بررسی ارتباط كیفیت ثبت و انجام مراقبتهای پرستاری در بخش اورژانس با میزان ازدحام

Introduction: Overcrowding in the emergency department is a major obstacle in receiving care. The present study was done with the aim of evaluating the relationship of nursing care and documentation qualities with overcrowding in emergency department. Methods: The present cross-sectional study was carried out in Alzahra Hospital, Isfahan, Iran in 2012. Data were gathered by a trained observer throughout working hours of the hospital using a standard checklist extracted from nursing textbooks. Overcrowded shifts were separated from other shifts by considering the number of patients admitted, and results were compared between the 2 situations using statistical analyses. Results: 170 patient files were evaluated regarding the quality of nursing and its documentation. According to the statistical analyses, documenting the nursing care given decreased at overcrowded times (p = 0.028), however the quality of care given did not vary (p = 0.36). Conclusion: The results of this study showed that despite the decline in quality of nursing care documentation following overcrowding in emergency department, rate and quality of care were not affected by overcrowding. مقدمه: ازدحام در بخش اورژانس به عنوان یکی از موانع اصلی در دریافت مراقبت های درمانی به شمار می رود و می تواند بازتابی از عدم تطابق عرضه و تقاضا در سیستم های بهداشتی درمانی باشد. مطالعه حاضر با هدف ارزیابی ارتباط كیفیت ثبت و انجام مراقبتهای پرستاری در بخش اورژانس با میزان ازدحام طراحی و انجام شده است. روش کار: پژوهش حاضر یك مطالعه مقطعی است که در سال 1391 در مرکز پزشکی آموزشی و درمانی الزهرا شهر اصفهان، ایران انجام گرفته است. جمع آوری اطلاعات توسط یک مشاهده گر آموزش دیده در تمام ساعات بستری بیمار با استفاده از چک لیست مراقبتی استاندارد تهیه شده از کتب پرستاری انجام گرفت. با توجه به آمار تعداد بیماران پذیرش شده به نسبت پرستاران، شیفتهای کم ازدحام و پر ازدحام تفکیک گردیده و نتایج حاصله در دو وضعیت مورد آنالیز آماری و مقایسه قرار گرفت. يافته ها: در مجموع پرونده 170 بیمار از نظر كیفیت ثبت و انجام مراقبت‌های پرستاری در زمان پرازدحام و کم ازدحام بررسی شد. طبق آنالیز آماری انجام گرفته کیفیت ثبت اقدامات پرستاری در زمان پر ازدحام در اورژانس کاهش یافته است (028/0=p). ولی کیفیت انجام مراقبتهای پرستاری از بیماران با افزایش ازدحام تغییری حاصل نکرد (36/0=p). نتيجه گيری: نتایج مطالعه حاضر نشان داد که علی رغم کاهش کیفیت ثبت خدمات پرستاری به دنبال افزایش ازدحام در بخش اورژانس، میزان و کیفیت ارائه خدمات بالینی به بیماران از شلوغی متاثر نشده بود

Quality of Nursing Care and Documentation with Overcrowding in Emergency Department

Introduction: Overcrowding in the emergency department is a major obstacle in receiving care. The present study was done with the aim of evaluating the relationship of nursing care and documentation qualities with overcrowding in emergency department. Methods: The present cross-sectional study was carried out in Alzahra Hospital, Isfahan, Iran in 2012. Data were gathered by a trained observer throughout working hours of the hospital using a standard checklist extracted from nursing textbooks. Overcrowded shifts were separated from other shifts by considering the number of patients admitted, and results were compared between the 2 situations using statistical analyses. Results: 170 patient files were evaluated regarding the quality of nursing and its documentation. According to the statistical analyses, documenting the nursing care given decreased at overcrowded times (p = 0.028), however the quality of care given did not vary (p = 0.36). Conclusion: The results of this study showed that despite the decline in quality of nursing care documentation following overcrowding in emergency department, rate and quality of care were not affected by overcrowding

Transient inhibition of NF-κB signaling enhances ex vivo propagation of human hematopoietic stem cells

Despite extensive studies, defining culture conditions in which hematopoietic stem cells can be expanded ex vivo has been challenging. Here we show that chemical inhibition of the NF- κB signaling pathway leads to a significant improvement of hematopoietic stem cell function from ex vivo cultured human umbilical cord blood derived CD34+ cells. We found a distinct peak of activation of the NF-κB pathway shortly after cells were put in culture, and consequently inhibition of the pathway was both necessary and sufficient during the first 24 hours of culture where it reduced the levels of several pro-inflammatory cytokines. Taken together, NF-κB pathway inhibition facilitates propagation of hematopoietic stem cells in culture and may complement other strategies for hematopoietic stem cell expansion by relieving stress signals that are induced as an immediate response to culture initiation

RNAi screen identifies MAPK14 as a druggable suppressor of human hematopoietic stem cell expansion.

We report on a forward RNAi screen in primary human hematopoietic stem and progenitor cells, using pooled lentiviral shRNA libraries deconvoluted by next generation sequencing. We identify MAPK14/p38α as a modulator of ex vivo stem cell proliferation and show that pharmacological inhibition of p38 dramatically enhances the stem cell activity of cultured umbilical cord blood derived hematopoietic cells. p38 inhibitors should thus be considered in strategies aiming at expanding stem cells for clinical benefit

Optimization of ReaxFF Reactive Force Field Parameters for Cu/Si/O Systems via Neural Network Inversion with Application to Copper Oxide Interaction with Silicon

The presence of transition metal oxide impurities introduced during crystal formation or during the fabrication process may lead to a significant yield loss in microelectronics and device manufacturing. To enable a large-scale molecular dynamics study of the effects of copper oxide impurities inside silicon on the structural evolution and mechanical properties of Cu/Si/O systems, one needs to understand the diffusional characteristics of copper and oxygen compounds next to the silicon lattice. In this work, we introduce an accelerated deep learning-based reactive force field parametrization platform. In this platform, we train a deep neural network to learn the production of ReaxFF outputs, given a set of force field parameters. Subsequently, the trained neural network is used, as an alternative to ReaxFF, by means of the neural network inversion algorithm to seek the inputs to the neural network (force field parameters) that produce the experimental and quantum mechanics reference property values of the system. We compared the performance of the neural network inversion optimization algorithm with that of the previously used brute force search method by looking at the total optimization time and the total reduction of the discrepancies between the results of molecular dynamic simulation and the reference property values within the force field training set. The neural network inversion algorithm significantly reduces the average optimization time, which directly translates into less computational resources required for the optimization process. Moreover, we compared the quality of the force fields optimized by both algorithms in describing the chemical properties of the Cu/O systems, including the heat of formation and the relative phase stability. We demonstrated that the results of the force field, optimized using the proposed neural network inversion algorithm, align more closely with the reference chemical properties of Cu/O systems within the force field training set than those optimized by the brute force algorithm. We used this platform to develop a Cu/Si/O ReaxFF reactive force field by training on density functional theory (DFT) data, including heat of formation values for various Cu/Si/O materials. The developed force field was further used to perform molecular dynamics simulations on models with up to 3542 atoms to study atomistic interactions between copper oxide compounds and silicon by looking at the diffusional behavior of copper and oxygen atoms adjacent to the Si substrate. We found that the temperature substantially impacts the Cu oxide diffusion coefficient. Our simulation results enable us to comprehensively understand the effects of oxygen atoms on the diffusion of copper impurities into the silicon lattice. We showed that a Cu oxide cluster shows diffusion faster than that of a pure Cu cluster adjacent to a Si supercell. By studying the interaction between Cu oxide and Si nanolayers at different temperatures, we observed that at higher temperatures, oxygen atoms migrate from the initial CuOx material to diffuse into the Si phase. In addition, we showed that the absolute decay rate of the average Cu–Cu bond length is directly dependent on the simulation temperature