4 research outputs found

    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?

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    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

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

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    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

    SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

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    Background Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population.The aim of this study was to inform vaccination prioritization by modelling the impact of vaccination on elective inpatient surgery. The study found that patients aged at least 70 years needing elective surgery should be prioritized alongside other high-risk groups during early vaccination programmes. Once vaccines are rolled out to younger populations, prioritizing surgical patients is advantageous
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