Pediatric sepsis, a serious and potentially lethal condition, remains an important cause of morbidity and mortality (1). The World Health Organisation (WHO) estimates that 1.2 million children suffer from sepsis every year (2), and infections account for more than half of the deaths in children under 5 years old (3). While isolating the offending agent allows for definitive management, microbiological investigations usually take about 24–72 hours to return and are often influenced by factors including the adequacy of blood volume taken and the presence of low, transient bacteraemia (4,5). Therefore, early identification of patients with sepsis cannot rely on microbiology investigations alone (6); accurate prediction of which child has sepsis remains a clinical challenge.
The 2018 update to The Surviving Sepsis Campaign Bundle included an “hour-1 bundle” to be achieved within one hour from the time of triage in the Emergency Department (ED) (6). Clinicians need to be able to quickly identify a critically ill child and administer treatment protocols without definitive blood culture results. Many clinicians define pediatric sepsis based on the systemic inflammatory response syndrome (SIRS) criteria established by Goldstein in 2005 to identify a critically ill child with sepsis (7). However, the SIRS criteria has limited clinical applicability. A recent study showed that most children who fulfil the SIRS criteria do not require critical care, and many children who required resuscitation did not meet the SIRS criteria at the time of presentation (8). Moreover, identification of a septic child is often complicated by its heterogeneous clinical presentation, which can range from a non-specific presentation like fever, irritability, and poor feeding to fulminant sepsis with hemodynamic compromise (9).
The need for an objective assessment in pediatric critical illness has led to the use of vital signs. Vital signs have been and continue to be extensively studied as part of triage systems and warning scores (10-16). Scoring and triggering systems which include heart rate have been used to predict potential deterioration and the need for intensive care (17). Other investigators have attempted to define normal ranges for heart rate, built on the understanding that an abnormal heart rate is an important indicator of critical illness, including sepsis (18-20). As such, heart rate parameters are attractive to clinicians in that they can potentially add to the timely recognition of pediatric sepsis.
This review seeks to: (I) review the role of heart rate in pediatric warning scores, including its role as a predictor for critical illness including sepsis; and (II) introduce the concept of heart rate variability (HRV) analysis. In this review, we will highlight the current uses of HRV analysis (including in adult and neonatal sepsis) and explore how it can be utilized in pediatric sepsis. We present the following article in accordance with the Narrative Review reporting checklist (available at http://dx.doi.org/10.21037/atm-20-148).
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. Study selection was based on three medical databases, PubMed, EMBASE and Web of Science, with the following search strategy (including specific Medical Subject Headings, MeSH): “heart rate/physiology”, “sepsis/diagnosis”, “sepsis/mortality” and “sepsis/complications”. Other free text terms used were: “heart rate variability”, “emergency medical service”, “critical care”, “intensive care unit”, “neonate”, “infant” and “child”. Qualitative and quantitative data were extracted through interpretation of each article in cycles to avoid missing on data of potential value.
Heart rate as a predictor for critical illness including sepsis
Heart rate is an easily obtained parameter that many clinicians use as an early marker of deterioration in children. Various hospitals have developed pediatric early warning systems (PEWS) (10-13). A large systematic review of 66 studies of various PEWS and its derivatives demonstrated limited evidence of PEWS in identifying children with impending clinical deterioration (16). Of note, there was marked heterogeneity of outcome metrics, interventions, populations and clinical settings in the various studies (16). Categorical examples with their respective heart rate reference ranges can be found in Table S1, where we compare age-related thresholds for abnormal heart rate in selected PEWS scores to currently published heart rate guidelines and threshold limits used in large cross-sectional studies.
Although heart rate is a convenient and easily accessed physiological parameter, there is a lack of consensus among warning scores on what constitutes significant, out-of-proportion tachycardia in a sick child (Table S1). For instance, the normal heart rate of a 8-year-old child is between 80 to 120 bpm according to APLS guidelines, and PALS places the normal heart rate of a 8-year-old child at between 60 to 140 bpm (21,22).
There have been multiple attempts to define a normal heart rate range for different age groups in large and robust study populations (18-20). When one considers the normal ranges of heart rate based on these population studies, the heart rate ranges in various PEWS scores may not necessarily be representative of a “sick” child. This is especially so for PEWS scores that incorporate wide age bands. We know that with increasing age comes a steady decrease in heart rate. Consequently, these PEWS scores may result in false positive triggers (18-20). If implemented into monitoring systems, it can result in unnecessary resource utilisation, poor performance of scoring and triggering systems, and ultimately alarm fatigue (23). This creates a conundrum fundamental to the importance of heart rate as a vital component of prediction scores.
Tachycardia out of proportion to age and height of fever has also been proven not to have good discriminatory value in the prediction for infants with sepsis (24). Multiple contributors to tachycardia including pain, anxiety, and fever limit the interpretation of this important vital sign in children. It is recognized that continuously measured physiologic variables and their trends may better inform monitoring strategies for critically ill children with different admission diagnoses (including sepsis) (25).
The clinical value of traditional heart rate as a predictive tool is thus limited, and this has led to the exploration of novel methods such as HRV analysis.
Heart rate variability (HRV)
The study on measuring heart rate and rhythm has progressed from cardiac auscultation, the advent of the galvanometer (used to detect and measure small electric currents), to the era of digital signal processing systems such as the electrocardiogram (ECG). It was through the 1996 report of the Task Force of the European Society of Cardiology and The North American Society of Pacing and Electrophysiology that a novel method of HRV analysis was definitively introduced (26). HRV analyzes the oscillation in the interval between consecutive heart beats (RR interval), and is a measure of autonomic nervous system (ANS) regulation (27). ANS dysfunction is a maladaptive response in injury and critical illness, including sepsis (27). In the past few decades, more studies have delved into the relationship between HRV as a measure of ANS dysfunction, and various critical illnesses (26,28).
The three domains employed in HRV are the time-domain; frequency-domain; and the non-linear domain. Time-domain parameters are derived from measuring the normal “RR intervals”, otherwise known as “NN intervals”, or from the differences between NN intervals. In practice, these three measurements are often used interchangeably. Frequency-domain parameters measure how often a signal recurs within a specific frequency band, and this is derived from spectral analysis. Non-linear methods are a means to explain the complex interactions of HRV involving the hemodynamic, electrophysiological and humoral variables, and our autonomic and central nervous system (26). Many of these parameters are well-described in the report of the Task Force (26). Some of the parameters discussed in this report are listed in Table 1.
Current applications of HRV
The clinical applications of HRV analysis are well documented in the practice of adult cardiology. Reduced HRV in adults is predictive for sudden cardiac death (29-31), increased mortality after an acute myocardial infarction (26,32,33), and is deemed an independent risk factor for developing cardiovascular diseases (34,35). In recent years, as a risk stratification tool in chest pain, HRV has been consistently demonstrated to outperform commonly used validated scoring systems [e.g., thrombolysis in myocardial infarction (TIMI) score, patient acuity category scale (PACS), and the modified early warning score (MEWS)] (36,37). In diabetes mellitus, patients with diabetic autonomic neuropathy demonstrated a reduced low frequency/high frequency (LF/HF) ratio (38) and this reduction in variability preceded clinical symptoms of diabetic neuropathy (39,40). In anesthesiology, reduced HRV is also associated with the risk for developing hypotension following general anesthesia induction (41). In sepsis, HRV analysis has been studied in the adult and neonatal setting with promising results when compared to traditional heart rate alone. In the next two subsections, we will describe the use of HRV analysis in these settings and explore how these methods can be potentially applied in pediatrics.
In adult sepsis, HRV analysis has paved the way for the development of new scoring systems, such as the Singapore Emergency Department Sepsis (SEDS) model (42). The SEDS model, which includes HRV-derived parameters (mean NN and DFA alpha-2) and other parameters such as age, respiratory rate and systolic blood pressure, was shown to outperform the qSOFA score, MEWS and NEWS in predicting 30-day in-hospital mortality for adults with sepsis (42). This was followed by a subsequent study which outlined the high performance of a HRV-based machine learning model in predicting 30-day in-hospital mortality among suspected sepsis patient in the ED (43).
Specific HRV parameters to predict sepsis in the ED have also been explored. An increased square root of the mean of the sum of the squares of differences between adjacent NN intervals (RMSSD) was found in patients who developed septic shock within 6 hours of presentation at the ED (44). Reduced RMSSD has also been shown to predict for 28-day mortality in septic patients presenting at the ED (45). Some prior studies demonstrated that a decreased LF/HF ratio of less than 1.0 may predict severity of illness in septic patients (46,47). When integrated with various components of other warning scores, HRV parameters have been found to be superior in risk-stratifying septic patients at the ED (48). In the adult intensive care units (ICU), the use of artificial intelligence has allowed HRV parameters to be incorporated into systems and scores that detect sepsis and severe sepsis (49-51). Continuous HRV monitoring has reduced the gap between the onset of sepsis and its clinical recognition by up to five hours, allowing clinicians to direct early intervention efforts in sepsis treatment (52-54).
Given current research efforts, scoring systems incorporating HRV parameters may outperform those with traditional heart rate alone (Table 2). Short-term HRV analysis is a potential game-changer in better diagnostic accuracy for adult sepsis in the ED and ICUs and should be integrated with other vital signs obtained at triage for better performance (55,56). HRV remains a promising research field and there are ongoing studies that evaluate its utility as part of scoring systems (57).
Unlike pediatric and adult sepsis, there is still no commonly agreed definition for neonatal sepsis (58-60). Since continuous non-invasive cardiac monitoring is often standard procedure in the neonatal intensive care unit (NICU), studies have explored the use of HRV analysis as a diagnostic and prognostic tool for sepsis. Heart rate characteristic (HRC) index measures the degree of reduced variability and decelerations to determine the fold-increase in the risk of developing neonatal sepsis (61,62). The detection of sepsis by HRC index precedes clinician suspicion of sepsis (62-64). Studies have shown that HRC index monitoring in the NICU resulted in a reduction in mortality in very-low-birth-weight (VLBW) neonates, and its use as an independent tool in predicting for neonatal sepsis has been validated (62-65) (Table 3).
Looking at specific HRV parameters, time-domain indices such as NN50 count divided by the total number of all NN intervals (pNN50) was significantly decreased in neonates with sepsis as compared to healthy controls, while changes in frequency-domain indices such as very low frequency (VLF), LF, HF, and LF/HF ratio were statistically insignificant (66). However, another study showed that specific HRV parameters were not significantly modified following sepsis (67). As such, further studies are needed to determine the added value of HRV, and if time domain indices are truly more sensitive than frequency domain indices in predicting for neonatal sepsis.
HRV prediction in sepsis has been explored in the adults and neonates, but data on infants and children beyond the first month of life is very limited. An old PICU study of children with critical illness and injury demonstrated that HRV trends correlate with severity of illness and may have important clinical implications, but did not focus specifically on sepsis (28). ANS dysfunction in pediatric septic shock has been successfully demonstrated with HRV, but this has not translated into the use of HRV to guide clinical practice (68). In this small study of 7 children with septic shock, 6 children showed changes in the low/high frequency ratio and the authors postulate added value in using loss of HRV and complexity in monitoring these ill children (68). In another study of 22 children with known cardiovascular diseases, HRV changes may precede clinical diagnosis of sepsis by up to 24 hours (69).
Given the potential application demonstrated in adult and neonatal patients with sepsis, we postulate that HRV use can be expanded in the pediatric population. For example, HRV analysis can be investigated as a potential tool to identify septic children in the pediatric ED. Higher frequency data collection would allow the patient’s evolving clinical status to be more accurately captured (70). If proven to discriminate between children with sepsis and those without, it has the potential to add to the ED physician’s armamentarium on which child should have early cultures and urgent antibiotic administration, thus guiding resource utilisation.
Continuous HRV analysis, similar to those performed in the NICU, could also be explored in the PICU. Similar to the NICU septic population, a reduction in HRV could potentially precede clinical symptoms and signs of sepsis. New applications of HRV including predicting and prognosticating nosocomial and line-related sepsis in the critically ill PICU population should also be explored. The responsiveness of abnormal HRV parameters in successful treatment and resolving sepsis deserves further study. If promising, it may prove useful to guide clinicians in their monitoring and treatment strategy (28).
Limitations of HRV
Despite ongoing research efforts for the past century, HRV remains a relatively new concept to many. Before considering its use for pediatric sepsis, several limitations of HRV need to be taken into account. The current availability of ECG machines does not equate to the commercial availability of HRV analysis, and this may explain why HRV analysis has not been integrated into everyday use. There is often proprietary software and hardware requirements, with upfront cost barriers that need to be overcome. Training of personnel in data interpretation remains an issue, and healthcare professionals including doctors and nurses have to understand the principles of HRV analysis and how it may impact sepsis diagnosis and prognostication. In children specifically, artefacts need to be dealt with and post-processing capabilities are needed for meaningful analysis of HRV signals. In neonates, abnormal HRV can be affected by factors other than sepsis, such as gestational age and underlying medical conditions (71), and as such needs to be interpreted accordingly. Many prior studies have also excluded patients with cardiovascular diseases such as arrhythmias due to the lack of satisfactory RR intervals for analysis (36,37,42,43). This may potentially limit the generalisability to the wider population with a history of congenital and acquired cardiac disorders. The use of HRV in different settings can also result in undesirable effects on health services with an overall increase in interventions, hence impact on the wider healthcare setting must be evaluated before translation into practice (72). Most importantly, we acknowledge that the use of HRV has not been documented in pediatric sepsis, and the findings relating HRV to adult sepsis and neonatal sepsis may not apply similarly in this population. To establish definitive evidence, it is necessary to conduct similar studies in this setting.
When compared to traditional heart rate, HRV has been shown to value-add in the identification and prognostication of adults and neonates with sepsis. This exciting non-invasive tool could guide the recognition and management of pediatric sepsis and impact clinical practice.
Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at http://dx.doi.org/10.21037/atm-20-148
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Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/atm-20-148). JHL reports personal fees from KK Women’s and Children’s Hospital, outside the submitted work. The other authors have no conflicts of interest to declare.
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