临床护理人员用药风险防范认知度调查分析

目的：了解护理人员对用药风险防范的认知和重视程度,加强用药风险管理,保障患者用药安全。方法：对护理人员进行用药风险防范认知度问卷调查,并对调查结果进行分析。结果：有13.04%的护理人员没有认识到防范用药风险的责任;对药品不良反应、用药错误和药品损害三个基本概念的总体认知率分别为39.13%,30.43%和58.69%;对药物不良事件的报告意愿率为67.39%。结论：以药品不良反应、用药错误和药品损害为用药风险的主要来源,采用教育、制度和督查并重的方法,不断强化防范用药风险的责任意识。     

Clinical pharmacy services in the emergency department

The emergency department (ED) is a fast-paced, high-risk, and often overburdened work environment. Formal policy statements from several notable organizations, including the American College of Emergency Physicians (ACEP) and the American Society of Health-System Pharmacists (ASHP), have recognized the importance of clinical pharmacists in the emergency medicine (EM) setting. EM clinical pharmacists work alongside emergency physicians and nurses at the bedside to optimize pharmacotherapy, improve patient safety, increase efficiency and cost-effectiveness of care, facilitate antibiotic stewardship, educate patients and clinicians, and contribute to scholarly efforts. This paper examines the history of EM clinical pharmacists and associated training programs, the diverse responsibilities and roles of EM clinical pharmacists, their impact on clinical and financial outcomes, and proposes a conceptual model for EM clinical pharmacist integration into ED patient care. Finally, barriers to implementing EM clinical pharmacy programs and limitations are considered.     

Economic repercussions of fisheries-induced evolution

Fish stocks experiencing high fishing mortality show a tendency to mature earlier and at a smaller size, which may have a genetic component and therefore long-lasting economic and biological effects. To date, the economic effects of such ecoevolutionary dynamics have not been empirically investigated. Using 70 y of data, we develop a bioeconomic model for Northeast Arctic cod to compare the economic yield in a model in which life-history traits can vary only through phenotypic plasticity with a model in which, in addition, genetic changes can occur. We find that evolutionary changes toward faster growth and earlier maturation occur consistently even if a stock is optimally managed. However, if a stock is managed optimally, the evolutionary changes actually increase economic yield because faster growth and earlier maturation raise the stock’s productivity. The optimal fishing mortality is almost identical for the evolutionary and nonevolutionary model and substantially lower than what it has been historically. Therefore, the costs of ignoring evolution under optimal management regimes are negligible. However, if fishing mortality is as high as it has been historically, evolutionary changes may result in economic losses, but only if the fishery is selecting for medium-sized individuals. Because evolution facilitates growth, the fish are younger and still immature when they are susceptible to getting caught, which outweighs the increase in productivity due to fish spawning at an earlier age.     

ECG beat classification based on discrete wavelet transformation and nearest neighbour classifier

Abstract

Myocardial infarction (MI) is a coronary artery disease acquired due to the lack of blood supply in one or more sections of the myocardium, resulting in necrosis in that region. It has different types based on the region of necrosis. In this paper, a statistical approach for classification of Anteroseptal MI (ASMI) is proposed. The first step of the method involves noise elimination and feature extraction from the Electrocardiogram (ECG) signals, using multi-resolution wavelet analysis and thresholding-based techniques. In the next step a classification scheme is developed using the nearest neighbour classification rule (NN rule). Both temporal and amplitude features relevant for automatic ASMI diagnosis are extracted from four chest leads v1–v4. The distance metric for NN classifier is calculated using both Euclidian distance and Mahalanobis distance. A relative comparison between these two techniques reveals that the later is superior to the former, as evident from the classification accuracy. The proposed method is tested and validated using the PTB diagnostic database. Classification accuracy for Mahalanobis distance and Euclidean distance-based NN rule are 95.14% and 81.83%, respectively.