Chelyabinsk airburst, damage assessment, meteorite recovery, and characterization.

The asteroid impact near the Russian city of Chelyabinsk on 15 February 2013 was the largest airburst on Earth since the 1908 Tunguska event, causing a natural disaster in an area with a population exceeding one million. Because it occurred in an era with modern consumer electronics, field sensors, and laboratory techniques, unprecedented measurements were made of the impact event and the meteoroid that caused it. Here, we document the account of what happened, as understood now, using comprehensive data obtained from astronomy, planetary science, geophysics, meteorology, meteoritics, and cosmochemistry and from social science surveys. A good understanding of the Chelyabinsk incident provides an opportunity to calibrate the event, with implications for the study of near-Earth objects and developing hazard mitigation strategies for planetary protection.

Continuous left ventricular ejection fraction monitoring by aortic pressure waveform analysis.

We developed a technique to monitor left ventricular ejection fraction (EF) by model-based analysis of the aortic pressure waveform. First, the aortic pressure waveform is represented with a lumped parameter circulatory model. Then, the model is fitted to each beat of the waveform to estimate its lumped parameters to within a constant scale factor equal to the arterial compliance (C (a)). Finally, the proportional parameter estimates are utilized to compute beat-to-beat absolute EF by cancelation of the C (a) scale factor. In this way, in contrast to conventional imaging, EF may be continuously monitored without any ventricular geometry assumptions. Moreover, with the proportional parameter estimates, relative changes in beat-to-beat left ventricular end-diastolic volume (EDV), cardiac output (CO), and maximum left ventricular elastance (E (max)) may also be monitored. To evaluate the technique, we measured aortic pressure waveforms, reference EF and EDV via standard echocardiography, and other cardiovascular variables from six dogs during various pharmacological influences and total intravascular volume changes. Our results showed overall EF and calibrated EDV root-mean-squared-errors of 5.6% and 4.1 mL, and reliable estimation of relative E (max) and beat-to-beat CO changes. These results demonstrate, perhaps for the first time, the feasibility of estimating EF from only a blood pressure waveform.

Continuous ejection fraction estimation by model-based analysis of an aortic pressure waveform: comparison to echocardiography.

Left ventricular ejection fraction (EF) is perhaps the most clinically significant index of global ventricular function. EF is measured in clinical practice using imaging methods such as non-invasive echocardiography. However, imaging methods generally require a skilled operator and expensive equipment. Thus, EF is not sufficiently monitored. To this end, we have recently developed a novel technique to continuously (i.e., automatically) estimate EF by model-based analysis of an aortic pressure waveform. Here, we review the technique and present its evaluation with respect to reference echocardiography measurements from three dogs during diverse interventions. We report an overall EF error of only 8.3%. With further successful testing, the technique may ultimately be utilized for continuous EF monitoring in research and clinical settings in which an aortic catheter is employed.

Continuous left ventricular ejection fraction monitoring by central aortic pressure waveform analysis.

Left ventricular ejection fraction (EF) is perhaps the most clinically significant index of global ventricular function. EF is measured in clinical practice via imaging methods such as echocardiography. However, these methods generally require a well-trained operator and expensive capital equipment. Thus, EF measurements are only obtained in the clinical setting and are usually made few and far between. To expand the measurement of this critical hemodynamic variable, our overarching hypothesis is that EF may be continuously (i.e., automatically) monitored by mathematical analysis of routinely measured blood pressure waveforms. Here, we introduce a novel technique for estimating the absolute EF by model-based analysis of only a central aortic pressure (CAP) waveform. We then demonstrate the validity of the technique with respect to five conscious dogs in which reference EF was independently measured before and after chronic pacing induced heart failure. With further successful testing, the technique may potentially be utilized for continuous EF monitoring in research and clinical settings in which an aortic catheter is employed as well as for ambulatory EF monitoring in conjunction with recently developed implantable devices for measuring CAP.