A new case manager for diabetic patients: a pilot observational study of the role of community pharmacists and pharmacy services in the case management of diabetic patients

The adherence of type 2 diabetes mellitus (DM2) patients with an individual care plan (ICP) is often not satisfactory, nor does it allow for a significant improvement in outcome, because of poor accessibility to services, poor integration of pathway articulations, poor reconciliation with the patient's life, or the lack of a constant reference person. The purpose of this study was to evaluate the contribution of community pharmacists and pharmacy services in improving adherence with periodic controls in DM2. The study was conducted at a rural pharmacy. A sample of 40 patients was calculated with respect to a historical cohort and subsequently enrolled. Clinical and personal data were collected in an electronic case report form. Pharmacists acting as a case manager followed patients carrying out their ICP developed by an attending physician. Some of the activities foreseen by the ICP, such as electrocardiogram, fundus examination, and self-analysis of blood and urine, were carried out directly in the pharmacy by the pharmacist through the use of telemedicine services and point of care units. Activities that could not be performed in the pharmacy were booked by the pharmacist at the accredited units. Examination results were electronically reported by the pharmacist to the attending physician. The primary endpoint was the variation in patient adherence with the ICP compared to a historical cohort. Secondary endpoints were variation in waiting time for the examinations, mean percentage change in glycated hemoglobin (HbA1c) and low-density lipoprotein (LDL) cholesterol levels and blood pressure, impact on healthcare-related costs, and perceived quality of care. Adherence to the ICP significantly increased. Waiting times were reduced and clinical outcomes improved with conceivable effects on costs. Patients appreciated the easier access to services. Community pharmacists and pharmacy services represent ideal actors and context that, integrated in the care network, can really favor ICP adherence and obtain daily morbidity reduction and cost savings through proper disease control and an early diagnosis of complications

The use of pediatric flexible bronchoscopy in the COVID-19 pandemic era

On March 11, 2020, the World Health Organization (WHO) declared the pandemic because of a novel coronavirus, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In January 2020, the first transmission to healthcare workers (HCWs) was described. SARS-CoV-2 is transmitted between people because of contact, droplets, and airborne. Airborne transmission is caused by aerosols that remain infectious when suspended in air over long distances and time. In the clinical setting, airborne transmission may occur during aerosol generating procedures like flexible bronchoscopy. To date, although the role of children in the transmission of SARS-CoV-2 is not clear the execution of bronchoscopy is associated with a considerably increased risk of SARS-CoV-2 transmission to HCWs. The aim of this overview is to summarize available recommendations and to apply them to pediatric bronchoscopy. We performed systematic literature searches using the MEDLINE (accessed via PubMed) and Scopus databases. We reviewed major recommendations and position statements published at the moment by the American Association for Bronchology and Interventional Pulmonology, WHO, European Center for Disease Prevention and Control and expert groups on the management of patients with COVID-19 to limit transmission among HCWs. To date there is a lack of recommendations for safe bronchoscopy during the pandemic period. The main indications concern adults and little has been said about children. We have summarized available recommendations and we have applied them to pediatric bronchoscopy

Modelling Hospital Medical Wards to Address Patient Complexity: A Case-Based Simulation-Optimization Approach

In this paper we focus on patient flows inside Internal Medicine Departments, with the aim of supporting new organizational models taking into account the patient relevant characteristics such as complexity and frailty. The main contribution of this paper is to develop a Discrete Event Simulation model to describe in detail the pathways of complex patients through medical hospital wards. The model has been applied to reproduce a case study of an Italian middle size hospital. The objective is quantifying the impact on resource use and outcome of introducing a new organizational model for medical departments. The re-organization is mainly focused on changing the available beds assignment among the wards to better address the complexity of care of patients with comorbidities. Following a patient-centered approach, patients are segmented considering the clinical characteristics (i.e. the pathology, proxy of Diagnoses Related Groups classification) and sub-grouped considering other characteristics, such as comorbidities and ward of admission. Then, an optimization component embedded into the model chooses the best pooling strategy to reorganize medical wards, determining the corresponding number of beds able to improve process indicators, such as length of stay. The simulation model is presented, and preliminary results are analyzed and discussed

Analysis of the RLMS Adaptive Beamforming Algorithm Implemented with Finite Precision

This paper studies the influence of the use of finite wordlength on the operation of the RLMS adaptive beamformingalgorithm. The convergence behavior of RLMS, based on the minimum mean square error (MSE), is analyzed for operation with finite precision. Computer simulation results verify that a wordlength of nine bits is sufficient for the RLMS algorithm to achieve performance close to that provided by full precision. The performance measures used include residual MSE, rate of convergence, error vector magnitude (EVM), and beam pattern. Based on all these measures, it is shown that the RLMS algorithm outperforms other earlier algorithms, such as least mean square (LMS), recursive least square (RLS), modified robust variable step size (MRVSS) and constrained stability LMS (CSLMS)

The search for the 'next' euphoric non-fentanil novel synthetic opioids on the illicit drugs market: current status and horizon scanning

Purpose: A detailed review on the chemistry and pharmacology of non-fentanil novel synthetic opioid receptor agonists, particularly N-substituted benzamides and acetamides (known colloquially as U-drugs) and 4-aminocyclohexanols, developed at the Upjohn Company in the 1970s and 1980s is presentedMethod: Peer-reviewed literature, patents, professional literature, data from international early warning systems and drug user fora discussion threads have been used to track their emergence as substances of abuse.Results: In terms of impact on drug markets, prevalence and harm, the most significant compound of this class to date has been U-47700 (trans-3,4-dichloro-N-[2-(dimethylamino)cyclohexyl]-N-methylbenzamide), reported by users to give short-lasting euphoric effects and a desire to re-dose. Since U-47700 was internationally controlled in 2017, a range of related compounds with similar chemical structures, adapted from the original patented compounds, have appeared on the illicit drugs market. Interest in a structurally unrelated opioid developed by the Upjohn Company and now known as BDPC/bromadol appears to be increasing and should be closely monitored.Conclusions: International early warning systems are an essential part of tracking emerging psychoactive substances and allow responsive action to be taken to facilitate the gathering of relevant data for detailed risk assessments. Pre-emptive research on the most likely compounds to emerge next, so providing drug metabolism and pharmacokinetic data to ensure that new substances are detected early in toxicological samples is recommended. As these compounds are chiral compounds and stereochemistry has a large effect on their potency, it is recommended that detection methods consider the determination of configuration

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

Multivariate Protein Signatures of Pre-Clinical Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative (ADNI) Plasma Proteome Dataset

Background: Recent Alzheimer's disease (AD) research has focused on finding biomarkers to identify disease at the pre-clinical stage of mild cognitive impairment (MCI), allowing treatment to be initiated before irreversible damage occurs. Many studies have examined brain imaging or cerebrospinal fluid but there is also growing interest in blood biomarkers. The Alzheimer's Disease Neuroimaging Initiative (ADNI) has generated data on 190 plasma analytes in 566 individuals with MCI, AD or normal cognition. We conducted independent analyses of this dataset to identify plasma protein signatures predicting pre-clinical AD. Methods and Findings: We focused on identifying signatures that discriminate cognitively normal controls (n = 54) from individuals with MCI who subsequently progress to AD (n = 163). Based on p value, apolipoprotein E (APOE) showed the strongest difference between these groups (p = 2.3×10−13). We applied a multivariate approach based on combinatorial optimization ((α,β)-k Feature Set Selection), which retains information about individual participants and maintains the context of interrelationships between different analytes, to identify the optimal set of analytes (signature) to discriminate these two groups. We identified 11-analyte signatures achieving values of sensitivity and specificity between 65% and 86% for both MCI and AD groups, depending on whether APOE was included and other factors. Classification accuracy was improved by considering “meta-features,” representing the difference in relative abundance of two analytes, with an 8-meta-feature signature consistently achieving sensitivity and specificity both over 85%. Generating signatures based on longitudinal rather than cross-sectional data further improved classification accuracy, returning sensitivities and specificities of approximately 90%. Conclusions: Applying these novel analysis approaches to the powerful and well-characterized ADNI dataset has identified sets of plasma biomarkers for pre-clinical AD. While studies of independent test sets are required to validate the signatures, these analyses provide a starting point for developing a cost-effective and minimally invasive test capable of diagnosing AD in its pre-clinical stages

Induction of autophagy by spermidine promotes longevity.

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