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Changes in Heart Rate Volatility In A Murine Model Of Sepsis Goel N, Skaf J, Guglielmi M, Foley B, Zanotti S, Parrillo JE, Hollenberg SM Cardiology and Critical Care, Cooper University Hospital, Camden, NJ. Background - PowerPoint PPT Presentation
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Changes in Heart Rate Volatility In A Murine Model Of SepsisChanges in Heart Rate Volatility In A Murine Model Of Sepsis
Goel N, Skaf J, Guglielmi M, Foley B, Zanotti S, Parrillo JE, Hollenberg SM Cardiology and Critical Care, Cooper University Hospital, Camden, NJ
Background
• Nonlinear analysis of hemodynamic parameters such as Heart Rate Variability (HRV) may provide insights not available from standard linear measures
• Power spectral analysis of HRV is commonly used. However, challenges arise from artifacts and dense data capture.
Hypothesis
• Sepsis will be associated with perturbations in Heart Rate Volatility (standard deviation variability), a means of assessing HRV that minimizes artifact-induced error.
Methods
• C57/Bl6 mice (8-12 weeks, 20 g., n=24)• Radiotelemeters for hemodynamic measurements in
awake animals were implanted in the ascending aorta via the carotid artery.
• Animals were allowed to recover for 5 to 7 days.• Baseline data was obtained for 24 hours.• Sepsis was induced by cecal ligation and puncture
(CLP, n=20).• Controls received sham-operation (SO, n = 4).• Animals were resuscitated with fluids and antibiotics
every 6 hours.• Heart Rate (HR) was calculated from blood pressure
waveforms obtained from radiotelemeters.• HR standard deviations (SD) were calculated on each
5 minute interval.
Methods
• For each animal, SD histograms were constructed and the cutoff that represented the lowest 5% was calculated for the baseline period.
• The percentage of low SD’s (representing low HRV) in the entire experimental period was defined by this cutoff.
• A time course was generated by calculating the percentage of low HRV over 4 hour intervals.
Results
• Animals in the control group had low HRV detected in 1.5% of all intervals (p =NS versus baseline)
• Animals in the septic group had low HRV in 38.72% of intervals post-CLP (p<0.01 versus baseline and versus controls)
• Mortality in the septic group was 60%.• Survivors and nonsurvivors had a similar decrease in
HR volatility early, with partial recovery, but then HRV responses diverged, with normalization in survivors, and further perturbation in non-survivors.
Conclusions
• Analysis of Heart Rate Volatility is less demanding, more intuitive and less susceptible to artifact as a means of measuring HRV than spectral analysis.
• We have shown dramatic differences between septic and control animals in a clinically relevant murine model of sepsis using these techniques.
• Extrapolation of this methodology to critically ill patients has the potential to provide novel markers of hemodynamic decompensation.
Control Group - Baseline HR Histogram
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SD value at 5%= 13.59
Control Group - Post-SO HR Histogram
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Frequency
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% of intervals less than 13.59 in post-SO periods = 5.00
Septic Group - Baseline HR Histogram
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SD Value at 5%= 16.28
Septic Group - Post-CLP HR Histogram
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Frequency
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% of intervals less than 16.28 in septic periods = 38.72
Heart Rate - Septic Animal
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Mean Arterial Pressure - Septic Animal
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Heart Rate - Control Animal
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0 12 24 36 48 60 84 96
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Mean Arterial Pressure - Control Animal
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HR vs. HR volatility in Septics and Controls
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Septics HRCtrls HRCtrls HRVSeptics HRV
HR vs. HR volatility in Septics and Controls
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t (hrs)
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SD C
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Survivors HRNon-Surv. HRSurvivors HRVNon-Surv. HRV