Publications
Department of Medicine faculty members published more than 3,600 peer-reviewed articles in 2024.
2019
2019
2019
2019
BACKGROUND
The Coronary Artery Calcium Data and Reporting System (CAC-DRS), which takes into account the Agatston score category (A) and the number of calcified vessels (N) has not yet been validated in terms of its prognostic significance.
METHODS
We included 54,678 patients from the CAC Consortium, a large retrospective clinical cohort of asymptomatic individuals free of baseline cardiovascular disease (CVD). CAC-DRS groups were derived from routine, cardiac-gated CAC scans. Cox proportional hazards regression models, adjusted for traditional CVD risk factors, were used to assess the association between CAC-DRS groups and CHD, CVD, and all-cause mortality. CAC-DRS was then compared to CAC score groups and regional CAC distribution using area under the curve (AUC) analysis.
RESULTS
The study population had a mean age of 54.2 ± 10.7, 34.4% female, and mean ASCVD score 7.3% ± 9.0. Over a mean follow-up of 12 ± 4 years, a total of 2,469 deaths (including 398 CHD deaths and 762 CVD deaths) were recorded. There was a graded risk for CHD, CVD and all-cause mortality with increasing CAC-DRS groups ranging from an all-cause mortality rate of 1.2 per 1,000 person-years for A0 to 15.4 per 1,000 person-years for A3/N4. In multivariable-adjusted models, those with CAC-DRS A3/N4 had significantly higher risk for CHD mortality (HR 5.9 (95% CI 3.6-9.9), CVD mortality (HR4.0 (95% CI 2.8-5.7), and all-cause mortality a (HR 2.5 (95% CI 2.1-3.0) compared to CAC-DRS A0. CAC-DRS had higher AUC than CAC score groups (0.762 vs 0.754, P < 0.001) and CAC distribution (0.762 vs 0.748, P < 0.001).
CONCLUSION
The CAC-DRS system, combining the Agatston score and the number of vessels with CAC provides better stratification of risk for CHD, CVD, and all-cause death than the Agatston score alone. These prognostic data strongly support new SCCT guidelines recommending the use CAC-DRS scoring.
View on PubMed2019
2019
2019
2019
Eremothecium coryli is a dimorphic fungus of the Saccharomycetes class. While species within this class are known to cause human infection, Eremothecium species have previously only been known as phytopathogens and never been isolated from a human sample. Here, we report the first known case of human E. coryli infection.
View on PubMed2019
OBJECTIVES
This paper reports the development, validation, and public availability of a new neural network-based system which attempts to identify the manufacturer and even the model group of a pacemaker or defibrillator from a chest radiograph.
BACKGROUND
Medical staff often need to determine the model of a pacemaker or defibrillator (cardiac rhythm device) quickly and accurately. Current approaches involve comparing a device's radiographic appearance with a manual flow chart.
METHODS
In this study, radiographic images of 1,676 devices, comprising 45 models from 5 manufacturers were extracted. A convolutional neural network was developed to classify the images, using a training set of 1,451 images. The testing set contained an additional 225 images consisting of 5 examples of each model. The network's ability to identify the manufacturer of a device was compared with that of cardiologists, using a published flowchart.
RESULTS
The neural network was 99.6% (95% confidence interval [CI]: 97.5% to 100.0%) accurate in identifying the manufacturer of a device from a radiograph and 96.4% (95% CI: 93.1% to 98.5%) accurate in identifying the model group. Among 5 cardiologists who used the flowchart, median identification of manufacturer accuracy was 72.0% (range 62.2% to 88.9%), and model group identification was not possible. The network's ability to identify the manufacturer of the devices was significantly superior to that of all the cardiologists (p < 0.0001 compared with the median human identification; p < 0.0001 compared with the best human identification).
CONCLUSIONS
A neural network can accurately identify the manufacturer and even model group of a cardiac rhythm device from a radiograph and exceeds human performance. This system may speed up the diagnosis and treatment of patients with cardiac rhythm devices, and it is publicly accessible online.
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