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.

Heart rate and oxygen saturation patterns in very low birth weight infants with early onset sepsis and histologic chorioamnionitis.

BACKGROUND: Chorioamnionitis and early onset sepsis (EOS) in very low birth weight (VLBW,< 1500 g) infants may cause a systemic inflammatory response reflected in patterns of heart rate (HR) and oxygenation measured by pulse oximetry (SpO2). Identification of these patterns might inform decisions about duration of antibiotic therapy after birth. OBJECTIVE: Compare early HR and SpO2 patterns in VLBW infants with or without early onset sepsis (EOS) or histologic chorioamnionitis (HC). STUDY DESIGN: Retrospective study of placental pathology and HR and SpO2 in the first 72 h from birth in relation to EOS status for inborn VLBW NICU patients 2012-2019. RESULT: Among 362 VLBW infants with HR and SpO2 data available, clinical, or culture-positive EOS occurred in 91/362 (25%) and HC in 81/355 (22%). In univariate analysis, EOS was associated with higher mean HR, lower mean SpO2, and less negative skewness of HR in the first 3 days after birth. HC was associated with higher standard deviation and skewness of HR but no difference in SpO2. In multivariable modeling, significant risk factors for EOS were mean HR, gestational age, HC, mean SpO2, and skewness of SpO2. CONCLUSION: HR and SpO2 patterns differ shortly after birth in VLBW infants exposed to HC or with EOS, likely reflecting a systemic inflammatory response.

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

Objectives: Detection of changes in cardiorespiratory events, including apnea, periodic breathing, intermittent hypoxemia (IH), and bradycardia, may facilitate earlier detection of sepsis. Our objective was to examine the association of cardiorespiratory events with late-onset sepsis for extremely preterm infants (<29 weeks' gestational age (GA)) on versus off invasive mechanical ventilation. Study Design: Retrospective analysis of data from infants enrolled in Pre-Vent (ClinicalTrials.gov identifier NCT03174301), an observational study in five level IV neonatal intensive care units. Clinical data were analyzed for 737 infants (mean GA 26.4w, 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 >72h after birth and ≥5d 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 IH80 events 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 predicted sepsis with an AUC 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.

Inflammatory biomarkers and physiomarkers of late-onset sepsis and necrotizing enterocolitis in premature infants.

Background: Early diagnosis of late-onset sepsis (LOS) and necrotizing enterocolitis (NEC) in very low birth weight (VLBW, <1,500 g) infants is challenging due to non-specific clinical signs. Inflammatory biomarkers increase in response to infection, but non-infectious conditions also cause inflammation. Cardiorespiratory data contain physiological biomarkers, or physiomarkers, of sepsis that may be useful in combination with inflammatory hematologic biomarkers for sepsis diagnosis. Objectives: To determine whether inflammatory biomarkers measured at the time of LOS or NEC diagnosis differ from times without infection and whether biomarkers correlate with cardiorespiratory sepsis physiomarkers in VLBW infants. Methods: Remnant plasma sample collection from VLBW infants occurred with blood draws for routine laboratory testing and suspected sepsis. We analyzed 11 inflammatory biomarkers and a pulse oximetry sepsis warning score (POWS). We compared biomarker levels obtained at the time of gram-negative (GN) bacteremia or NEC, gram-positive (GP) bacteremia, negative blood cultures, and no suspected infection. Results: We analyzed 188 samples in 54 VLBW infants. Several biomarkers were increased at the time of GN LOS or NEC diagnosis compared with all other samples. POWS was higher in patients with LOS and correlated with five biomarkers. IL-6 had 78% specificity at 100% sensitivity to detect GN LOS or NEC and added information to POWS. Conclusions: Inflammatory plasma biomarkers discriminate sepsis due to GN bacteremia or NEC and correlate with cardiorespiratory physiomarkers.

Heart Rate Variability as a Prognostic Tool for Gastroschisis Infants in the Neonatal Intensive Critical Unit.

OBJECTIVE: Gastroschisis is the most common congenital abdominal wall defect, with an increasing incidence. It results in extrusion of abdominal contents with associated delayed intestinal motility. Abnormal heart rate characteristics (HRCs) such as decreased variability occur due to the inflammatory response to sepsis in preterm infants. This study aimed to test the hypothesis that infants with gastroschisis have decreased heart rate variability (HRV) after birth and that this physiomarker may predict outcomes. STUDY DESIGN: We analyzed heart rate data from and clinical variables for all infants admitted with gastroschisis from 2009 to 2020. RESULTS: Forty-seven infants were admitted during the study period and had available data. Complex gastroschisis infants had reduced HRV after birth. For those with sepsis and necrotizing enterocolitis, abnormal HRCs occurred early in the course of illness. CONCLUSION: Decreased HRV was associated with complex gastroschisis. Infants in this group experienced complications that prolonged time to full enteral feeding and time on total parenteral nutrition. KEY POINTS: · Infants with gastroschisis can be classified into two subcategories, simple and complex disease.. · Those with complex disease often require prolonged stays in the neonatal intensive care unit and costly hospitalizations. We hypothesized that infants with complex gastroschisis are more likely to have abnormal HRC due to intestinal inflammation.. · In this study, we identified associations between abnormal HRV, heart rate characteristicHRC, and the development of gastroschisis complications. Additionally, we described differences in clinical characteristics between infants with complex versus simple gastroschisis..

Transforming neonatal care with artificial intelligence: challenges, ethical consideration, and opportunities.

Artificial intelligence (AI) offers tremendous potential to transform neonatology through improved diagnostics, personalized treatments, and earlier prevention of complications. However, there are many challenges to address before AI is ready for clinical practice. This review defines key AI concepts and discusses ethical considerations and implicit biases associated with AI. Next we will review literature examples of AI already being explored in neonatology research and we will suggest future potentials for AI work. Examples discussed in this article include predicting outcomes such as sepsis, optimizing oxygen therapy, and image analysis to detect brain injury and retinopathy of prematurity. Realizing AI's potential necessitates collaboration between diverse stakeholders across the entire process of incorporating AI tools in the NICU to address testability, usability, bias, and transparency. With multi-center and multi-disciplinary collaboration, AI holds tremendous potential to transform the future of neonatology.

Inflammatory Biomarkers and Physiomarkers of Late-Onset Sepsis and Necrotizing Enterocolitis in Premature Infants.

Background: Early diagnosis of late-onset sepsis (LOS) and necrotizing enterocolitis (NEC) in VLBW (<1500g) infants is challenging due to non-specific clinical signs. Inflammatory biomarkers increase in response to infection, but non-infectious conditions also cause inflammation in premature infants. Physiomarkers of sepsis exist in cardiorespiratory data and may be useful in combination with biomarkers for early diagnosis. Objectives: To determine whether inflammatory biomarkers at LOS or NEC diagnosis differ from times without infection, and whether biomarkers correlate with a cardiorespiratory physiomarker score. Methods: We collected remnant plasma samples and clinical data from VLBW infants. Sample collection occurred with blood draws for routine laboratory testing and blood draws for suspected sepsis. We analyzed 11 inflammatory biomarkers and a continuous cardiorespiratory monitoring (POWS) score. We compared biomarkers at gram-negative (GN) bacteremia or NEC, gram-positive (GP) bacteremia, negative blood cultures, and routine samples. Results: We analyzed 188 samples in 54 VLBW infants. Biomarker levels varied widely, even at routine laboratory testing. Several biomarkers were increased at the time of GN LOS or NEC diagnosis compared with all other samples. POWS was higher in patients with LOS and correlated with five biomarkers. IL-6 had 78% specificity at 100% sensitivity to detect GN LOS or NEC and added information to POWS (AUC POWS = 0.610, POWS + IL-6 = 0.680). Conclusions: Inflammatory biomarkers discriminate sepsis due to GN bacteremia or NEC and correlate with cardiorespiratory physiomarkers. Baseline biomarkers did not differ from times of GP bacteremia diagnosis or negative blood cultures.

Neighborhood Deprivation and Association With Neonatal Intensive Care Unit Mortality and Morbidity for Extremely Premature Infants.

Importance: Socioeconomic status affects pregnancy and neurodevelopment, but its association with hospital outcomes among premature infants is unknown. The Area Deprivation Index (ADI) is a validated measure of neighborhood disadvantage that uses US Census Bureau data on income, educational level, employment, and housing quality. Objective: To determine whether ADI is associated with neonatal intensive care unit (NICU) mortality and morbidity in extremely premature infants. Design, Setting, and Participants: This retrospective cohort study was performed at 4 level IV NICUs in the US Northeast, Mid-Atlantic, Midwest, and South regions. Non-Hispanic White and Black infants with gestational age of less than 29 weeks and born between January 1, 2012, and December 31, 2020, were included in the analysis. Addresses were converted to census blocks, identified by Federal Information Processing Series codes, to link residences to national ADI percentiles. Exposures: ADI, race, birth weight, sex, and outborn status. Main Outcomes and Measures: In the primary outcome, the association between ADI and NICU mortality was analyzed using bayesian logistic regression adjusted for race, birth weight, outborn status, and sex. Risk factors were considered significant if the 95% credible intervals excluded zero. In the secondary outcome, the association between ADI and NICU morbidities, including late-onset sepsis, necrotizing enterocolitis (NEC), and severe intraventricular hemorrhage (IVH), were also analyzed. Results: A total of 2765 infants with a mean (SD) gestational age of 25.6 (1.7) weeks and mean (SD) birth weight of 805 (241) g were included in the analysis. Of these, 1391 (50.3%) were boys, 1325 (47.9%) reported Black maternal race, 498 (18.0%) died before NICU discharge, 692 (25.0%) developed sepsis or NEC, and 353 (12.8%) had severe IVH. In univariate analysis, higher median ADI was found among Black compared with White infants (77 [IQR, 45-93] vs 57 [IQR, 32-77]; P < .001), those who died before NICU discharge vs survived (71 [IQR, 45-89] vs 64 [IQR, 36-86]), those with late-onset sepsis or NEC vs those without (68 [IQR, 41-88] vs 64 [IQR, 35-86]), and those with severe IVH vs those without (69 [IQR, 44-90] vs 64 [IQR, 36-86]). In a multivariable bayesian logistic regression model, lower birth weight, higher ADI, and male sex were risk factors for mortality (95% credible intervals excluded zero), while Black race and outborn status were not. The ADI was also identified as a risk factor for sepsis or NEC and severe IVH. Conclusions and Relevance: The findings of this cohort study of extremely preterm infants admitted to 4 NICUs in different US geographic regions suggest that ADI was a risk factor for mortality and morbidity after adjusting for multiple covariates.

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.

Impact of race on heart rate characteristics monitoring in very low birth weight infants.

BACKGROUND: A multicenter RCT showed that displaying a heart rate characteristics index (HRCi) predicting late-onset sepsis reduced mortality for VLBW infants. We aimed to assess whether HRCi display had a differential impact for Black versus White infants. METHODS: We performed secondary data analysis of Black and White infants enrolled in the HeRO RCT. We evaluated the predictive performance of the HRCi for infants with Black or White maternal race. Using models adjusted for birth weight, we assessed outcomes and interventions for a race × randomization interaction. RESULTS: Among 2607 infants, Black infants had lower birth weight, gestational age, length of stay, and ventilator days, while sepsis and mortality were similar. The HRCi performed equally for sepsis prediction in Black and White infants. We found no differential effect of randomization by race on sepsis, mortality, antibiotic days, length of stay, or ventilator days. However, there was a differential randomization effect by race for blood cultures per patient: White RR 1.11 (95% CrI 1.04-1.18), Black RR 1.00 (0.93-1.07). CONCLUSIONS: The HRCi performed similarly for sepsis prediction in Black and White infants. Randomization to HRCi display increased blood cultures in White but not in Black infants, while the impact on other outcomes or interventions was similar. IMPACT: Predictive analytics, such as heart rate characteristics (HRC) monitoring for late-onset neonatal sepsis, should have equal impact among patients of different race. Infants with Black or White maternal race randomized to HRC display had similar outcomes, but randomization to the study arm increased a related clinical intervention, blood cultures, in White but not in Black infants. This study provides evidence of a differential effect of predictive models on clinical care by race. The work will promote consideration and analysis of equity in the implementation of predictive analytics.

Sepsis and Mortality Prediction in Very Low Birth Weight Infants: Analysis of HeRO and nSOFA.

OBJECTIVE: Scores to predict sepsis or define sepsis severity could improve care for very low birth weight (VLBW) infants. The heart rate characteristics (HRC) index (HeRO score) was developed as an early warning system for late-onset sepsis (LOS), and also rises before necrotizing enterocolitis (NEC). The neonatal sequential organ failure assessment (nSOFA) was developed to predict sepsis-associated mortality using respiratory, hemodynamic, and hematologic data. The aim of this study was to analyze the HRC index and nSOFA near blood cultures in VLBW infants relative to diagnosis and sepsis-associated mortality. STUDY DESIGN: Retrospective, single-center study of VLBW infants from 2011 to 2019. We analyzed HRC index and nSOFA around blood cultures diagnosed as LOS/NEC. In a subgroup of the cohort, we analyzed HRC and nSOFA near the first sepsis-like illness (SLI) or sepsis ruled-out (SRO) compared with LOS/NEC. We compared scores by diagnosis and mortality during treatment. RESULTS: We analyzed 179 LOS/NEC, 93 SLI, and 96 SRO blood culture events. In LOS/NEC, the HRC index increased before the blood culture, while nSOFA increased at the time of culture. Both scores were higher in nonsurvivors compared with survivors and in LOS/NEC compared with SRO. The nSOFA 12 hours after the time of blood culture predicted mortality during treatment better than any other time point analyzed (area under the curve 0.91). CONCLUSION: The HRC index provides earlier warning of imminent sepsis, whereas nSOFA after blood culture provides better prediction of mortality. KEY POINTS: · The HRC index and nSOFA provide complementary information on sepsis risk and sepsis-related mortality risk.. · This study adds to existing literature evaluating these risk scores independently by analyzing them together and in cases of not only proven but also suspected infections.. · The impact of combining risk models could be improved outcomes for premature infants..

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.

Implementation of a 24-hour empiric antibiotic duration for negative early-onset sepsis evaluations to reduce early antibiotic exposure in premature infants.

OBJECTIVE: Antibiotic exposure increases the risk of morbidity and mortality in premature infants. Many centers use at least 48 hours of antibiotics in the evaluation of early-onset sepsis (EOS, <72 hours after birth), yet most important pathogens grow within 24 hours. We investigated the safety and efficacy of reducing empiric antibiotic duration to 24 hours. DESIGN: Quality improvement study. SETTING: A tertiary-care neonatal intensive care unit. PATIENTS: Inborn infants <35 weeks gestational age at birth (ie, preterm) admitted January 2019 through December 2020. INTERVENTION: In December 2019, we changed the recommended duration of empiric antibiotics for negative EOS evaluations from 48 hours to 24 hours. RESULTS: Patient characteristics before and after the intervention were similar. After the intervention, 71 preterm infants (57%) with negative EOS evaluations received ≤24 hours of antibiotics, an increase from 15 (10%) before the intervention. These 71 infants comprised 77% of infants with negative EOS blood cultures after excluding those treated as clinical sepsis (≥5 days of antibiotics). For all negative EOS blood cultures, the mean treatment duration decreased by 0.5 days from 3.9 days to 3.4 days. This finding equated to 2.4 fewer antibiotic days per 100 patient days for negative EOS blood cultures but similar antibiotic days per 30 patient days (7.2 days vs 7.5 days). This measure did not change over time. Subsequent sepsis evaluations <7 days after a negative EOS blood culture did not increase. Excluding contaminants, the median time to positivity was 13.2 hours (range, 8-23) in 8 positive blood cultures. CONCLUSION: Implementation of a 24-hour antibiotic course for negative EOS evaluations safely reduced antibiotic exposure in 77% of infants <35 weeks gestational age at birth in whom EOS was ruled out. All clinically significant pathogens grew within 24 hours.

Artificial and human intelligence for early identification of neonatal sepsis.

Artificial intelligence may have a role in the early detection of sepsis in neonates. Machine learning can identify patterns that predict high or increasing risk for clinical deterioration from a sepsis-like illness. In developing this potential addition to NICU care, careful consideration should be given to the data and methods used to develop, validate, and evaluate prediction models. When an AI system alerts clinicians to a change in a patient's condition that warrants a bedside evaluation, human intelligence and experience come into play to determine an appropriate course of action: evaluate and treat or wait and watch closely. With intelligently developed, validated, and implemented AI sepsis systems, both clinicians and patients stand to benefit. IMPACT: This narrative review highlights the application of AI in neonatal sepsis prediction. It describes issues in clinical prediction model development specific to this population. This article reviews the methods, considerations, and literature on neonatal sepsis model development and validation. Challenges of AI technology and potential barriers to using sepsis AI systems in the NICU are discussed.

Evaluation of the Neonatal Sequential Organ Failure Assessment and Mortality Risk in Preterm Infants with Necrotizing Enterocolitis.

INTRODUCTION: The neonatal sequential organ failure assessment (nSOFA) score is a tool for calculating mortality risk of infants in the neonatal intensive care unit. The utility of the nSOFA in determining the risk of mortality or the association with surgical intervention among infants with necrotizing enterocolitis (NEC) has not been investigated. METHODS: We performed a retrospective, cohort study of preterm (<37 weeks) infants with NEC Bell's stage ≥ IIA at six hospitals from 2008 to 2020. An nSOFA score (range 0-15) was assigned to each patient at nine time points from 48 h before or after clinical illness was suspected. RESULTS: Of the 259 infants, nSOFA scores for infants who died (n = 39) or had the composite outcome of surgery or death (n = 114) were significantly higher (p < 0.05) early in the NEC course compared to nSOFA scores for infants who survived medical NEC. Twelve hours after evaluation, the area under the receiver operating characteristic curve was 0.87 (95% confidence interval [CI], 0.80-0.93) to discriminate for mortality and 0.84 (95% CI, 0.79-0.90) for surgery or death (p < 0.001). A maximum nSOFA score of ≥4 at -6, 0, 6, or 12 h following evaluation was associated with a 20-fold increase in mortality and 19-fold increase in surgery or death compared with a score of <4 (p < 0.001). CONCLUSION: In this multicenter cohort, the nSOFA score was able to discriminate well for death as well as surgery or death among infants with NEC. The nSOFA is a clinical research tool that may be used in infants with NEC to improve classification by objective quantification of organ dysfunction.

Major cardiorespiratory events do not increase after immunizations, eye exams, and other stressors in most very low birth weight infants.

BACKGROUND: Increased cardiorespiratory events with bradycardia and oxygen desaturation have been reported in very low birthweight (VLBW) infants following stressors such as immunizations. These events are difficult to quantify and may be mild. Our group developed an automated algorithm to analyze bedside monitor data from NICU patients for events with bradycardia and prolonged oxygen desaturation (BDs) and used this to compare BDs 24 hours before and after potentially stressful interventions. METHODS: We included VLBW infants from 2012-2017 with data available around at least one of four interventions: two-month immunizations, retinopathy of prematurity (ROP) examinations, ROP therapy, and inguinal hernia surgery. We used a validated algorithm to analyze electrocardiogram heart rate and pulse oximeter saturation data (HR, SpO2) to quantify BD events of HR < 100 beats/minute for≥4 seconds with oxygen desaturation < 80%SpO2 for≥10 seconds. BDs were analyzed 24 hours before and after interventions using Wilcoxon rank-sum tests. RESULTS: In 354 of 493 (72%) interventions, BD frequency stayed the same or decreased in the 24 hours after the event. An increase of at least five BD's occurred in 17/146 (12%) after immunizations, 85/290 (29%) after ROP examinations, 4/33 (12%) after ROP therapy, and 3/25 (12%) after hernia surgery. Infants with an increase in BDs after interventions had similar demographics compared to those without. More infants with an increase in BDs following immunizations were on CPAP or caffeine than those without. CONCLUSIONS: Most VLBW infants in our cohort had no increase in significant cardiorespiratory events in the 24 hours following potentially stressful interventions.

Individual illness dynamics: An analysis of children with sepsis admitted to the pediatric intensive care unit.

Illness dynamics and patterns of recovery may be essential features in understanding the critical illness course. We propose a method to characterize individual illness dynamics in patients who experienced sepsis in the pediatric intensive care unit. We defined illness states based on illness severity scores generated from a multi-variable prediction model. For each patient, we calculated transition probabilities to characterize movement among illness states. We calculated the Shannon entropy of the transition probabilities. Using the entropy parameter, we determined phenotypes of illness dynamics based on hierarchical clustering. We also examined the association between individual entropy scores and a composite variable of negative outcomes. Entropy-based clustering identified four illness dynamic phenotypes in a cohort of 164 intensive care unit admissions where at least one sepsis event occurred. Compared to the low-risk phenotype, the high-risk phenotype was defined by the highest entropy values and had the most ill patients as defined by a composite variable of negative outcomes. Entropy was significantly associated with the negative outcome composite variable in a regression analysis. Information-theoretical approaches to characterize illness trajectories offer a novel way of assessing the complexity of a course of illness. Characterizing illness dynamics with entropy offers additional information in conjunction with static assessments of illness severity. Additional attention is needed to test and incorporate novel measures representing the dynamics of illness.