423 research outputs found

    Study Drugs for Underprivileged Children

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    Abstract The effects of stimulant medication have been beneficial for individuals with Narcolepsy and especially individuals with Attention Deficit Hyperactivity Disorder. Keisha Ray has offered a solution in her academic work that could help also help underprivileged children. The solution she is proposing is to offer stimulant medication to them. In this paper, I assert my thesis, offering stimulant medication to underprivileged children would not be a good, right, and practical solution to helping their social inequalities. The treatment/enhancement distinction in medicine is elaborated between Ray and me. The definition of what is a healthy normal functioning body and a body that is disabled is defined. I document the research I did which involves a book by Elizabeth Barnes and a theory discussed by Richard Arneson. I offer a definition for the term “social disability.” I then assert the possible alternative solutions to Ray’s proposal that she will agree with. Keywords: disability, social disability, ADHD, underprivileged children, Philosophy of Disability, social inequality, healthy body, stimulants, Keisha Ray

    Late time cosmological phase transitions 1: Particle physics models and cosmic evolution

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    We described a natural particle physics basis for late-time phase transitions in the universe. Such a transition can seed the formation of large-scale structure while leaving a minimal imprint upon the microwave background anisotropy. The key ingredient is an ultra-light pseudo-Nambu-Goldstone boson with an astronomically large (O(kpc-Mpc)) Compton wavelength. We analyze the cosmological signatures of and constraints upon a wide class of scenarios which do not involve domain walls. In addition to seeding structure, coherent ultra-light bosons may also provide unclustered dark matter in a spatially flat universe, omega sub phi approx. = 1

    Evaluation of Guideline-Directed Medication Therapy for Heart Failure with Reduced Ejection Fraction Patients at Discharge on 30-Day Readmission Rates at Two Tertiary Healthcare Centers

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    Evaluation of Guideline-Directed Medication Therapy for Heart Failure with Reduced Ejection Fraction Patients at Discharge on 30-Day Readmission Rates at Two Tertiary Healthcare Centers Principal Investigator: Jacqueline Hesse, Pharm.D. Preceptors: Yan Xu, Pharm.D., BCPS, BCCP; Meri Slavica, Ph.D., BCPS Pharmacy Student: James Watkins, 2020 Pharm.D. Candidate Sub-Investigators: Alan Rankin, MD; Joshua Remick, MD Background: Heart failure with reduced ejection fraction (HFrEF) is a chronic, progressive disease leading to symptoms such as dyspnea, cough, edema, fatigue, and exercise intolerance. The use of anangiotensin converting enzyme inhibitor (ACEi), angiotensin II receptor blocker (ARB), or angiotensin receptor-neprilysin inhibitor (ARNI) in combination with an evidence-based beta blocker (BB) is guideline-supported Class I recommended therapy for HFrEF with an LVEF Methods: A retrospective chart review was completed using the Epic Electronic Medical Record of all patients admitted to one of our tertiary medical centers between January 1, 2018 and December 31, 2019 with a primary diagnosis of HFrEF. Patients were included if they were at least 18 years of age and had an LVEF of Results A total of 1,999 patient admissions underwent chart review with 752 admissions not meeting inclusion criteria and 1,247 admissions being included in the final analysis. Of those included, 202 patients (16%) were readmitted within 30 days. Patients discharged with any GDMT had less readmissions within 30 days than those without any GDMT (OR 0.6, 95% CI 0.4-1.0, p = 0.0369). However, patients discharged on an ACEi or ARB had more readmissions within 30 days than patients discharged on no GDMT (OR 1.4, 95% CI 1.0-1.9, p = 0.0283). 49% of patients (N = 609) had an idiopathic cause of heart failure followed by 32% of patients with non-ischemic cardiomyopathy (N = 394) and 20% of patients with ischemic cardiomyopathy (N = 244). No significant differences were found between the 30-day readmission rate and cause of heart failure. For highest K value on readmission, no significant differences were found between groups. For highest SCr on readmission, discharging on an ACEi or ARB or discharging on an ACEi or ARB in combination with a BB yielded a significantly lower SCr on readmission compared to no GDMT (1.6 vs. 2.6, p = Conclusion In conclusion, patients admitted with a primary diagnosis of HFrEF that are discharged on any GDMT were found to have less readmissions for any reason within 30 days than those without any GDMT. However, subgroup analysis for individual GDMT may not have a lower rate of readmissions. Further research with prospective randomized controlled trials is needed to determine statistical significance of subgroups of GDMT on the rate of readmission within 30 days.https://digitalcommons.psjhealth.org/pharmacy_PGY1/1010/thumbnail.jp

    Balancing health and financial protection in health benefit package design

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    Policymakers face difficult choices over which health interventions to publicly finance. We developed an approach to health benefits package design that accommodates explicit tradeoffs between improvements in health and provision of financial risk protection (FRP). We designed a mathematical optimization model to balance gains in health and FRP across candidate interventions when publicly financed. The optimal subset of interventions selected for inclusion was determined with bi-criterion integer programming conditional on a budget constraint. The optimal set of interventions to publicly finance in a health benefits package varied according to whether the objective for optimization was population health benefits or FRP. When both objectives were considered jointly, the resulting optimal essential benefits package depended on the weights placed on the two objectives. In the Sustainable Development Goals era, smart spending toward universal health coverage is essential. Mathematical optimization provides a quantitative framework for policymakers to design health policies and select interventions that jointly prioritize multiple objectives with explicit financial constraints.publishedVersio

    Implementation Support Improves Outcomes of a Fluency-Based Mathematics Strategy: A Cluster-Randomized Controlled Trial

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    The Say-All-Fast-Minute-Every-Day-Shuffled (SAFMEDS) strategy promotes fast and accurate recall. The existing literature suggests that the strategy can help learners improve academic outcomes. Through a cluster randomized controlled trial, we assessed the impact of implementation support on children’s mathematics outcomes during a teacher-led SAFMEDS intervention. Following training and prior to baseline assessments, we randomly allocated schools to receive either no (n = 31) or ongoing (n = 33) support from a researcher. Support consisted of three in-situ visits and email contact. Assessors remained blind to the condition of the schools throughout. We analyzed the outcomes of children (nSupport = 294, nNoSupport = 281) using a multi-level mixed-effects model; accounting for the children nested within schools. The results suggest that implementation support has a small effect on children’s fluency of arithmetic facts (Mathematics Fluency and Calculation Tests (MFaCTs): Grades 1–2, d = 0.23, 95% CI: 0.06–0.40; MFaCTs: Grades 3–5, d = 0.25, 95% CI: 0.08–0.42). These results are larger than the average effect sizes reported within professional development literature that apply coaching elements to mathematics programs

    SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers

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    We investigate Siamese networks for learning related embeddings for augmented samples of molecular conformers. We find that a non-contrastive (positive-pair only) auxiliary task aids in supervised training of Euclidean neural networks (E3NNs) and increases manifold smoothness (MS) around point-cloud geometries. We demonstrate this property for multiple drug-activity prediction tasks while maintaining relevant performance metrics, and propose an extension of MS to probabilistic and regression settings. We provide an analysis of representation collapse, finding substantial effects of task-weighting, latent dimension, and regularization. We expect the presented protocol to aid in the development of reliable E3NNs from molecular conformers, even for small-data drug discovery programs.Comment: Submitted to the MLDD workshop, ICLR 202
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