What is the easier and more reliable dose calculation for iv Phenytoin in children at risk of developing convulsive status epilepticus, 18 mg/kg or 20 mg/kg?

Background: With the Convulsive Status Guidelines due for renewal, we wondered if a phenytoin dose of ‘20 mg/kg’ would be easier to calculate correctly and therefore safer than the current ‘18 mg/kg’. An educational exercise in dose calculation was therefore undertaken to assess ease of calculation. Method: A standard question paper was prepared, comprising five clinical scenarios with children of varying ages and estimated body weights. Medical students, trainee doctors at registrar and senior house officer level, and consultant paediatricians were asked to complete the exercise, in private, by one of two medical students (SD, PS). Calculations were done with and without a calculator, for 18 mg/kg and for 20 mg/kg in randomised order. Speed and errors (greater than 10%) were determined. The data analysis was performed using SPSS version 18. Results: All answered all 20 scenarios, giving a total of 300 answers per doctor/student group, and 300 answers per type of calculation. When comparing the 2 doses, the numbers of errors more than 10% were significantly less in 20 mg/kg dose (0.33%) as compared to the 18 mg/kg dose (9.3%) (p<0.0001). Speed off calculation was significantly decreased in 20 mg/kg dose when compared with 18 mg/kg dose, with (p<0.001) or without (p<0.0001) the calculator. Speed was more than halved and errors were much less frequent by using a calculator, for the 18 mg/kg dose but no difference with or without the calculator for 20 mg/kg dose. Conclusion: We recommend that the future guidelines should suggest iv Phenytoin at 20 mg/kg rather than 18 mg/kg. This will make the calculation easier and reduce the risk of significant errors

Enabling FAIR data stewardship in complex international multi-site studies: Data Operations for the Accelerating Medicines Partnership® Schizophrenia Program.

Modern research management, particularly for publicly funded studies, assumes a data governance model in which grantees are considered stewards rather than owners of important data sets. Thus, there is an expectation that collected data are shared as widely as possible with the general research community. This presents problems in complex studies that involve sensitive health information. The latter requires balancing participant privacy with the needs of the research community. Here, we report on the data operation ecosystem crafted for the Accelerating Medicines Partnership® Schizophrenia project, an international observational study of young individuals at clinical high risk for developing a psychotic disorder. We review data capture systems, data dictionaries, organization principles, data flow, security, quality control protocols, data visualization, monitoring, and dissemination through the NIMH Data Archive platform. We focus on the interconnectedness of these steps, where our goal is to design a seamless data flow and an alignment with the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles while balancing local regulatory and ethical considerations. This process-oriented approach leverages automated pipelines for data flow to enhance data quality, speed, and collaboration, underscoring the projects contribution to advancing research practices involving multisite studies of sensitive mental health conditions. An important feature is the datas close-to-real-time quality assessment (QA) and quality control (QC). The focus on close-to-real-time QA/QC makes it possible for a subject to redo a testing session, as well as facilitate course corrections to prevent repeating errors in future data acquisition. Watch Dr. Sylvain Bouix discuss his work and this article: https://vimeo.com/1025555648

Cognitive assessment in the Accelerating Medicines Partnership® Schizophrenia Program:harmonization priorities and strategies in a diverse international sample

Cognitive impairment occurs at higher rates in individuals at clinical high risk (CHR) for psychosis relative to healthy peers, and it contributes unique variance to multivariate prediction models of transition to psychosis. Such impairment is considered a core biomarker of schizophrenia. Thus, cognition is a key domain measured in the Accelerating Medicines Partnership® program for Schizophrenia (AMP SCZ initiative). The aim of this paper is to describe the rationale, processes, considerations, and final harmonization of the cognitive battery used in AMP SCZ across the two data collection networks. This battery comprises tests of general intellect and specific cognitive domains. We estimate premorbid intelligence at baseline and measure current intelligence at baseline and 2 years. Eight tests from the Penn Computerized Neurocognitive Battery (PennCNB), which measure verbal learning and memory, sensorimotor ability, attention, emotion recognition, working memory, processing speed, verbal memory, visual memory, and motor speed are administered repeatedly at baseline, and four follow-up timepoints over 2 years.</p

Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals

Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ):Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals.</p

Enabling FAIR data stewardship in complex international multi-site studies: Data Operations for the Accelerating Medicines Partnership® Schizophrenia Program.

Enabling FAIR data stewardship in complex international multi-site studies: Data Operations for the Accelerating Medicines Partnership® Schizophrenia Program

Digital health technologies in the accelerating medicines Partnership® Schizophrenia Program

Abstract Although meta-analytic studies have shown that 25-33% of those at Clinical High Risk (CHR) for psychosis transition to a first episode of psychosis within three years, less is known about estimating the risk of transition at an individual level. Digital phenotyping offers a novel approach to explore the nature of CHR and may help to improve personalized risk prediction. Specifically, digital data enable detailed mapping of experiences, moods and behaviors during longer periods of time (e.g., weeks, months) and offer more insight into patterns over time at the individual level across their routine daily life. However, while novel digital health technologies open up many new avenues of research, they also come with specific challenges, including replicability of results and the adherence of participants. This paper outlines the design of the digital component of the Accelerating Medicines Partnership® Schizophrenia Program (AMP SCZ) project, a large international collaborative project that follows individuals at CHR for psychosis over a period of two years. The digital component comprises one-year smartphone-based digital phenotyping and actigraphy. Smartphone-based digital phenotyping includes 30-item short daily self-report surveys and voice diaries as well as passive data capture (geolocation, on/off screen state, and accelerometer). Actigraphy data are collected via an Axivity wristwatch. The aim of this paper is to describe the design and the three goals of the digital measures used in AMP SCZ to: (i) better understand the symptoms, real-life experiences, and behaviors of those at CHR for psychosis, (ii) improve the prediction of transition to psychosis and other health outcomes in this population based on digital phenotyping and, (iii) serve as an example for replicable and ethical research across geographically diverse regions and cultures. Accordingly, we describe the rationale, protocol and implementation of these digital components of the AMP SCZ project. **Link to video interview: https://vimeo.com/1060935583 *

Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis

Abstract This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals