Quality of Care in Patients with Cirrhosis and Ascites, Hepatic Encephalopathy or Spontaneous Bacterial Peritonitis

Objective: To analyze concordance with evidence-based clinical care guidelines in real world clinical practice in patients with cirrhosis and ascites, hepatic encephalopathy (HE), or spontaneous bacterial peritonitis (SBP). Methods: A retrospective cohort analysis of the UPMC EMR database (2009-2014) with access to full outpatient and limited inpatient data was conducted to identify patients with cirrhosis and ascites, HE or SBP. Data regarding patient demographics, clinical characteristics, laboratory values and medication utilization were extracted. Analyses included examination of patient demographic and clinical characteristics, change in disease severity (via MELDNa scoring) from cirrhosis to complication development and outpatient/inpatient healthcare utilization patterns. Additionally, concordance with investigator-designed quality care indicators adapted from AASLD guidelines and other sources were assessed to understand real world clinical care. Patient- and physician- factors predicting concordance with pharmacotherapy recommendations were assessed via the use of logistic regression models. Results: The inclusion/exclusion criteria yielded 4,116 patients with liver cirrhosis and 986, 665 and 148 patients with ascites, HE, and SBP respectively. Concordance with quality indicators ranged from 49.83% (recommended medication for HE) to 99.32% (MELD at SBP index). Body mass index and physician type were the only predictors that predicted concordance within the regression models for the selected indicators (prescription for recommended ascites and HE medications). A significant increase in MELDNa was observed from cirrhosis to complication index. No differences in healthcare utilization patterns were observed across complications. Conclusions: Several opportunities for improvement in quality of care were noted. However, factors assessed in this study revealed limited information regarding opportunities to improve concordance to clinical guidance

TIME-ON-TASK IN PRIMARY CLASSROOMS, DURING DIFFERENT TEACHING-LEARNING APPROACHES

The entire education system is moving from the teacher-centered teaching-learning approaches towards student-centered teaching-learning approaches, with anticipation that it would increase the learning outcomes. This empirical study was carried out to compare the traditional and non-traditional classrooms. It also tried to understand the effectiveness of the Alternate Instructions in the Mathematics and Primary Language (Marathi) classrooms. This study collected about 8000 snapshots from the classrooms of Government schools. Based on the empirical evidences, study can claim that Non-Traditional classrooms show more Time-on-Task (ToT) as compared to the Traditional classrooms. Study could show interesting trends of ToT throughout a session of 35mins. It also compared those trends for Mathematics and Marathi.  Article visualizations

A Survey Report On Elliptic Curve Cryptography

The paper presents an extensive and careful study of elliptic curve cryptography (ECC) and its applications. This paper also discuss the arithmetic involved in elliptic curve  and how these curve operations is crucial in determining the performance of cryptographic systems. It also presents  different forms of elliptic curve in various coordinate system , specifying which is most widely used and why. It also explains how isogenenies between elliptic curve  provides the secure ECC. Exentended form of elliptic curve i.e hyperelliptic curve has been presented here with its pros and cons. Performance of ECC and HEC is also discussed based on scalar multiplication and DLP. Keywords: Elliptic curve cryptography (ECC), isogenies, hyperelliptic curve (HEC) , Discrete Logarithm Problem (DLP), Integer  Factorization , Binary Field, Prime FieldDOI:http://dx.doi.org/10.11591/ijece.v1i2.8

Fixed Point Approximation for Asymptotically Nonexpansive Type Mappings in Uniformly Convex Hyperbolic Spaces

We use a modified S-iterative process to prove some strong and Δ-convergence results for asymptotically nonexpansive type mappings in uniformly convex hyperbolic spaces, which includes Banach spaces and CAT(0) spaces. Thus, our results can be viewed as extension and generalization of several known results in Banach spaces and CAT(0) spaces (see, e.g., Abbas et al. (2012), Abbas et al. (2013), Bruck et al. (1993), and Xin and Cui (2011)) and improve many results in the literature

Carotenoids: Role in Neurodegenerative Diseases Remediation

Numerous factors can contribute to the development of neurodegenerative disorders (NDs), such as Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, Huntington’s disease, and multiple sclerosis. Oxidative stress (OS), a fairly common ND symptom, can be caused by more reactive oxygen species being made. In addition, the pathological state of NDs, which includes a high number of protein aggregates, could make chronic inflammation worse by activating microglia. Carotenoids, often known as “CTs”, are pigments that exist naturally and play a vital role in the prevention of several brain illnesses. CTs are organic pigments with major significance in ND prevention. More than 600 CTs have been discovered in nature, and they may be found in a wide variety of creatures. Different forms of CTs are responsible for the red, yellow, and orange pigments seen in many animals and plants. Because of their unique structure, CTs exhibit a wide range of bioactive effects, such as anti-inflammatory and antioxidant effects. The preventive effects of CTs have led researchers to find a strong correlation between CT levels in the body and the avoidance and treatment of several ailments, including NDs. To further understand the connection between OS, neuroinflammation, and NDs, a literature review has been compiled. In addition, we have focused on the anti-inflammatory and antioxidant properties of CTs for the treatment and management of NDs

Predictors of Hyperkalemia and Outcomes of Dyskalemia in US Veterans with Advanced Chronic Kidney Disease Transitioning to Dialysis

Background: The kidneys play a crucial role in maintaining homeostasis of serum potassium levels (K+). Patients with advanced chronic kidney disease (CKD) are at a higher risk of experiencing dyskalemia events (i.e. hyper- and hypokalemia; especially the former) and thus future adverse outcomes. Currently, there is a dearth of literature on prediction models for hyperkalemia and the effects of dyskalemia on outcomes such as incidence of ischemic stroke and short-term hospital/emergency room (ER) utilization in an advanced CKD population transitioning to dialysis. Objectives: Using a nationally representative sample of US veterans with advanced CKD transitioning to dialysis, in the pre-dialysis period we studied the following aims: Aim 1) Develop and validate a prediction model for predicting hyperkalemia in individual patients; Aim 2) Examine the association of dyskalemias with time to first ischemic stroke; Aim 3) Examine the association of dyskalemias with time to short-term hospital/ER utilization. Methods: A retrospective cohort analysis of the Transition of Care in Chronic Kidney Disease cohort (n=102,477), a nationally representative sample of US veterans with advanced CKD transitioning to dialysis between October 1, 2007 through March 31, 2015 identified from the United States Renal Data System was conducted. Across the three study aims, we identified patients with an initial selection criterion (prior to dialysis initiation) of two estimated glomerular filtration rate (eGFR) of /min/1.73m2 90-365 days apart (second eGFR as index); at least one-year each of baseline period (prior to index) and follow-up period (following index but prior to dialysis initiation); and at least one K+ measurement each in the baseline and follow-up period. For each study aim, further inclusion criteria were used to yield a final sample size of 21,654, 21,357, and 21,366 for aim 1, aim 2, and aim 3, respectively. For Aim 1 (Chapter 2), we compared the performance (area under the receiver operating curve [AUROC]) of different machine learning methods including logistic regression (LR), random forest, extreme gradient boosting, and support vector machines using geographical splitting (for creating training and test set) with 10-fold cross validation to predict the outcome of hyperkalemia (K+ \u3e5.5 mEq/L). The method that yielded the best performance was used to build a reduced model with 10 predictors to develop a patient-level hyperkalemia risk score. For Aim 2 (Chapter 3), we assessed the association of baseline time-averaged K+ levels (distant exposure) and time-updated K+ levels (acute exposure) (both categorized as hypokalemia [K+ 5.5 mEq/L] and referent [3.5 mEq/L ≤ K+ ≤ 5.5 mEq/L]) with time to first ischemic stroke using Cox regression models. Finally, for Aim 3 (Chapter 4), we assessed the association of time-updated outpatient K+ levels (categorized as hypokalemia [K+ 5.5 mEq/L] and referent [3.5 mEq/L ≤ K+ ≤ 5.5 mEq/L]) with hospital/ER utilization (as separate events) using generalized estimating equations. Across all the three study aims (Aim 1, 2, and 3) several different sensitivity analyses were conducted to test the robustness of the results. Results: Across the analytic samples (Aim 1, 2, and 3), the mean age was 69 years, ~98% were males; ~28% were African Americans, ~69% had diabetes mellitus, and the one-year baseline averaged K+ was 4.5 mEq/L. In aim 1 (n=21,654), the LR model yielded the best performance with an average AUROC (95% confidence interval [CI]) of 0.765 (0.756-0.774) (training set) and 0.763 (0.753-0.771) (test set) using the geographical splitting with 10-fold cross validation. Using the LR method, the top 10 predictors identified were K+ value prior to index, age, having at least 1 K+ \u3e5.5 mEq/L in the baseline, index eGFR, baseline averaged SBP, baseline averaged HCO3-, number of K+ counts, thiazide use, number of outpatient visits, and NSAIDs use in baseline. The LR parameter estimates for the above listed predictors were used to develop a patient-level risk score for predicting hyperkalemia. In aim 2 (n=21,357), hypokalemia (distant exposure) was associated with higher risk of ischemic stroke (hazard ratio [HR]; 95 % CI: 1.35, 1.01-1.81). Conversely, hyperkalemia (acute exposure) was associated with a lower risk of ischemic stroke (HR; 95% CI: 0.82, 0.68-0.98). Finally, in aim 3 (n=21,366) using outpatient K+ levels, both hyperkalemia (odds ratio [OR]; 95% CI: 2.04; 1.88-2.21) and hypokalemia (OR; 95% CI: 1.66; 1.48-1.86) were associated with higher risk of hospital visit within 2 calendar days of outpatient K+ measurement. Similarly, both hyperkalemia (OR; 95% CI: 1.83; 1.65-2.03) and hypokalemia (OR; 95% CI: 1.24; 1.07-1.44) were associated with higher risk of ER visit within 2 calendar days of outpatient K+ measurement. Across all the three study aims, the results were robust to various sensitivity analysis. Conclusion: In an advanced CKD population transitioning to dialysis, in the pre-dialysis period, we developed an internally valid model for predicting hyperkalemia. We observed that hypokalemia as a chronic exposure is associated with higher risk of ischemic stroke and hyperkalemia as an acute exposure is associated with lower risk of ischemic stroke. Finally, both hyper- and hypokalemia are associated with higher risk of short-term hospital/ER visits. Further studies are needed to externally validate the hyperkalemia risk prediction model; understand the mechanisms underlying the association of dyskalemias with stroke; and expand on the association of dyskalemias with short-term hospital/ER visits by including cost as an outcome