health services) of individuals who will develop a first psychotic disorder can be detected at the time of their at-risk stage. To overcome these challenges a pragmatic, clinically-based, individualized, transdiagnostic risk calculator has been developed to detect individuals at-risk of psychosis in secondary mental health care at scale. This calculator has been externally validated and has demonstrated good prognostic performance. However, it is not known whether it can be used in the real world clinical routine. For example, clinicians may not be willing to adhere to the recommendations made by the transdiagnostic risk calculator. Implementation studies are needed to address pragmatic challenges relating to the real world use of the transdiagnostic risk calculator. The aim of the current study is to provide and feasibility data to support the implementation of the transdiagnostic risk calculator in clinical routine. This is a study which comprises of two subsequent phases: an phase of 1 month and an phase of 11 months. The phase aims at developing and integrating the transdiagnostic risk calculator in the local electronic health register (primary outcome). The phase aims at addressing the clinicians' adherence to the recommendations made by the transdiagnostic risk calculator (primary outcome) and other secondary feasibility parameters that are necessary to estimate the resources needed for its implementation. This is the first implementation study for risk prediction models in individuals at-risk for psychosis. Ultimately, successful implementation is the true measure of a prediction model's utility. Therefore, the overall translational deliverable of the current study would be to extend the benefits of primary indicated prevention and improve outcomes of first episode psychosis. This may produce significant social benefits for many adolescents and young adults and their families.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fpsyt.2019.00109DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6436079PMC
March 2019

Neurochemical effects of oxytocin in people at clinical high risk for psychosis.

Eur Neuropsychopharmacol 2019 05 28;29(5):601-615. Epub 2019 Mar 28.

Early Psychosis: Interventions & Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AF, UK; National Institute for Health Research (NIHR) Biomedical Research Centre (BRC), South London and Maudsley NHS Foundation Trust, London, UK; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy; Outreach and Support in South London (OASIS) Service, South London and Maudsley NHS Foundation Trust, London, UK.

Alterations in neurochemical metabolites are thought to play a role in the pathophysiology of psychosis onset. Oxytocin, a neuropeptide with prosocial and anxiolytic properties, modulates glutamate neurotransmission in preclinical models but its neurochemical effects in people at high risk for psychosis are unknown. We used proton magnetic resonance spectroscopy (H-MRS) to examine the effects of intranasal oxytocin on glutamate and other metabolites in people at Clinical High Risk for Psychosis (CHR-P) in a double-blind, placebo-controlled, crossover design. 30 CHR-P males were studied on two occasions, once after 40IU intranasal oxytocin and once after placebo. The effects of oxytocin on the concentration of glutamate, glutamate+glutamine and other metabolites (choline, N-acetylaspartate, myo-inositol) scaled to creatine were examined in the left thalamus, anterior cingulate cortex (ACC) and left hippocampus, starting approximately 75, 84 and 93 min post-dosing, respectively. Relative to placebo, administration of oxytocin was associated with an increase in choline levels in the ACC (p=.008, Cohen's d = 0.54). There were no other significant effects on metabolite concentrations (all p>.05). Our findings suggest that, at ∼75-99 min post-dosing, a single dose of intranasal oxytocin does not alter levels of neurochemical metabolites in the thalamus, ACC, or hippocampus in those at CHR-P, aside from potential effects on choline in the ACC.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.euroneuro.2019.03.008DOI Listing
May 2019

Unmet needs in patients with brief psychotic disorders: Too ill for clinical high risk services and not ill enough for first episode services.

Eur Psychiatry 2019 04 15;57:26-32. Epub 2019 Jan 15.

Early Psychosis: Interventions & Clinical-detection (EPIC) lab, Department of Psychosis Studies, King's College London, Institute of Psychiatry Psychology and Neuroscience, London, United Kingdom; OASIS Service, South London and the Maudsley NHS Foundation Trust, London, United Kingdom; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy. Electronic address:

Background: Patients with acute and transient psychotic disorders (ATPDs) are by definition remitting, but have a high risk of developing persistent psychoses, resembling a subgroup of individuals at Clinical High Risk for Psychosis (CHR-P). Their pathways to care, treatment offered and long-term clinical outcomes beyond risk to psychosis are unexplored. We conducted an electronic health record-based retrospective cohort study including patients with ATPDs within the SLaM NHS Trust and followed-up to 8 years.

Methods: A total of 2561 ATPDs were included in the study. A minority were detected (8%) and treated (18%) by Early Intervention services (EIS) and none by CHR-P services. Patients were offered a clinical follow-up of 350.40 ± 589.90 days. The cumulative incidence of discharges was 40% at 3 months, 60% at 1 year, 69% at 2 years, 77% at 4 years, and 82% at 8 years. Treatment was heterogeneous: the majority of patients received antipsychotics (up to 52%), only a tiny minority psychotherapy (up to 8%).

Results: Over follow-up, 32.88% and 28.54% of ATPDS received at least one mental health hospitalization or one compulsory hospital admission under the Mental Health Act, respectively. The mean number of days spent in psychiatric hospital was 66.39 ± 239.44 days.

Conclusions: The majority of ATPDs are not detected/treated by EIS or CHR-P services, receive heterogeneous treatments and short-term clinical follow-up. ATPDs have a high risk of developing severe clinical outcomes beyond persistent psychotic disorders and unmet clinical needs that are not targeted by current mental health services.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.eurpsy.2018.12.006DOI Listing
April 2019

Oxytocin modulates hippocampal perfusion in people at clinical high risk for psychosis.

Neuropsychopharmacology 2019 06 9;44(7):1300-1309. Epub 2019 Jan 9.

Early Psychosis: Interventions & Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.

Preclinical and human studies suggest that hippocampal dysfunction is a key factor in the onset of psychosis. People at Clinical High Risk for psychosis (CHR-P) present with a clinical syndrome that can include social withdrawal and have a 20-35% risk of developing psychosis in the next 2 years. Recent research shows that resting hippocampal blood flow is altered in CHR-P individuals and predicts adverse clinical outcomes, such as non-remission/transition to frank psychosis. Previous work in healthy males indicates that a single dose of intranasal oxytocin has positive effects on social function and marked effects on resting hippocampal blood flow. The present study examined the effects of intranasal oxytocin on hippocampal blood flow in CHR-P individuals. In a double-blind, placebo-controlled, crossover design, 30 CHR-P males were studied using pseudo-continuous Arterial Spin Labelling on 2 occasions, once after 40IU intranasal oxytocin and once after placebo. The effects of oxytocin on left hippocampal blood flow were examined in a region-of-interest analysis of data acquired at 22-28 and at 30-36 minutes post-intranasal administration. Relative to placebo, administration of oxytocin was associated with increased hippocampal blood flow at both time points (p = .0056; p = .034), although the effect at the second did not survive adjustment for the effect of global blood flow. These data indicate that oxytocin can modulate hippocampal function in CHR-P individuals and therefore merits further investigation as a candidate novel treatment for this group.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41386-018-0311-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6784972PMC
June 2019

Transdiagnostic Risk Calculator for the Automatic Detection of Individuals at Risk and the Prediction of Psychosis: Second Replication in an Independent National Health Service Trust.

Schizophr Bull 2019 04;45(3):562-570

Division of Psychiatry, University College London, London, UK.

Background: The benefits of indicated primary prevention among individuals at Clinical High Risk for Psychosis (CHR-P) are limited by the difficulty in detecting these individuals. To overcome this problem, a transdiagnostic, clinically based, individualized risk calculator has recently been developed and subjected to a first external validation in 2 different catchment areas of the South London and Maudsley (SLaM) NHS Trust.

Methods: Second external validation of real world, real-time electronic clinical register-based cohort study. All individuals who received a first ICD-10 index diagnosis of nonorganic and nonpsychotic mental disorder within the Camden and Islington (C&I) NHS Trust between 2009 and 2016 were included. The model previously validated included age, gender, ethnicity, age by gender, and ICD-10 index diagnosis to predict the development of any ICD-10 nonorganic psychosis. The model's performance was measured using Harrell's C-index.

Results: This study included a total of 13702 patients with an average age of 40 (range 16-99), 52% were female, and most were of white ethnicity (64%). There were no CHR-P or child/adolescent services in the C&I Trust. The C&I and SLaM Trust samples also differed significantly in terms of age, gender, ethnicity, and distribution of index diagnosis. Despite these significant differences, the original model retained an acceptable predictive performance (Harrell's C of 0.73), which is comparable to that of CHR-P tools currently recommended for clinical use.

Conclusions: This risk calculator may pragmatically support an improved transdiagnostic detection of at-risk individuals and psychosis prediction even in NHS Trusts in the United Kingdom where CHR-P services are not provided.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/schbul/sby070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6483570PMC
April 2019

Long term outcomes of acute and transient psychotic disorders: The missed opportunity of preventive interventions.

Eur Psychiatry 2018 08 19;52:126-133. Epub 2018 May 19.

Early Psychosis: Interventions and Clinical Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, SE5 8AF, London, United Kingdom; OASIS Service, South London and Maudsley NHS Foundation Trust, 190 Kennington Ln, Lambeth, SE11, London, United Kingdom; National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, De Crespigny Park, Camberwell, SE5 8AF, London, United Kingdom; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.

Background: Acute and transient psychotic disorders (ATPD) are characterized by an acute onset and a remitting course, and overlap with subgroups of the clinical high-risk state for psychosis. The long-term course and outcomes of ATPD are not completely clear.

Methods: Electronic health record-based retrospective cohort study, including all patients who received a first index diagnosis of ATPD (F23, ICD-10) within the South London and Maudsley (SLaM) National Health Service Trust, between 1 st April 2006 and 15th June 2017. The primary outcome was risk of developing persistent psychotic disorders, defined as the development of any ICD-10 diagnoses of non-organic psychotic disorders. Cumulative risk of psychosis onset was estimated through Kaplan-Meier failure functions (non-competing risks) and Greenwood confidence intervals.

Results: A total of 3074 patients receiving a first index diagnosis of ATPD (F23, ICD-10) within SLaM were included. The mean follow-up was 1495 days. After 8-year, 1883 cases (61.26%) retained the index diagnosis of ATPD; the remaining developed psychosis. The cumulative incidence (Kaplan-Meier failure function) of risk of developing any ICD-10 non-organic psychotic disorder was 16.10% at 1-year (95%CI 14.83-17.47%), 28.41% at 2-year (95%CI 26.80-30.09%), 33.96% at 3-year (95% CI 32.25-35.75%), 36.85% at 4-year (95%CI 35.07-38.69%), 40.99% at 5-year (95% CI 39.12-42.92%), 42.58% at 6-year (95%CI 40.67-44.55%), 44.65% at 7-year (95% CI 42.66-46.69%), and 46.25% at 8-year (95% CI 44.17-48.37%). The cumulative risk of schizophrenia-spectrum disorder at 8-year was 36.14% (95% CI 34.09-38.27%).

Conclusions: Individuals with ATPD have a very high risk of developing persistent psychotic disorders and may benefit from early detection and preventive treatments to improve their outcomes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.eurpsy.2018.05.004DOI Listing
August 2018

Can We Reduce the Duration of Untreated Psychosis? A Systematic Review and Meta-Analysis of Controlled Interventional Studies.

Schizophr Bull 2018 10;44(6):1362-1372

Early Psychosis: Interventions & Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.

Reduction of duration of untreated psychosis (DUP) is the key strategy of early interventions for improving the outcomes of first-episode psychosis. Although several controlled interventional studies have been conducted with the aim of reducing DUP, the results are highly inconsistent and conflicting. The current study systematically searches Web of Science and Ovid for English original articles investigating interventions adopted to reduce DUP, compared to a control intervention, up to April 6, 2017. Sixteen controlled interventional studies were retrieved, including 1964 patients in the intervention arm and 1358 in the control arm. The controlled intervention studies were characterized by standalone first episode psychosis services, standalone clinical high risk services, community interventions, healthcare professional training, and multifocus interventions. Random effects meta-analyses were conducted. There was no summary evidence that available interventions are successful in reducing DUP during the first episode of psychosis (Hedges' g = -0.12, 95% CI = -0.25 to 0.01). Subgroup analyses showed no differences within each subgroup, with the exception of clinical high risk services (Hedges' g = -0.386, 95% CI = -0.726 to -0.045). These negative findings may reflect a parceled research base in the area, lack of prospective randomized controlled trials (only 2 randomized cluster designed studies were present) and small sample sizes. There was substantial heterogeneity (I2 = 66.4%), most of which was accounted by different definitions of DUP onset (R2 = .88). Psychometric standardization of DUP definition, improvement of study design, and implementation of preventative strategies seem the most promising avenues for reducing DUP and improving outcomes of first-episode psychosis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/schbul/sbx166DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6192469PMC
October 2018