out a significant collateral vein, and its diagnostic accuracy is high. The use of PESOS as an indicator for treatment implies that physical examination may represent a useful surveillance tool.

PESOS can be used to diagnose ≥75% outflow stenosis in an AVF, with or without a significant collateral vein, and its diagnostic accuracy is high. The use of PESOS as an indicator for treatment implies that physical examination may represent a useful surveillance tool.

The main advantage of GeneXpert MTB/RIF® (Xpert) molecular diagnostic technology is the rapid detection of M.tuberculosis DNA and mutations associated with rifampicin (RIF) resistance for timely initiation of appropriate treatment and, consequently, preventing further transmission of the disease. We assessed time to treatment initiation and treatment outcomes of RIF-resistant and RIF-susceptible TB patients diagnosed and treated in Vladimir TB Dispensary, Russia in 2012, before and after implementation of GeneXpert MTB/RIF® diagnostic technology.

All adult patients suspected of having TB during February-December 2012 underwent a clinical examination, chest x-ray, microscopy, culture, and phenotypic drug susceptibility testing (DST). Starting August 2012 Xpert diagnostic technology became available in the facility. We used logistic regression to compare treatment outcomes in pre-Xpert and post-Xpert periods. BRN 0067676 Kaplan-Meier curves and log-rank test were used to compare the time to treatment initiation betweenoutcome including 94/114 (82%) in post-Xpert group versus 105/138 (76%) in pre-Xpert group (OR0.68; 95%CI0.36,1.26).

We observed that availability of Xpert for initial diagnosis significantly reduced the time to SLD treatment for RIF-resistant patients in the Vladimir TB Dispensary. Although implementation of rapid diagnostics did not improve treatment outcomes, early diagnosis of MDR-TB is important for selection of appropriate treatment regimen and prevention of transmission of drug-resistant strains of TB.

We observed that availability of Xpert for initial diagnosis significantly reduced the time to SLD treatment for RIF-resistant patients in the Vladimir TB Dispensary. Although implementation of rapid diagnostics did not improve treatment outcomes, early diagnosis of MDR-TB is important for selection of appropriate treatment regimen and prevention of transmission of drug-resistant strains of TB.

Under competing risks, the commonly used sub-distribution hazard ratio (SHR) is not easy to interpret clinically and is valid only under the proportional sub-distribution hazard (SDH) assumption. This paper introduces an alternative statistical measure the restricted mean time lost (RMTL).

First, the definition and estimation methods of the measures are introduced. Second, based on the differences in RMTLs, a basic difference test (Diff) and a supremum difference test (sDiff) are constructed. Then, the corresponding sample size estimation method is proposed. The statistical properties of the methods and the estimated sample size are evaluated using Monte Carlo simulations, and these methods are also applied to two real examples.

The simulation results show that sDiff performs well and has relatively high test efficiency in most situations. Regarding sample size calculation, sDiff exhibits good performance in various situations. The methods are illustrated using two examples.

RMTL can meaningfully summarize treatment effects for clinical decision making, which can then be reported with the SDH ratio for competing risks data. The proposed sDiff test and the two calculated sample size formulas have wide applicability and can be considered in real data analysis and trial design.

RMTL can meaningfully summarize treatment effects for clinical decision making, which can then be reported with the SDH ratio for competing risks data. The proposed sDiff test and the two calculated sample size formulas have wide applicability and can be considered in real data analysis and trial design.

Missing data are common in statistical analyses, and imputation methods based on random forests (RF) are becoming popular for handling missing data especially in biomedical research. Unlike standard imputation approaches, RF-based imputation methods do not assume normality or require specification of parametric models. However, it is still inconclusive how they perform for non-normally distributed data or when there are non-linear relationships or interactions.

To examine the effects of these three factors, a variety of datasets were simulated with outcome-dependent missing at random (MAR) covariates, and the performances of the RF-based imputation methods missForest and CALIBERrfimpute were evaluated in comparison with predictive mean matching (PMM).

Both missForest and CALIBERrfimpute have high predictive accuracy but missForest can produce severely biased regression coefficient estimates and downward biased confidence interval coverages, especially for highly skewed variables in nonlinear models. CALIBERrfimpute typically outperforms missForest when estimating regression coefficients, although its biases are still substantial and can be worse than PMM for logistic regression relationships with interaction.

RF-based imputation, in particular missForest, should not be indiscriminately recommended as a panacea for imputing missing data, especially when data are highly skewed and/or outcome-dependent MAR. A correct analysis requires a careful critique of the missing data mechanism and the inter-relationships between the variables in the data.

RF-based imputation, in particular missForest, should not be indiscriminately recommended as a panacea for imputing missing data, especially when data are highly skewed and/or outcome-dependent MAR. A correct analysis requires a careful critique of the missing data mechanism and the inter-relationships between the variables in the data.

Due to demographic change within an aging population as announced by the WHO, the involvement of caregivers is essential. Caregivers are required to change their roles within the family unit. Such life transitions experienced by caregivers to people confronted with dementia-type pathologies are sometimes difficult, necessitating the acquisition and development of certain skills. Few studies have shown that caregivers develop specific and essential skills to promote quality care and safety. To characterize their skills, there is a need to identify the abilities, knowledge, resources, obstacles and constraints that contribute to caregivers’ transitions. The research question for this study was What skills do caregivers use to care for their loved one with dementia?

Qualitative observational research based on the epistemological paradigm of socioconstructivist knowledge was conducted. The study was carried out in the canton of Geneva and recruitment was carried out through the participation of the Alzheimer’s association and the association for the support and assistance of elderly people in medical and social institutions and their families (APAF).