Development and validation of a portable platform for deploying decision-support algorithms in prehospital settings.

BACKGROUND: Advanced decision-support capabilities for prehospital trauma care may prove effective at improving patient care. Such functionality would be possible if an analysis platform were connected to a transport vital-signs monitor. In practice, there are technical challenges to implementing such a system. Not only must each individual component be reliable, but, in addition, the connectivity between components must be reliable. OBJECTIVE: We describe the development, validation, and deployment of the Automated Processing of Physiologic Registry for Assessment of Injury Severity (APPRAISE) platform, intended to serve as a test bed to help evaluate the performance of decision-support algorithms in a prehospital environment. METHODS: We describe the hardware selected and the software implemented, and the procedures used for laboratory and field testing. RESULTS: The APPRAISE platform met performance goals in both laboratory testing (using a vital-sign data simulator) and initial field testing. After its field testing, the platform has been in use on Boston MedFlight air ambulances since February of 2010. CONCLUSION: These experiences may prove informative to other technology developers and to healthcare stakeholders seeking to invest in connected electronic systems for prehospital as well as in-hospital use. Our experiences illustrate two sets of important questions: are the individual components reliable (e.g., physical integrity, power, core functionality, and end-user interaction) and is the connectivity between components reliable (e.g., communication protocols and the metadata necessary for data interpretation)? While all potential operational issues cannot be fully anticipated and eliminated during development, thoughtful design and phased testing steps can reduce, if not eliminate, technical surprises.

Monitoring non-invasive cardiac output and stroke volume during experimental human hypovolaemia and resuscitation.

BACKGROUND: Multiple methods for non-invasive measurement of cardiac output (CO) and stroke volume (SV) exist. Their comparative capabilities are not clearly established. METHODS: Healthy human subjects (n=21) underwent central hypovolaemia through progressive lower body negative pressure (LBNP) until the onset of presyncope, followed by termination of LBNP, to simulate complete resuscitation. Measurement methods were electrical bioimpedance (EBI) of the thorax and three measurements of CO and SV derived from the arterial blood pressure (ABP) waveform: the Modelflow (MF) method, the long-time interval (LTI) method, and pulse pressure (PP). We computed areas under receiver-operating characteristic curves (ROC AUCs) for the investigational metrics, to determine how well they discriminated between every combination of LBNP levels. RESULTS: LTI and EBI yielded similar reductions in SV during progressive hypovolaemia and resuscitation (correlation coefficient 0.83) with ROC AUCs for distinguishing major LBNP (-60 mm Hg) vs resuscitation (0 mm Hg) of 0.98 and 0.99, respectively. MF yielded very similar reductions and ROC AUCs during progressive hypovolaemia, but after resuscitation, MF-CO did not return to baseline, yielding lower ROC AUCs (ΔROC AUC range, -0.18 to -0.26, P < 0.01). PP declined during hypovolaemia but tended to be an inferior indicator of specific LBNP levels, and PP did not recover during resuscitation, yielding lower ROC curves (P < 0.01). CONCLUSIONS: LTI, EBI, and MF were able to track progressive hypovolaemia. PP decreased during hypovolaemia but its magnitude of reduction underestimated reductions in SV. PP and MF were inferior for the identification of resuscitation.

Comparison of cardiac output monitoring methods for detecting central hypovolemia due to lower body negative pressure.

Reduction in mean arterial pressure (MAP) is a late indictor of progressive circulatory pathology. Non-invasive monitoring methods that are superior indicators of circulatory compromise would be clinically valuable. With IRB approval, 21 healthy volunteers were subjected to progressive lower body negative pressure (LBNP) until the onset of presyncopal symptoms. We evaluated the usefulness of four investigational methods of arterial blood pressure waveform analysis during progressive hypovolemia: mean arterial pressure (MAP); the ModelFlow cardiac output algorithm (MF); the long time interval method (LTI); and the product of pulse pressure and heart rate (PP*HR). Electrical bioimpedance measurement of cardiac output (EBI) provided a reference. When results were analyzed, we found significant differences between the methods. MF, LTI, and EBI all corresponded with LBNP severity, while MAP and PP*HR did not. In terms of discriminating between (a) decompression to -45 mmHg; versus (b) recovery five minutes after LBNP cessation, there was a significant difference between MF and LTI: the receiver operating characteristic area-under-the-curve (ROC AUC) for MF was 0.57 and for LTI was 0.76. In terms of discriminating between (a) the 11 subjects who tolerated the protocol (i.e., tolerated higher levels of LBNP); versus (b) the 10 non-tolerant subjects, there was also a significant difference between MF and LTI: the ROC AUC for MF was 0.40 and for LTI was 0.66. There were no significant differences between MF nor EBI, however. In conclusion, LTI is notable as the only method which (a) correlated with decompression: (b) distinguished between decompression to -45 mmHg versus recovery; and (c) distinguished between those subjects who adequately compensated for central hypovolemia (tolerant) and those who did not have such robust physiologic compensation (non-tolerant).