Douglas E. Lake

Mortality reduction by heart rate characteristic monitoring in very low birth weight neonates: A randomized trial

OBJECTIVE To test the hypothesis that heart rate characteristics (HRC) monitoring improves neonatal outcomes. STUDY DESIGN We conducted a two-group, parallel, individually randomized controlled clinical trial of 3003 very low birth weight infants in 9 neonatal intensive care units. In one group, HRC monitoring was displayed; in the other, it was masked. The primary outcome was number of days alive and ventilator-free in the 120 days after randomization. Secondary outcomes were mortality, number of ventilator days, neonatal intensive care unit stay, and antibiotic use. RESULTS The mortality rate was reduced in infants whose HRC monitoring was displayed, from 10.2% to 8.1% (hazard ratio, 0.78; 95% CI, 0.61-0.99; P = .04; number needed to monitor = 48), and there was a trend toward increased days alive and ventilator-free (95.9 of 120 days compared with 93.6 in control subjects, P = .08). The mortality benefit was concentrated in infants with a birth weight <1000 g (hazard ratio, 0.74; 95% CI, 0.57-0.95; P = .02; number needed to monitor = 23). There were no significant differences in the other outcomes. CONCLUSION HRC monitoring can reduce the mortality rate in very low birth weight infants.

Abnormal heart rate characteristics preceding neonatal sepsis and sepsis-like illness.

Late-onset neonatal sepsis is a significant cause of morbidity and mortality, and early detection could prove beneficial. Previously, we found that abnormal heart rate characteristics (HRC) of reduced variability and transient decelerations occurred early in the course of neonatal sepsis and sepsis-like illness in infants in a single neonatal intensive care unit (NICU). We hypothesized that this finding can be generalized to other NICUs. We prospectively collected clinical data and continuously measured RR intervals in all infants in two NICUs who stayed for >7 d. We defined episodes of sepsis and sepsis-like illness as acute clinical deteriorations that prompted physicians to obtain blood cultures and start antibiotics. A predictive statistical model yielding an HRC index was developed on a derivation cohort of 316 neonates in the University of Virginia NICU and then applied to the validation cohort of 317 neonates in the Wake Forest University NICU. In the derivation cohort, there were 155 episodes of sepsis and sepsis-like illness in 101 infants, and in the validation cohort, there were 118 episodes in 93 infants. In the validation cohort, the HRC index 1) showed highly significant association with impending sepsis and sepsis-like illness (receiver operator characteristic area 0.75, p < 0.001) and 2) added significantly to the demographic information of birth weight, gestational age, and days of postnatal age in predicting sepsis and sepsis-like illness (p < 0.001). Continuous HRC monitoring is a generally valid and potentially useful noninvasive tool in the early diagnosis of neonatal sepsis and sepsis-like illness.

Heart rate characteristics : Novel physiomarkers to predict neonatal infection and death

Objective. Monitoring of regulated physiologic processes using physiomarkers such as heart rate variability may be important in the early diagnosis of subacute, potentially catastrophic illness. Early in the course of neonatal sepsis, there are physiomarkers of reduced heart rate variability and transient decelerations similar to fetal distress. The goal of this study was to determine the degree of increased risk for sepsis, urinary tract infection (UTI), and death when these abnormal heart rate characteristics (HRC) were observed. Methods. We monitored 1022 infants at 2 tertiary care NICUs, 458 of whom were very low birth weight. We calculated an HRC index from validated regression models relating mathematical features of heart rate time series and histograms to episodes of illness. We calculated the risks for adverse events of sepsis, UTI, and death for infants stratified by HRC measurements. Results. Compared with infants with low-risk HRC measurements, infants with high-risk HRC measurements had 5- to 6-fold increased risk for an adverse event in the next day and 3-fold increased risk in the next week. Laboratory tests that were relevant to infection added information to HRC measurements. Infants with both high-risk HRC and abnormal laboratory tests had 6- to 7-fold increased risk for an adverse event in the next day compared with infants who had neither. Conclusion. HRC are noninvasively monitored physiomarkers that identify infants in the NICU who are at high risk for sepsis, UTI, and death.

Accurate estimation of entropy in very short physiological time series: the problem of atrial fibrillation detection in implanted ventricular devices

Entropy estimation is useful but difficult in short time series. For example, automated detection of atrial fibrillation (AF) in very short heart beat interval time series would be useful in patients with cardiac implantable electronic devices that record only from the ventricle. Such devices require efficient algorithms, and the clinical situation demands accuracy. Toward these ends, we optimized the sample entropy measure, which reports the probability that short templates will match with others within the series. We developed general methods for the rational selection of the template length m and the tolerance matching r. The major innovation was to allow r to vary so that sufficient matches are found for confident entropy estimation, with conversion of the final probability to a density by dividing by the matching region volume, 2r(m). The optimized sample entropy estimate and the mean heart beat interval each contributed to accurate detection of AF in as few as 12 heartbeats. The final algorithm, called the coefficient of sample entropy (COSEn), was developed using the canonical MIT-BIH database and validated in a new and much larger set of consecutive Holter monitor recordings from the University of Virginia. In patients over the age of 40 yr old, COSEn has high degrees of accuracy in distinguishing AF from normal sinus rhythm in 12-beat calculations performed hourly. The most common errors are atrial or ventricular ectopy, which increase entropy despite sinus rhythm, and atrial flutter, which can have low or high entropy states depending on dynamics of atrioventricular conduction.

Heart Rate Characteristics and Clinical Signs in Neonatal Sepsis

To test the hypothesis that heart rate characteristic (HRC) monitoring adds information to clinical signs of illness in diagnosing neonatal sepsis, we prospectively recorded clinical data and the HRC index in 76 episodes of proven sepsis and 80 episodes of clinical sepsis in 337 infants in the University of Virginia NICU more than 7 d old. We devised an illness severity score based on clinical findings and tests relevant to sepsis. Point scores were derived from coefficients of multivariable regression models, and we internally validated a total score. We determined relationships of the HRC index with individual clinical signs, laboratory tests, and the total score. We found highly significant correlations of the clinical score and individual clinical signs with the HRC index. The clinical score and HRC index added independent information in predicting sepsis, and were similar in clinical and proven sepsis. The clinical score and the HRC index rose before sepsis, and the HRC index rose first. We conclude that clinical signs of illness and HRC monitoring add independent information to one another in the diagnosis of neonatal sepsis.

Heart rate characteristics monitoring for neonatal sepsis

While heart rate variability has been measured in many clinical settings and has offered insights into how HR is controlled, rarely has it offered unique information that has led to changes in patient management. We review our experience in developing continuous HR characteristics monitoring to aid in the early diagnosis of sepsis in premature infants in the neonatal intensive care unit. A predictive algorithm, developed at one center and validated at another, has led to diagnosis and treatment of this subacute and potentially catastrophic illness prior to appearance of symptoms of severe illness.

Heart Rate Characteristics and Laboratory Tests in Neonatal Sepsis

Objective. The evaluation of an infant for suspected sepsis often includes obtaining blood for laboratory tests. The shortcomings of the current practice are that the infant has to appear clinically ill for the diagnosis to be entertained, and the conventional laboratory tests are invasive. We have found that the clinical diagnosis of neonatal sepsis is preceded by abnormal heart rate characteristics (HRC) of reduced variability and transient decelerations, and we have devised a predictive HRC monitoring strategy based on multivariable logistic regression analysis that was developed at one tertiary care NICU and validated at another. We hypothesized that HRC monitoring, which is continuous and noninvasive, might be an adjunct to conventional laboratory tests in the diagnosis of neonatal sepsis. The objective of this study was to test the hypothesis that HRC monitoring adds information to conventional laboratory tests in diagnosing neonatal sepsis. Methods. We prospectively collected heart rate data in 678 consecutive infants who stayed >7 days in the University of Virginia NICU from July 1999 to July 2003. We prospectively measured HRC and noted 149 episodes of sepsis with positive blood cultures for which data were available in 137. We obtained all laboratory test results for ratio of immature to total neutrophil count, white blood cell count, glucose, platelet count, HCO3, arterial partial pressure of carbon dioxide, and pH. We tested hypotheses using multivariable logistic regression modeling adjusted for repeated measures. Results. We found that the HRC index, which was available 92% of the time, was highly significantly associated with sepsis (receiver-operating characteristic [ROC] area: 0.73). The ratio of immature to total neutrophil count, white blood cell count (available 4%–8% of the time, usually around the time of suspected sepsis), and blood glucose and pH (available 28% and 38% of the time) were also significantly associated with sepsis (ROC area: 0.75). HRC and laboratory values added independent information to each other, and a predictive model using all significant variables had ROC area of 0.82. Conclusions. HRC monitoring adds independent information to laboratory tests in the diagnosis of culture-positive neonatal sepsis.

Renyi entropy measures of heart rate Gaussianity

Sample entropy and approximate entropy are measures that have been successfully utilized to study the deterministic dynamics of heart rate (HR). A complementary stochastic point of view and a heuristic argument using the Central Limit Theorem suggests that the Gaussianity of HR is a complementary measure of the physiological complexity of the underlying signal transduction processes. Renyi entropy (or q-entropy) is a widely used measure of Gaussianity in many applications. Particularly important members of this family are differential (or Shannon) entropy (q=1) and quadratic entropy (q=2). We introduce the concepts of differential and conditional Renyi entropy rate and, in conjunction with Burgs theorem, develop a measure of the Gaussianity of a linear random process. Robust algorithms for estimating these quantities are presented along with estimates of their standard errors.

Endotoxin depresses heart rate variability in mice: cytokine and steroid effects

Heart rate variability (HRV) falls in humans with sepsis, but the mechanism is not well understood. We utilized a mouse model of endotoxemia to test the hypothesis that cytokines play a role in abnormal HRV during sepsis. Adult male C57BL/6 mice underwent surgical implantation of probes to continuously monitor electrocardiogram and temperature or blood pressure via radiotelemetry. Administration of high-dose LPS (Escherichia coli LPS, 10 mg/kg, n = 10) caused a biphasic response characterized by an early decrease in temperature and heart rate at 1 h in some mice, followed by a prolonged period of depressed HRV in all mice. Further studies showed that LPS doses as low as 0.01 mg/kg evoked a significant decrease in HRV. With high-dose LPS, the initial drops in temperature and HR were temporally correlated with peak expression of TNFalpha 1 h post-LPS, whereas maximal depression in HRV coincided with peak levels of multiple other cytokines 3-9 h post-LPS. Neither hypotension nor hypothermia explained the HRV response. Pretreatment with dexamethasone prior to LPS significantly blunted expression of 7 of the 10 cytokines studied and shortened the duration of depressed HRV by about half. Interestingly, dexamethasone treatment alone caused a dramatic increase in both low- and high-frequency HRV. Administration of recombinant TNFalpha caused a biphasic response in HR and HRV similar to that caused by LPS. Understanding the role of cytokines in abnormal HRV during sepsis could lead to improved strategies for detecting life-threatening nosocomial infections in intensive care unit patients.

Sample asymmetry analysis of heart rate characteristics with application to Neonatal sepsis and systemic inflammatory response syndrome

We introduce the sample asymmetry analysis (SAA) and illustrate its utility for assessment of heart rate characteristics occurring early in the course of neonatal sepsis and systemic inflammatory response syndrome (SIRS). Conceptually, SAA describes changes in the shape of the histogram of RR intervals that are caused by reduced accelerations and/or transient decelerations of heart rate. Unlike other measures of heart rate variability, SAA allows separate quantification of the contribution of accelerations and decelerations. The application of SAA is exemplified by a study comparing 50 infants, who experienced a total of 75 episodes of sepsis and SIRS, with 50 control infants. The two groups were matched by birth weight and gestational age. RR intervals were recorded for all infants throughout their course in the Neonatal Intensive Care Unit. The sample asymmetry of the RR intervals increased in the 3–4 d preceding sepsis and SIRS, with the steepest increase in the last 24 h, from a baseline value of 3.3 (SD = 1.6) to 4.2 (SD = 2.3), p = 0.02. After treatment and recovery, sample asymmetry returned to its baseline value of 3.3 (SD = 1.3). The difference between sample asymmetry in health and before sepsis and SIRS was mainly due to fewer accelerations than to decelerations. Compared with healthy infants, infants who experienced sepsis had similar sample asymmetry in health, and elevated values before sepsis and SIRS (p = 0.002). We conclude that SAA is a useful new mathematical technique for detecting the abnormal heart rate characteristics that precede neonatal sepsis and SIRS.