The difficult doctor? Characteristics of physicians who report frustration with patients: an analysis of survey data

BACKGROUND: Literature on difficult doctor-patient relationships has focused on the "difficult patient." Our objective was to determine physician and practice characteristics associated with greater physician-reported frustration with patients. METHODS: We conducted a secondary analysis of the Physicians Worklife Survey, which surveyed a random national sample of physicians. Participants were 1391 family medicine, general internal medicine, and medicine subspecialty physicians. The survey assessed physician and practice characteristics, including stress, depression and anxiety symptoms, practice setting, work hours, case-mix, and control over administrative and clinical practice. Physicians estimated the percentage of their patients who were "generally frustrating to deal with." We categorized physicians by quartile of reported frustrating patients and compared characteristics of physicians in the top quartile to those in the other three quartiles. We used logistic regression to model physician characteristics associated with greater frustration. RESULTS: In unadjusted analyses, physicians who reported high frustration with patients were younger (p < 0.001); worked more hours per week (p = 0.041); and had more symptoms of depression, stress, and anxiety (p < 0.004 for all). In the final model, factors independently associated with high frustration included age < 40 years, work hours > 55 per week, higher stress, practice in a medicine subspeciality, and greater number of patients with psychosocial problems or substance abuse. CONCLUSION: Personal and practice characteristics of physicians who report high frustration with patients differ from those of other physicians. Understanding factors contributing to physician frustration with patients may allow us to improve the quality of patient-physician relationships

The need for education on health related-quality of life

<p>Abstract</p> <p>Background</p> <p>Health-related quality of life is increasingly recognised as an important outcome measure that complements existing measures of clinical effectiveness. The education available on this subject for different healthcare professionals is varied. This article describes the design, implementation and evaluation of a Special Study Module on Health-Related Quality of Life for undergraduate medical students at the University of Birmingham.</p> <p>Methods</p> <p>The course involves 10 hours of "guided discovery learning" covering core concepts of Health-Related Quality of Life assessment including methodological considerations, use in clinical trials, routine practice and in health policy followed by self-directed learning. The taught components aim to provide students with the skills and knowledge to enable them to explore and evaluate the use of quality of life assessments in a particular patient group, or setting, through self-directed learning supported by tutorials.</p> <p>Results</p> <p>The use of case studies, recent publications and research, and discussion with a research oncology nurse in task-based learning appeared to provide students with a stimulating environment in which to develop their ideas and was reflected in the diverse range of subjects chosen by students for self-directed study and the positive feedback on the module. Course evaluation and student assessment suggests that quality of life education appears to integrate well within the medical curriculum and allows students to develop and utilise skills of time-management and independent, self-directed learning that can be applied in any context.</p> <p>Conclusion</p> <p>We suggest that education and training initiatives in quality of life may improve the quality of studies, and help bridge the gap between research and clinical practice. Resources for curriculum development on health-related quality of life have been developed by the International Society for Quality of Life Research and may prove a useful tool to educators interested in this area.</p

Multimodal Treatment Eliminates Cancer Stem Cells and Leads to Long-Term Survival in Primary Human Pancreatic Cancer Tissue Xenografts.

Copyright: 2013 Hermann et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.PURPOSE: In spite of intense research efforts, pancreatic ductal adenocarcinoma remains one of the most deadly malignancies in the world. We and others have previously identified a subpopulation of pancreatic cancer stem cells within the tumor as a critical therapeutic target and additionally shown that the tumor stroma represents not only a restrictive barrier for successful drug delivery, but also serves as a paracrine niche for cancer stem cells. Therefore, we embarked on a large-scale investigation on the effects of combining chemotherapy, hedgehog pathway inhibition, and mTOR inhibition in a preclinical mouse model of pancreatic cancer. EXPERIMENTAL DESIGN: Prospective and randomized testing in a set of almost 200 subcutaneous and orthotopic implanted whole-tissue primary human tumor xenografts. RESULTS: The combined targeting of highly chemoresistant cancer stem cells as well as their more differentiated progenies, together with abrogation of the tumor microenvironment by targeting the stroma and enhancing tissue penetration of the chemotherapeutic agent translated into significantly prolonged survival in preclinical models of human pancreatic cancer. Most pronounced therapeutic effects were observed in gemcitabine-resistant patient-derived tumors. Intriguingly, the proposed triple therapy approach could be further enhanced by using a PEGylated formulation of gemcitabine, which significantly increased its bioavailability and tissue penetration, resulting in a further improved overall outcome. CONCLUSIONS: This multimodal therapeutic strategy should be further explored in the clinical setting as its success may eventually improve the poor prognosis of patients with pancreatic ductal adenocarcinoma

Cardiogenic shock following administration of propofol and fentanyl in a healthy woman: a case report

<p>Abstract</p> <p>Introduction</p> <p>Cardiogenic shock is very uncommon in healthy people. The differential diagnosis for patients with acute heart failure in previously healthy hearts includes acute myocardial infarction and myocarditis. However, many drugs can also depress myocardial function. Propofol and fentanyl are frequently used during different medical procedures. The cardiovascular depressive effect of both drugs has been well established, but the development of cardiogenic shock is very rare when these agents are used.</p> <p>Case presentation</p> <p>After a minor surgical intervention, a 32-year-old Caucasian woman with no significant medical history went into sudden hemodynamic deterioration due to acute heart failure. An urgent echocardiogram showed severe biventricular dysfunction and an estimated left ventricular ejection fraction of 20%. Extracorporeal life support and mechanical ventilation were required. Five days later her ventricular function had fully recovered, which allowed the progressive withdrawal of medical treatment. Prior to her hospital discharge, cardiac MRI showed neither edema nor pathological deposits on the delayed contrast enhancement sequences. At her six-month follow-up examination, the patient was asymptomatic and did not require treatment.</p> <p>Conclusion</p> <p>Although there are many causes of cardiogenic shock, the presence of abrupt hemodynamic deterioration and the absence of a clear cause could be related to the use of propofol and fentanyl.</p

Dealing with substantial heterogeneity in Cochrane reviews. Cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Dealing with heterogeneity in meta-analyses is often tricky, and there is only limited advice for authors on what to do. We investigated how authors addressed different degrees of heterogeneity, in particular whether they used a fixed effect model, which assumes that all the included studies are estimating the same true effect, or a random effects model where this is not assumed.</p> <p>Methods</p> <p>We sampled randomly 60 Cochrane reviews from 2008, which presented a result in its first meta-analysis with substantial heterogeneity (I²greater than 50%, i.e. more than 50% of the variation is due to heterogeneity rather than chance). We extracted information on choice of statistical model, how the authors had handled the heterogeneity, and assessed the methodological quality of the reviews in relation to this.</p> <p>Results</p> <p>The distribution of heterogeneity was rather uniform in the whole I²interval, 50-100%. A fixed effect model was used in 33 reviews (55%), but there was no correlation between I²and choice of model (P = 0.79). We considered that 20 reviews (33%), 16 of which had used a fixed effect model, had major problems. The most common problems were: use of a fixed effect model and lack of rationale for choice of that model, lack of comment on even severe heterogeneity and of reservations and explanations of its likely causes. The problematic reviews had significantly fewer included trials than other reviews (4.3 vs. 8.0, P = 0.024). The problems became less pronounced with time, as those reviews that were most recently updated more often used a random effects model.</p> <p>Conclusion</p> <p>One-third of Cochrane reviews with substantial heterogeneity had major problems in relation to their handling of heterogeneity. More attention is needed to this issue, as the problems we identified can be essential for the conclusions of the reviews.</p

Living biointerfaces based on non-pathogenic bacteria to direct cell differentiation

Genetically modified Lactococcus lactis, non-pathogenic bacteria expressing the FNIII7-10 fibronectin fragment as a protein membrane have been used to create a living biointerface between synthetic materials and mammalian cells. This FNIII7-10 fragment comprises the RGD and PHSRN sequences of fibronectin to bind α5β1 integrins and triggers signalling for cell adhesion, spreading and differentiation. We used L. lactis strain to colonize material surfaces and produce stable biofilms presenting the FNIII7-10 fragment readily available to cells. Biofilm density is easily tunable and remains stable for several days. Murine C2C12 myoblasts seeded over mature biofilms undergo bipolar alignment and form differentiated myotubes, a process triggered by the FNIII7-10 fragment. This biointerface based on living bacteria can be further modified to express any desired biochemical signal, establishing a new paradigm in biomaterial surface functionalisation for biomedical applications

JNK2 Promotes Endothelial Cell Alignment under Flow

Endothelial cells in straight, unbranched segments of arteries elongate and align in the direction of flow, a feature which is highly correlated with reduced atherosclerosis in these regions. The mitogen-activated protein kinase c-Jun N-terminal kinase (JNK) is activated by flow and is linked to inflammatory gene expression and apoptosis. We previously showed that JNK activation by flow is mediated by integrins and is observed in cells plated on fibronectin but not on collagen or basement membrane proteins. We now show thatJNK2 activation in response to laminar shear stress is biphasic, with an early peak and a later peak. Activated JNK localizes to focal adhesions at the ends of actin stress fibers, correlates with integrin activation and requires integrin binding to the extracellular matrix. Reducing JNK2 activation by siRNA inhibits alignment in response to shear stress. Cells on collagen, where JNK activity is low, align slowly. These data show that an inflammatory pathway facilitates adaptation to laminar flow, thereby revealing an unexpected connection between adaptation and inflammatory pathways

More Scalable LTL Model Checking via Discovering Design-Space Dependencies (D3)

Modern system design often requires comparing several models over a large design space. Different models arise out of a need to weigh different design choices, to check core capabilities of versions with varying features, or to analyze a future version against previous ones. Model checking can compare different models; however, applying model checking off-the-shelf may not scale due to the large size of the design space for today’s complex systems. We exploit relationships between different models of the same (or related) systems to optimize the model-checking search. Our algorithm, D3 , preprocesses the design space and checks fewer model-checking instances, e.g., using nuXmv. It automatically prunes the search space by reducing both the number of models to check, and the number of LTL properties that need to be checked for each model in order to provide the complete model-checking verdict for every individual model-property pair. We formalize heuristics that improve the performance of D3 . We demonstrate the scalability of D3 by extensive experimental evaluation, e.g., by checking 1,620 real-life models for NASA’s NextGen air traffic control system. Compared to checking each model-property pair individually, D3 is up to 9.4 × faster

LNCS

Discrete-time Markov Chains (MCs) and Markov Decision Processes (MDPs) are two standard formalisms in system analysis. Their main associated quantitative objectives are hitting probabilities, discounted sum, and mean payoff. Although there are many techniques for computing these objectives in general MCs/MDPs, they have not been thoroughly studied in terms of parameterized algorithms, particularly when treewidth is used as the parameter. This is in sharp contrast to qualitative objectives for MCs, MDPs and graph games, for which treewidth-based algorithms yield significant complexity improvements. In this work, we show that treewidth can also be used to obtain faster algorithms for the quantitative problems. For an MC with n states and m transitions, we show that each of the classical quantitative objectives can be computed in O((n+m)⋅t2) time, given a tree decomposition of the MC with width t. Our results also imply a bound of O(κ⋅(n+m)⋅t2) for each objective on MDPs, where κ is the number of strategy-iteration refinements required for the given input and objective. Finally, we make an experimental evaluation of our new algorithms on low-treewidth MCs and MDPs obtained from the DaCapo benchmark suite. Our experiments show that on low-treewidth MCs and MDPs, our algorithms outperform existing well-established methods by one or more orders of magnitude