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A new study investigates the impact of power posing - the holding of wide and expansive postures - on self-reported feelings of power and the subsequent effect on paranoia.
Real-world implementation of precision psychiatry: Transdiagnostic risk calculator for the automatic detection of individuals at-risk of psychosis
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.
Real-world digital implementation of the Psychosis Polyrisk Score (PPS): A pilot feasibility study
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.
Worldwide implementation of clinical services for the prevention of psychosis: The IEPA early intervention in mental health survey
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.
Universal and selective interventions to promote good mental health in young people: Systematic review and meta-analysis
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.
Adverse effects of cannabidiol: a systematic review and meta-analysis of randomized clinical trials.
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.
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.
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.
Intranasal oxytocin increases heart-rate variability in men at clinical high risk for psychosis: a proof-of-concept study.
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.
Psychiatric and neuropsychiatric presentations associated with severe coronavirus infections: a systematic review and meta-analysis with comparison to the COVID-19 pandemic
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, I2 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.
Acute oxytocin effects in inferring others' beliefs and social emotions in people at clinical high risk for psychosis.
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.
T97. REAL WORLD IMPLEMENTATION OF A TRANSDIAGNOSTIC RISK CALCULATOR FOR THE AUTOMATIC DETECTION OF INDIVIDUALS AT RISK OF PSYCHOSIS IN CLINICAL ROUTINE
Abstract Background Detection of individuals at-risk for psychosis is the rate-limiting step of primary indicated prevention. Improvement is imperative to improving clinical outcomes; to mitigate this, our group has developed a transdiagnostic, clinically-based, individualised risk calculator. The risk calculator uses simple predictors (age, gender, ethnicity, ICD-10 diagnosis and age*gender interaction) selected a priori and recorded as part of clinical routine. While there are numerous examples of prognostic tools in psychiatry that have been externally validated, there are none that have been implemented into clinical practice. This is the first study assessing the implementation of a prognostic tool in psychiatry. Methods A feasibility study was composed of both an initial in-vitro phase, aiming to successfully integrate the risk calculator into the local electronic case register, as well as an in-vivo phase to investigate the feasibility of real world implementation of the calculator in clinical routine. The in-vitro phase involved development of the risk calculator prototype, addressing of feasibility problems associated with its implementation in clinical practice, and conducting clinician engagement work prior to initiating in-vivo piloting. In the in-vivo phase, the risk calculator was implemented into the local electronic health records. Clinicians were not required to enter any new variables as predictors were recorded as part of clinical routine. All patients over the age of 14 receiving a non-organic, non-psychotic primary index diagnosis were automatically assessed for psychosis risk, with responsible clinicians being contacted if their patient was considered to be above 5% risk within 2 years. The primary outcome was adherence of clinicians to the use of the transdiagnostic risk calculator, as measured by the proportion of clinicians who responded to prompts sent on the recommendation of the calculator. Results Of the 88 patients included in the final sample, mean (SD) age was 39.05 (18.27) and 33 (37.5%) were male. The calculator was successfully integrated into the local electronic case register, running automatically to estimate psychosis risk on all new cases in our mental health trust. Clinician adherence was high (84%), providing evidence of successful implementation of the risk calculator in clinical routine. 55% of clinicians who responded also referred their patient for a refined psychosis risk assessment, highlighting the applicability of the calculator. Discussion This implementation study provides the rationale for a prospective effectiveness study for our transdiagnostic, clinically-based, individualised risk calculator. This risk calculator has the potential to significantly improve the identification of individuals at-risk for psychosis and has been shown to be feasible to use in clinical routine. Additionally, this highlights the absence of implementation research in psychiatry, in spite of the prolific publishing of prognostically accurate models.
T139. OXYTOCIN ENHANCES NEURAL EFFICIENCY IN INFERRING OTHERS’ SOCIAL EMOTIONS IN PEOPLE AT CLINICAL HIGH RISK FOR PSYCHOSIS
Abstract Background Negative symptoms are core contributors to social deficits in psychosis. However, currently available interventions do not significantly ameliorate negative symptoms or social outcomes in individuals at Clinical High Risk of Psychosis (CHR-P). Given its critical role in human social behaviour and cognition, the oxytocin (OT) system is a promising target for the treatment of social impairments in CHR-P subjects. Methods 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 intranasal OT and once after placebo. A modified version of the Sally-Anne task was used to record brain activation during inferring others’ beliefs (cognitive empathy) and social emotions (emotional empathy). The Reading the Mind in the Eyes Test was acquired to test whether OT effects were mediated by baseline social-emotional abilities. Results OT did not modulate behavioural task performance but reduced activation in the bilateral inferior frontal gyrus compared with placebo during emotional empathy. Furthermore, the relationship between brain activation and task performance after OT administration was mediated by baseline social-emotional abilities; while task accuracy during emotional empathy 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 individual with high social-emotional abilities. Discussion These findings suggest that OT enhances neural efficiency in inferring others’ social emotions in those people at clinical high risk for psychosis with attenuated emotional empathy.
M136. PSYCHOSIS POLYRISK SCORE (PPS): IMPROVING DETECTION OF INDIVIDUALS AT-RISK AND PREDICTION OF CLINICAL OUTCOMES
Abstract Background Primary prevention in 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. This underlies the limited identification power for at-risk individuals and the relatively modest ability of CHR-P interviews to rule-in a state of risk for psychosis. One potential avenue for improving identification of individuals at risk for psychosis is a Psychosis Polyrisk Score (PPS) integrating genetic and non-genetic risk and protective factors for psychosis. The PPS hinges on recent findings that risk enrichment in CHR-P samples is accounted for by the accumulation of non-genetic factors e.g. parental and sociodemographic risk factors, perinatal risk factors, later risk factors, and antecedents. Methods A prototype of the PPS has been developed encompassing 26 non-genetic risk and protective factors, utilising Relative Risks (RR) from an umbrella review of risk and protective factors for psychosis onset in the general population. This was combined with prevalence data to ensure positive scores indicated increased psychosis risk and negative scores indicated decreased psychosis risk. To pilot this, patients referred for a CHR-P assessment (n=15) and healthy controls (n=66) were recruited and assessed with the PPS. Additionally, to investigate the range and distribution of these scores in the general population, 10,000,000 permutations were run utilising prevalence data to produce a simulated dataset. Results In the simulated general population data, scores ranged from -15 (least risk, equivalent RR = 0.03) to 39.5 (highest risk, RR = 8912.51). 50% of individuals had an RR < 1 (PPS < 0), 26.7% of individuals had an RR > 3 (PPS > 5), and 2.7% RR > 30 (PPS > 15). Patients referred for a CHR-P assessment had higher PPS scores (median=9, IQR=12.75) than healthy controls (median=-1.75, IQR=8.875). PPS scores in the simulated general population dataset (median=0, IQR=9.5) were similarly lower than patients. Discussion The PPS has potential for improving identification of individuals at risk for psychosis. Its distribution in a simulated general population is reflective of expected psychosis risk, with the vast majority of people not being at-risk and very few being at high risk. In addition to supplementing current assessments for CHR-P, this could be implemented at an earlier stage to stratify individuals based on psychosis risk and inform prognoses and clinical decision-making. This promise warrants further research to ascertain its prognostic accuracy and optimal thresholds for clinical intervention.
Implementation of a real-time psychosis risk detection and alerting system based on electronic health records using cogstack
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.
Prenatal and perinatal risk and protective factors for psychosis: a systematic review and meta-analysis
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, I2 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.
Are You on My Wavelength? Interpersonal Coordination in Dyadic Conversations
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 (n = 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.
Data Science in Support of Radiation Detection for Border Monitoring: An Exploratory Study
Radiation detection technology is widely deployed to identify undeclared nuclear or radiological materials in transit. However, in certain environments the effective use of radiation detection systems is complicated by the presence of significant quantities of naturally occurring radioactive materials that trigger nuisance alarms which divert attention from valid investigations. The frequency of nuisance alarms sometimes results in the raising of alarming thresholds, reducing the likelihood that systems will detect the low levels of radioactivity produced by key threat materials such as shielded highly enriched uranium. This paper explores the potential of using data science techniques, such as dynamic time warping and agglomerative hierarchical clustering, to provide new insights into the cause of alarms within the maritime shipping environment. These methods are used to analyze the spatial radiation profiles generated by shipments of naturally occurring radioactive materials as they are passed through radiation portal monitors. Applied to a real-life dataset of alarming occupancies, the application of these techniques is shown to preferentially group and identify similar commodities. With further testing and development, the data-driven approach to alarm assessment presented in this paper could be used to characterize shipments of naturally occurring radioactive materials at the primary scanning stage, significantly reducing time spent resolving nuisance alarms.