Heart rate characteristic index monitoring for bloodstream infection in an NICU: a 3-year experience

Hemoglobin, Ferritin, and Lactate Dehydrogenase as Predictive Markers for Neonatal Sepsis

(1) Background: This study evaluates the predictive effectiveness of biomarkers in diagnosing newborn sepsis. (2) Methods: This was a case-control study conducted on neonates hospitalized at the Clinical Hospital "Louis Turcanu", Timisoara, Romania, from October 2018 to July 2023. Using a vacutainer collection device, venous blood was collected at admission for complete blood tests, including ferritin, hemoglobin, LDH, and blood culture analysis. Neonates were divided into two groups: sepsis-positive and sepsis-negative. The outcome of interest was a diagnosis of sepsis. (3) Results: Data from 86 neonates, 51 of whom had been confirmed to have sepsis, were analyzed. This study found no significant difference in gestational age, infant weight, fetal growth restriction, or APGAR score between neonates with and without sepsis. However, there was a higher incidence of sepsis among neonates delivered via cesarean section. Neonatal patients with sepsis showed significantly higher levels of neonatal serum ferritin and LDH compared to those without sepsis. Ferritin and LDH biomarkers demonstrated excellent discriminatory capabilities in diagnosing neonatal sepsis. Logistic regression analysis revealed a significant association between elevated ferritin and LDH levels and the likelihood of neonatal sepsis, while anemia did not show a significant association. (4) Conclusions: LDH and ferritin concentrations are found to be predictive biomarkers for neonatal sepsis, indicating a potential role in detecting susceptible neonates and implementing prompt interventions to improve patient outcomes.

Framework for Considering Abnormal Heart Rate Characteristics and Other Signs of Sepsis in Very Low Birth Weight Infants

OBJECTIVE

 A heart rate characteristics index (HeRO score), incorporating low variability and superimposed decelerations, was developed as a sepsis risk indicator for preterm infants in the neonatal intensive care unit (NICU). A rise in the risk score should prompt consideration of other clinical changes that may be signs of sepsis to decide whether a workup and antibiotics are needed. We aimed to develop a framework to systematically consider signs potentially indicating sepsis in very low birth weight (VLBW) infants.

STUDY DESIGN

 We developed easy-recall acronyms for 10 signs of sepsis in VLBW infants. Over 12 months in a level IV NICU, neonatology fellows completed a brief survey after each shift to document changes prompting sepsis workups. We analyzed associations between survey data, hourly heart rate characteristic data, and the diagnosis of the workup, grouped as culture-positive sepsis (CXSEP, positive blood or urine culture), clinical sepsis (CLINSEP, negative cultures treated with antibiotics ≥5 days), or sepsis ruled out (SRO, negative cultures and <3 days antibiotics).

RESULTS

 We analyzed 93 sepsis workups in 48 VLBW infants (35 CXSEP, 20 CLINSEP, and 38 SRO). The most frequently cited changes prompting the workups were heart rate patterns and respiratory deterioration, which were common in all three categories. Low blood pressure and poor perfusion were uncommonly cited but were more likely to be associated with CXSEP than the other signs. A rise in the HeRO score ≥1 from 0 to 12 hours before compared with 12to 72 hours prior the blood culture occurred in 31% of workups diagnosed as CXSEP, 16% CLINSEP, and 31% SRO.

CONCLUSION

 The HeRO score can alert clinicians to VLBW infants at high or increasing risk of a sepsis-like illness, but heart rate characteristic patterns are highly variable in individual babies. The easy-recall NeoSEP-10 framework can assist clinicians in considering other clinical changes when making decisions about sepsis workups and the duration of antibiotics.

KEY POINTS

· Abnormal heart rate characteristics can indicate sepsis or other pathologies in preterm infants.. · We developed a simple bedside tool to consider clinical signs potentially associated with sepsis.. · Considering vital sign trends together with clinical changes is a key to right-timing antibiotics..

The Relationship Between Blood Culture, C-reactive Protein, and Neonatal Sepsis: A Cross-Sectional Study

Background Sepsis is one of the most common causes of morbidity and mortality in newborns. Diagnosis of neonatal sepsis may be difficult because the clinical presentations are often nonspecific. Neonatal sepsis may have an early onset (zero to three days) or a late onset (four days or later). Onset is most rapid in premature neonates. In this study, we aimed to assess the correlation between positive cultures, high C-reactive protein (CRP) levels, and the diagnosis of neonatal sepsis. Methodology This descriptive, prospective, cross-sectional study was undertaken over four months starting from December 15, 2019, to April 15, 2020, in Atbara Teaching Hospital, Sudan. Data were collected from 71 patients. CRP levels were measured, and blood cultures were performed. Results High CRP level >10 mg/L was seen in patients having positive blood culture (55.3%), mainly in preterm babies (CRP >10 mg/dL (61.1%), positive culture (55.6%)) and very low birth weight babies (CRP >10 mg/dL (83.3%) and positive culture (67%)). Conclusions Our findings suggest that Klebsiella is an important cause of neonatal sepsis. CRP was positive in babies mainly with proven sepsis. There is a high correlation between CRP and blood culture in patients with neonatal sepsis which may give access to remodeling the prioritization of the management options in the clinical setting.

Association Between Hypoglycemia and the Occurrence of Early Onset Sepsis in Premature Infants

BACKGROUND

We examined the association between hypoglycemia and the occurrence of early onset sepsis (EOS) in premature infants admitted to the neonatal intensive care unit (NICU).

METHODS

We included infants discharged from 358 NICUs between 1997 and 2020 with gestational age <34 weeks, ≥1 culture collected in the first 3 days of life, and ≥1 serum glucose value recorded on the day of or day prior to culture collection. We used multivariable logistic regression and inverse probability weighting (IPW) and constructed models for three definitions of hypoglycemia: American Academy of Pediatrics (AAP), Pediatric Endocrine Society, and a definition based on neurodevelopmental studies. We performed subgroup analysis in EOS episodes caused by Gram-negative and Gram-positive organisms.

RESULTS

Of the 62,178 infants and 64,559 cultures that met study inclusion criteria, 739 (1%) cultures were positive. The median (25th, 75th percentile) glucose value was 75 mg/dL (50, 106) on the day of or day prior to a positive culture versus 70 mg/dL (50, 95) on the day of or day prior to a negative culture. We found that hypoglycemia was not associated with the occurrence of EOS for all organisms and Gram-positive organisms, whereas there was a small but significant association between the lower AAP glucose cutoff value and EOS due to Gram-negative organisms (logistic regression: risk difference [RD] 0.24% [95% CI, 0.01-0.47]; IPW: RD 0.22% [95% CI, 0.00-0.43]).

CONCLUSIONS

Hypoglycemia may be an early marker of EOS, particularly in episodes caused by Gram-negative organisms and when using a stricter definition of hypoglycemia.

Heart rate variability as a marker and predictor of inflammation, nosocomial infection, and sepsis - A systematic review

PURPOSE

The autonomic nervous system interacts with the immune system via the inflammatory response. Heart rate variability (HRV), a marker of autonomic activity, is associated with inflammation, and nosocomial infections/sepsis, and has clinical implications for the monitoring of at-risk patients. Due to the vagal tone's influence on anti-inflammatory immune response, this association may predominately be reflected by vagally-mediated HRV indices. However, HRV's predictive significance on inflammation/infection remains unclear.

METHODS

843 studies examining the associations/prognostic value of HRV indices on inflammation, and nosocomial infection/sepsis were screened in this systematic review. According to inclusion and exclusion criteria, 68 associative studies and 14 prediction studies were included.

RESULTS

HRV and pro-inflammatory state were consistently associated in healthy subjects and patient groups. Pro-inflammatory state was related to reduced total power HRV including vagally- and non-vagally-mediated HRV indices. Similar, compared to controls, HRV reductions were observed during nosocomial infections/sepsis. Only limited evidence supports the predictive value of HRV in the development of nosocomial infections/sepsis. Reduced very low frequency power HRV showed the highest predictive value in adults, even with different clinical conditions. In neonates, an increased heart rate characteristic score, combining reduced total power HRV, decreased complexity, and vagally-dominated asymmetry, predicted sepsis.

CONCLUSIONS

Pro-inflammatory state is related to an overall reduction in HRV rather than a singular reduction in vagally-mediated HRV indices, reflecting the complex autonomic-regulatory changes occurring during inflammation. The potential benefit of using continuous HRV monitoring for detecting nosocomial infection-related states, and the implications for clinical outcome, need further clarification.

Heart Rate Characteristics Monitoring for Late-Onset Sepsis in Preterm Infants: A Systematic Review

BACKGROUND

Early diagnosis of late-onset sepsis (LOS) and necrotizing enterocolitis (NEC) by monitoring heart rate characteristics (HRC) of preterm infants might reduce the risk of death and morbidities. We aimed to systematically assess the effects of HRC monitoring on death, LOS, and NEC.

METHODS

A systematic search was performed in MEDLINE, Embase, Cochrane Library, and Web of Science.

RESULTS

Fifteen papers were included in this review. Three of these papers reported results from the only identified randomized controlled trial (RCT). This RCT showed that HRC monitoring resulted in a small but significant reduction in mortality (absolute risk reduction 2.1% [95% confidence interval 0.01-4.14]) without any differences in neurodevelopmental impairment. The risk of bias was rated high due to performance and detection bias and failure to correct for multiple testing. Most diagnostic cohort studies showed high discriminating accuracy in predicting LOS but lacked sufficient quality and generalizability. No studies for the detection of NEC were identified.

CONCLUSION

Supported by multiple observational cohort studies, the RCT identified in this systematic review showed that HRC monitoring as an early warning system for LOS might reduce the risk of death in preterm infants. However, methodological weaknesses and limited generalizability do not justify implementation of HRC in clinical care. A large international RCT is warranted.

Vital sign-based detection of sepsis in neonates using machine learning

AIM

Sepsis is a leading cause of morbidity and mortality in neonates. Early diagnosis is key but difficult due to non-specific signs. We investigate the predictive value of machine learning-assisted analysis of non-invasive, high frequency monitoring data and demographic factors to detect neonatal sepsis.

METHODS

Single centre study, including a representative cohort of 325 infants (2866 hospitalisation days). Personalised event timelines including interventions and clinical findings were generated. Time-domain features from heart rate, respiratory rate and oxygen saturation values were calculated and demographic factors included. Sepsis prediction was performed using Naïve Bayes algorithm in a maximum a posteriori framework up to 24 h before clinical sepsis suspicion.

RESULTS

Twenty sepsis cases were identified. Combining multiple vital signs improved algorithm performance compared to heart rate characteristics alone. This enabled a prediction of sepsis with an area under the receiver operating characteristics curve of 0.82, up to 24 h before clinical sepsis suspicion. Moreover, 10 h prior to clinical suspicion, the risk of sepsis increased 150-fold.

CONCLUSION

The present algorithm using non-invasive patient data provides useful predictive value for neonatal sepsis detection. Machine learning-assisted algorithms are promising novel methods that could help individualise patient care and reduce morbidity and mortality.

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..

Novel approaches to capturing and using continuous cardiorespiratory physiological data in hospitalized children

Continuous cardiorespiratory physiological monitoring is a cornerstone of care in hospitalized children. The data generated by monitoring devices coupled with machine learning could transform the way we provide care. This scoping review summarizes existing evidence on novel approaches to continuous cardiorespiratory monitoring in hospitalized children. We aimed to identify opportunities for the development of monitoring technology and the use of machine learning to analyze continuous physiological data to improve the outcomes of hospitalized children. We included original research articles published on or after January 1, 2001, involving novel approaches to collect and use continuous cardiorespiratory physiological data in hospitalized children. OVID Medline, PubMed, and Embase databases were searched. We screened 2909 articles and performed full-text extraction of 105 articles. We identified 58 articles describing novel devices or approaches, which were generally small and single-center. In addition, we identified 47 articles that described the use of continuous physiological data in prediction models, but only 7 integrated multidimensional data (e.g., demographics, laboratory results). We identified three areas for development: (1) further validation of promising novel devices; (2) more studies of models integrating multidimensional data with continuous cardiorespiratory data; and (3) further dissemination, implementation, and validation of prediction models using continuous cardiorespiratory data. IMPACT: We performed a comprehensive scoping review of novel approaches to capture and use continuous cardiorespiratory physiological data for monitoring, diagnosis, providing care, and predicting events in hospitalized infants and children, from novel devices to machine learning-based prediction models. We identified three key areas for future development: (1) further validation of promising novel devices; (2) more studies of models integrating multidimensional data with continuous cardiorespiratory data; and (3) further dissemination, implementation, and validation of prediction models using cardiorespiratory data.

Monitoring of heart rate characteristics to detect neonatal sepsis

BACKGROUND

Monitoring of heart rate characteristics (HRC) index may improve outcomes of late-onset neonatal sepsis (LOS) through early detection. We aimed at describing the association between LOS and elevated HRC index.

METHODS

This single-center retrospective case-control study included neonates who presented with blood culture-proven hospital-acquired LOS. Controls were matched to cases (ratio 1:2) based on gestational age, postnatal age, and birthweight. We compared the highest HRC indexes in the 48 h preceding blood culture sampling in LOS cases to the highest HRC indexes at the same postnatal days in controls.

RESULTS

In 59 LOS cases and 123 controls, an HRC index > 2 was associated with LOS (OR 7.1, 95% CI 2.6-19.0). Sensitivity and specificity of an HRC index > 2 to predict LOS were 53% (32/59) and 79% (98/123). Sensitivity increased from 25% in infants born > 32 weeks to 76% in infants born < 28 weeks. Specificity decreased from 97% in infants > 32 weeks to 63% in those born < 28 weeks.

CONCLUSIONS

An increase of HRC index > 2 has a significant association with the diagnosis of LOS, supporting the use of HRC monitoring to assist early detection of LOS. Clinicians using HRC monitoring should be aware of its diagnostic accuracy and limitations in different gestational age groups.

IMPACT

There is a paucity of data regarding the predictive value of heart rate characteristics (HRC) monitoring for early diagnosis of late-onset neonatal sepsis (LOS) in daily clinical practice. Monitoring of heart rate characteristics provides valuable information to assist the early diagnosis of LOS across all gestational age groups. However, the strong influence of gestational age on positive and negative predictive values adds complexity to the interpretation of HRC indexes.

Using Temporal Data Mining on Patient Data for Clinical Decision Making in the Care of the Sick Newborn

BACKGROUND

In a neonatal intensive care unit, streaming healthcare data comes from many sources, but humans are unable to understand relationships between data variables. Data mining and analysis are just beginning to get utilized in critical care. We present a case study using electronic medical record data in the neonatal intensive care unit and explore possible avenues of advancement using temporal data analytics.

CASE PRESENTATION

Electronic medical record data were collected for physiological monitor data. Heart rate, respiratory rate, oxygen saturation and temperature data were retrospectively analyzed by temporal data mining. Three premature babies were selected and data de-identified. The first case of a urinary tract infection showed nursing ability to synthesize data streams coming from a patient. For the second case of necrotizing enterocolitis, Temporal-Data-Mining analysis of combinations of clinical events based on deviations from the mean showed specific heuristic biomarkers related to events before discovery of necrotizing enterocolitis. Specific sequences 6-event and 5-event in length were identified with nursing unease at clinical deterioration, which were 100- and 87-times unlikely to occur randomly with 99.5% confidence. No such sequences were found in the rest of the 37 days for the second case and entire 133 days of stay in the third case of an uneventful premature baby.

CONCLUSION

Temporal data mining is a possible clinical tool in providing useful information in the neonatal intensive care unit for diagnosis of adverse clinical occurrences such as necrotizing enterocolitis. There is the possibility of changing the clinical paradigm of episodic watchfulness to constant vigilance using real-time data gathering.

The principles of whole-hospital predictive analytics monitoring for clinical medicine originated in the neonatal ICU

In 2011, a multicenter group spearheaded at the University of Virginia demonstrated reduced mortality from real-time continuous cardiorespiratory monitoring in the neonatal ICU using what we now call Artificial Intelligence, Big Data, and Machine Learning. The large, randomized heart rate characteristics trial made real, for the first time that we know of, the promise that early detection of illness would allow earlier and more effective intervention and improved patient outcomes. Currently, though, we hear as much of failures as we do of successes in the rapidly growing field of predictive analytics monitoring that has followed. This Perspective aims to describe the principles of how we developed heart rate characteristics monitoring for neonatal sepsis and then applied them throughout adult ICU and hospital medicine. It primarily reflects the work since the 1990s of the University of Virginia group: the theme is that sudden and catastrophic deteriorations can be preceded by subclinical but measurable physiological changes apparent in the continuous cardiorespiratory monitoring and electronic health record.

MicroRNA as an Early Biomarker of Neonatal Sepsis

Sepsis is a major cause of lethality in neonatal intensive care units. Despite significant advances in neonatal care and growing scientific knowledge about the disease, 4 of every 10 infants born in developed countries and suffering from sepsis die or experience considerable disability, including substantial and permanent neurodevelopmental impairment. Pharmacological treatment strategies for neonatal sepsis remain limited and mainly based upon early initiation of antibiotics and supportive treatment. In this context, numerous clinical and serum-based markers have been evaluated for diagnosing sepsis and evaluating its severity and etiology. MicroRNAs (miRNAs) do not encode for proteins but regulate gene expression by inhibiting the translation or transcription of their target mRNAs. Recently, it was demonstrated in adult patients that miRNAs are released into the circulation and that the spectrum of circulating miRNAs is altered during various pathologic conditions, such as inflammation, infection, and sepsis. Here, we summarize current findings on the role of circulating miRNAs in the diagnosis and staging of neonatal sepsis. The conclusions point to substantial diagnostic potential, and several miRNAs have been validated independently by different teams, namely miR-16a, miR-16, miR-96-5p, miR-141, miR-181a, and miR-1184.

Knowledge gaps in late-onset neonatal sepsis in preterm neonates: a roadmap for future research

Late-onset neonatal sepsis (LONS) remains an important threat to the health of preterm neonates in the neonatal intensive care unit. Strategies to optimize care for preterm neonates with LONS are likely to improve survival and long-term neurocognitive outcomes. However, many important questions on how to improve the prevention, early detection, and therapy for LONS in preterm neonates remain unanswered. This review identifies important knowledge gaps in the management of LONS and describe possible methods and technologies that can be used to resolve these knowledge gaps. The availability of computational medicine and hypothesis-free-omics approaches give way to building bedside feedback tools to guide clinicians in personalized management of LONS. Despite advances in technology, implementation in clinical practice is largely lacking although such tools would help clinicians to optimize many aspects of the management of LONS. We outline which steps are needed to get possible research findings implemented on the neonatal intensive care unit and provide a roadmap for future research initiatives. IMPACT: This review identifies knowledge gaps in prevention, early detection, antibiotic, and additional therapy of late-onset neonatal sepsis in preterm neonates and provides a roadmap for future research efforts. Research opportunities are addressed, which could provide the means to fill knowledge gaps and the steps that need to be made before possible clinical use. Methods to personalize medicine and technologies feasible for bedside clinical use are described.

Introducing heart rate variability monitoring combined with biomarker screening into a level IV NICU: a prospective implementation study

The aim of this study was to investigate the association between the implementation of a local heart rate variability (HRV) monitoring guideline combined with determination of inflammatory biomarkers and mortality, measures of sepsis severity, frequency of sepsis testing, and antibiotic usage, among very preterm neonates. In January 2018, a guideline was implemented for early detection of late-onset neonatal sepsis using HRV monitoring combined with determination of inflammatory biomarkers. Data on all patients admitted with a gestational age at birth of < 32 weeks were reviewed in the period January 2016-June 2020 (n = 1,135; n = 515 pre-implementation, n = 620 post-implementation). Outcomes of interest were (sepsis-related) mortality, sepsis severity (neonatal sequential organ failure assessment (nSOFA)), sepsis testing, and antibiotic usage. Differences before and after implementation of the guideline were assessed using logistic and linear regression analysis for binary and continuous outcomes respectively. All analyses were adjusted for gestational age and sex. Mortality within 10 days of a sepsis episode occurred in 39 (10.3%) and 34 (7.6%) episodes in the pre- and post-implementation period respectively (P = 0.13). The nSOFA course during a sepsis episode was significantly lower in the post-implementation group (P = 0.01). We observed significantly more blood tests for determination of inflammatory biomarkers, but no statistically significant difference in number of blood cultures drawn and in antibiotic usage between the two periods.Conclusion: Implementing HRV monitoring with determination of inflammatory biomarkers might help identify patients with sepsis sooner, resulting in reduced sepsis severity, without an increased use of antibiotics or number of blood cultures.

Neonatal heart rate variability: a contemporary scoping review of analysis methods and clinical applications

BACKGROUND

Neonatal heart rate variability (HRV) is widely used as a research tool. However, HRV calculation methods are highly variable making it difficult for comparisons between studies.

OBJECTIVES

To describe the different types of investigations where neonatal HRV was used, study characteristics, and types of analyses performed.

ELIGIBILITY CRITERIA

Human neonates ≤1 month of corrected age.

SOURCES OF EVIDENCE

A protocol and search strategy of the literature was developed in collaboration with the McGill University Health Center's librarians and articles were obtained from searches in the Biosis, Cochrane, Embase, Medline and Web of Science databases published between 1 January 2000 and 1 July 2020.

CHARTING METHODS

A single reviewer screened for eligibility and data were extracted from the included articles. Information collected included the study characteristics and population, type of HRV analysis used (time domain, frequency domain, non-linear, heart rate characteristics (HRC) parameters) and clinical applications (physiological and pathological conditions, responses to various stimuli and outcome prediction).

RESULTS

Of the 286 articles included, 171 (60%) were small single centre studies (sample size <50) performed on term infants (n=136). There were 138 different types of investigations reported: physiological investigations (n=162), responses to various stimuli (n=136), pathological conditions (n=109) and outcome predictor (n=30). Frequency domain analyses were used in 210 articles (73%), followed by time domain (n=139), non-linear methods (n=74) or HRC analyses (n=25). Additionally, over 60 different measures of HRV were reported; in the frequency domain analyses alone there were 29 different ranges used for the low frequency band and 46 for the high frequency band.

CONCLUSIONS

Neonatal HRV has been used in diverse types of investigations with significant lack of consistency in analysis methods applied. Specific guidelines for HRV analyses in neonates are needed to allow for comparisons between studies.

Neonatal sepsis prediction through clinical decision support algorithms: A systematic review

AIM

To systematically summarise the current evidence of employing clinical decision support algorithms (CDSAs) using non-invasive parameters for sepsis prediction in neonates.

METHODS

A comprehensive search in PubMed, CENTRAL and EMBASE was conducted. Screening, data extraction and risk of bias were performed by two authors. The certainty of the evidence was assessed using GRADE.

PROSPERO ID

CRD42020205143.

RESULTS

After abstract and full-text screening, 36 studies comprising 18,096 infants were included. Most CDSAs evaluated heart rate (HR)-based parameters. Two publications derived from one randomised-controlled trial assessing HR characteristics reported significant reduction in 30-day septicaemia-related mortality. Thirty-four non-randomised studies found promising yet inconclusive results.

CONCLUSION

Heart rate-based parameters are reliable components of CDSAs for sepsis prediction, particularly in combination with additional vital signs and demographics. However, inconclusive evidence and limited standardisation restricts clinical implementation of CDSAs outside of a controlled research environment. Further experimentation and comparison of parameter combinations and testing of new CDSAs are warranted.

Development of a Heart Rate Variability Risk Score to Predict Organ Dysfunction and Death in Critically Ill Children

OBJECTIVES

Determine whether the Heart Rate Variability Dysfunction score, a novel age-normalized measure of autonomic nervous system dysregulation, is associated with the development of new or progressive multiple organ dysfunction syndrome or death in critically ill children.

DESIGN, SETTING, AND PATIENTS

This was a retrospective, observational cohort study from 2012 to 2018. Patients admitted to the PICU with at least 12 hours of continuous heart rate data available from bedside monitors during the first 24 hours of admission were included in the analysis.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Heart rate variability was measured using the integer heart rate variability, which is the sd of the heart rate sampled every 1 second over 5 consecutive minutes. The Heart Rate Variability Dysfunction score was derived from age-normalized values of integer heart rate variability and transformed, so that higher scores were indicative of lower integer heart rate variability and a proxy for worsening autonomic nervous system dysregulation. Heart Rate Variability Dysfunction score performance as a predictor of new or progressive multiple organ dysfunction syndrome and 28-day mortality were determined using the area under the receiver operating characteristic curve. Of the 7,223 patients who met inclusion criteria, 346 patients (4.8%) developed new or progressive multiple organ dysfunction syndrome, and 103 (1.4%) died by day 28. For every one-point increase in the median Heart Rate Variability Dysfunction score in the first 24 hours of admission, there was a 25% increase in the odds of new or progressive multiple organ dysfunction syndrome and a 51% increase in the odds of mortality. The median Heart Rate Variability Dysfunction score in the first 24 hours had an area under the receiver operating characteristic curve to discriminate new or progressive multiple organ dysfunction syndrome of 0.67 and to discriminate mortality of 0.80. These results were reproducible in a temporal validation cohort.

CONCLUSIONS

The Heart Rate Variability Dysfunction score, an age-adjusted proxy for autonomic nervous system dysregulation derived from bedside monitor data is independently associated with new or progressive multiple organ dysfunction syndrome and mortality in PICU patients. The Heart Rate Variability Dysfunction score could potentially be used as a single continuous physiologic biomarker or as part of a multivariable prediction model to increase awareness of at-risk patients and augment clinical decision-making.

Stratified Management for Bacterial Infections in Late Preterm and Term Neonates: Current Strategies and Future Opportunities Toward Precision Medicine

Bacterial infections remain a major cause of morbidity and mortality in the neonatal period. Therefore, many neonates, including late preterm and term neonates, are exposed to antibiotics in the first weeks of life. Data on the importance of inter-individual differences and disease signatures are accumulating. Differences that may potentially influence treatment requirement and success rate. However, currently, many neonates are treated following a "one size fits all" approach, based on general protocols and standard antibiotic treatment regimens. Precision medicine has emerged in the last years and is perceived as a new, holistic, way of stratifying patients based on large-scale data including patient characteristics and disease specific features. Specific to sepsis, differences in disease susceptibility, disease severity, immune response and pharmacokinetics and -dynamics can be used for the development of treatment algorithms helping clinicians decide when and how to treat a specific patient or a specific subpopulation. In this review, we highlight the current and future developments that could allow transition to a more precise manner of antibiotic treatment in late preterm and term neonates, and propose a research agenda toward precision medicine for neonatal bacterial infections.

Cardiorespiratory Alterations in a Newborn Ovine Model of Systemic Inflammation Induced by Lipopolysaccharide Injection

Although it is well known that neonatal sepsis can induce important alterations in cardiorespiratory control, their detailed early features and the mechanisms involved remain poorly understood. As a first step in resolving this issue, the main goal of this study was to characterize these alterations more extensively by setting up a full-term newborn lamb model of systemic inflammation using lipopolysaccharide (LPS) injection. Two 6-h polysomnographic recordings were performed on two consecutive days on eight full-term lambs: the first after an IV saline injection (control condition, CTRL); the second, after an IV injection of 2.5 μg/kg Escherichia coli LPS 0127:B8 (LPS condition). Rectal temperature, locomotor activity, state of alertness, arterial blood gases, respiratory frequency and heart rate, mean arterial blood pressure, apneas and cardiac decelerations, and heart-rate and respiratory-rate variability (HRV and RRV) were assessed. LPS injection decreased locomotor activity (p = 0.03) and active wakefulness (p = 0.01) compared to the CTRL. In addition, LPS injection led to a biphasic increase in rectal temperature (p = 0.01 at ∼30 and 180 min) and in respiratory frequency and heart rate (p = 0.0005 and 0.005, respectively), and to an increase in cardiac decelerations (p = 0.05). An overall decrease in HRV and RRV was also observed. Interestingly, the novel analysis of the representations of the horizontal and vertical visibility network yielded the most statistically significant alterations in HRV structure, suggesting its potential clinical importance for providing an earlier diagnosis of neonatal bacterial sepsis. A second goal was to assess whether the reflexivity of the autonomic nervous system was altered after LPS injection by studying the cardiorespiratory components of the laryngeal and pulmonary chemoreflexes. No difference was found. Lastly, preliminary results provide proof of principle that brainstem inflammation (increased IL-8 and TNF-α mRNA expression) can be shown 6 h after LPS injection. In conclusion, this full-term lamb model of systemic inflammation reproduces several important aspects of neonatal bacterial sepsis and paves the way for studies in preterm lambs aiming to assess both the effect of prematurity and the central neural mechanisms of cardiorespiratory control alterations observed during neonatal sepsis.

A narrative review of heart rate and variability in sepsis

Clinicians face challenges in the timely diagnosis and management of pediatric sepsis. Pediatric heart rate has been incorporated into early warning systems and studied as a predictor for critical illness. We aim to review: (I) the role of heart rate in pediatric warning systems and (II) the role of heart rate variability (HRV) in adult and neonatal sepsis, with a focus on its potential applications in pediatrics. We conducted a literature search for papers published up to December 2019 on the utility of heart rate and HRV analysis in the diagnosis and management of sepsis, using four medical databases: PubMed, Google Scholar, EMBASE and Web of Science. This review demonstrates that the clinical utility of pediatric heart rate in predicting clinical deterioration is limited by the lack of consensus among warning systems, consensus-based guidelines, and evidence-based studies as to what constitutes abnormal heart rate in the pediatric age group. Current studies demonstrate that abnormal heart rate itself does not adequately discriminate children with sepsis from those without. HRV analysis provides a quick and non-invasive method of assessment and can provide more information than traditional heart rate. HRV analysis has the potential to add value in identification and prognostication of adult and neonatal sepsis. With further studies to explore its role, HRV analysis has the potential to add to current tools in the diagnosis and prognosis of pediatric sepsis.

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.

Comparison of multiple cardiac signal acquisition technologies for heart rate variability analysis

Heart rate variability analysis is a recognized non-invasive tool that is used to assess autonomic nervous system regulation in various clinical settings and medical conditions. A wide variety of HRV analysis methods have been proposed, but they all require a certain number of cardiac beats intervals. There are many ways to record cardiac activity: electrocardiography, phonocardiography, plethysmocardiography, seismocardiography. However, the feasibility of performing HRV analysis with these technologies and particularly their ability to detect autonomic nervous system changes still has to be studied. In this study, we developed a technology allowing the simultaneous monitoring of electrocardiography, phonocardiography, seismocardiography, photoplethysmocardiography and piezoplethysmocardiography and investigated whether these sensors could be used for HRV analysis. We therefore tested the evolution of several HRV parameters computed from several sensors before, during and after a postural change. The main findings of our study is that even if most sensors were suitable for mean HR computation, some of them demonstrated limited agreement for several HRV analyses methods. We also demonstrated that piezoplethysmocardiography showed better agreement with ECG than other sensors for most HRV indexes.

Visual assessment of heart rate variability patterns associated with neonatal infection in preterm infants

Early identification of neonatal sepsis may help reduce morbidity. From Heart Rate Variability (HRV) visually assessed in preterm infants, eight of nine recordings in babies with positive blood cultures had low HRV and six infants without positive cultures had normal HRV. Straightforward HRV display could help identify infection in infants.

Machine learning models for early sepsis recognition in the neonatal intensive care unit using readily available electronic health record data

BACKGROUND

Rapid antibiotic administration is known to improve sepsis outcomes, however early diagnosis remains challenging due to complex presentation. Our objective was to develop a model using readily available electronic health record (EHR) data capable of recognizing infant sepsis at least 4 hours prior to clinical recognition.

METHODS AND FINDINGS

We performed a retrospective case control study of infants hospitalized ≥48 hours in the Neonatal Intensive Care Unit (NICU) at the Children's Hospital of Philadelphia between September 2014 and November 2017 who received at least one sepsis evaluation before 12 months of age. We considered two evaluation outcomes as cases: culture positive-positive blood culture for a known pathogen (110 evaluations); and clinically positive-negative cultures but antibiotics administered for ≥120 hours (265 evaluations). Case data was taken from the 44-hour window ending 4 hours prior to evaluation. We randomly sampled 1,100 44-hour windows of control data from all times ≥10 days removed from any evaluation. Model inputs consisted of up to 36 features derived from routine EHR data. Using 10-fold nested cross-validation, 8 machine learning models were trained to classify inputs as sepsis positive or negative. When tasked with discriminating culture positive cases from controls, 6 models achieved a mean area under the receiver operating characteristic (AUC) between 0.80-0.82 with no significant differences between them. Including both culture and clinically positive cases, the same 6 models achieved an AUC between 0.85-0.87, again with no significant differences.

CONCLUSIONS

Machine learning models can identify infants with sepsis in the NICU hours prior to clinical recognition. Learning curves indicate model improvement may be achieved with additional training examples. Additional input features may also improve performance. Further research is warranted to assess potential performance improvements and clinical efficacy in a prospective trial.

Rational Use of Antibiotics in Neonates: Still in Search of Tailored Tools

Rational medicine use in neonates implies the prescription and administration of age-appropriate drug formulations, selecting the most efficacious and safe dose, all based on accurate information on the drug and its indications in neonates. This review illustrates that important uncertainties still exist concerning the different aspects (when, what, how) of rational antibiotic use in neonates. Decisions when to prescribe antibiotics are still not based on robust decision tools. Choices (what) on empiric antibiotic regimens should depend on the anticipated pathogens, and the available information on the efficacy and safety of these drugs. Major progress has been made on how (beta-lactam antibiotics, aminoglycosides, vancomycin, route and duration) to dose. Progress to improve rational antibiotic use necessitates further understanding of neonatal pharmacology (short- and long-term safety, pharmacokinetics, duration and route) and the use of tailored tools and smarter practices (biomarkers, screening for colonization, and advanced therapeutic drug monitoring techniques). Implementation strategies should not only facilitate access to knowledge and guidelines, but should also consider the most effective strategies (‘skills’) and psychosocial aspects involved in the prescription process: we should be aware that both the decision not to prescribe as well as the decision to prescribe antibiotics is associated with risks and benefits.

The Effect of Complete Blood Count Timing on Lumbar Puncture Rates in Asymptomatic Infants Born to Mothers with Chorioamnionitis

Background

Maternal chorioamnionitis is a risk factor for sepsis but, often, these infants are asymptomatic at birth. Different markers for infections, such as the immature to total (I/T) white blood cell (WBC) ratio, are used to help determine which infants require lumbar punctures (LPs), in addition to blood cultures and antibiotics. The timing of when the complete blood count (CBC) is obtained may have some effect on the length of antibiotic treatment.

Aims

The purpose of this proof-of-concept study was to assess if obtaining a CBC at greater than four hours of life as compared to less than four hours of life has an impact on the incidence of LPs performed in asymptomatic, full-term infants undergoing evaluation for sepsis secondary to maternal chorioamnionitis.

Methods

We performed a retrospective study of full-term, asymptomatic infants admitted for sepsis evaluation secondary to maternal chorioamnionitis. Subjects were grouped based upon the timing of their initial CBC (early = < four hours of life or late = > four hours of life). The incidence of LPs, duration of antibiotic treatment, and length of hospitalization were compared between the groups.

Results

A total of 230 subjects were included in the study (early group = 124, late group = 106). Subjects in the late group underwent significantly fewer LPs than subjects in the early group, 5.7% vs. 22.6% (p<0.001). There was no difference in length of treatment or hospitalization.

Conclusions

Asymptomatic full-term infants undergoing evaluation for sepsis secondary to maternal chorioamnionitis are less likely to undergo an LP if their initial CBC is obtained at greater than four hours of life.

Emerging Technologies for Molecular Diagnosis of Sepsis

Rapid and accurate profiling of infection-causing pathogens remains a significant challenge in modern health care. Despite advances in molecular diagnostic techniques, blood culture analysis remains the gold standard for diagnosing sepsis. However, this method is too slow and cumbersome to significantly influence the initial management of patients. The swift initiation of precise and targeted antibiotic therapies depends on the ability of a sepsis diagnostic test to capture clinically relevant organisms along with antimicrobial resistance within 1 to 3 h. The administration of appropriate, narrow-spectrum antibiotics demands that such a test be extremely sensitive with a high negative predictive value. In addition, it should utilize small sample volumes and detect polymicrobial infections and contaminants. All of this must be accomplished with a platform that is easily integrated into the clinical workflow. In this review, we outline the limitations of routine blood culture testing and discuss how emerging sepsis technologies are converging on the characteristics of the ideal sepsis diagnostic test. We include seven molecular technologies that have been validated on clinical blood specimens or mock samples using human blood. In addition, we discuss advances in machine learning technologies that use electronic medical record data to provide contextual evaluation support for clinical decision-making.

Diagnostics for neonatal sepsis: current approaches and future directions

Progress has been made in the reduction of morbidity and mortality from neonatal sepsis. However, diagnosis continues to rely primarily on conventional microbiologic techniques, which can be inaccurate. The objective of this review is to provide the clinician with an overview of the current information available on diagnosing this condition. We review currently available diagnostic approaches for documenting neonatal sepsis and also describe novel approaches for diagnosing infection in neonates who are under development and investigation. Substantial progress has been made with molecular approaches and further development of non-culture-based methods offer promise. The potential ability to incorporate antimicrobial resistance gene testing in addition to pathogen identification may provide a venue to incorporate a predominantly molecular platform into a larger program of neonatal care.

Early-onset neonatal sepsis is associated with a high heart rate during automatically selected stationary periods

AIM

This study examined the heart rate variability characteristics associated with early-onset neonatal sepsis in a prospective, observational controlled study.

METHODS

Eligible patients were full-term neonates hospitalised with clinical signs that suggested early-onset sepsis and a C-reactive protein of >10 mg/L. Sepsis was considered proven in cases of symptomatic septicaemia, meningitis, pneumonia or enterocolitis. Heart rate variability parameters (n = 16) were assessed from five-, 15- and 30-minute stationary sequences automatically selected from electrocardiographic recordings performed at admission and compared with a control group using the U-test with post hoc Benjamini-Yekutieli correction. Stationary sequences corresponded to the periods with the lowest changes of heart rate variability over time.

RESULTS

A total of 40 full-term infants were enrolled, including 14 with proven sepsis. The mean duration of the cardiac cycle length was lower in the proven sepsis group than in the control group (n = 11), without other significant changes in heart rate variability parameters. These durations, measured in five-minute stationary periods, were 406 (367-433) ms in proven sepsis group versus 507 (463-522) ms in the control group (p < 0.05).

CONCLUSION

Early-onset neonatal sepsis was associated with a high mean heart rate measured during automatically selected stationary periods.

Current Research on the Epidemiology, Pathogenesis, and Management of Necrotizing Enterocolitis

Despite decades of research on necrotizing enterocolitis, we still do not fully understand the pathogenesis of the disease, or how to prevent or how to treat it. However, as a result of recent significant advances in the microbiology, molecular biology, and cell biology of the intestine of preterm infants and infants with necrotizing enterocolitis, there is some hope that research into this devastating disease will yield some important translation into effective prevention, more rapid diagnosis, and novel therapies.

Defining neonatal sepsis

PURPOSE OF REVIEW

Although infection rates have modestly decreased in the neonatal intensive care unit (NICU) as a result of ongoing quality improvement measures, neonatal sepsis remains a frequent and devastating problem among hospitalized preterm neonates. Despite multiple attempts to address this unmet need, there have been minimal advances in clinical management, outcomes, and accuracy of diagnostic testing options over the last 3 decades. One strong contributor to a lack of medical progress is a variable case definition of disease. The inability to agree on a precise definition greatly reduces the likelihood of aligning findings from epidemiologists, clinicians, and researchers, which, in turn, severely hinders progress toward improving outcomes.

RECENT FINDINGS

Pediatric consensus definitions for sepsis are not accurate in term infants and are not appropriate for preterm infants. In contrast to the defined multistage criteria for other devastating diseases encountered in the NICU (e.g., bronchopulmonary dysplasia), there is significant variability in the criteria used by investigators to substantiate the diagnosis of neonatal sepsis.

SUMMARY

The lack of an accepted consensus definition for neonatal sepsis impedes our efforts toward improved diagnostic and prognostic options, and accurate outcomes information for this vulnerable population.