A Direct Assessment of Noninvasive Continuous Blood Pressure Monitoring in the Emergency Department and Intensive Care Unit

INTRODUCTION

Noninvasive continuous blood pressure monitoring has the potential to improve patient treatment in the hospital setting. Such noninvasive devices can be applied earlier in the treatment process to empower nurses and clinicians to react more quickly to patient deterioration with the added benefit of eliminating the risks associated with invasive monitoring. However, emerging technologies must be capable of reproducing current clinical measures for medical decision making.

METHODS

This study aimed to determine the usability and willingness of nurses to implement a noninvasive continuous blood pressure monitoring device. The secondary aim directly compared the systolic blood pressure, diastolic blood pressure, and mean arterial pressure values recorded by the device (VitalStream; CareTaker Medical LLC, Charlottesville, VA) with the "gold standard" brachial cuff and arterial line measures recorded in the emergency department and intensive care unit settings.

RESULTS

VitalStream was similarly received by nurses in the emergency department and intensive care setting, but ultimately had greater promotion from emergency nurses. Despite some statistical similarity between measurement methodologies, all direct comparisons were found to not meet the Association for the Advancement of Medical Instrumentation 2008 and Association for the Advancement of Medical Instrumentation / European Society of Hypertension / International Organization for Standardization 2019 consensus statement criteria for acceptable blood pressure measure differences between the VitalStream and "gold standard" clinical measures. In all instances, the standard deviation of the Bland-Altman bias exceeded 8 mm Hg with less than 85% of paired differences falling within 10 mm Hg of the "gold standard."

DISCUSSION

Taken together, the tested device requires additional postprocessing for medical decision making in trauma or emergent care.

Agreement between cardiac output estimation with a wireless, wearable pulse decomposition analysis device and continuous thermodilution in post cardiac surgery intensive care unit patients

PURPOSE

Pulse Decomposition Analysis (PDA) uses integration of the systolic area of a distally transmitted aortic pulse as well as arterial stiffness estimates to compute cardiac output. We sought to assess agreement of cardiac output (CO) estimation between continuous pulmonary artery catheter (PAC) guided thermodilution (CO-CCO) and a wireless, wearable noninvasive device, (Vitalstream, Caretaker Medical, Charlottesville, VA), that utilizes the Pulse Decomposition Analysis (CO-PDA) method in postoperative cardiac surgery patients in the intensive care unit.

METHODS

CO-CCO measurements were compared with post processed CO-PDA measurements in prospectively enrolled adult cardiac surgical intensive care unit patients. Uncalibrated CO-PDA values were compared for accuracy with CO-CCO via a Bland-Altman analysis considering repeated measurements and a concordance analysis with a 10% exclusion zone.

RESULTS

259.7 h of monitoring data from 41 patients matching 15,583 data points were analyzed. Mean CO-CCO was 5.55 L/min, while mean values for the CO-PDA were 5.73 L/min (mean of differences +- SD 0.79 ± 1.11 L/min; limits of agreement - 1.43 to 3.01 L/min), with a percentage error of 37.5%. CO-CCO correlation with CO-PDA was moderate (0.54) and concordance was 0.83.

CONCLUSION

Compared with the CO-CCO Swan-Ganz, cardiac output measurements obtained using the CO-PDA were not interchangeable when using a 30% threshold. These preliminary results were within the 45% limits for minimally invasive devices, and pending further robust trials, the CO-PDA offers a noninvasive, wireless solution to complement and extend hemodynamic monitoring within and outside the ICU.

Multi-Gaussian fitting for pulse waveform using Weighted Least Squares and multi-criteria decision making method

Analysis of pulse waveform is a low cost, non-invasive method for obtaining vital information related to the conditions of the cardiovascular system. In recent years, different Pulse Decomposition Analysis (PDA) methods have been applied to disclose the pathological mechanisms of the pulse waveform. All these methods decompose single-period pulse waveform into a constant number (such as 3, 4 or 5) of individual waves. Furthermore, those methods do not pay much attention to the estimation error of the key points in the pulse waveform. The estimation of human vascular conditions depends on the key points' positions of pulse wave. In this paper, we propose a Multi-Gaussian (MG) model to fit real pulse waveforms using an adaptive number (4 or 5 in our study) of Gaussian waves. The unknown parameters in the MG model are estimated by the Weighted Least Squares (WLS) method and the optimized weight values corresponding to different sampling points are selected by using the Multi-Criteria Decision Making (MCDM) method. Performance of the MG model and the WLS method has been evaluated by fitting 150 real pulse waveforms of five different types. The resulting Normalized Root Mean Square Error (NRMSE) was less than 2.0% and the estimation accuracy for the key points was satisfactory, demonstrating that our proposed method is effective in compressing, synthesizing and analyzing pulse waveforms.