Background and objectives Living donor kidney transplantation, the treatment of choice for ESRD, is underused by women and blacks. To better understand sex differences in the context of potential barriers to living donor kidney transplantation, the Dialysis Patient Transplant Questionnaire was administered in two urban, predominantly black hemodialysis units. Results Women were less likely to want living donor kidney transplantation compared with men (58.5% versus 87.5%, P=0.003), despite being nearly two times as likely as men to receive unsolicited offers for kidney transplant (73.2% versus 43.2%, P=0.02). They were also less likely to have been evaluated for a kidney transplant (28.3% versus 52.2%, P=0.01). The multiple logistic regression analysis showed that sex was a statistically significant predictor of wanting living donor kidney transplantation (women versus men odds ratio, 0.13; 95% confidence interval, 0.04 to 0.46), controlling for various factors known to influence transplant decisions. A sensitivity analysis indicated that mode of administration did not bias these results. ConclusionsIn contrast to previous studies, the study found that black women were less likely to want living donor kidney transplantation compared with black men. Black women were also less likely to be evaluated for a kidney transplant, although they were more likely to receive an unsolicited living donor kidney transplantation offer.

While living donor kidney transplantation (LDKT) is the treatment of choice for end-stage renal disease patients (ESRD), the potential barriers to LDKT are not well understood, especially among African American patients who have higher rates of ESRD but lower LDKT than Whites. To address this gap, a cross-sectional survey (n=101) identified LDKT experiences and attitudes among urban African American adults receiving hemodialysis at two outpatient clinics in Philadelphia. Most patients (72.3%) were interested in LDKT but only 34.2% had asked someone for a donation. Concerns about the donor (33.3%), asking for a kidney (28.1%), and their own health (24.6%) were major barriers. Patients also expressed guilt (56.3%) and fear (37.2%). About half (49.5%) had an unsolicited offer, regardless of whether or not they asked. The survey results suggest that interventions should focus on overcoming reluctance to ask for a kidney donation or to accept unsolicited offers.

Abstract:The analysis of social networks often assumes time invariant scenario, while in practice actor attributes and links in such networks often evolve over time and are inextricably dependent on each other. In this article, we propose a new method to predict actor attributes and links in temporal networks. Our approach takes into account the attributes corresponding to the participating actors together with topological and structural changes of the network over time. This is achieved by building two conditional predictors to jointly infer links and actor attributes. The proposed prediction method was significantly more accurate than alternatives when evaluated on synthetic data sets and two well-studied real-life temporal social networks. In addition, the new algorithm is computationally more efficient than a related alternative scaling up linearly with the number of temporal observations and quadratically with the number of actors considered. 

Abstract-We propose a unified approach for imputation of the links and attributes in longitudinal social surveys which accounts for changing network topology and interdependence between the actor's links and attributes. The previous studies on the treatment of non-respondents in longitudinal social networks were mostly concerned with imputation of the missing links only or imputation effects on the networks statistics. For this study we conduct a set of experiments on synthetic and real life datasets with 20%-60% of nodes missing under four mechanisms. The obtained results were better than when using alternative methods which suggest that our method can be used as a viable imputation tool.

Abstract-We propose a unified approach for imputation of the links and attributes in longitudinal social surveys which accounts for changing network topology and interdependence between the actor's links and attributes. The previous studies on the treatment of non-respondents in longitudinal social networks were mostly concerned with imputation of the missing links only or imputation effects on the networks statistics. For this study we conduct a set of experiments on synthetic and real life datasets with 20%-60% of nodes missing under four mechanisms. The obtained results were better than when using alternative methods which suggest that our method can be used as a viable imputation tool.