Pilot study on developing a decision support tool for guiding re-administration of chemotherapeutic agent after a serious adverse drug reaction

<p>Abstract</p> <p>Background</p> <p>Currently, there are no standard guidelines for recommending re-administration of a chemotherapeutic drug to a patient after a serious adverse drug reaction (ADR) incident. The decision on whether to rechallenge the patient is based on the experience of the clinician and is highly subjective. Thus the aim of this study is to develop a decision support tool to assist clinicians in this decision making process.</p> <p>Methods</p> <p>The inclusion criteria for patients in this study are: (1) had chemotherapy at National Cancer Centre Singapore between 2004 to 2009, (2) suffered from serious ADRs, and (3) were rechallenged. A total of 46 patients fulfilled the inclusion criteria. A genetic algorithm attribute selection method was used to identify clinical predictors for patients' rechallenge status. A Naïve Bayes model was then developed using 35 patients and externally validated using 11 patients.</p> <p>Results</p> <p>Eight patient attributes (age, chemotherapeutic drug, albumin level, red blood cell level, platelet level, abnormal white blood cell level, abnormal alkaline phosphatase level and abnormal alanine aminotransferase level) were identified as clinical predictors for rechallenge status of patients. The Naïve Bayes model had an AUC of 0.767 and was found to be useful for assisting clinical decision making after clinicians had identified a group of patients for rechallenge. A platform independent version and an online version of the model is available to facilitate independent validation of the model.</p> <p>Conclusion</p> <p>Due to the limited size of the validation set, a more extensive validation of the model is necessary before it can be adopted for routine clinical use. Once validated, the model can be used to assist clinicians in deciding whether to rechallenge patients by determining if their initial assessment of rechallenge status of patients is accurate.</p

Exploring the impact of mentoring functions on job satisfaction and organizational commitment of new staff nurses

<p>Abstract</p> <p>Background</p> <p>Although previous studies proved that the implementation of mentoring program is beneficial for enhancing the nursing skills and attitudes, few researchers devoted to exploring the impact of mentoring functions on job satisfaction and organizational commitment of new nurses. In this research we aimed at examining the effects of mentoring functions on the job satisfaction and organizational commitment of new nurses in Taiwan's hospitals.</p> <p>Methods</p> <p>We employed self-administered questionnaires to collect research data and select new nurses from three regional hospitals as samples in Taiwan. In all, 306 nurse samples were obtained. We adopted a multiple regression analysis to test the impact of the mentoring functions.</p> <p>Results</p> <p>Results revealed that career development and role modeling functions have positive effects on the job satisfaction and organizational commitment of new nurses; however, the psychosocial support function was incapable of providing adequate explanation for these work outcomes.</p> <p>Conclusion</p> <p>It is suggested in this study that nurse managers should improve the career development and role modeling functions of mentoring in order to enhance the job satisfaction and organizational commitment of new nurses.</p

Magnetism and its microscopic origin in iron-based high-temperature superconductors

High-temperature superconductivity in the iron-based materials emerges from, or sometimes coexists with, their metallic or insulating parent compound states. This is surprising since these undoped states display dramatically different antiferromagnetic (AF) spin arrangements and N$\rm \acute{e}$el temperatures. Although there is general consensus that magnetic interactions are important for superconductivity, much is still unknown concerning the microscopic origin of the magnetic states. In this review, progress in this area is summarized, focusing on recent experimental and theoretical results and discussing their microscopic implications. It is concluded that the parent compounds are in a state that is more complex than implied by a simple Fermi surface nesting scenario, and a dual description including both itinerant and localized degrees of freedom is needed to properly describe these fascinating materials.Comment: 14 pages, 4 figures, Review article, accepted for publication in Nature Physic

Doing politics in the recent Arab uprisings: Towards a political discourse analysis of the Arab Spring slogans

The present paper aims to analyse a number of those slogans collected from the sit-in quarters in Egypt, Libya and Yemen. Using political discourse analysis, it unravels various typical discourse structures and strategies that are used in slogans in the construction of a sub-genre of political discourse in the Arab world. Drawing data from several mediums, including banners, wall graffiti, audio-visual instruments, chanting, speeches and songs, this paper tries to show the extent to which the slogans serve as a medium by which political complaints and comments are dispensed and consumed. This paper draws on a rhetorical analysis to find out their persuasive effect on shaping the Arab intellect and on the change of the political atmosphere in the region. Lastly, this paper attempts to show to what extent the slogans meet the standards of political discourse and whether they can be considered as a sub-genre of political discourse or not.IS

A computational approach to identify point mutations associated with occult hepatitis B: significant mutations affect coding regions but not regulative elements of HBV

<p>Abstract</p> <p>Background</p> <p>Occult Hepatitis B Infection (OBI) is characterized by absence of serum HBsAg and persistence of HBV-DNA in liver tissue, with low to undetectable serum HBV-DNA. The mechanisms underlying OBI remain to be clarified. To evaluate if specific point mutations of HBV genome may be associated with OBI, we applied an approach based on bioinformatics analysis of complete genome HBV sequences. In addition, the feasibility of bioinformatics prediction models to classify HBV infections into OBI and non-OBI by molecular data was evaluated.</p> <p>Methods</p> <p>41 OBI and 162 non-OBI complete genome sequences were retrieved from GenBank, aligned and subjected to univariable analysis including statistical evaluation. Their S coding region was analyzed for Stop codon mutations too, while S amino acid variability could be evaluated for genotype D only, due to the too small number of available complete genome OBI sequences from other genotypes.</p> <p>Prediction models were derived by multivariable analysis using Logistic Regression, Rule Induction and Random Forest approaches, with extra-sample error estimation by Multiple ten-fold Cross-Validation (MCV). Models were compared by t-test on the Area Under the Receiver Operating Characteristic curve (AUC) distributions obtained from the MCV runs for each model against the best-performing model.</p> <p>Results</p> <p>Variations in seven nucleotide positions were significantly associated with OBI, and occurred in 11 out of 41 OBI sequences (26.8%): likely, other mutations did not reach statistical significance due to the small size of OBI dataset. All variations affected at least one HBV coding region, but none of them mapped to regulative elements. All viral proteins, with the only exception of the X, were affected. Stop codons in the S, that might account for absence of serum HBsAg, were not significantly enriched in OBI sequences. In genotype D, amino acid variability in the S was higher in OBI than non-OBI, particularly in the immunodominant region. A Random Forest prediction model showed the best performance, but all models were not satisfactory in terms of specificity, due to the small sample size of OBIs; however results are promising in the perspective of a broader dataset of complete genome OBI sequences.</p> <p>Conclusions</p> <p>Data suggest that point mutations rarely occur in regulative elements of HBV, if ever, and contribute to OBI by affecting different viral proteins, suggesting heterogeneous mechanisms may be responsible for OBI, including, at least in genotype D, an escape mutation mechanism due to imperfect immune control. It appears possible to derive prediction models based on molecular data when a larger set of complete genome OBI sequences will become available.</p

Cyclic AMP Control Measured in Two Compartments in HEK293 Cells: Phosphodiesterase KM Is More Important than Phosphodiesterase Localization

The intracellular second messenger cyclic AMP (cAMP) is degraded by phosphodiesterases (PDE). The knowledge of individual families and subtypes of PDEs is considerable, but how the different PDEs collaborate in the cell to control a cAMP signal is still not fully understood. In order to investigate compartmentalized cAMP signaling, we have generated a membrane-targeted variant of the cAMP Bioluminiscence Resonance Energy Transfer (BRET) sensor CAMYEL and have compared intracellular cAMP measurements with it to measurements with the cytosolic BRET sensor CAMYEL in HEK293 cells. With these sensors we observed a slightly higher cAMP response to adenylyl cyclase activation at the plasma membrane compared to the cytosol, which is in accordance with earlier results from Fluorescence Resonance Energy Transfer (FRET) sensors. We have analyzed PDE activity in fractionated lysates from HEK293 cells using selective PDE inhibitors and have identified PDE3 and PDE10A as the major membrane-bound PDEs and PDE4 as the major cytosolic PDE. Inhibition of membrane-bound or cytosolic PDEs can potentiate the cAMP response to adenylyl cyclase activation, but we see no significant difference between the potentiation of the cAMP response at the plasma membrane and in cytosol when membrane-bound and cytosolic PDEs are inhibited. When different levels of stimulation were tested, we found that PDEs 3 and 10 are mainly responsible for cAMP degradation at low intracellular cAMP concentrations, whereas PDE4 is more important for control of cAMP at higher concentrations

Method for Assigning Priority Levels in Acute Care (MAPLe-AC) predicts outcomes of acute hospital care of older persons - a cross-national validation

To access publisher full text version of this article. Please click on the hyperlink in Additional Links field.BACKGROUND: Although numerous risk factors for adverse outcomes for older persons after an acute hospital stay have been : identified, a decision making tool combining all available information in a clinically meaningful way would be helpful for daily hospital practice. The purpose of this study was to evaluate the ability of the Method for Assigning Priority Levels for Acute Care (MAPLe-AC) to predict adverse outcomes in acute care for older people and to assess its usability as a decision making tool for discharge planning. METHODS: Data from a prospective multicenter study in five Nordic acute care hospitals with information from admission to a one year follow-up of older acute care patients were compared with a prospective study of acute care patients from admission to discharge in eight hospitals in Canada. The interRAI Acute Care assessment instrument (v1.1) was used for data collection. Data were collected during the first 24 hours in hospital, including pre-morbid and admission information, and at day 7 or at discharge, whichever came first. Based on this information a crosswalk was developed from the original MAPLe algorithm for home care settings to acute care (MAPLe-AC). The sample included persons 75 years or older who were admitted to acute internal medical services in one hospital in each of the five Nordic countries (n = 763) or to acute hospital care either internal medical or combined medical-surgical services in eight hospitals in Ontario, Canada (n = 393). The outcome measures considered were discharge to home, discharge to institution or death. Outcomes in a 1-year follow-up in the Nordic hospitals were: living at home, living in an institution or death, and survival. Logistic regression with ROC curves and Cox regression analyses were used in the analyses. RESULTS: Low and mild priority levels of MAPLe-AC predicted discharge home and high and very high priority levels predicted adverse outcome at discharge both in the Nordic and Canadian data sets, and one-year outcomes in the Nordic data set. The predictive accuracy (AUC's) of MAPLe-AC's was higher for discharge outcome than one year outcome, and for discharge home in Canadian hospitals but for adverse outcome in Nordic hospitals. High and very high priority levels in MAPLe-AC were also predictive of days to death adjusted for diagnoses in survival models. CONCLUSION: MAPLe-AC is a valid algorithm based on risk factors that predict outcomes of acute hospital care. It could be a helpful tool for early discharge planning although further testing for active use in clinical practice is still needed.Reykjavik Hospital Research Fund St. Joseph's Research Fund, Iceland Norwegian Medical Society 2 Diakonhjemmet Hospital Diakonhjemmet University College Diakonhjemmet Research Fund, Norway Sweden's Lions Fund, Sweden Health Transition Fund Health Canada Canadian Institutes for Health Research (CIHR) Nordic Lions Red Feather Fund Nordic Council of Ministers Roikjer Fund, Denmark Finnish Lions Fund, Finland Icelandic Lions Fund Memorial Fund of Helgu Jensdottur and Sigurliða Kristjanssona

Automated systems to identify relevant documents in product risk management

<p>Abstract</p> <p>Background</p> <p>Product risk management involves critical assessment of the risks and benefits of health products circulating in the market. One of the important sources of safety information is the primary literature, especially for newer products which regulatory authorities have relatively little experience with. Although the primary literature provides vast and diverse information, only a small proportion of which is useful for product risk assessment work. Hence, the aim of this study is to explore the possibility of using text mining to automate the identification of useful articles, which will reduce the time taken for literature search and hence improving work efficiency. In this study, term-frequency inverse document-frequency values were computed for predictors extracted from the titles and abstracts of articles related to three tumour necrosis factors-alpha blockers. A general automated system was developed using only general predictors and was tested for its generalizability using articles related to four other drug classes. Several specific automated systems were developed using both general and specific predictors and training sets of different sizes in order to determine the minimum number of articles required for developing such systems.</p> <p>Results</p> <p>The general automated system had an area under the curve value of 0.731 and was able to rank 34.6% and 46.2% of the total number of 'useful' articles among the first 10% and 20% of the articles presented to the evaluators when tested on the generalizability set. However, its use may be limited by the subjective definition of useful articles. For the specific automated system, it was found that only 20 articles were required to develop a specific automated system with a prediction performance (AUC 0.748) that was better than that of general automated system.</p> <p>Conclusions</p> <p>Specific automated systems can be developed rapidly and avoid problems caused by subjective definition of useful articles. Thus the efficiency of product risk management can be improved with the use of specific automated systems.</p