scholarly journals PROPOSAL FOR NEW CALIBRATION INDEX REFLECTING THE DECISION-MAKING IN ACTUAL CLINICAL PRACTICE: A SIMULATION STUDY

2021 ◽  
Vol 70 (2) ◽  
pp. 201-218
Author(s):  
Yuki Shiko ◽  
Shuhei Yamamoto ◽  
Yosuke Inaba ◽  
Ippeita Dan ◽  
Yohei Kawasaki
Author(s):  
Б.И. Гельцер ◽  
Э.В. Слабенко ◽  
Ю.В. Заяц ◽  
В.Н. Котельников

Одним из основных требований к разработке экспериментальных моделей цереброваскулярных заболеваний является их максимальная приближенность к реальной клинической практике. В работе систематизированы данные по основным методам моделирования острой ишемии головного мозга (ОИГМ), представлена их классификация, анализируются данные о преимуществах и недостатках той или иной модели. Обсуждаются результаты экспериментальных исследований по изучению патогенеза ОИГМ с использованием различных моделей (полной и неполной глобальной, локальной и мультифокальной ишемии) и способов их реализации (перевязка артерий, клипирование, коагуляция, эмболизация и др.). Особое внимание уделяется «стабильности» последствий острого нарушения мозгового кровообращения: необратимых ишемических повреждений головного мозга или обратимых с реперфузией заданной продолжительности. Отмечается, что важное значение в этих исследованиях должно принадлежать современным методам прижизненной визуализации очагов острого ишемического повреждения, что позволяет оценивать динамику патологического процесса. Предлагаемый метод отвечает требованиям гуманного обращения с животными. Подчеркивается, что выбор релевантной модели ОИГМ определяется задачами предстоящего исследования и технологическими ресурсами научной лаборатории. Development of experimental models for acute forms of cerebrovascular diseases is essential for implementation of methods for their prevention and treatment. One of the principal requirements to such models is their maximum approximation to actual clinical practice. This review systematized major models of acute cerebral ischemia (ACI), their classification, and presented information about their advantages and shortcomings. Also, the review presented results of experimental studies on pathophysiological mechanisms of different types of modeled ACI (complete and incomplete global, local, and multifocal ischemia) and methods for creating these models (arterial ligation, clipping, coagulation, embolization, etc.). Particular attention was paid to “stability” of the consequences of acutely impaired cerebral circulation - an irreversible ischemic brain injury or a reversible injury with reperfusion of a given duration. The authors emphasized that in such studies, a special significance should be given to intravital imaging of acute ischemic damage foci using modern methods, which allow assessing the dynamics of the pathological process and meet the requirements to humane treatment of animals. The choice of a relevant ACI model is determined by objectives of the planned study and the technological resources available at the research laboratory.


Author(s):  
Anjali Mullick ◽  
Jonathan Martin

Advance care planning (ACP) is a process of formal decision-making that aims to help patients establish decisions about future care that take effect when they lose capacity. In our experience, guidance for clinicians rarely provides detailed practical advice on how it can be successfully carried out in a clinical setting. This may create a barrier to ACP discussions which might otherwise benefit patients, families and professionals. The focus of this paper is on sharing our experience of ACP as clinicians and offering practical tips on elements of ACP, such as triggers for conversations, communication skills, and highlighting the formal aspects that are potentially involved. We use case vignettes to better illustrate the application of ACP in clinical practice.


2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Hiroko Yuzawa ◽  
Yousuke Hirose ◽  
Tomonori Kimura ◽  
Keisuke Shinozaki ◽  
Moe Oguchi ◽  
...  

Abstract Background In continuous renal replacement therapy (CRRT), administration of anticoagulants is necessary for achieving a certain level of filter lifetime. Generally, anticoagulant doses are controlled to keep activated partial thromboplastin time and other indicators within a certain target range, regardless of the membrane materials used for the filter. However, in actual clinical practice, the filter lifetime varies significantly depending on the membrane material used. The objective of this study was to demonstrate that the minimum anticoagulant dose necessary for prolonging the filter lifetime while reducing the risk of hemorrhagic complications varies depending on the type of membrane. Methods In three beagles, hemodiafiltration was performed with hemofilters using polysulfone (PS), polymethylmethacrylate (PMMA), and AN69ST membranes separately. The minimum dose of nafamostat mesylate (NM) that would allow for 6 h of hemodiafiltration (required dose) was investigated for each membrane material. Results The NM doses required for 6 h of hemodiafiltration were 2 mg/kg/h for the PS membrane, 6 mg/kg/h for the PMMA membrane, and 6 mg/kg/h for the AN69ST membrane. Conclusion For hemodiafiltration performed in beagles, the required NM dose varied for each filter membrane material. Using the optimal anticoagulant dose for each membrane material would allow for safer CRRT performance.


2021 ◽  
Vol 11 (8) ◽  
pp. 3296
Author(s):  
Musarrat Hussain ◽  
Jamil Hussain ◽  
Taqdir Ali ◽  
Syed Imran Ali ◽  
Hafiz Syed Muhammad Bilal ◽  
...  

Clinical Practice Guidelines (CPGs) aim to optimize patient care by assisting physicians during the decision-making process. However, guideline adherence is highly affected by its unstructured format and aggregation of background information with disease-specific information. The objective of our study is to extract disease-specific information from CPG for enhancing its adherence ratio. In this research, we propose a semi-automatic mechanism for extracting disease-specific information from CPGs using pattern-matching techniques. We apply supervised and unsupervised machine-learning algorithms on CPG to extract a list of salient terms contributing to distinguishing recommendation sentences (RS) from non-recommendation sentences (NRS). Simultaneously, a group of experts also analyzes the same CPG and extract the initial patterns “Heuristic Patterns” using a group decision-making method, nominal group technique (NGT). We provide the list of salient terms to the experts and ask them to refine their extracted patterns. The experts refine patterns considering the provided salient terms. The extracted heuristic patterns depend on specific terms and suffer from the specialization problem due to synonymy and polysemy. Therefore, we generalize the heuristic patterns to part-of-speech (POS) patterns and unified medical language system (UMLS) patterns, which make the proposed method generalize for all types of CPGs. We evaluated the initial extracted patterns on asthma, rhinosinusitis, and hypertension guidelines with the accuracy of 76.92%, 84.63%, and 89.16%, respectively. The accuracy increased to 78.89%, 85.32%, and 92.07% with refined machine-learning assistive patterns, respectively. Our system assists physicians by locating disease-specific information in the CPGs, which enhances the physicians’ performance and reduces CPG processing time. Additionally, it is beneficial in CPGs content annotation.


2017 ◽  
Vol 3 (3) ◽  
pp. 88-93 ◽  
Author(s):  
Maureen Anne Jersby ◽  
Paul Van-Schaik ◽  
Stephen Green ◽  
Lili Nacheva-Skopalik

BackgroundHigh-Fidelity Simulation (HFS) has great potential to improve decision-making in clinical practice. Previous studies have found HFS promotes self-confidence, but its effectiveness in clinical practice has not been established. The aim of this research is to establish if HFS facilitates learning that informs decision-making skills in clinical practice using MultipleCriteria DecisionMaking Theory (MCDMT).MethodsThe sample was 2nd year undergraduate pre-registration adult nursing students.MCDMT was used to measure the students’ experience of HFS and how it developed their clinical decision-making skills. MCDMT requires characteristic measurements which for the learning experience were based on five factors that underpin successful learning, and for clinical decision-making, an analytical framework was used. The study used a repeated-measures design to take two measurements: the first one after the first simulation experience and the second one after clinical placement. Baseline measurements were obtained from academics. Data were analysed using the MCDMT tool.ResultsAfter their initial exposure to simulation learning, students reported that HFS provides a high-quality learning experience (87%) and supports all aspects of clinical decision-making (85%). Following clinical practice, the level of support for clinical decision-making remained at 85%, suggesting that students believe HFS promotes transferability of knowledge to the practice setting.ConclusionOverall, students report a high level of support for learning and developing clinical decision-making skills from HFS. However, there are no comparative data available from classroom teaching of similar content so it cannot be established if these results are due to HFS alone.


2021 ◽  
Vol 164 (4) ◽  
pp. 704-711
Author(s):  
Samantha Anne ◽  
Sandra A. Finestone ◽  
Allison Paisley ◽  
Taskin M. Monjur

This plain language summary explains pain management and careful use of opioids after common otolaryngology operations. The summary applies to patients of any age who need treatment for pain within 30 days after having a common otolaryngologic operation (having to do with the ear, nose, or throat). It is based on the 2021 “Clinical Practice Guideline: Opioid Prescribing for Analgesia After Common Otolaryngology Operations.” This guideline uses available research to best advise health care providers, and it includes recommendations that are explained in this summary. Recommendations may not apply to every patient but can be used to facilitate shared decision making between patients and their health care providers.


Author(s):  
Rikke Torenholt ◽  
Henriette Langstrup

In both popular and academic discussions of the use of algorithms in clinical practice, narratives often draw on the decisive potentialities of algorithms and come with the belief that algorithms will substantially transform healthcare. We suggest that this approach is associated with a logic of disruption. However, we argue that in clinical practice alongside this logic, another and less recognised logic exists, namely that of continuation: here the use of algorithms constitutes part of an established practice. Applying these logics as our analytical framing, we set out to explore how algorithms for clinical decision-making are enacted by political stakeholders, healthcare professionals, and patients, and in doing so, study how the legitimacy of delegating to an algorithm is negotiated and obtained. Empirically we draw on ethnographic fieldwork carried out in relation to attempts in Denmark to develop and implement Patient Reported Outcomes (PRO) tools – involving algorithmic sorting – in clinical practice. We follow the work within two disease areas: heart rehabilitation and breast cancer follow-up care. We show how at the political level, algorithms constitute tools for disrupting inefficient work and unsystematic patient involvement, whereas closer to the clinical practice, algorithms constitute a continuation of standardised and evidence-based diagnostic procedures and a continuation of the physicians’ expertise and authority. We argue that the co-existence of the two logics have implications as both provide a push towards the use of algorithms and how a logic of continuation may divert attention away from new issues introduced with automated digital decision-support systems.


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