Apnea, Intermittent Hypoxemia, and Bradycardia Events Predict Late-Onset Sepsis in Infants Born Extremely Preterm.

OBJECTIVE: The objective of this study was to examine the association of cardiorespiratory events, including apnea, periodic breathing, intermittent hypoxemia (IH), and bradycardia, with late-onset sepsis for extremely preterm infants (<29 weeks of gestational age) on vs off invasive mechanical ventilation. STUDY DESIGN: This is a retrospective analysis of data from infants enrolled in Pre-Vent (ClinicalTrials.gov identifier NCT03174301), an observational study in 5 level IV neonatal intensive care units. Clinical data were analyzed for 737 infants (mean gestational age: 26.4 weeks, SD 1.71). Monitoring data were available and analyzed for 719 infants (47 512 patient-days); of whom, 109 had 123 sepsis events. Using continuous monitoring data, we quantified apnea, periodic breathing, bradycardia, and IH. We analyzed the relationships between these daily measures and late-onset sepsis (positive blood culture >72 hours after birth and ≥5-day antibiotics). RESULTS: For infants not on a ventilator, apnea, periodic breathing, and bradycardia increased before sepsis diagnosis. During times on a ventilator, increased sepsis risk was associated with longer events with oxygen saturation <80% (IH80) and more bradycardia events before sepsis. IH events were associated with higher sepsis risk but did not dynamically increase before sepsis, regardless of ventilator status. A multivariable model including postmenstrual age, cardiorespiratory variables (apnea, periodic breathing, IH80, and bradycardia), and ventilator status predicted sepsis with an area under the receiver operator characteristic curve of 0.783. CONCLUSION: We identified cardiorespiratory signatures of late-onset sepsis. Longer IH events were associated with increased sepsis risk but did not change temporally near diagnosis. Increases in bradycardia, apnea, and periodic breathing preceded the clinical diagnosis of sepsis.

Maturation of cardioventilatory physiological trajectories in extremely preterm infants.

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.

Cardiorespiratory Monitoring Data to Predict Respiratory Outcomes in Extremely Preterm Infants.

Rationale: Immature control of breathing is associated with apnea, periodic breathing, intermittent hypoxemia, and bradycardia in extremely preterm infants. However, it is not clear if such events independently predict worse respiratory outcome. Objectives: To determine if analysis of cardiorespiratory monitoring data can predict unfavorable respiratory outcomes at 40 weeks postmenstrual age (PMA) and other outcomes, such as bronchopulmonary dysplasia at 36 weeks PMA. Methods: The Prematurity-related Ventilatory Control (Pre-Vent) study was an observational multicenter prospective cohort study including infants born at <29 weeks of gestation with continuous cardiorespiratory monitoring. The primary outcome was either "favorable" (alive and previously discharged or inpatient and off respiratory medications/O2/support at 40 wk PMA) or "unfavorable" (either deceased or inpatient/previously discharged on respiratory medications/O2/support at 40 wk PMA). Measurements and Main Results: A total of 717 infants were evaluated (median birth weight, 850 g; gestation, 26.4 wk), 53.7% of whom had a favorable outcome and 46.3% of whom had an unfavorable outcome. Physiologic data predicted unfavorable outcome, with accuracy improving with advancing age (area under the curve, 0.79 at Day 7, 0.85 at Day 28 and 32 wk PMA). The physiologic variable that contributed most to prediction was intermittent hypoxemia with oxygen saturation as measured by pulse oximetry <90%. Models with clinical data alone or combining physiologic and clinical data also had good accuracy, with areas under the curve of 0.84-0.85 at Days 7 and 14 and 0.86-0.88 at Day 28 and 32 weeks PMA. Intermittent hypoxemia with oxygen saturation as measured by pulse oximetry <80% was the major physiologic predictor of severe bronchopulmonary dysplasia and death or mechanical ventilation at 40 weeks PMA. Conclusions: Physiologic data are independently associated with unfavorable respiratory outcome in extremely preterm infants.

Cardiorespiratory signature of neonatal sepsis: development and validation of prediction models in 3 NICUs.

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 (SpO2) 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 SpO2, and cross-correlation. We compared feature importance, discrimination, calibration, and dynamic prediction across models and cohorts. We built models of demographics and HR or SpO2 features alone for comparison with HR-SpO2 models. RESULTS: Performance, feature importance, and calibration were similar among modeling methods. All models had favorable external validation performance. The HR-SpO2 model performed better than models using either HR or SpO2 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 SpO2 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 SpO2, 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 SpO2 features provides the best dynamic risk prediction. The results increase understanding of physiologic signatures of neonatal sepsis.

Continuous ECG monitoring should be the heart of bedside AI-based predictive analytics monitoring for early detection of clinical deterioration.

The idea that we can detect subacute potentially catastrophic illness earlier by using statistical models trained on clinical data is now well-established. We review evidence that supports the role of continuous cardiorespiratory monitoring in these predictive analytics monitoring tools. In particular, we review how continuous ECG monitoring reflects the patient and not the clinician, is less likely to be biased, is unaffected by changes in practice patterns, captures signatures of illnesses that are interpretable by clinicians, and is an underappreciated and underutilized source of detailed information for new mathematical methods to reveal.

Autism risk in neonatal intensive care unit patients associated with novel heart rate patterns.

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.

Vital sign metrics of VLBW infants in three NICUs: implications for predictive algorithms.

BACKGROUND: Continuous heart rate (HR) and oxygenation (SpO2) 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 SpO2. 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 SpO2 metrics were similar at the three NICUs, with mean HR rising by ~10 beats/min over the first 2 weeks and mean SpO2 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 SpO2 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 SpO2 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 SpO2 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.

Central Apnea of Prematurity: Does Sex Matter?

OBJECTIVE: Apnea is common among infants in the neonatal intensive care unit (NICU). Our group previously developed an automated algorithm to quantitate central apneas with associated bradycardia and desaturation (ABDs). Sex differences in lung disease are well described in preterm infants, but the influence of sex on apnea has not been established. STUDY DESIGN: This study includes infants < 34 weeks' gestation admitted to the University of Virginia NICU from 2009 to 2014 with at least 1 day of bedside monitor data available when not on mechanical ventilation. Waveform and vital sign data were analyzed using a validated algorithm to detect ABD events of low variance in chest impedance signal lasting at least 10 seconds with associated drop in heart rate to < 100 beats/minute and drop in oxygen saturation to < 80%. Male and female infants were compared for prevalence of at least one ABD event during the NICU stay, treatment with caffeine, occurrence of ABDs at each week of postmenstrual age, and number of events per day. RESULTS: Of 926 infants studied (median gestational age 30 weeks, 53% male), median days of data analyzed were 19 and 22 for males and females, respectively. There was no sex difference in prevalence of at least one ABD event during the NICU stay (males 62%, females 64%, p = 0.47) or in the percentage of infants treated with caffeine (males 64%, females 67%, p = 0.40). Cumulative prevalence of ABDs from postmenstrual ages 24 to 36 weeks was comparable between sexes. Males had 18% more ABDs per day of data, but this difference was not statistically significant (p = 0.16). CONCLUSION: In this large cohort of infants < 34 weeks' gestation, we did not detect a sex difference in prevalence of central ABD events. There was a nonsignificant trend toward a greater number of ABDs per day in male infants. KEY POINTS: · Central apnea is pervasive among preterm infants in the NICU, but potential disparities between males and females have not been thoroughly studied.. · Identification of risk factors for central apnea can lead to improved treatment protocols.. · The rate and prevalence of central apnea events accompanied by bradycardia and desaturation does not significantly differ between male and female preterm infants..

Mortality and Neurodevelopmental Outcomes in the Heart Rate Characteristics Monitoring Randomized Controlled Trial.

OBJECTIVE: To test whether the composite outcome of death or neurodevelopmental impairment (NDI) at 18-22 months corrected age for infants ≤1000 g at birth is decreased by continuous monitoring of heart rate characteristics during neonatal intensive care. STUDY DESIGN: We studied a subset of participants enrolled in a multicenter randomized trial of heart rate characteristics monitoring. Survivors were evaluated at 18-22 months corrected age with a standardized neurologic examination and the Bayley Scales of Infant Development-III (BSID-III). NDI was defined as Gross Motor Function Classification System of >2 (moderate or severe cerebral palsy), BSID-III language or cognitive scores of <70, severe bilateral hearing impairment, and/or bilateral blindness. RESULTS: The composite outcome, death or NDI, was obtained for 628 of 884 study infants (72%). The prevalence of this outcome was 44.4% (136/306) among controls (infants randomized to heart rate characteristics monitored but not displayed) and 38.9% (125/322) among infants randomized to heart rate characteristics monitoring displayed (relative risk, 0.87; 95% CI, 0.73-1.05; P = .17). Mortality was reduced from 32.0% (99/307) among controls to 24.8% (81/326) among monitoring displayed infants (relative risk, 0.75; 95% CI, 0.59 to 0.97; P = .028). The composite outcomes of death or severe CP and death or mildly low Bayley cognitive score occurred less frequently in the displayed group (P < .05). CONCLUSIONS: We found no difference in the composite outcome of death or NDI for extremely preterm infants whose heart rate characteristics were and were not displayed during neonatal intensive care. Two outcomes that included mortality or a specific NDI were less frequent in the displayed group.

Correction: Oxygen desaturations in the early neonatal period predict development of bronchopulmonary dysplasia.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Correction: Recovery from bradycardia and desaturation events at 32 weeks corrected age and NICU length of stay: an indicator of physiologic resilience?

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Meningitis, urinary tract, and bloodstream infections in very low birth weight infants enrolled in a heart rate characteristics monitoring trial.

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.

Towards development of alert thresholds for clinical deterioration using continuous predictive analytics monitoring.

Patients who deteriorate while on the acute care ward and are emergently transferred to the Intensive Care Unit (ICU) experience high rates of mortality. To date, risk scores for clinical deterioration applied to the acute care wards rely on static or intermittent inputs of vital sign and assessment parameters. We propose the use of continuous predictive analytics monitoring, or data that relies on real-time physiologic monitoring data captured from ECG, documented vital signs, laboratory results, and other clinical assessments to predict clinical deterioration. A necessary step in translation to practice is understanding how an alert threshold would perform if applied to a continuous predictive analytic that was trained to detect clinical deterioration. The purpose of this study was to evaluate the positive predictive value of 'risk spikes', or large abrupt increases in the output of a statistical model of risk predicting clinical deterioration. We studied 8111 consecutive patient admissions to a cardiovascular medicine and surgery ward with continuous ECG data. We first trained a multivariable logistic regression model for emergent ICU transfer in a test set and tested the characteristics of the model in a validation set of 4059 patient admissions. Then, in a nested analysis we identified large, abrupt spikes in risk (increase by three units over the prior 6 h; a unit is the fold-increase in risk of ICU transfer in the next 24 h) and reviewed hospital records of 91 patients for clinical events such as emergent ICU transfer. We compared results to 59 control patients at times when they were matched for baseline risk including the National Warning Score (NEWS). There was a 3.4-fold higher event rate for patients with risk spikes (positive predictive value 24% compared to 7%, p = 0.006). If we were to use risk spikes as an alert, they would fire about once per day on a 73-bed acute care ward. Risk spikes that were primarily driven by respiratory changes (ECG-derived respiration (EDR) or charted respiratory rate) had highest PPV (30-35%) while risk spikes driven by heart rate had the lowest (7%). Alert thresholds derived from continuous predictive analytics monitoring are able to be operationalized as a degree of change from the person's own baseline rather than arbitrary threshold cut-points, which can likely better account for the individual's own inherent acuity levels. Point of care clinicians in the acute care ward settings need tailored alert strategies that promote a balance in recognition of clinical deterioration and assessment of the utility of the alert approach.

Oxygen desaturations in the early neonatal period predict development of bronchopulmonary dysplasia.

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 (SpO2 < 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 FiO2 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.

Recovery from bradycardia and desaturation events at 32 weeks corrected age and NICU length of stay: an indicator of physiologic resilience?

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 (SpO2 <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.

Predictive analytics in the pediatric intensive care unit for early identification of sepsis: capturing the context of age.

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.

Impact of predictive analytics based on continuous cardiorespiratory monitoring in a surgical and trauma intensive care unit.

Predictive analytics monitoring, the use of patient data to provide continuous risk estimation of deterioration, is a promising new application of big data analytical techniques to the care of individual patients. We tested the hypothesis that continuous display of novel electronic risk visualization of respiratory and cardiovascular events would impact intensive care unit (ICU) patient outcomes. In an adult tertiary care surgical trauma ICU, we displayed risk estimation visualizations on a large monitor, but in the medical ICU in the same institution we did not. The risk estimates were based solely on analysis of continuous cardiorespiratory monitoring. We examined 4275 individual patient records within a 7 month time period preceding and following data display. We determined cases of septic shock, emergency intubation, hemorrhage, and death to compare rates per patient care pre-and post-implementation. Following implementation, the incidence of septic shock fell by half (p < 0.01 in a multivariate model that included age and APACHE) in the surgical trauma ICU, where the data were continuously on display, but by only 10% (p = NS) in the control Medical ICU. There were no significant changes in the other outcomes. Display of a predictive analytics monitor based on continuous cardiorespiratory monitoring was followed by a reduction in the rate of septic shock, even when controlling for age and APACHE score.

Neonatal Intensive Care Unit Length of Stay Reduction by Heart Rate Characteristics Monitoring.

OBJECTIVE: To examine the effect of heart rate characteristics (HRC) monitoring on length of stay among very low birth weight (VLBW; <1500 g birth weight) neonates in the HeRO randomized controlled trial (RCT). STUDY DESIGN: We performed a retrospective analysis of length of stay metrics among 3 subpopulations (all patients, all survivors, and survivors with positive blood or urine cultures) enrolled in a multicenter, RCT of HRC monitoring. RESULTS: Among all patients in the RCT, infants randomized to receive HRC monitoring were more likely than controls to be discharged alive and prior to day 120 (83.6% vs 80.1%, P = .014). The postmenstrual age at discharge for survivors with positive blood or urine cultures was 3.2 days lower among infants randomized to receive HRC monitoring when compared with controls (P = .026). Although there were trends in other metrics toward reduced length of stay in HRC-monitored patients, none reached statistical significance. CONCLUSIONS: HRC monitoring is associated with reduced mortality in VLBW patients and a reduction in length of stay among infected surviving VLBW infants. TRIAL REGISTRATION: ClinicalTrials.gov: NCT00307333.

Cross-Correlation of Heart Rate and Oxygen Saturation in Very Low Birthweight Infants: Association with Apnea and Adverse Events.

BACKGROUND: Analysis of subtle vital sign changes could facilitate earlier treatment of acute inflammatory illnesses. We previously showed that high cross-correlation of heart rate and oxygen saturation (XCorr-HR-SpO2) occurs in some very low birthweight (VLBW) infants with sepsis, and hypothesized that this corresponds to apnea. METHODS: In 629 VLBW infants, we analyzed XCorr-HR-SpO2 in relation to central apnea with bradycardia and desaturation (ABD), BD with or without central apnea (BD), and percent time in periodic breathing (PB) throughout the neonatal intensive care unit (NICU) stay (75 infant-years). We reviewed 100 days with extremely high XCorr-HR-SpO2 (>0.7) and control days for clinical associations. Next, we identified all cases of late-onset septicemia (LOS) and necrotizing enterocolitis (NEC) and analyzed change in XCorr-HR-SpO2 before diagnosis. RESULTS: Mean XCorr-HR-SpO2 was ∼0.10, and increasing XCorr-HR-SpO2 was associated with increasing ABD, BD, and PB (correlation coefficients >0.93). Days with maximum XCorr-HR-SpO2 >0.7 were more likely to have an adverse event than control days (49% versus 13%). In 93 cases of LOS or NEC, there was a 67% increase in XCorr-HR-SpO2 in the 24-hour period prior to diagnosis compared with the previous day (p < 0.01). CONCLUSION: High XCorr-HR-SpO2 is associated with apnea and adverse events including LOS and NEC.

New-Onset Atrial Fibrillation in the Critically Ill.

OBJECTIVE: To determine the association of new-onset atrial fibrillation with outcomes, including ICU length of stay and survival. DESIGN: Retrospective cohort of ICU admissions. We found atrial fibrillation using automated detection (≥ 90 s in 30 min) and classed as new-onset if there was no prior diagnosis of atrial fibrillation. We identified determinants of new-onset atrial fibrillation and, using propensity matching, characterized its impact on outcomes. SETTING: Tertiary care academic center. PATIENTS: A total of 8,356 consecutive adult admissions to either the medical or surgical/trauma/burn ICU with available continuous electrocardiogram data. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: From 74 patient-years of every 15-minute observations, we detected atrial fibrillation in 1,610 admissions (19%), with median burden less than 2%. Most atrial fibrillation was paroxysmal; less than 2% of admissions were always in atrial fibrillation. New-onset atrial fibrillation was subclinical or went undocumented in 626, or 8% of all ICU admissions. Advanced age, acute respiratory failure, and sepsis were the strongest predictors of new-onset atrial fibrillation. In propensity-adjusted regression analyses, clinical new-onset atrial fibrillation was associated with increased hospital mortality (odds ratio, 1.63; 95% CI, 1.01-2.63) and longer length of stay (2.25 d; CI, 0.58-3.92). New-onset atrial fibrillation was not associated with survival after hospital discharge (hazard ratio, 0.99; 95% CI, 0.76-1.28 and hazard ratio, 1.11; 95% CI, 0.67-1.83, respectively, for subclinical and clinical new-onset atrial fibrillation). CONCLUSIONS: Automated analysis of continuous electrocardiogram heart rate dynamics detects new-onset atrial fibrillation in many ICU patients. Though often transient and frequently unrecognized, new-onset atrial fibrillation is associated with poor hospital outcomes.