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Background-Patients with left ventricular dysfunction have an elevated risk of sudden cardiac death. However, the substrate for ventricular arrhythmia in patients with nonischemic cardiomyopathy remains poorly understood. We hypothesized that the distribution of scar identified by MRI is predictive of inducible ventricular tachycardia. Methods and Results-Short-axis cine steady-state free-precession and postcontrast inversion-recovery gradient-echo MRI sequences were obtained before electrophysiological study in 26 patients with nonischemic cardiomyopathy. Left ventricular ejection fraction was measured from end-diastolic and end-systolic cine images. The transmural extent of scar as a percentage of wall thickness (percent scar transmurality) in each of 12 radial sectors per slice was calculated in all myocardial slices. The percentages of sectors with 1% to 25%, 26% to 50%, 51% to 75%, and 76% to 100% scar transmurality were determined for each patient. Predominance of scar distribution involving 26% to 75% of wall thickness was significantly predictive of inducible ventricular tachycardia and remained independently predictive in the multivariable model after adjustment for left ventricular ejection fraction (odds ratio, 9.125; Pϭ0.020). Conclusions-MR

This paper analyzes the social impacts of the commitment to “sustainability” in donor-funded AIDS programs. Using survey, interview, and ethnographic data from rural Malawi, we examine how efforts to mobilize and empower local communities affect three strata of Malawian society: the villagers these programs are meant to help, the insecure local elites whose efforts directly link programs to their intended beneficiaries, and, more briefly, national elites who implement AIDS policies and programs. We describe indirect effects of sustainability on the experiences, identities, and aspirations of Malawians—effects that are much broader and deeper than the direct impacts of funding.

Demographers have argued increasingly that social interaction is an important mechanism for understanding fertility behavior. Yet it is still quite uncertain whether social learning or social influence is the dominant mechanism through which social networks affect individuals' contraceptive decisions. In this paper we argue that these mechanisms can be distinguished by analyzing the density of the social network and its interaction with the proportion of contraceptive users among network partners. Our analyses indicate that social learning is most relevant with high market activity; in regions with only modest market activity, however, social influence is the dominant means by which social networks affect women's contraceptive use.