How to harvest waveforms? An overview of vital signs waveform collection, storage and viewing in a prospective multicenter clinical study
CCCF ePoster library. Scales N. Nov 2, 2016; 150979
Disclosure(s): Andrew Seely holds patents related to multiorgan variability analysis, and has shares in Therapeutic Monitoring Systems Inc, a company whose mission is to help deliver variability-directed clinical decision support products to the bedside to improve care. Christophe Herry is a patent holder related to waveform quality assessment necessary for variability analysis.
Dr. Nathan Scales
Dr. Nathan Scales
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Topic: Basic or Translational Science

How to harvest waveforms? An overview of vital signs waveform collection, storage and viewing in a prospective multicenter clinical study


Scales N1, Herry C1, Anstee C1, Waldauf P5, van Beinum A3, Hornby L2, Dhanani S2,3,4, Seely AJ1,6,7
1.Ottawa Hospital Research Institute, 725 Parkdale Avenue, Ottawa, ON K1Y 4E9, Canada
2.Bertram Loeb Research Consortium in Organ and Tissue Donation, University of Ottawa, Ottawa, ON, Canada.
3.Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada.
4.Division of Pediatric Critical Care, Children’s Hospital of Eastern Ontario, University of Ottawa, Ottawa, ON, Canada.
5.Department of Anesthesiology and Critical Care, University Hospital Kralovske Vinohrady, Prague, Czech Republic
6.University of Ottawa, 75 Laurier Avenue East, Ottawa, ON K1N 6N5, Canada
7.Divisions of Thoracic Surgery & Critical Care Medicine, 501 Smyth Road, Ottawa, ON K1H 8L6, Canada
 
 
Conflict of Interest Statement

Andrew Seely holds patents related to multiorgan variability analysis, and has shares in Therapeutic Monitoring Systems Inc, a company whose mission is to help deliver variability-directed clinical decision support products to the bedside to improve care.

Christophe Herry is a patent holder related to waveform quality assessment necessary for variability analysis.

Grant acknowledgements:
We are grateful for funding provided for the DePPaRT study by CIHR through the Canadian National Transplant Research Program, as well as funding provided through the PSI Foundation.

Abstract:

Introduction
The vital signs of patients in the ICU are monitored continuously 24/7, providing instantaneous feedback on changes in heart rate, blood pressure, and respiratory rate. Physiologic waveform data (e.g. electrocardiogram) is routinely displayed on bedside monitors and discarded, rarely recorded for more than a few days or made available for more sophisticated offline analyses. For research purposes, collected waveforms may be used to track vital signs simultaneously, precisely and continuously, or derive predictive analytics based on patterns of variation of heart or respiratory rate that herald an impending change in a patient's status [1], or identify patients at higher risk of a negative outcome [2].
At present, there is no standard method to extract waveform data from bedside monitors or central stations in the ICU. Waveform capture solutions for a given ICU depend on the brand and model of the equipment in the unit, and can cost anywhere from zero to tens of thousands of dollars per ICU. At present, any study requiring waveform capture will need to develop a unique solution for each ICU in the study, convert all data into a common format, and develop a method to easily review the large amount of data uploaded from each site.

Objectives
We aim to summarize our experience setting up a multicenter study requiring waveform capture at sites participating in the Death Prediction and Physiology after Removal of Therapy study. Our objectives were to (1) enable waveform capture at 13 sites and describe the range of waveform capture solutions, (2) develop a server capable of uploading and storing waveform data from all sites, as well as serving it upon request, and (3) design a waveform viewer capable of reading, displaying, and annotating all file types, with data residing either locally or on the study server.

Methods
A questionnaire was sent to the Biomed department of each potential site, asking for details on the brand, model, and software version of the monitors and central stations, and details of existing waveform capture solutions. The results were used to develop a list of individualized affordable options (if any) for each site. All code for the viewer was written in Matlab (The Mathworks). The server was an Amazon Web Services (EC2) server.

Results
Waveform capture was successfully set up at 13 sites in Canada and 3 sites in the Czech Republic. The simplest cases could be set up in 3 to 6 months; others could take over a year. At 6 unsuccessful sites, solutions were technically possible but were either not affordable or required extensive software development. The solutions found for the different vendors and the requirements for each are outlined in Figure 1 and in Table 1. To date, waveform data for almost 250 patients have been uploaded to the study server. A waveform viewer was developed that can display multiple waveforms simultaneously, allowing the user to easily navigate the patient’s waveform record, as well as to zoom in/out as necessary, create annotations, make screenshots, and videos (Figure 2). The waveform data can be read locally or be requested from the study server.

Conclusion
It is challenging yet possible to conduct multicenter clinical studies requiring waveform capture from multiple vendors. The tools, methods, and network of sites created by this study may assist future studies requiring continuous waveform collection or investigating waveform-derived predictive analytics.

 


References:

[1] Ahmad S, Ramsay T, Huebsch L, et al. Continuous Multi-Parameter Heart Rate
Variability Analysis Heralds Onset of Sepsis in Adults. PloS one 2009;4:e6642
 
[2] Seely AJ, Bravi A, Herry C, et al. Do heart and respiratory rate variability improve
prediction of extubation outcomes in critically ill patients? Critical care (London, England)
2014;18:R65.
 



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