e5SCAI Meeting Abstracts

The feasibility of continuous heart and respiratory rate variabilityanalysis in the intensive care unit: A pilot investigationBeverly Bradley a, Geoffrey Green a, Rajeev Yadav a, Izmail Batkin a,

Andrew J.E. Seely a,b,c

aOttawa Hospital Research Institute, Ottawa, Ontario, CanadabDivision of Thoracic Surgery, University of Ottawa,Ottawa,Ontario, CanadacDepartment of Critical Care Medicine, University of Ottawa, Ottawa,

Ontario, Canada

Objectives: There is increasing evidence that heart rate variability(HRV) is reduced in association with stress, age, and diseaseincluding critical illness and degree of alteration correlates withillness severity. Respiratory rate variability (RRV) is also altered inassociation with critical illness, with reduced RRV duringspontaneous breathing trials being evaluated as a predictor ofextubation failure. The clinical value of longitudinal or continuoustracking of HRV and/or RRV in critically ill patients remains tobe characterized. We hypothesize that continuous HRV and RRVmonitoring could provide a means to track severity of illness andpatient trajectory in critically ill patients; however, feasibility hasnot been demonstrated. We have developed CIMVA (continuousindividualized multiorgan variability analysis) as a software toolto enable standardized, comprehensive, and transparent continuousmultiorgan variability monitoring. The objective of this study wasto explore the feasibility of applying CIMVA to critically illpatients in the intensive care unit (ICU), evaluating waveform dataquality, disconnection, arrhythmia, beat and breath detection, andvariability analyses.Methods: Thirty-four critically ill patients experiencing respiratoryand/or cardiac failure were enrolled, undergoing continuousrecording of electrocardiogram (ECG) and end-tidal capnography(CO2) waveforms using Philips Intellivue monitors. With waivedconsent approved by institutional REB, ECG monitoring wasinitiated at time of ICU admission and continued until ICUdischarge or a maximum of 14 days; CO2 monitoring was initiatedwhen CO2 modules were applied at time of enrollment andcontinued until extubation or a maximum of 14 days. Waveformdata were downloaded daily on a per-patient basis using the PhilipsIntellivue Information Centre. De-identified data were thentransferred from the Philips Database Server over the hospitalnetwork to a research file server where data processing occurredusing the CIMVA software engine. For each patient, variability oftheir interbeat and interbreath intervals were calculated over5-minute windows of waveform data; in total, 25 measures ofvariability representing time, frequency, time-frequency, entropy,scale-invariant, and nonlinear domains of complexity analysis werecomputed for every interval. The feasibility of continuousmonitoring and variability analysis was assessed qualitatively,evaluating setup and ease of use, and quantitatively, evaluating theproportion of missing or rejected data vs usable high-qualitywaveform data remaining. Measures of data quality includedquantification of disconnection and number of interbeat andinterbreath intervals removed because of artifact and/or arrhythmia,most commonly atrial fibrillation.Results:Mean age of patients was 56.5 (±15.9) years. On the day ofadmission, mean Acute Physiology and Chronic Health EvaluationII score was 22.8 (±6.7) and mean daily MODS score was 6.8(±2.9). Mean number of days enrolled in the study was 11.0 (±3.6)and on average, 10.3 (±4.3) days of ECG data and 8.2 (±4.9) days of

CO2 data were collected per patient. The mean proportion ofmissing data was 6.1% (±9.25%) and 10.37% (±18.34%) for ECGand CO2 waveforms, respectively. Ninety-four percent of enrolledpatients had over 75% of their ECG waveform data available fordata processing, whereas this proportion was 88% for CO2 data.The HRV and RRV variability data were computed successfullyfrom interbeat interval and interbreath interval time series derivedfrom the waveform data available. The average proportion ofvariability windows remaining after data quality filtering was81.2% and 87.5% for HRV and RRV data, respectively. Of the 7patients who had N25% of their HRV windows rejected by dataquality filters, all 7 experienced atrial fibrillation or another form ofnonsinus rhythm. An average of 1.6% (±1.0%) of 5-minute HRVwindows was rejected because of disconnection artifact. Discon-nection artifact was higher for CO2 data (9.1% ± 8.7%), possiblybecause of short periods of apnea being detected as disconnections.Conclusions: We evaluated the feasibility of continuous heart andrespiratory rate variability analysis in 2 principal ways, namely, by(1) quantifying the degree of missing waveform data (evaluatingquality of continuous waveform data harvest) and (2) quantifyingremoved or rejected variability data after CIMVA processing(evaluating feasibility of continuous variability computations).Maintenance activity (software update) on the patient-monitoringnetwork and minor issues with tubing for the CO2 module were themajor contributing causes of missing waveform data. Although it isstill unclear how much data can be missing without fundamentallycompromising analysis of variability, the trajectories plotted forindividual patients subjectively demonstrate the potential to observeboth short- and long-term trends in variability despite missing data.Variability analysis remains indeterminate for patients withnonsinus rhythm, and this study highlights their prevalence andits implications for continuous HRV analysis in this population.Although applied with a Philips Intellivue monitoring system andnetwork, the general setup presented is applicable to otherwaveform-monitoring systems, and work is ongoing to interfaceCIMVA with these systems. By evaluating both the quality of thewaveforms as well as the subsequent variability data, we concludethat continuously recorded ECG and CO2 waveform data incritically ill patients are of adequate quality for subsequentcontinuous multiorgan variability analysis and that long-termcontinuous monitoring of variability in the ICU is feasible withoutexcessive data loss.

doi:10.1016/j.jcrc.2010.12.026

Early prediction of length of intensive care unit stay from inflammatorymediators in trauma patientsCordelia Ziraldo c, Ali Ghuma a, Rajaie Namas a, Juan Ochoa a,

Timothy R. Billiar a, Ruben Zamora a, Qi Mi b, Yoram Vodovotz a

aDepartment of Surgery, University of Pittsburgh, Pittsburgh, PA, USAbDepartment of SportsMedicine, University of Pittsburgh, Pittsburgh, PA,USAcDepartment of Computational Biology, University of Pittsburgh,

Pittsburgh, PA, USA

Objectives: The prognosis for any 2 trauma patients who suffer theexact same injury can be vastly different. The body's inflammatoryresponse to trauma has a major contribution to the course of apatient's progress. We hypothesized that assessment of circulatinginflammatory mediators combined with a small amount of