Survival in 190 consecutive patients with congestive heart failure, discharged from a general hospital, was studied. Sixteen patients were in New York Heart Association (NYHA) class I, 87 in II, 83 in III and 4 in IV. Median left ventricular ejection fraction (LVEF) from radionuclide ventriculography was 0.30 (range 0.06-0.74). Two-year survival was 68%. Wall motion index was the only echocardiographic variable with significant, independent, prognostic information on survival. The 2-year survival in NYHA classes I and II was 90.7% for wall motion index ≧ 1.3, and 78.6% when < 1.3. In classes III and IV survival was 68.9% for wall motion index ≧ 1.3 and 39.9% when < 1.3. Addition of LVEF gave further information about survival. This study demonstrates that echocardiography is of great value in determining prognosis in congestive heart failure patients, and that wall motion index contains the majority of the information. Wall motion index is closely correlated to LVEF, however prognostication is improved when information about LVEF is added.

Virtual ray lights (VRL) are a powerful representation for multiple‐scattered light transport in volumetric participating media. While efficient Monte Carlo estimators can importance sample the contribution of a VRL along an entire sensor subpath, render time still scales linearly in the number of VRLs. We present a new scalable hierarchial VRL method that preferentially samples VRLs according to their image contribution. Similar to Lightcuts‐based approaches, we derive a tight upper bound on the potential contribution of a VRL that is efficient to compute. Our bound takes into account the sampling probability densities used when estimating VRL contribution. Ours is the first such upper bound formulation, leading to an efficient and scalable rendering technique with only a few intuitive user parameters. We benchmark our approach in scenes with many VRLs, demonstrating improved scalability compared to existing state‐of‐the‐art techniques.

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