RESUMO
AIMS: In the USA, transthyretin cardiac amyloidosis usually results from 'wild-type' transthyretin (senile cardiac amyloidosis [SCA]) or the V122I variant. PATIENTS & METHODS: We compared presentations and outcomes among SCA and V122I patients referred to the Center for Advanced Cardiac Care at Columbia University Medical Center (NY, USA) between 2001 and 2012. RESULTS: V122I patients were younger (mean: 71 years, standard deviation [SD]: 7) than SCA patients (mean: 77, SD: 6; p = 0.0002) and 96% were black compared with 3% of SCA patients (p < 0.0001). Average ejection fraction was lower among V122I patients (mean: 25% [SD: 12] vs mean: 47% [SD: 15]; p = 0.0001), as was mean cardiac index. Median time to death or orthotopic heart transplant was 36.4 months for V122I patients and 66.5 for SCA patients (p = 0.09). CONCLUSION: In this study of patients with transthyretin cardiac amyloidosis, V122I patients presented to a tertiary academic medical center at a younger age than SCA patients but had higher levels of cardiac dysfunction, despite genetic screening availability. There was a trend toward shorter time to orthotopic heart transplant or death among V122I patients. Whether this is a result of a different biologic progression or late diagnosis requires further study.
RESUMO
When the driver encounters a signal change from green to yellow, he is required to make a stop or go decision based on his speed and the distance to the stop bar. Making the wrong decision will lead to a red-light running violation or an abrupt stop at the intersection. In this study, a field data collection was conducted at a high-speed signalized intersection, where a video-based system with three cameras was used to record the drivers' behavior related to the onset of yellow. Observed data include drivers' stop/go decisions, red-light running violation, lane position in the highway, positions (leading/following) in the traffic flow, vehicle type, and vehicles' yellow-onset speeds and distances from the intersection. Further, classification tree models were applied to analyze how the probabilities of a stop or go decision and of red-light running are associated with the traffic parameters. The data analysis indicated that vehicle's distance from the intersection at the onset of yellow, operating speed, and position in the traffic flow are the most important predictors for both the stop/go decision and red-light running violation. This study illustrates that the tree models are helpful to recognize and predict how drivers make stop/go decisions and partake in red-light running violations corresponding to the traffic parameters.
