Transcatheter aortic valve implantation in patients with pre-existing chronic kidney disease

AbstractBackgroundWe investigated the effect of chronic kidney disease (CKD) on morbidity and mortality following transcatheter aortic valve implantation (TAVI) including patients on haemodialysis, often excluded from randomised trials.Methods and resultsWe performed a retrospective post hoc analysis of all patients undergoing TAVI at our centre between 2008 and 2012. 118 consecutive patients underwent TAVI; 63 were considered as having (CKD) and 55 not having (No-CKD) significant pre-existing CKD, (defined as estimated glomerular filtration rate (eGFR)<60mL/min/1.73m2). Chronic haemodialysis patients (n=4) were excluded from acute kidney injury (AKI) analysis. Following TAVI, in CKD and No-CKD patients respectively, AKI occurred in 23.7% and 14.5% (p=0.455) and renal replacement therapy (RRT) was necessary in 8.5% and 3.6% (relative risk (RR) [95% CI]=2.33 [0.47–11.5], p=0.440); 30-day mortality rates were 6.3% and 1.8% (p=0.370); and 1-year mortality rates were 17.5% and 18.2% (p=0.919). Patients who developed AKI had a significantly increased risk of 30-day (12.5% vs. 1.1%, p=0.029) mortality. We found the presence of diabetes (odds ratio (OR) [95% CI]=4.58 [1.58–13.3], p=0.005) and elevated baseline serum creatinine (OR [95% CI]=1.02 [1.00–1.03], p=0.026) to independently predict AKI to statistical significance by multivariate analysis.ConclusionTAVI is a safe, acceptable treatment for patients with pre-existing CKD, however caution must be exercised, particularly in patients with pre-existing diabetes mellitus and elevated pre-operative serum creatinine levels as this confers a greater risk of AKI development, which is associated with increased short-term post-operative mortality

Energy productivity and efficiency of maize accounting for the choice of growing season and environmental factors: An empirical analysis from Bangladesh

The paper evaluates sustainability of maize cultivation in Bangladesh in terms of energy use while taking into account factors affecting choice of the growing season and farmers' production environment using a sample selection framework applied to stochastic frontier models. Results reveal that the probability of growing winter maize is influenced positively by gross return, irrigation, subsistence pressure, soil suitability and temperature variability whereas extension contact influences choice negatively. Significant differences exist between winter and summer maize regarding yield, specific energy, net energy balance, energy use efficiency and technical energy efficiency although both systems are highly sustainable and efficient. The energy output from winter maize is 199,585 MJ/ha which is 53.9% higher than the summer maize output of 129,701 MJ/ha. Also, energy input use of winter maize is 110.6% higher than the summer maize. Energy inputs from mechanical power, seeds, fertilizers and organic manures significantly increase energy productivity of winter maize whereas only mechanical power influences summer maize productivity. However, temperature variation and rainfall significantly reduce energy productivity of summer maize. Policy implications include investments in soil conservation and irrigation, development of weather resistant varieties and raising maize price will boost maize cultivation in Bangladesh, a highly sustainable production technology. © 2012 Elsevier Ltd

Joint determination of the choice of growing season and economic efficiency of maize in Bangladesh

The paper jointly evaluates the determinants of the choice of maize growing season (winter vs. summer maize) and economic efficiency of individual producers in Bangladesh using a sample selection framework applied to stochastic frontier models. Model diagnostics reveal that sample selection bias is significant, thereby justifying the use of this approach. Probit results reveal that the probability to choose winter maize are influenced positively by gross return, subsistence pressure and soil suitability, whereas extension contact influences choice negatively. Stochastic cost frontier results reveal that a rise in input prices and output level increases production cost as expected. Among the variables representing the production environment, soil suitability and stability of mean temperature reduce cost, whereas precipitation increases cost. The mean level of economic efficiency is estimated at 0.91, implying that scope still exists to reduce cost further by jointly eliminating technical and allocative inefficiency. Policy implications include measures to improve soil suitability, development of temperature-resistant varieties and price policies to check input price rise while boosting maize price, which will synergistically increase adoption rate as well as profitability of winter maize cultivation in Bangladesh

Validation measures for prognostic models for independent and correlated binary and survival outcomes

Prognostic models are developed to guide the clinical management of patients or to assess the performance of health institutions. It is essential that performances of these models are evaluated using appropriate validation measures. Despite the proposal of several validation measures for survival outcomes, it is still unclear which measures should be generally used in practice. In this thesis, a simulation study was performed to investigate a range of validation measures for survival outcomes in order to make practical recommendations regarding their use. Measures were evaluated with respect to their robustness to censoring and their sensitivity to the omission of important predictors. Based on the simulation results, from the discrimination measures, Gonen and Heller's K statistic can be recommended for validating a survival risk model developed using the Cox proportional hazards model, since it is both robust to censoring and reasonably sensitive to predictor omission. Royston and Sauerbrei's D statistic can be recommended provided that the distribution of the prognostic index is approximately normal. Harrell's C-index was affected by censoring and cannot be recommended for use with data with more than 30% censoring. The calibration slope can be recommended as a measure of calibration since it is not affected by censoring. The measures of predictive accuracy and explained variation (Graf et al's integrated Brier Score and its R-square version, and Schemper and Henderson's V) cannot be recommended due to their poor performance in the presence of censored data. In multicentre studies patients are typically clustered within centres and are likely to be correlated. Typically, random effects logistic and frailty models are fitted to clustered binary and survival outcomes, respectively. However, limited work has been done to assess the predictive ability of these models. This research extended existing validation measures for independent data, such as the C-index, D statistic, calibration slope, Brier score, and the K statistic for use with random effects/frailty models. Two approaches: the `overall' and `pooled cluster-specific' are proposed. The `overall' approach incorporates comparisons of subjects both within-and between-clusters. The `pooled cluster-specific' measures are obtained by pooling the cluster-specific estimates based on comparisons of subjects within each cluster; the pooling is achieved using a random effects summary statistics method. Each approach can produce three different values for the validation measures, depending on the type of predictions: conditional predictions using the estimates of the random effects or setting these as zero and marginal predictions by integrating out the random effects. Their performances were investigated using simulation studies. The `overall' measures based on the conditional predictions including the random effects performed reasonably well in a range of scenarios and are recommended for validating models when using subjects from the same clusters as the development data. The measures based on the marginal predictions and the conditional predictions that set the random effects to be zero were biased when the intra-cluster correlation was moderate to high and can be used for subjects in new clusters when the intra-cluster correlation coefficient is less than 0.05. The `pooled cluster-specific' measures performed well when the clusters had reasonable number of events. Generally, both the `overall' and `pooled' measures are recommended for use in practice. In choosing a validation measure, the following characteristics of the validation data should be investigated: the level of censoring (for survival outcome), the distribution of the prognostic index, whether the clusters are the same or different to those in the development data, the level of clustering and the cluster size

Adoption Of Selected Wheat Production Technologies In Two Northern Districts Of Bangladesh

The study was conducted in two major wheat growing areas of Bangladesh to determine the adoption level and factors affecting the adoption of wheat production practices in the study areas during 2011. Descriptive statistics along with multiple regression technique was used to achieve the objectives. The results revealed that most of the farmers (60.91%) in the study areas were cultivating Shatabdi variety of wheat. Adoption level of seed rate, TSP and MoP application were found to be very low. On the other hand, production practices like time of wheat sowing and number of irrigation were highly adopted by the farmers. Most of the farmers (69.09%) applied TSP below the recommended dose while 81.82% of the farmers applied MoP over the recommended dose. The study also revealed a positive and significant relationship between adoption and the variables like education, experience and extension contact. Lack of proper information and technical knowledge were the major problems that hinder the adoption of wheat production technologies in the study areas. Adoption gaps are needed to be eliminated to enhance the productivity as well as net return of wheat cultivation. Int. J. Agril. Res. Innov. &amp; Tech. 3 (1): 5-11, June, 2013 DOI: http://dx.doi.org/10.3329/ijarit.v3i1.1604

Pre-determined fixed fare structure for rickshaws to integrate with mass transit systems

This paper examines the feasibility of pre-determined fare structures for rickshaws. An empirical study was conducted with two case study locations (prospective BRT stations) in Dhaka City, Bangladesh. Eleven focus group discussions (FGDs) were held with rickshaw-pullers and other stakeholder groups, and semi-structured open-ended interviews were conducted with twenty five transport professionals/policymakers. It was found that rickshaw-pullers often like a bargaining process for fixing a fare so that they can charge more from passengers, particularly from those who are new in the area or ‘seem to be’ wealthy, or when there is no other alternative mode available for passengers. On the other hand, passengers prefer a fixed fare structure and do not like the bargaining process. Rickshaw-pullers, passengers and policymakers all mentioned that it would be possible to have a pre-determined fixed fare structure for rickshaws if rickshaws were more localised (serving only within a particular neighbourhood or for a short distance, as an access leg to public transport). However, this policy would need to be backed by effective planning, regular monitoring and enforcement, along with ‘awareness generation’ for rickshaw-pullers and wide scale publicity campaigns