changes in heart rate volatility in a murine model of sepsis

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Changes in Heart Rate Volatility In A Murine Model Of Changes in Heart Rate Volatility In A Murine Model Of Sepsis 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. C ontrolG roup -B aseline H R H istogram 0 10 20 30 40 50 60 Bin F req u en cy 00% 20% 40% 60% 80% 100% 120% Frequency Cum ulative % SD value at5% = 13.59 C ontrolG roup -Post-SO H R H istogram 0 20 40 60 80 100 120 140 160 180 200 Bin F req u en cy 00% 20% 40% 60% 80% 100% 120% Frequency Cum ulative % % ofintervals less than 13.59 in post-SO periods = 5.00 Septic G roup -B aseline H R H istogram 0 50 100 150 200 250 300 Bin F req u en cy 00% 20% 40% 60% 80% 100% 120% Frequency Cum ulative % SD V alue at5% = 16.28 Septic G roup -Post-C LP H R H istogram 0 100 200 300 400 500 600 700 800 Bin F req u en cy 00% 20% 40% 60% 80% 100% 120% Frequency Cum ulative % % ofintervals less than 16.28 in septic periods = 38.72 H eartR ate -Septic Anim al 0 100 200 300 400 500 600 700 800 bpm 0 12 24 36 48 60 84 96 C LP M ean ArterialPressure -Septic Anim al 0 20 40 60 80 100 120 140 160 180 m m Hg 0 12 24 36 48 60 84 96 C LP H eartR ate -C ontrolAnim al 0 100 200 300 400 500 600 700 800 bpm 0 12 24 36 48 60 84 96 SO M ean ArterialPressure -C ontrolAnim al 0 20 40 60 80 100 120 140 160 180 200 m m Hg 0 12 24 36 48 60 84 96 SO H R vs.H R volatility in S eptics and C ontrols 0 100 200 300 400 500 600 700 -24 -12 0 12 24 36 48 60 72 t(hrs) bpm 0 10 20 30 40 50 60 70 80 90 100 SD Cum% Septics HR Ctrls HR Ctrls HRV Septics HRV H R vs.H R volatility in S eptics and C ontrols 0 100 200 300 400 500 600 700 -24 -12 0 12 24 36 48 60 72 t(hrs) bpm 0 20 40 60 80 100 120 SD Cum% Survivors HR Non-Surv.HR Survivors HRV Non-Surv.HRV

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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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Page 1: Changes in Heart Rate Volatility In A Murine Model Of Sepsis

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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HR vs. HR volatility in Septics and Controls

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HR vs. HR volatility in Septics and Controls

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