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Background: A pulse oximetry warning system (POWS) to analyze heart rate and oxygen saturation data and predict risk of sepsis was developed for very low birth weight (VLBW) infants., Methods: We determined the clinical correlates and positive predictive value (PPV) of a high POWS score in VLBW infants. In a two-NICU retrospective study, we identified times when POWS increased above 6 (POWS spike). We selected an equal number of control times, matched for gestational and chronologic age. We reviewed records for infection and non-infection events around POWS spikes and control times. We calculated the frequencies and PPV of a POWS spike for infection or another significant event., Results: We reviewed 111 POWS spike times and 111 control times. Days near POWS spikes were more likely to have clinical events than control days (77% vs 50%). A POWS spike had 52% PPV for suspected or confirmed infection and 77% for any clinically significant event. Respiratory deterioration occurred near more POWS spike times than control times (34% vs 18%)., Conclusions: In a retrospective cohort, infection and respiratory deterioration were common clinical correlations of a POWS spike. POWS had a high PPV for significant clinical events with or without infection., Impact: There are significant gaps in understanding the best approach to implementing continuous sepsis prediction models so that clinicians can best respond to early signals of deterioration. Infection and respiratory deterioration were common clinical events identified at the time of a high predictive model score. Understanding the clinical correlates of a high-risk early warning score will inform future implementation efforts., (© 2024. The Author(s).)

Background: In extremely preterm infants, persistence of cardioventilatory events is associated with long-term morbidity. Therefore, the objective was to characterize physiologic growth curves of apnea, periodic breathing, intermittent hypoxemia, and bradycardia in extremely preterm infants during the first few months of life., Methods: The Prematurity-Related Ventilatory Control study included 717 preterm infants <29 weeks gestation. Waveforms were downloaded from bedside monitors with a novel sharing analytics strategy utilized to run software locally, with summary data sent to the Data Coordinating Center for compilation., Results: Apnea, periodic breathing, and intermittent hypoxemia events rose from day 3 of life then fell to near-resolution by 8-12 weeks of age. Apnea/intermittent hypoxemia were inversely correlated with gestational age, peaking at 3-4 weeks of age. Periodic breathing was positively correlated with gestational age peaking at 31-33 weeks postmenstrual age. Females had more periodic breathing but less intermittent hypoxemia/bradycardia. White infants had more apnea/periodic breathing/intermittent hypoxemia. Infants never receiving mechanical ventilation followed similar postnatal trajectories but with less apnea and intermittent hypoxemia, and more periodic breathing., Conclusions: Cardioventilatory events peak during the first month of life but the actual postnatal trajectory is dependent on the type of event, race, sex and use of mechanical ventilation., Impact: Physiologic curves of cardiorespiratory events in extremely preterm-born infants offer (1) objective measures to assess individual patient courses and (2) guides for research into control of ventilation, biomarkers and outcomes. Presented are updated maturational trajectories of apnea, periodic breathing, intermittent hypoxemia, and bradycardia in 717 infants born <29 weeks gestation from the multi-site NHLBI-funded Pre-Vent study. Cardioventilatory events peak during the first month of life but the actual postnatal trajectory is dependent on the type of event, race, sex and use of mechanical ventilation. Different time courses for apnea and periodic breathing suggest different maturational mechanisms., (© 2023. The Author(s), under exclusive licence to the International Pediatric Research Foundation, Inc.)

Background: Heart rate characteristics aid early detection of late-onset sepsis (LOS), but respiratory data contain additional signatures of illness due to infection. Predictive models using cardiorespiratory data may improve early sepsis detection. We hypothesized that heart rate (HR) and oxygenation (SpO 2 ) data contain signatures that improve sepsis risk prediction over HR or demographics alone., Methods: We analyzed cardiorespiratory data from very low birth weight (VLBW, <1500 g) infants admitted to three NICUs. We developed and externally validated four machine learning models to predict LOS using features calculated every 10 m: mean, standard deviation, skewness, kurtosis of HR and SpO 2 , and cross-correlation. We compared feature importance, discrimination, calibration, and dynamic prediction across models and cohorts. We built models of demographics and HR or SpO 2 features alone for comparison with HR-SpO 2 models., Results: Performance, feature importance, and calibration were similar among modeling methods. All models had favorable external validation performance. The HR-SpO 2 model performed better than models using either HR or SpO 2 alone. Demographics improved the discrimination of all physiologic data models but dampened dynamic performance., Conclusions: Cardiorespiratory signatures detect LOS in VLBW infants at 3 NICUs. Demographics risk-stratify, but predictive modeling with both HR and SpO 2 features provides the best dynamic risk prediction., Impact: Heart rate characteristics aid early detection of late-onset sepsis, but respiratory data contain signatures of illness due to infection. Predictive models using both heart rate and respiratory data may improve early sepsis detection. A cardiorespiratory early warning score, analyzing heart rate from electrocardiogram or pulse oximetry with SpO 2 , predicts late-onset sepsis within 24 h across multiple NICUs and detects sepsis better than heart rate characteristics or demographics alone. Demographics risk-stratify, but predictive modeling with both HR and SpO 2 features provides the best dynamic risk prediction. The results increase understanding of physiologic signatures of neonatal sepsis., (© 2022. The Author(s), under exclusive licence to the International Pediatric Research Foundation, Inc.)

Background: Neonatal intensive care unit (NICU) patients are at increased risk for autism spectrum disorder (ASD). Autonomic nervous system aberrancy has been described in children with ASD, and we aimed to identify heart rate (HR) patterns in NICU patients associated with eventual ASD diagnosis., Methods: This retrospective cohort study included NICU patients from 2009 to 2016 with archived HR data and follow-up beyond age 3 years. Medical records provided clinical variables and ASD diagnosis. HR data were compared in infants with and without ASD., Results: Of the 2371 patients, 88 had ASD, and 689,016 h of data were analyzed. HR skewness (HRskw) was significantly different between ASD and control infants. Preterm infants at early postmenstrual ages (PMAs) had negative HRskw reflecting decelerations, which increased with maturation. From 34 to 42 weeks PMA, positive HRskw toward accelerations was higher in males with ASD. In 931 males with at least 4 days of HR data, overall ASD prevalence was 5%, whereas 11% in the top 5th HRskw percentile had ASD., Conclusion: High HRskw in NICU males, perhaps representing autonomic imbalance, was associated with increased ASD risk. Further study is needed to determine whether HR analysis identifies highest-risk infants who might benefit from earlier screening and therapies., Impact: In a large retrospective single-center cohort of NICU patients, we found that high positive skewness of heart rate toward more accelerations was significantly associated with increased risk of eventual autism spectrum disorder diagnosis in male infants but not in females. Existing literature describes differences in heart rate characteristics in children, adolescents, and adults with autism spectrum disorders, but the finding from our study in NICU infants is novel. Heart rate analysis during the NICU stay might identify, among an inherently high-risk population, those infants with especially high risk of ASD who might benefit from earlier screening and therapies., (© 2021. The Author(s), under exclusive licence to the International Pediatric Research Foundation, Inc.)

Background: Continuous heart rate (HR) and oxygenation (SpO 2 ) metrics can be useful for predicting adverse events in very low birth weight (VLBW) infants. To optimize the utility of these tools, inter-site variability must be taken into account., Methods: For VLBW infants at three neonatal intensive care units (NICUs), we analyzed the mean, standard deviation, skewness, kurtosis, and cross-correlation of electrocardiogram HR, pulse oximeter pulse rate, and SpO 2 . The number and durations of bradycardia and desaturation events were also measured. Twenty-two metrics were calculated hourly, and mean daily values were compared between sites., Results: We analyzed data from 1168 VLBW infants from birth through day 42 (35,238 infant-days). HR and SpO 2 metrics were similar at the three NICUs, with mean HR rising by ~10 beats/min over the first 2 weeks and mean SpO 2 remaining stable ~94% over time. The number of bradycardia events was higher at one site, and the duration of desaturations was longer at another site., Conclusions: Mean HR and SpO 2 were generally similar among VLBW infants at three NICUs from birth through 6 weeks of age, but bradycardia and desaturation events differed in the first 2 weeks after birth. This highlights the importance of developing predictive analytics tools at multiple sites., Impact: HR and SpO 2 analytics can be useful for predicting adverse events in VLBW infants in the NICU, but inter-site differences must be taken into account in developing predictive algorithms. Although mean HR and SpO 2 patterns were similar in VLBW infants at three NICUs, inter-site differences in the number of bradycardia events and duration of desaturation events were found. Inter-site differences in bradycardia and desaturation events among VLBW infants should be considered in the development of predictive algorithms., (© 2021. The Author(s), under exclusive licence to the International Pediatric Research Foundation, Inc.)

Background: Displaying heart rate characteristic (HRC) scores was associated with lower sepsis-associated mortality in very low birth weight (VLBW) infants in a multicenter randomized controlled trial (HeRO trial). The aim of this study was to test whether HRC indices rise before diagnosis of urinary tract infection (UTI) or meningitis, with and without concomitant BSI., Methods: Blood, urine, and cerebrospinal fluid (CSF) culture data after 3 days of age and within 120 days of study enrollment were analyzed from 2989 VLBW infants. The HRC index was analyzed 12 h prior to positive cultures compared to 36 h prior, using paired signed-rank tests., Results: UTI, meningitis, and BSI were diagnosed in 10%, 2%, and 24% of infants, respectively. The mean hourly HRC index was significantly higher 12 h prior to diagnosis of UTI and BSI compared to 36 h prior (UTI 2.07 versus 1.81; BSI 2.62 versus 2.25, both p < 0.0001). The baseline HRC index was higher for meningitis, compared to UTI or BSI, but without a statistically significant rise in the day prior to meningitis diagnosis., Conclusions: In a large cohort of VLBW infants enrolled in the HeRO trial, the HRC index increased in the 24-h period prior to diagnosis of UTI and BSI but not meningitis.

Background: Early recognition of patients at risk for sepsis is paramount to improve clinical outcomes. We hypothesized that subtle signatures of illness are present in physiological and biochemical time series of pediatric-intensive care unit (PICU) patients in the early stages of sepsis., Methods: We developed multivariate models in a retrospective observational cohort to predict the clinical diagnosis of sepsis in children. We focused on age as a predictor and asked whether random forest models, with their potential for multiple cut points, had better performance than logistic regression., Results: One thousand seven hundred and eleven admissions for 1425 patients admitted to a mixed cardiac and medical/surgical PICU were included. We identified, through individual chart review, 187 sepsis diagnoses that were not within 14 days of a prior sepsis diagnosis. Multivariate models predicted sepsis in the next 24 h: cross-validated C-statistic for logistic regression and random forest were 0.74 (95% confidence interval (CI): 0.71-0.77) and 0.76 (95% CI: 0.73-0.79), respectively., Conclusions: Statistical models based on physiological and biochemical data already available in the PICU identify high-risk patients up to 24 h prior to the clinical diagnosis of sepsis. The random forest model was superior to logistic regression in capturing the context of age.

Background: Preterm very low birth weight (VLBW) infants experience physiologic maturation and transitions off therapies from 32 to 35 weeks postmenstrual age (PMA), which may impact episodic bradycardia and oxygen desaturation. We sought to characterize bradycardias and desaturations from 32 to 35 weeks PMA and test whether events at 32 weeks PMA are associated with NICU length of stay., Methods: For 265 VLBW infants from 32 to 35 weeks PMA, we quantified the number and duration of bradycardias (HR <100 for ≥4 s) and desaturations (SpO 2 <80% for ≥10 s) and compared events around discontinuation of CPAP, caffeine, and supplemental oxygen. We modeled associations between clinical variables, bradycardias and desaturations at 32 weeks PMA, and discharge PMA., Results: Desaturations decreased from 60 to 41 per day at 32 and 35 weeks, respectively (p < 0.01). Duration of desaturations and number and duration of bradycardias decreased to a smaller extent (p < 0.05), and there was a non-significant trend toward increased desaturations after stopping CPAP and caffeine. Controlling for clinical variables, longer duration of bradycardias and desaturations at 32 weeks PMA was associated with later discharge PMA., Conclusion: Delayed recovery from bradycardias and desaturations at 32 weeks PMA, perhaps reflecting less physiologic resilience, is associated with prolonged NICU stay for VLBW infants.

Background: Bradycardia and oxygen desaturation episodes are common among preterm very low birth weight (VLBW) infants in the Neonatal Intensive Care Unit (NICU), and their association with adverse outcomes such as bronchopulmonary dysplasia (BPD) is unclear., Methods: For 502 VLBW infants we quantified bradycardias (HR < 100 for ≥ 4 s) and desaturations (SpO 2  < 80% for ≥ 10 s), combined bradycardia and desaturation (BD) events, and percent time in events in the first 4 weeks after birth (32 infant-years of data). We tested logistic regression models of clinical risks (including a respiratory acuity score incorporating FiO 2 and level of respiratory support) to estimate the risks of BPD or death and secondary outcomes. We then tested the additive value of the bradycardia and desaturation metrics for outcomes prediction., Results: BPD occurred in 187 infants (37%). The clinical risk model had ROC area for BPD of 0.874. Measures of desaturation, but not bradycardia, significantly added to the predictive model. Desaturation metrics also added to clinical risks for prediction of severe intraventricular hemorrhage, retinopathy of prematurity and prolonged length of stay in the NICU., Conclusions: Oxygen desaturations in the first month of the NICU course are associated with risk of BPD and other morbidities in VLBW infants.

Background: Subtle changes in vital signs and their interactions occur in preterm infants prior to overt deterioration from late-onset septicemia (LOS) or necrotizing enterocolitis (NEC). Optimizing predictive algorithms may lead to earlier treatment., Methods: For 1,065 very-low-birth-weight (VLBW) infants in two neonatal intensive care units (NICUs), mean, SD, and cross-correlation of respiratory rate, heart rate (HR), and oxygen saturation (SpO 2 ) were analyzed hourly (131 infant-years' data). Cross-correlation (cotrending) between two vital signs was measured allowing a lag of ± 30 s. Cases of LOS and NEC were identified retrospectively (n = 186) and vital sign models were evaluated for ability to predict illness diagnosed in the ensuing 24 h., Results: The best single illness predictor within and between institutions was cross-correlation of HR-SpO 2 . The best combined model (mean SpO 2 , SDHR, and cross-correlation of HR-SpO 2 ,) trained at one site with ROC area 0.695 had external ROC area of 0.754 at the other site, and provided additive value to an established HR characteristics index for illness prediction (Net Reclassification Improvement: 0.205; 95% confidence interval (CI): 0.113, 0.328)., Conclusion: Despite minor inter-institutional differences in vital sign patterns of VLBW infants, cross-correlation of HR-SpO 2 and a 3-variable vital sign model performed well at both centers for preclinical detection of sepsis or NEC.

Background: Abnormal heart rate characteristics (HRC) wax and wane in early stages of culture-positive, late-onset septicemia (LOS) in patients in the neonatal intensive care unit (NICU). Continuously monitoring an HRC index leads to a reduction in mortality among very low birth weight (VLBW) infants. We hypothesized that the reduction in mortality was due to a decrease in septicemia-associated mortality., Methods: This is a secondary analysis of clinical and HRC data from 2,989 VLBW infants enrolled in a randomized clinical trial of HRC monitoring in nine NICUs from 2004 to 2010., Results: LOS was diagnosed 974 times in 700 patients, and the incidence and distribution of organisms were similar in HRC display and nondisplay groups. Mortality within 30 d of LOS was lower in the HRC display as compared with the nondisplay group (11.8 vs. 19.6%; relative risk: 0.61; 95% confidence interval: 0.43, 0.87; P < 0.01), but mortality reduction was not statistically significant for patients without LOS. There were fewer large, abrupt increases in the HRC index in the days leading up to LOS diagnosis in infants whose HRC index was displayed., Conclusion: Continuous HRC monitoring is associated with a lower septicemia-associated mortality in VLBW infants, possibly due to diagnosis earlier in the course of illness.

Background: Infants admitted to the neonatal intensive care unit (NICU), and especially those born with very low birth weight (VLBW; <1,500 g), are at risk for respiratory decompensation requiring endotracheal intubation and mechanical ventilation. Intubation and mechanical ventilation are associated with increased morbidity, particularly in urgent unplanned cases., Methods: We tested the hypothesis that the systemic response associated with respiratory decompensation can be detected from physiological monitoring and that statistical models of bedside monitoring data can identify infants at increased risk of urgent unplanned intubation. We studied 287 VLBW infants consecutively admitted to our NICU and found 96 events in 51 patients, excluding intubations occurring within 12 h of a previous extubation., Results: In order of importance in a multivariable statistical model, we found that the characteristics of reduced O(2) saturation, especially as heart rate was falling; increased heart rate correlation with respiratory rate; and the amount of apnea were all significant independent predictors. The predictive model, validated internally by bootstrap, had a receiver-operating characteristic area of 0.84 ± 0.04., Conclusion: We propose that predictive monitoring in the NICU for urgent unplanned intubation may improve outcomes by allowing clinicians to intervene noninvasively before intubation is required.

Introduction: Biomarkers and physiomarkers may be useful adjunct tests for sepsis detection in neonatal intensive care unit (NICU) patients. We studied whether measuring plasma cytokines at the time of suspected sepsis could identify patients with bacteremia in centers in which patients were undergoing continuous physiomarker screening using a heart rate characteristics (HRC) index monitor., Results: Six cytokines were higher in Gram-negative bacteremia (GNB) than in Gram-positive bacteremia or candidemia (GPBC). A cytokine score using thresholds for granulocyte colony-stimulating factor (G-CSF), interleukin (IL)-6, IL-8, and tumor necrosis factor (TNF)-α had 100% sensitivity and 69% positive predictive value (PPV) for GNB. A single cytokine marker, IL-6 < 130 pg/ml, had 100% sensitivity and 52% PPV for sepsis ruled out (SRO). The average HRC index was abnormal in this cohort of patients with clinical suspicion of sepsis and did not discriminate between the final sepsis designations., Discussion: In summary, in NICU patients with suspected late-onset sepsis, plasma cytokines can identify those with SRO and those with GNB, potentially aiding in decisions regarding therapy., Methods: Seven cytokines were measured in 226 plasma samples from patients >3 d old with sepsis suspected based on clinical signs, abnormal HRC index, or both. Cases were classified as SRO, clinical sepsis (CS), GPBC, or GNB.

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.

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.

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.

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.