Heart Rate Variability: A Potential Tool for Monitoring Immunomodulatory Effects of Parenteral Fish Oil Feeding in Patients With Sepsis

Fish oil, rich in the very-long chain omega (ω)-3 polyunsaturated fatty acids (PUFAs), has been found to have immunomodulatory effects in different groups of critically ill patients. In addition, its parenteral administration seems to attenuate the inflammatory response within 2 to 3 days. The activation of the cholinergic anti-inflammatory pathway has been suggested to mediate such immunoregulatory effects. As different experimental studies have convincingly illustrated that enhanced vagal tone can decrease pro-inflammatory cytokine secretion, novel monitoring tools of its activity at the bedside could be developed, to evaluate nutritional manipulation of immune response in the critically ill. Heart rate variability (HRV) is the variability of R-R series in the electrocardiogram and could be a promising surrogate marker of immune response and its modulation during fish oil feeding, rich in ω-3 PUFAs. Heart rate variability is an indirect measure of autonomic nervous system (ANS) output, reflecting mainly fluctuations in ANS activity. Through HRV analysis, different "physiomarkers" can be estimated that could be used as early and more accurate "smart alarms" because they are based on high-frequency measurements and are much more easy to get at the bedside. On the contrary, various "biomarkers" such as cytokines exhibit marked interdependence, pleiotropy, and their plasma concentrations fluctuate from day to day in patients with sepsis. In this respect, an inverse relation between different HRV components and inflammatory biomarkers has been observed in patients with severe sepsis and septic shock, whereas a beneficial effect of ω-3 PUFAs on HRV has been demonstrated in patients with cardiovascular diseases. Consequently, in this article, we suggest that a beneficial effect of ω-3 PUFAs on HRV and clinical outcome in patients with sepsis merits further investigation and could be tested in future clinical trials as a real-time monitoring tool of nutritional manipulation of the inflammatory response in the critically ill.

Correlations between frequency-domain HRV indices and lagged Poincaré plot width in healthy and diabetic subjects

The conventional Poincaré plot for heart rate variability (HRV) analysis is a scatterplot of successive (lag 1) pairs of RR intervals (intervals between heartbeats), and its width (SD1) is considered a measure of short-term variability. It has been shown that SD1 correlates better with HF than with LF (high- and low-frequency bands of the spectrum, respectively). Our aim was to assess how these correlations were affected when SD1 was obtained for longer lags. 10 min ECGs were used to construct Poincaré plots with lags of 1-10 heartbeats in two groups of subjects, one with normal HRV and the other with impaired HRV (control and diabetic groups respectively, N = 15 each). SD1 was quantified for these subjects and HRV spectral indices were estimated. The diabetic group had lower LF, HF and SD1 than the control group (p < 0.05). In both groups, SD1 tended to increase as the lag increased. In the control group, SD1 for lags 1 and 2 was highly correlated with HF (r(s) > 0.9), while SD1 for lags 4 correlated better with LF (r(s) 0.9) than with HF (0.65 <or= r(s) <or= 0.73). However, in the diabetic group, the correlation results did not change in that way for different lags (correlation results between HF and SD1: r(s) 0.95 for lags 1-10). In conclusion, the comparative strength of the correlations between lagged Poincaré widths and spectral indices might be useful to distinguish normal from pathological HRV.

Investigation of altered heart rate variability, nonlinear properties of heart rate signals, and organ dysfunction longitudinally over time in intensive care unit patients

PURPOSE

To investigate longitudinally over time heart rate dynamics and relation with mortality and organ dysfunction alterations in patients admitted to a multidisciplinary intensive care unit.

METHODS

Data from 53 patients were used, with heart rate recorded from monitors and analyzed on a daily basis (every morning) for 600 seconds and sampling rate at 250 Hz, from admission to the intensive care unit until final discharge from the unit. Variance, which is a measure of heart rate variability; exponent alpha2; and approximate entropy (ApEn), which assess long-range correlations and periodicity within a signal, respectively; were measured and compared with every day Sequential Organ Failure Assessment Score (SOFA) and mortality.

RESULTS

Nonsurvivors had lower ApEn mean (greater periodicity in their signals) and minimum values compared to survivors (0.53 +/- 0.25 vs 0.62 +/- 0.23, P = .04; 0.24 +/- 0.23 vs 0.48 +/- 0.23, P = .01, respectively). Patients in better conditions with SOFA of less than 7 (mean value) had higher variance and ApEn (more variable, less periodic signals) than those with SOFA of 7 or higher (0.47 +/- 0.51 vs 0.10 +/- 0.65, P < .001; 0.67 +/- 0.28 vs 0.49 +/- 0.24, P < .001, respectively). The alpha2 exponent and variance were correlated with length of stay (r = 0.55, P = .02, and r = 0.53, P = .02, respectively) and minimum ApEn with mortality (r = 0.41, P = .01).

CONCLUSIONS

Loss of variability and increase in periodicity in heart rate of critically ill patients are linked with parallel deterioration of organ dysfunction and high mortality.

Heart rate variability as early marker of multiple organ dysfunction syndrome in septic patients

PURPOSE

To determine whether measuring heart rate variability (HRV) in a group of septic patients without multiple organ dysfunction syndrome (MODS) made it possible to predict which of them would later develop this syndrome.

MATERIAL AND METHODS

We studied 46 septic patients without MODS at the time of admission to an intensive care unit (ICU). During the first 24 hours of admission, a 10-minute electrocardiogram (ECG) was performed and 8 HRV indexes were calculated off-line. Eleven patients later developed MODS (MODS group) during their ICU stay, and 28 did not (non-MODS group). Seven patients were excluded.

RESULTS

Although Acute Physiological and Chronic Health Evaluation (APACHE II) scores were similar for both groups, most HRV indices on admission were reduced significantly in the MODS group. Compared with a subset from the non-MODS group (control group, n = 11) paired by age, the MODS group had significantly lower low-frequency spectral components (LF, P =.0128) and mean squared successive differences of R-R intervals (rMSSD) (P =.0473) values. Multivariable logistic regression identified LF as the best predictor of MODS and received operating characteristic (ROC) curves established its cut-off point at 18 ms(2). Mortality rates were 63.6% for the MODS group and 0% for the non-MODS group (P <.0001).

CONCLUSIONS

Reduction of HRV on ICU admission may be useful in identifying septic patients at risk for development of MODS.

Linear and nonlinear analysis of heart rate variability during propofol anesthesia for short-duration procedures in children

OBJECTIVE

To determine whether heart rate variability metrics provide an accurate method of monitoring depth of anesthesia, assessing the response to painful stimuli, and assessing neuroautonomic regulation of cardiac activity in children receiving propofol anesthesia for short-duration procedures.

DESIGN

Prospective, case series.

SETTING

Sixteen-bed pediatric intensive care unit, oncology unit, and endoscopy suite in a tertiary care children's hospital and ophthalmology examination rooms in an associated eye institute.

PATIENTS

Thirty-three pediatric patients undergoing propofol anesthesia for short procedures.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Heart rate variability metrics studied included mean, SD, low- and high-frequency power, detrended fluctuation analysis (represented by correlation coefficient, alpha), and approximate entropy. Compared with the initial anesthetized state, we found increased heart rate SD (3.17 +/- 1.31 vs. 7.05 +/- 0.26 bpm, p <.0001), heart rate low-frequency power (3.69 +/- 0.36 vs. 4.48 +/- 0.41 bpm(2)/Hz, p <.0001), heart rate low-/high-frequency ratio (1.47 +/- 0.26 vs. 1.26 +/- 0.24, p =.001), and heart rate alpha (1.12 +/- 0.24 vs. 1.35 +/- 0.21, p <.0001) during painful procedure. Mean heart rate (105.8 +/- 13.4 vs. 101.5 +/- 12.4 bpm, p =.005) and heart rate approximate entropy decreased with painful procedure (0.75 +/- 0.19 vs. 0.53 + 0.16, p <.001), whereas there was no significant change in heart rate high-frequency power (3.04 +/- 0.63 vs. 3.16 +/- 0.71 bpm(2)/Hz, p =.26).

CONCLUSIONS

We conclude that power spectral analysis of heart rate variability may be an accurate and clinically useful measure of depth of propofol anesthesia. We speculate that high-frequency heart rate power during propofol anesthesia correlates with depth of anesthesia, whereas low-frequency power allows for assessment of the patient's sympathetic response to pain.

Physiologic data acquisition system and database for the study of disease dynamics in the intensive care unit

OBJECTIVE

To describe a real-time, continuous physiologic data acquisition system for the study of disease dynamics in the intensive care unit.

DESIGN

Descriptive report.

SETTING

A 16-bed pediatric intensive care unit in a tertiary care children's hospital.

PATIENTS

A total of 170 critically ill or injured pediatric patients.

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

None.

RESULTS

We describe a computerized data acquisition and analysis system for the study of critical illness and injury from the perspective of complex dynamic systems. Both parametric (1 Hz) and waveform (125-500 Hz) signals are recorded and analyzed. Waveform data include electrocardiogram, respiration, systemic arterial pressure (invasive and noninvasive), central venous pressure, pulmonary arterial pressure, left and right atrial pressures, intracranial pressure, body temperature, and oxygen saturation. Details of the system components are explained and examples are given from the resultant physiologic database of signal processing algorithms and signal analyses using linear and nonlinear metrics.

CONCLUSIONS

We have successfully developed a real-time, continuous physiologic data acquisition system that can capture, store, and archive data from pediatric intensive care unit patients for subsequent time series analysis of dynamic changes in physiologic state. The physiologic signal database generated from this system is available for analysis of dynamic changes caused by critical illness and injury.

Heart rate variability in critical illness and critical care

Although the rhythm of a healthy heart is clinically described as regular, the rate is variable. Studies of diverse populations have led to several generalizations about heart rate variability (HRV): (1) HRV is physiologic and normally declines with age, (2) acute changes in HRV are associated with several disease processes that require critical care, (3) measures of HRV can be used to describe the status of critically ill patients, and (4) measures of HRV can be used to predict events subsequent to at least one type of critical illness, myocardial infarction. This brief review considers the mechanisms underlying HRV, the measures that are used to describe HRV, and recent information regarding the use of HRV measures as predictive tools in critical care. The reviewers' opinion is that real-time analysis of HRV in critical illness may provide caregivers with additional information about patient status, effects of intervention, and prognosis.

Linear and nonlinear analysis of hemodynamic signals during sepsis and septic shock

OBJECTIVE

Neuroautonomic modulation of heart rate (HR) and blood pressure were assessed in sepsis or septic shock. We hypothesized that these metrics would be diminished in pediatric patients with sepsis and septic shock, indicating uncoupling of the autonomic and cardiovascular systems.

DESIGN

Prospective case series.

SETTING

Pediatric intensive care unit in a tertiary care children's hospital.

PATIENTS

Thirty pediatric patients with sepsis or septic shock.

INTERVENTIONS

None.

MEASURES AND MAIN RESULTS

Metrics used included power spectral analysis, a linear frequency domain measure, and detrended fluctuation analysis, a nonlinear technique that assesses the degree of long-range correlation in HR or blood pressure. We found decreased low-frequency (2.68 +/- 0.24 vs. 3.37 +/- 0.17 [SEM] bpm2; p = .03) and high-frequency HR power (2.18 +/- 0.14 vs. 2.79 +/- 0.23 bpm2; p = .04) and increased detrended fluctuation analysis scaling exponent (1.22 +/- 0.06 vs. 1.00 +/- 0.07 bpm2; p = .02) in sepsis vs. shock patients, respectively. Compared with sepsis or shock, recovery was associated with increases in low-frequency (3.61 +/- 0.15 vs. 3.05 +/- 0.19 bpm2; p < .0001) and high-frequency HR power (3.11 +/- 0.15 vs. 2.50 +/- 0.22 bpm2; p < .0001).

CONCLUSIONS

We conclude that uncoupling of the autonomic and cardiovascular systems occurs over both short- and long-range time scales during sepsis, and the degree of uncoupling may help differentiate between sepsis, septic shock, and recovery states.