Protocol of the sepsivit study: a prospective observational study to determine whether continuous heart rate variability measurement during the first 48 hours of hospitalisation provides an early warning for deterioration in patients presenting with infection or sepsis to the emergency department of a Dutch academic teaching hospital

Lipopolysaccharide-induced sepsis impairs M2R-GIRK signaling in the mouse sinoatrial node

Sepsis has emerged as a global health burden associated with multiple organ dysfunction and 20% mortality rate in patients. Numerous clinical studies over the past two decades have correlated the disease severity and mortality in septic patients with impaired heart rate variability (HRV), as a consequence of impaired chronotropic response of sinoatrial node (SAN) pacemaker activity to vagal/parasympathetic stimulation. However, the molecular mechanism(s) downstream to parasympathetic inputs have not been investigated yet in sepsis, particularly in the SAN. Based on electrocardiography, fluorescence Ca2+ imaging, electrophysiology, and protein assays from organ to subcellular level, we report that impaired muscarinic receptor subtype 2-G protein-activated inwardly-rectifying potassium channel (M2R-GIRK) signaling in a lipopolysaccharide-induced proxy septic mouse model plays a critical role in SAN pacemaking and HRV. The parasympathetic responses to a muscarinic agonist, namely IKACh activation in SAN cells, reduction in Ca2+ mobilization of SAN tissues, lowering of heart rate and increase in HRV, were profoundly attenuated upon lipopolysaccharide-induced sepsis. These functional alterations manifested as a direct consequence of reduced expression of key ion-channel components (GIRK1, GIRK4, and M2R) in the mouse SAN tissues and cells, which was further evident in the human right atrial appendages of septic patients and likely not mediated by the common proinflammatory cytokines elevated in sepsis.

Predicting deterioration of patients with early sepsis at the emergency department using continuous heart rate variability analysis: a model-based approach

BACKGROUND

Sepsis is a life-threatening disease with an in-hospital mortality rate of approximately 20%. Physicians at the emergency department (ED) have to estimate the risk of deterioration in the coming hours or days and decide whether the patient should be admitted to the general ward, ICU or can be discharged. Current risk stratification tools are based on measurements of vital parameters at a single timepoint. Here, we performed a time, frequency, and trend analysis on continuous electrocardiograms (ECG) at the ED to try and predict deterioration of septic patients.

METHODS

Patients were connected to a mobile bedside monitor that continuously recorded ECG waveforms from triage at the ED up to 48 h. Patients were post-hoc stratified into three groups depending on the development of organ dysfunction: no organ dysfunction, stable organ dysfunction or progressive organ dysfunction (i.e., deterioration). Patients with de novo organ dysfunction and those admitted to the ICU or died were also stratified to the group of progressive organ dysfunction. Heart rate variability (HRV) features over time were compared between the three groups.

RESULTS

In total 171 unique ED visits with suspected sepsis were included between January 2017 and December 2018. HRV features were calculated over 5-min time windows and summarized into 3-h intervals for analysis. For each interval, the mean and slope of each feature was calculated. Of all analyzed features, the average of the NN-interval, ultra-low frequency, very low frequency, low frequency and total power were different between the groups at multiple points in time.

CONCLUSIONS

We showed that continuous ECG recordings can be automatically analyzed and used to extract HRV features associated with clinical deterioration in sepsis. The predictive accuracy of our current model based on HRV features derived from the ECG only shows the potential of HRV measurements at the ED. Unlike other risk stratification tools employing multiple vital parameters this does not require manual calculation of the score and can be used on continuous data over time. Trial registration The protocol of this study is published by Quinten et al., 2017.

Prognostic value of serial score measurements of the national early warning score, the quick sequential organ failure assessment and the systemic inflammatory response syndrome to predict clinical outcome in early sepsis

BACKGROUND AND IMPORTANCE

Sepsis is a common and potentially lethal syndrome, and early recognition is critical to prevent deterioration. Yet, currently available scores to facilitate recognition of sepsis lack prognostic accuracy.

OBJECTIVE

To identify the optimal time-point to determine NEWS, qSOFA and SIRS for the prediction of clinical deterioration in early sepsis and to determine whether the change in these scores over time improves their prognostic accuracy.

DESIGN

Post hoc analysis of prospectively collected data.

SETTINGS AND PARTICIPANTS

This study was performed in the emergency department (ED) of a tertiary-care teaching hospital. Adult medical patients with (potential) sepsis were included.

OUTCOME MEASURES AND ANALYSIS

The primary outcome was clinical deterioration within 72 h after admission, defined as organ failure development, the composite outcome of ICU-admission and death. Secondary outcomes were the composite of ICU-admission/death and a rise in SOFA at least 2. Scores were calculated at the ED with 30-min intervals. ROC analyses were constructed to compare the prognostic accuracy of the scores.

RESULTS

In total, 1750 patients were included, of which 360 (20.6%) deteriorated and 79 (4.5%) went to the ICU or died within 72 h. The NEWS at triage (AUC, 0.62; 95% CI, 0.59-0.65) had a higher accuracy than qSOFA (AUC, 0.60; 95% CI, 0.56-0.63) and SIRS (AUC, 0.59; 95% CI, 0.56-0.63) for predicting deterioration. The AUC of the NEWS at 1 h (0.65; 95% CI, 0.63-0.69) and 150 min after triage (0.64; 95% CI, 0.61-0.68) was higher than the AUC of the NEWS at triage. The qSOFA had the highest AUC at 90 min after triage (0.62; 95% CI, 0.58-0.65), whereas the SIRS had the highest AUC at 60 min after triage (0.60; 95% CI, 0.56-0.63); both are not significantly different from triage. The NEWS had a better accuracy to predict ICU-admission/death <72 h compared with qSOFA (AUC difference, 0.092) and SIRS (AUC difference, 0.137). No differences were found for the prediction of a rise in SOFA at least 2 within 72 h between the scores. Patients with the largest improvement in any of the scores were more prone to deteriorate.

CONCLUSION

NEWS had a higher prognostic accuracy to predict deterioration compared with SIRS and qSOFA; the highest accuracy was reached at 1 h after triage.

Sepsis Mortality Prediction Using Wearable Monitoring in Low-Middle Income Countries

Sepsis is associated with high mortality-particularly in low-middle income countries (LMICs). Critical care management of sepsis is challenging in LMICs due to the lack of care providers and the high cost of bedside monitors. Recent advances in wearable sensor technology and machine learning (ML) models in healthcare promise to deliver new ways of digital monitoring integrated with automated decision systems to reduce the mortality risk in sepsis. In this study, firstly, we aim to assess the feasibility of using wearable sensors instead of traditional bedside monitors in the sepsis care management of hospital admitted patients, and secondly, to introduce automated prediction models for the mortality prediction of sepsis patients. To this end, we continuously monitored 50 sepsis patients for nearly 24 h after their admission to the Hospital for Tropical Diseases in Vietnam. We then compared the performance and interpretability of state-of-the-art ML models for the task of mortality prediction of sepsis using the heart rate variability (HRV) signal from wearable sensors and vital signs from bedside monitors. Our results show that all ML models trained on wearable data outperformed ML models trained on data gathered from the bedside monitors for the task of mortality prediction with the highest performance (area under the precision recall curve = 0.83) achieved using time-varying features of HRV and recurrent neural networks. Our results demonstrate that the integration of automated ML prediction models with wearable technology is well suited for helping clinicians who manage sepsis patients in LMICs to reduce the mortality risk of sepsis.

Wearable Patch Heart Rate Variability is An Early Marker of Systemic Inflammation During Experimental Human Endotoxemia

INTRODUCTION

Early diagnosis and treatment can reduce the risk of organ failure and mortality in systemic inflammatory conditions. Heart rate variability (HRV) has potential for early identification of the onset of systemic inflammation, as it may detect changes in sympathetic nervous system activity resulting from the developing inflammatory response before clinical signs appear. With the use of new methodologies, we investigated the onset and kinetics of HRV changes as well as several inflammatory parameters and symptoms during experimental human endotoxemia, a model of systemic inflammation in humans in vivo.

MATERIAL AND METHODS

Healthy volunteers were intravenously administered lipopolysaccharide (LPS, n = 15) or placebo (n = 15). HRV was determined using a wireless wearable device, and parameters low to high frequency (LF:HF) ratio, root mean square of the successive differences (RMSSD), and standard deviation of normal-to-normal R-R intervals (SDNN)were calculated through 1-min-rolling 6-minute windows. Plasma cytokine levels and flu-like symptoms and vital signs were serially assessed.

RESULTS

The increase in LF:HF ratio, reflecting sympathetic predominance, was more pronounced in the LPS group compared to the placebo group, with the difference becoming statistically significant 65 minutes following LPS administration (1.63 [1.42-1.83] vs. 1.28 [1.11-1.44], p = 0.005). Significant between-group differences in RMSSD and SDNN were observed from 127 and 140 minutes post-LPS administration onwards, respectively. Plasma cytokine levels showed significant between-group differences staring 60 minutes post-LPS. For symptom score, heart rate, temperature and diastolic blood pressure, significant differences compared with the placebo group were observed at 90, 118, 120, and 124 minutes post-LPS, respectively.

CONCLUSION

In a controlled human model of systemic inflammation, elevations in the LF:HF ratio followed very shortly after elevations in plasma cytokine levels and preceded onset of flu-like symptoms and alterations in vital signs. HRV may represent a promising non-invasive tool for early detection of a developing systemic inflammatory response.

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.

Combining quick sequential organ failure assessment score with heart rate variability may improve predictive ability for mortality in septic patients at the emergency department

Background

Although the quick Sequential Organ Failure Assessment (qSOFA) score was recently introduced to identify patients with suspected infection/sepsis, it has limitations as a predictive tool for adverse outcomes. We hypothesized that combining qSOFA score with heart rate variability (HRV) variables improves predictive ability for mortality in septic patients at the emergency department (ED).

Methods

This was a retrospective study using the electronic medical record of a tertiary care hospital in Singapore between September 2014 and February 2017. All patients aged 21 years or older who were suspected with infection/sepsis in the ED and received electrocardiography monitoring with ZOLL X Series Monitor (ZOLL Medical Corporation, Chelmsford, MA) were included. We fitted a logistic regression model to predict the 30-day mortality using one of the HRV variables selected from one of each three domains those previously reported as strong association with mortality (i.e. standard deviation of NN [SDNN], ratio of low frequency to high frequency power [LF/HF], detrended fluctuation analysis α-2 [DFA α-2]) in addition to the qSOFA score. The predictive accuracy was assessed with other scoring systems (i.e. qSOFA alone, National Early Warning Score, and Modified Early Warning Score) using the area under the receiver operating characteristic curve.

Results

A total of 343 septic patients were included. Non-survivors were significantly older (survivors vs. non-survivors, 65.7 vs. 72.9, p <0.01) and had higher qSOFA (0.8 vs. 1.4, p <0.01) as compared to survivors. There were significant differences in HRV variables between survivors and non-survivors including SDNN (23.7s vs. 31.8s, p = 0.02), LF/HF (2.8 vs. 1.5, p = 0.02), DFA α-2 (1.0 vs. 0.7, P < 0.01). Our prediction model using DFA-α-2 had the highest c-statistic of 0.76 (95% CI, 0.70 to 0.82), followed by qSOFA of 0.68 (95% CI, 0.62 to 0.75), National Early Warning Score at 0.67 (95% CI, 0.61 to 0.74), and Modified Early Warning Score at 0.59 (95% CI, 0.53 to 0.67).

Conclusions

Adding DFA-α-2 to the qSOFA score may improve the accuracy of predicting in-hospital mortality in septic patients who present to the ED. Further multicenter prospective studies are required to confirm our results.

Repeated vital sign measurements in the emergency department predict patient deterioration within 72 hours: a prospective observational study

BACKGROUND

More than one in five patients presenting to the emergency department (ED) with (suspected) infection or sepsis deteriorate within 72 h from admission. Surprisingly little is known about vital signs in relation to deterioration, especially in the ED. The aim of our study was to determine whether repeated vital sign measurements in the ED can differentiate between patients who will deteriorate within 72 h and patients who will not deteriorate.

METHODS

We performed a prospective observational study in patients presenting with (suspected) infection or sepsis to the ED of our tertiary care teaching hospital. Vital signs (heart rate, mean arterial pressure (MAP), respiratory rate and body temperature) were measured in 30-min intervals during the first 3 h in the ED. Primary outcome was patient deterioration within 72 h from admission, defined as the development of acute kidney injury, liver failure, respiratory failure, intensive care unit admission or in-hospital mortality. We performed a logistic regression analysis using a base model including age, gender and comorbidities. Thereafter, we performed separate logistic regression analyses for each vital sign using the value at admission, the change over time and its variability. For each analysis, the odds ratios (OR) and area under the receiver operator curve (AUC) were calculated.

RESULTS

In total 106 (29.5%) of the 359 patients deteriorated within 72 h from admission. Within this timeframe, 18.3% of the patients with infection and 32.9% of the patients with sepsis at ED presentation deteriorated. Associated with deterioration were: age (OR: 1.02), history of diabetes (OR: 1.90), heart rate (OR: 1.01), MAP (OR: 0.96) and respiratory rate (OR: 1.05) at admission, changes over time of MAP (OR: 1.04) and respiratory rate (OR: 1.44) as well as the variability of the MAP (OR: 1.06). Repeated measurements of heart rate and body temperature were not associated with deterioration.

CONCLUSIONS

Repeated vital sign measurements in the ED are better at identifying patients at risk for deterioration within 72 h from admission than single vital sign measurements at ED admission.

Role of complement C5a and histones in septic cardiomyopathy

Polymicrobial sepsis (after cecal ligation and puncture, CLP) causes robust complement activation with release of C5a. Many adverse events develop thereafter and will be discussed in this review article. Activation of complement system results in generation of C5a which interacts with its receptors (C5aR1, C5aR2). This leads to a series of harmful events, some of which are connected to the cardiomyopathy of sepsis, resulting in defective action potentials in cardiomyocytes (CMs), activation of the NLRP3 inflammasome in CMs and the appearance of extracellular histones, likely arising from activated neutrophils which form neutrophil extracellular traps (NETs). These events are associated with activation of mitogen-activated protein kinases (MAPKs) in CMs. The ensuing release of histones results in defective action potentials in CMs and reduced levels of [Ca²⁺]i-regulatory enzymes including sarco/endoplasmic reticulum Ca²⁺-ATPase (SERCA2) and Na⁺/Ca²⁺ exchanger (NCX) as well as Na⁺/K⁺-ATPase in CMs. There is also evidence that CLP causes release of IL-1β via activation of the NLRP3 inflammasome in CMs of septic hearts or in CMs incubated in vitro with C5a. Many of these events occur after in vivo or in vitro contact of CMs with histones. Together, these data emphasize the role of complement (C5a) and C5a receptors (C5aR1, C5aR2), as well as extracellular histones in events that lead to cardiac dysfunction of sepsis (septic cardiomyopathy).