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Douglas E Lake

Publications and source records attributed to Douglas E Lake.

8 recordsLinked to original sources
PubMed2005

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.

Blood Chemical Analysis↗
PubMed2004

Abnormal heart rate characteristics are associated with neonatal mortality.

Estimating the risk of in-hospital mortality in the newborn intensive care unit can provide important information for health-care providers, and illness severity scores have been devised to provide mortality risk estimates. Calculation of illness severity scores is time-consuming, and the information used to predict mortality is collected only for the first 12 to 24 h of life. A noninvasive continuous measure that uses information collected throughout the hospitalization and that requires no data entry could be less costly and more informative. We have previously shown that the abnormal heart rate characteristics (HRC) of reduced variability and transient decelerations accompany neonatal illness such as late-onset sepsis. We hypothesized that more frequent and severe abnormal HRC are associated with an increased risk of death. We tested this hypothesis in two ways. Using data on infants older than 7 d of age, we first determined the association of the HRC index with death in the next week. Second, we devised a cumulative HRC score and determined its association with in-hospital death. There were 37 deaths in the 685 patients. The major findings were 1) the HRC index showed highly significant association with death in the succeeding 7 d (receiver-operating characteristic area > 0.7, p < 0.001), and 2) the cumulative HRC was highly significantly associated with neonatal in-hospital mortality (receiver-operating characteristic area > 0.80, p < 0.001). In both analyses, HRC added information to birth weight, gestational age, and postnatal age (p < 0.01). The HRC index provides independent information about the risk of neonatal death in the upcoming 7 d, and the cumulative HRC is an estimate of the risk of in-hospital neonatal mortality.

Birth Weight↗
PubMed2004

Sample entropy.

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Journal Article↗
PubMed2004

Increased nonstationarity of neonatal heart rate before the clinical diagnosis of sepsis.

The clinical diagnosis of neonatal sepsis is preceded by abnormal heart rate (HR) characteristics of transient decelerations and reduced variability, which intuitively appear to be more nonstationary than normal HR variability. Our goals were to investigate stationarity of HR, and to devise measures useful for early diagnosis of neonatal sepsis. In this context, we define non-stationarity to be present when the observed data differ from surrogate data generated by stationary Gaussian noise with arbitrary linear correlations. We devised statistical methods for determining stationarity of HR data based on the two-sample Kolmogorov-Smirnov (KS) test. We compared distributions of KS distances between small sample epochs from clinical data with those of isospectral surrogates and of surrogates generated using the amplitude-adjusted Fourier transform technique, reasoning that they should differ significantly for nonstationary data. We found significant evidence of non-stationarity for records longer than 1 min. We developed new HR measures based on the empirical cumulative distribution function (ECDF) that are highly significantly associated with sepsis, but are not correlated with HR measures such as moments or sample entropy. We conclude that neonatal HR data cannot be assumed to be stationary, and become even less stationary prior to sepsis.

Algorithms↗
PubMed2003

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.

Birth Weight↗
PubMed2003

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↗
PubMed2002

Sample entropy analysis of neonatal heart rate variability.

Abnormal heart rate characteristics of reduced variability and transient decelerations are present early in the course of neonatal sepsis. To investigate the dynamics, we calculated sample entropy, a similar but less biased measure than the popular approximate entropy. Both calculate the probability that epochs of window length m that are similar within a tolerance r remain similar at the next point. We studied 89 consecutive admissions to a tertiary care neonatal intensive care unit, among whom there were 21 episodes of sepsis, and we performed numerical simulations. We addressed the fundamental issues of optimal selection of m and r and the impact of missing data. The major findings are that entropy falls before clinical signs of neonatal sepsis and that missing points are well tolerated. The major mechanism, surprisingly, is unrelated to the regularity of the data: entropy estimates inevitably fall in any record with spikes. We propose more informed selection of parameters and reexamination of studies where approximate entropy was interpreted solely as a regularity measure.

Entropy↗