Cardiac variability in critically ill adults: influence of sepsis

Exploration of simultaneous transients between cerebral hemodynamics and the autonomic nervous system using windowed time-lagged cross-correlation matrices: a CENTER-TBI study

BACKGROUND

Traumatic brain injury (TBI) can significantly disrupt autonomic nervous system (ANS) regulation, increasing the risk for secondary complications, hemodynamic instability, and adverse outcome. This retrospective study evaluated windowed time-lagged cross-correlation (WTLCC) matrices for describing cerebral hemodynamics-ANS interactions to predict outcome, enabling identifying high-risk patients who may benefit from enhanced monitoring to prevent complications.

METHODS

The first experiment aimed to predict short-term outcome using WTLCC-based convolution neural network models on the Wroclaw University Hospital (WUH) database (Ptraining = 31 with 1,079 matrices, Pval = 16 with 573 matrices). The second experiment predicted long-term outcome, training on the CENTER-TBI database (Ptraining = 100 with 17,062 matrices) and validating on WUH (Pval = 47 with 6,220 matrices). Cerebral hemodynamics was characterized using intracranial pressure (ICP), cerebral perfusion pressure (CPP), pressure reactivity index (PRx), while ANS metrics included low-to-high-frequency heart rate variability (LF/HF) and baroreflex sensitivity (BRS) over 72 h. Short-term outcome at WUH was assessed using the Glasgow Outcome Scale (GOS) at discharge. Long-term outcome was evaluated at 3 months at WUH and 6 months at CENTER-TBI using GOS and GOS-Extended, respectively. The XGBoost model was used to compare performance of WTLCC-based model and averaged neuromonitoring parameters, adjusted for age, Glasgow Coma Scale, major extracranial injury, and pupil reactivity in outcome prediction.

RESULTS

For short-term outcome prediction, the best-performing WTLCC-based model used ICP-LF/HF matrices. It had an area under the curve (AUC) of 0.80, vs. 0.71 for averages of ANS and cerebral hemodynamics metrics, adjusted for clinical metadata. For long-term outcome prediction, the best-score WTLCC-based model used ICP-LF/HF matrices. It had an AUC of 0.63, vs. 0.66 for adjusted neuromonitoring parameters.

CONCLUSIONS

Among all neuromonitoring parameters, ICP and LF/HF signals were the most effective in generating the WTLCC matrices. WTLCC-based model outperformed adjusted neuromonitoring parameters in short-term but had moderate utility in long-term outcome prediction.

Roadmap for the evolution of monitoring: developing and evaluating waveform-based variability-derived artificial intelligence-powered predictive clinical decision support software tools

BACKGROUND

Continuous waveform monitoring is standard-of-care for patients at risk for or with critically illness. Derived from waveforms, heart rate, respiratory rate and blood pressure variability contain useful diagnostic and prognostic information; and when combined with machine learning, can provide predictive indices relating to severity of illness and/or reduced physiologic reserve. Integration of predictive models into clinical decision support software (CDSS) tools represents a potential evolution of monitoring.

METHODS

We perform a review and analysis of the multidisciplinary steps required to develop and rigorously evaluate predictive clinical decision support tools based on monitoring.

RESULTS

Development and evaluation of waveform-based variability-derived predictive models involves a multistep, multidisciplinary approach. The stepwise processes involves data science (data collection, waveform processing, variability analysis, statistical analysis, machine learning, predictive modelling), CDSS development (iterative research prototype evolution to commercial tool), and clinical research (observational and interventional implementation studies, followed by feasibility then definitive randomized controlled trials), and poses unique challenges (including technical, analytical, psychological, regulatory and commercial).

CONCLUSIONS

The proposed roadmap provides guidance for the development and evaluation of novel predictive CDSS tools with potential to help transform monitoring and improve care.

Prognostic value of heart rate variability for risk of serious adverse events in continuously monitored hospital patients

Technological advances allow continuous vital sign monitoring at the general ward, but traditional vital signs alone may not predict serious adverse events (SAE). This study investigated continuous heart rate variability (HRV) monitoring's predictive value for SAEs in acute medical and major surgical patients. Data was collected from four prospective observational studies and two randomized controlled trials using a single-lead ECG. The primary outcome was any SAE, secondary outcomes included all-cause mortality and specific non-fatal SAE groups, all within 30 days. Subgroup analyses of medical and surgical patients were performed. The primary analysis compared the last 24 h preceding an SAE with the last 24 h of measurements in patients without an SAE. The area under a receiver operating characteristics curve (AUROC) quantified predictive performance, interpretated as low prognostic ability (0.5-0.7), moderate prognostic ability (0.7-0.9), or high prognostic ability (> 0.9). Of 1402 assessed patients, 923 were analysed, with 297 (32%) experiencing at least one SAE. The best performing threshold had an AUROC of 0.67 (95% confidence interval (CI) 0.63-0.71) for predicting cardiovascular SAEs. In the surgical subgroup, the best performing threshold had an AUROC of 0.70 (95% CI 0.60-0.81) for neurologic SAE prediction. In the medical subgroup, thresholds for all-cause mortality, cardiovascular, infectious, and neurologic SAEs had moderate prognostic ability, and the best performing threshold had an AUROC of 0.85 (95% CI 0.76-0.95) for predicting neurologic SAEs. Predicting SAEs based on the accumulated time below thresholds for individual continuously measured HRV parameters demonstrated overall low prognostic ability in high-risk hospitalized patients. Certain HRV thresholds had moderate prognostic ability for prediction of specific SAEs in the medical subgroup.

Amlexanox reduces new-onset atrial fibrillation risk in sepsis by downregulating S100A12: a Mendelian randomization study

Background

Sepsis is characterized by high morbidity and mortality rates, alongside limited therapeutic efficacy. Atrial fibrillation (AF), the most common arrhythmia, has been closely linked to sepsis in prior research. However, the specific mechanisms through which sepsis leads to new-onset AF remain poorly understood. This study focuses on identifying critical genes that are dysregulated in the development of new-onset AF within the context of sepsis, with the goal of uncovering new potential targets for its diagnosis and prevention.

Material and methods

Our study began by applying Mendelian Randomization (MR) to assess the causal link between sepsis and AF. We then sourced sepsis and AF datasets from the Gene expression Omnibus (GEO) database. Using Weighted Gene Co-expression Network Analysis (WGCNA), we pinpointed key modules and genes associated with both sepsis and AF conditions. Protein-protein interaction (PPI) network was constructed. The Transcriptional Regulatory Relationships Unravelled by Sentence-based Text-mining (TRRUST) database helped build the transcription factor (TF) interaction network. Key genes were scrutinized through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) to delve into their roles in new-onset AF's pathophysiology during sepsis. We employed the CIBERSORT algorithm to evaluate immune infiltration and the association between key genes and immune cells. The Connectivity Map (CMap) database facilitated the prediction of potential small molecule compounds targeting key genes. To culminate, an acute sepsis mouse model was developed to validate the implicated mechanisms of key genes involved in new-onset AF during sepsis, and to assess the prophylactic effectiveness of identified drug candidates.

Results

MR revealed potential independent risk factors for new-onset AF in sepsis. S100A12 was identified as a core interaction gene with elevated levels in sepsis and AF, underscoring its diagnostic and predictive significance. S100A12, along with associated genes, was mainly linked to immune and inflammatory response signaling pathways, correlating with immune cell levels. Targeting S100A12 identifies five potential small molecule therapeutics: amlexanox, balsalazide, methandriol, olopatadine, and tiboloe. In animal studies, acute sepsis increased S100A12 expression in serum and atrial tissues, correlating positively with inflammatory markers (IL-1β, IL-6, TNF-α) and negatively with heart rate, indicating a predisposition to AF. Early amlexanox administration can reduced S100A12 expression, dampened inflammation, and lessened new-onset AF risk in sepsis.

Conclusion

This study demonstrates that sepsis may independently increase the risk of new-onset AF. We identified S100A12 as a key gene influencing the new-onset AF in sepsis through immune regulation, presenting considerable diagnostic and predictive value. Notably, amlexanox, by targeting S100A12 emerges as the most clinical relevant intervention for managing new-onset AF in sepsis patients.

Autonomic Function and Baroreflex Control in COVID-19 Patients Admitted to the Intensive Care Unit

Background: Autonomic function and baroreflex control might influence the survival rate of coronavirus disease 2019 (COVID-19) patients admitted to the intensive care unit (ICU) compared to respiratory failure patients without COVID-19 (non-COVID-19). This study describes physiological control mechanisms in critically ill COVID-19 patients admitted to the ICU in comparison to non-COVID-19 individuals with the aim of improving stratification of mortality risk. Methods: We evaluated autonomic and baroreflex control markers extracted from heart period (HP) and systolic arterial pressure (SAP) variability acquired at rest in the supine position (REST) and during a modified head-up tilt (MHUT) in 17 COVID-19 patients (age: 63 ± 10 years, 14 men) and 33 non-COVID-19 patients (age: 60 ± 12 years, 23 men) during their ICU stays. Patients were categorized as survivors (SURVs) or non-survivors (non-SURVs). Results: We found that COVID-19 and non-COVID-19 populations exhibited similar vagal and sympathetic control markers; however, non-COVID-19 individuals featured a smaller baroreflex sensitivity and an unexpected reduction in the HP-SAP association during the MHUT compared to the COVID-19 group. Nevertheless, none of the markers of the autonomic and baroreflex functions could distinguish SURVs from non-SURVs in either population. Conclusions: We concluded that COVID-19 patients exhibited a more preserved baroreflex control compared to non-COVID-19 individuals, even though this information is ineffective in stratifying mortality risk.

Influence of blood lactate variations and passive exercise on cardiac responses

[Purpose] This study aimed to investigate cardiovascular responses, including heart rate (HR) and heart rate variability (HRV), to various hyperlactatemia-passive exercise interactions. [Participants and Methods] Nine healthy male participants performed upper limb passive cycling movement, and their HR and HRV were assessed while their blood lactate levels were manipulated by sustained handgrip exercise at control, 15% maximum voluntary contraction (MVC), and 30% MVC, followed by postexercise circulatory occlusion. [Results] HR and root mean squared standard difference (rMSSD) of HRV response remained constant at all blood lactate levels during passive exercise (HR: control, 75.8 ± 3.4 bpm; 15% MVC, 76.9 ± 2.7 bpm; and 30% MVC, 77.0 ± 3.7 bpm; rMSSD: control, 33.2 ± 6.9 ms; 15% MVC, 36.3 ± 7.3 ms; and 30% MVC, 37.3 ± 8.9 ms). [Conclusion] Manipulating metaboreflex activation did not significantly alter HR or HRV during passive exercise. These results suggest that, in healthy participants, the interactions between mechanical and metabolic stimuli do not affect HR and HRV responses, implying that passive exercise may be safely implemented.

COVID-19 surveillance based on consumer wearable devices

Background

Consumer wearable devices such as wristbands and smartwatches have potential application value in communicable disease surveillance.

Objective

We investigated the ability of wearable devices to monitor COVID-19 patients of varying severity.

Methods

COVID-19 patients with mobile phones supporting wearable device applications were selected from Dalian Sixth People Hospital. Physiological parameters from the wearable devices and electronic questionnaires were collected from the device wearing until 14 days post-discharge. Clinical information during hospitalization was also recorded. Based on imaging data, the patients were categorized into the milder group without pneumonia and the more severe group with pneumonia. We plotted the curves of the physiological parameters of the two groups to compare the differences and changes.

Results

Ninety-eight patients were included in the analysis. The mean age was 39.6 ± 10.5 years, including 45 males (45.9%). There were 24 asymptomatic patients, 10 mild patients, 60 moderate patients, and 4 severe patients. Compared with the milder group, the more severe group had higher heart rate-related parameters, while the heart rate variability (HRV) was the opposite. In the more severe group, the heart rate-related parameters showed a downward trend from 0 to 7 days after the fever resolution. Among them, the resting heart rate and sleep heart rate decreased on the 25th day after the onset and were close to the milder group 1 week after discharge.

Conclusions

Consumer wearable devices have the potential to monitor respiratory infections. Heart rate-related parameters obtained from these devices can be sensitive indicators of COVID-19 severity and correlate with disease evolution.

Trial registration

ClinicalTrials.gov NCT04459637.

Comparison of behavioral and physiological changes in postpartum healthy and inflammatory diseased cows

During parturition, cows often experience intense pain and stress, which increases the risk of inflammatory diseases. This study aimed to compare the postpartum health status between healthy cows and those diagnoses with inflammatory diseases by examining behavioral and heart rate (HR) variability (HRV) changes, to provide information before the onset of disease. Eight Holstein cows were used in this study. HR, parameters of HRV (low-frequency power: LF; high-frequency power: HF; LF/HF ratio, and total power) and time budget of individual maintenance behaviors (standing, recumbency, feeding, rumination while standing and lying, and sleep) were continuously recorded from 0 to 168 h postpartum. Milk and blood samples were collected daily. Cows were categorized as diseases based on the positive result of California mastitis test and/or serum haptoglobin concentration that exceeded 50 μg/ml after all blood samples have been collected. Compared to healthy individuals (n = 3), diseased cows (n = 5) exhibited higher HR, LF/HF, and lower total power (p < 0.05), suggesting the dominance of the sympathetic nervous system in cows with inflammatory diseases. Additionally, diseased cows showed an increased standing time budget and reduced recumbency (p < 0.05), which may be a behavioral strategy in response to discomfort from inflammation.

Prediction of episode of hemodynamic instability using an electrocardiogram based analytic: a retrospective cohort study

BACKGROUND

Predicting the onset of hemodynamic instability before it occurs remains a sought-after goal in acute and critical care medicine. Technologies that allow for this may assist clinicians in preventing episodes of hemodynamic instability (EHI). We tested a novel noninvasive technology, the Analytic for Hemodynamic Instability-Predictive Indicator (AHI-PI), which analyzes a single lead of electrocardiogram (ECG) and extracts heart rate variability and morphologic waveform features to predict an EHI prior to its occurrence.

METHODS

Retrospective cohort study at a quaternary care academic health system using data from hospitalized adult patients between August 2019 and April 2020 undergoing continuous ECG monitoring with intermittent noninvasive blood pressure (NIBP) or with continuous intraarterial pressure (IAP) monitoring.

RESULTS

AHI-PI's low and high-risk indications were compared with the presence of EHI in the future as indicated by vital signs (heart rate > 100 beats/min with a systolic blood pressure < 90 mmHg or a mean arterial blood pressure of < 70 mmHg). 4,633 patients were analyzed (3,961 undergoing NIBP monitoring, 672 with continuous IAP monitoring). 692 patients had an EHI (380 undergoing NIBP, 312 undergoing IAP). For IAP patients, the sensitivity and specificity of AHI-PI to predict EHI was 89.7% and 78.3% with a positive and negative predictive value of 33.7% and 98.4% respectively. For NIBP patients, AHI-PI had a sensitivity and specificity of 86.3% and 80.5% with a positive and negative predictive value of 11.7% and 99.5% respectively. Both groups performed with an AUC of 0.87. AHI-PI predicted EHI in both groups with a median lead time of 1.1 h (average lead time of 3.7 h for IAP group, 2.9 h for NIBP group).

CONCLUSIONS

AHI-PI predicted EHIs with high sensitivity and specificity and within clinically significant time windows that may allow for intervention. Performance was similar in patients undergoing NIBP and IAP monitoring.

CLINICAL, MOLECULAR, AND EXOSOMAL MECHANISMS OF CARDIAC AND BRAIN DYSFUNCTION IN SEPSIS

ABSTRACT

Sepsis is a complex disease resulting from a dysregulated inflammatory response to an infection. Initiation of sepsis occurs from a localized infection that disseminates to the bloodstream placing all organ systems at risk. Septic shock is classically observed to manifest itself as systemic hypotension with hyporesponsiveness to vasopressor agents. Myocardial dysfunction occurs resulting in an inability to perfuse major organ systems throughout the body. Most importantly, the brain is hypoperfused creating an ischemic and inflammatory state resulting in the clinical observation of acute mental status changes and cognitive dysfunction commonly known as sepsis-associated encephalopathy. This short review describes the inflammatory molecular mechanisms of myocardial dysfunction, discusses the evidence of the dual roles of the microglia resulting in blood-brain barrier disruption, and suggests that septic-derived exosomes, endosome-derived lipid bilayer spheroids released from living cells, influence cardiac and neurological cellular function.

Correlation between heart rate variability and cerebral autoregulation in septic patients

BACKGROUND

Heart rate variability (HRV) may provide an estimation of the autonomous nervous system (ANS) integrity in critically ill patients. Disturbances of cerebral autoregulation (CAR) may share common pathways of ANS dysfunction.

AIM

To explore whether changes in HRV and CAR index correlate in critically ill septic patients.

METHODS

Prospectively collected data on septic adult (> 18 years) patients admitted into a mixed Intensive Care between February 2016 and August 2019 with a recorded transcranial doppler CAR assessment. CAR was assessed calculating the Pearson's correlation coefficient (i.e. mean flow index, Mxa) between the left middle cerebral artery flow velocity (FV), insonated with a 2-MHz probe, and invasive blood pressure (BP) signal, both recorded simultaneously through a Doppler Box (DWL, Germany). MATLAB software was used for CAR assessment using a validated script; a Mxa >0.3 was considered as impaired CAR. HRV was assessed during the same time period using a specific software (Kubios HRV 3.2.0) and analyzed in both time-domain and frequency domain methods. Correlation between HRV-derived variables and Mxa were assessed using the Spearman's coefficient.

RESULTS

A total of 141 septic patients was studied; median Mxa was 0.35 [0.13-0.60], with 77 (54.6 %) patients having an impaired CAR. Mxa had a significant although weak correlation with HRV time domain (SDNN, r = 0.17, p = 0.04; RMSSD, r = 0.18, p = 0.03; NN50, r = 0.23, p = 0.006; pNN50, r = 0.23, p = 0.007), frequency domain (FFT-HF, r = 0.21; p = 0.01; AR-HF, r = 0.19; p = 0.02), and non-linear domain (SD1, r = 0.18, p = 0.03) parameters. Impaired CAR patients had also all of these HRV-derived parameters higher than those with intact CAR.

CONCLUSIONS

In this exploratory study, a potential association of ANS dysfunction and impaired CAR during sepsis was observed.

Detection of Hemodynamic Status Using an Analytic Based on an Electrocardiogram Lead Waveform

OBJECTIVES

Delayed identification of hemodynamic deterioration remains a persistent issue for in-hospital patient care. Clinicians continue to rely on vital signs associated with tachycardia and hypotension to identify hemodynamically unstable patients. A novel, noninvasive technology, the Analytic for Hemodynamic Instability (AHI), uses only the continuous electrocardiogram (ECG) signal from a typical hospital multiparameter telemetry monitor to monitor hemodynamics. The intent of this study was to determine if AHI is able to predict hemodynamic instability without the need for continuous direct measurement of blood pressure.

DESIGN

Retrospective cohort study.

SETTING

Single quaternary care academic health system in Michigan.

PATIENTS

Hospitalized adult patients between November 2019 and February 2020 undergoing continuous ECG and intra-arterial blood pressure monitoring in an intensive care setting.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

One million two hundred fifty-two thousand seven hundred forty-two 5-minute windows of the analytic output were analyzed from 597 consecutive adult patients. AHI outputs were compared with vital sign indications of hemodynamic instability (heart rate > 100 beats/min, systolic blood pressure < 90 mm Hg, and shock index of > 1) in the same window. The observed sensitivity and specificity of AHI were 96.9% and 79.0%, respectively, with an area under the curve (AUC) of 0.90 for heart rate and systolic blood pressure. For the shock index analysis, AHI's sensitivity was 72.0% and specificity was 80.3% with an AUC of 0.81.

CONCLUSIONS

The AHI-derived hemodynamic status appropriately detected the various gold standard indications of hemodynamic instability (hypotension, tachycardia and hypotension, and shock index > 1). AHI may provide continuous dynamic hemodynamic monitoring capabilities in patients who traditionally have intermittent static vital sign measurements.

Early heart rate variability evaluation enables to predict ICU patients' outcome

Heart rate variability (HRV) is a mean to evaluate cardiac effects of autonomic nervous system activity, and a relation between HRV and outcome has been proposed in various types of patients. We attempted to evaluate the best determinants of such variation in survival prediction using a physiological data-warehousing program. Plethysmogram tracings (PPG) were recorded at 75 Hz from the standard monitoring system, for a 2 h period, during the 24 h following ICU admission. Physiological data recording was associated with metadata collection. HRV was derived from PPG in either the temporal and non-linear domains. 540 consecutive patients were recorded. A lower LF/HF, SD2/SD1 ratios and Shannon entropy values on admission were associated with a higher ICU mortality. SpO2/FiO2 ratio and HRV parameters (LF/HF and Shannon entropy) were independent correlated with mortality in the multivariate analysis. Machine-learning using neural network (kNN) enabled to determine a simple decision tree combining the three best determinants (SDNN, Shannon Entropy, SD2/SD1 ratio) of a composite outcome index. HRV measured on admission enables to predict outcome in the ICU or at Day-28, independently of the admission diagnosis, treatment and mechanical ventilation requirement.

Trial registration: ClinicalTrials.gov identifier NCT02893462.

Detecting Pathogen Exposure During the Non-symptomatic Incubation Period Using Physiological Data: Proof of Concept in Non-human Primates

Background and Objectives: Early warning of bacterial and viral infection, prior to the development of overt clinical symptoms, allows not only for improved patient care and outcomes but also enables faster implementation of public health measures (patient isolation and contact tracing). Our primary objectives in this effort are 3-fold. First, we seek to determine the upper limits of early warning detection through physiological measurements. Second, we investigate whether the detected physiological response is specific to the pathogen. Third, we explore the feasibility of extending early warning detection with wearable devices. Research Methods: For the first objective, we developed a supervised random forest algorithm to detect pathogen exposure in the asymptomatic period prior to overt symptoms (fever). We used high-resolution physiological telemetry data (aortic blood pressure, intrathoracic pressure, electrocardiograms, and core temperature) from non-human primate animal models exposed to two viral pathogens: Ebola and Marburg (N = 20). Second, to determine reusability across different pathogens, we evaluated our algorithm against three independent physiological datasets from non-human primate models (N = 13) exposed to three different pathogens: Lassa and Nipah viruses and Y. pestis. For the third objective, we evaluated performance degradation when the algorithm was restricted to features derived from electrocardiogram (ECG) waveforms to emulate data from a non-invasive wearable device. Results: First, our cross-validated random forest classifier provides a mean early warning of 51 ± 12 h, with an area under the receiver-operating characteristic curve (AUC) of 0.93 ± 0.01. Second, our algorithm achieved comparable performance when applied to datasets from different pathogen exposures - a mean early warning of 51 ± 14 h and AUC of 0.95 ± 0.01. Last, with a degraded feature set derived solely from ECG, we observed minimal degradation - a mean early warning of 46 ± 14 h and AUC of 0.91 ± 0.001. Conclusion: Under controlled experimental conditions, physiological measurements can provide over 2 days of early warning with high AUC. Deviations in physiological signals following exposure to a pathogen are due to the underlying host's immunological response and are not specific to the pathogen. Pre-symptomatic detection is strong even when features are limited to ECG-derivatives, suggesting that this approach may translate to non-invasive wearable devices.

Autonomic biomarkers of shock in idiopathic systemic capillary leak syndrome

OBJECTIVE

The term Idiopathic Systemic Capillary Leak Syndrome (ISCLS) refers to an uncommon condition of severe distributive shock, resulting from an abrupt shift of fluids and proteins from the intravascular to the interstitial compartment. We hypothesise that the autonomic nervous system (ANS) fails in regulating the response to hypovolemia in acute ISCLS and that ANS variables characterise the progression to the recovery.

DESIGN

Prospective cohort study of patients admitted to ICU for severe ISCLS flares.

SETTING

Single, referral center in Italy for ISCLS.

PATIENTS

Analysis of cardiovascular signals recorded during seven severe ISCLS attacks and one prodromal period in five patients.

INTERVENTIONS

ANS was studied non-invasively by means of heart rate variability (HRV) and blood pressure variability analysis, as an estimation of vagal and sympathetic modulation directed to the heart and vessels. Heart rate and systolic arterial pressure (SAP) variability were also used to assess baroreflex sensitivity. ANS variables were measured during the subsequent phases which characterise ISCLS flares, namely the acute phase, the post-acute phase, and the recovery phase.

MEASUREMENTS AND MAIN RESULTS

HRV was severely depressed during the acute phase accounting for the loss of ANS modulation during massive capillary extravasation. This phase was characterised by shock and impaired baroreflex control, which allowed SAP to oscillate driven by respiratory activity. Impending shock and transition from shock to a post-acute phase were marked by change of baroreflex spectral variables. The baroreflex control was fully restored during recovery.

CONCLUSIONS

ANS modulation and baroreflex control are severely impaired during the acute haemodynamic instability which characterises ISCLS crises and their progressive restoration may be a clue of improvement. ANS indices during ISCLS flares might serve as useful biomarkers, able to timely announce the transition from one phase to the subsequent one, thus helping to adapt therapy accordingly.

The autonomic nervous system in septic shock and its role as a future therapeutic target: a narrative review

The autonomic nervous system (ANS) regulates the cardiovascular system. A growing body of experimental and clinical evidence confirms significant dysfunction of this regulation during sepsis and septic shock. Clinical guidelines do not currently include any evaluation of ANS function during the resuscitation phase of septic shock despite the fact that the severity and persistence of ANS dysfunction are correlated with worse clinical outcomes. In the critical care setting, the clinical use of ANS-related hemodynamic indices is currently limited to preliminary investigations trying to predict and anticipate imminent clinical deterioration. In this review, we discuss the evidence supporting the concept that, in septic shock, restoration of ANS-mediated control of the cardiovascular system or alleviation of the clinical consequences induced by its dysfunction (e.g., excessive tachycardia, etc.), may be an important therapeutic goal, in combination with traditional resuscitation targets. Recent studies, which have used standard and advanced monitoring methods and mathematical models to investigate the ANS-mediated mechanisms of physiological regulation, have shown the feasibility and importance of monitoring ANS hemodynamic indices at the bedside, based on the acquisition of simple signals, such as heart rate and arterial blood pressure fluctuations. During the early phase of septic shock, experimental and/or clinical studies have shown the efficacy of negative-chronotropic agents (i.e., beta-blockers or ivabradine) in controlling persistent tachycardia despite adequate resuscitation. Central α-2 agonists have been shown to prevent peripheral adrenergic receptor desensitization by reducing catecholamine exposure. Whether these new therapeutic approaches can safely improve clinical outcomes remains to be confirmed in larger clinical trials. New technological solutions are now available to non-invasively modulate ANS outflow, such as transcutaneous vagal stimulation, with initial pre-clinical studies showing promising results and paving the way for ANS modulation to be considered as a new potential therapeutic target in patients with septic shock.

Heart rate variability in dairy cows with postpartum fever during night phase

Autonomic nervous function evaluated by heart rate variability (HRV) and blood characteristics were compared between Holstein Friesian cows that developed postpartum fever (PF; n = 5) and clinically healthy (CH; n = 6) puerperal cows in this case-control study. A cow was defined as having PF when its rectal temperature rose to ≥39.5°C between 1 and 3 days postpartum. We recorded electrocardiograms during this period using a Holter-type electrocardiograph and applied power spectral analysis of HRV. Comparisons between the groups were analyzed by t test or Mann-Whitney U test, and the relationship between rectal temperature and each parameter was analyzed using multiple regression analysis. Heart rate was higher in PF cows than in CH cows (Mean ± SE, 103.3 ± 2.7 vs. 91.5 ± 1.7 bpm). This result suggested that PF cows had a relatively dominant sympathetic nervous function. Total (44,472 ± 2,301 vs. 55,373 ± 1,997 ms) and low frequency power (24.5 ± 3.8 vs. 39.9 ± 5.3 ms) were lower in PF cows than in CH cows. These findings were possibly caused by a reduction in autonomic nervous function. The total white blood cell count (54.3 ± 5.1 vs. 84.5 ± 6.4 ×10²/μL) and the serum magnesium (2.1 ± 0.1 vs. 2.4 ± 0.1 mg/dL) and iron (81.5 ± 8.0 vs. 134.4 ± 9.1 μg/dL) concentrations were lower and the serum amyloid A concentration (277 ± 33 vs. 149 ± 21 μg/mL) was higher in PF cows than in CH cows. These results imply that more inflammation was present in PF cows than in CH cows. Multiple regression analysis showed that both of low frequency power and concentration of serum iron were associated with rectal temperature. We found differences in changes in hematologic results, biochemical findings, and HRV patterns between PF cows and CH cows.

Depressed sympathovagal modulation indicates sepsis in patients with suspected infection

This study explored whether sympathovagal modulation assessed through frequency domains of heart rate variability (HRV) can indicate sepsis in patients with suspected infection.In total, 370 consecutive adult patients with suspected infection admitted to the emergency department were enrolled in this single-center cohort study. A continuous 10-minute electrocardiography for HRV analysis was recorded immediately for these patients after inclusion. Patients were stratified into non-sepsis and sepsis groups based on a sepsis-related organ failure assessment score of ≥2 that met the Third International Consensus Definitions for Sepsis. Seven frequency domains of HRV were compared between these 2 groups.Compared with the non-sepsis group (n = 98), the sepsis group (n = 272) had a significantly lower incidence of respiratory tract infection, higher total power, higher very-low-frequency component, higher high-frequency (HF) component, higher normalized HF component, lower normalized low-frequency (LF) component, and lower LF component/HF component ratio (LF/HF). Multiple logistic regression model identified HF component (odds ratio [OR] = 0.994; 95% confidence interval [CI], 0.990-0.999) and LF/HF (OR = 0.494; 95% CI, 0.423-0.578) as significant variables associated with sepsis. The area under receiver operating characteristic curves of HF component and LF/HF was 0.741 (95% CI, 0.685-0.797) and 0.930 (95% CI, 0.900-0.960), respectively, in identifying sepsis in patients with suspected infection.Tilted sympathovagal balance toward increased vagal activity and depressed sympathetic modulation, assessed by the HF component and LF/HF, may indicate sepsis in patients with suspected infection.

Wharton's jelly-derived mesenchymal stem cells attenuate sepsis-induced organ injury partially via cholinergic anti-inflammatory pathway activation

Sepsis induces organ dysfunction due to overexpression of the inflammatory host response, resulting in cardiopulmonary and autonomic dysfunction, thus increasing the associated morbidity and mortality. Wharton's jelly-derived mesenchymal stem cells (WJ-MSCs) express genes and secrete factors with anti-inflammatory properties, neurological and immunological protection, as well as improve survival in experimental sepsis. The cholinergic anti-inflammatory pathway (CAP) is mediated by α7-nicotinic acetylcholine receptors (α7nAChRs), which play an important role in the control of systemic inflammation. We hypothesized that WJ-MSCs attenuate sepsis-induced organ injury in the presence of an activated CAP pathway. To confirm our hypothesis, we evaluated the effects of WJ-MSCs as a treatment for cardiopulmonary injury and on neuroimmunomodulation. Male Wistar rats were randomly divided into four groups: control (sham-operated); cecal ligation and puncture (CLP) alone; CLP+WJ-MSCs (1 × 10⁶ cells, at 6 h post-CLP); and CLP+methyllycaconitine (MLA)+WJ-MSCs (5 mg/kg body wt, at 5.5 h post-CLP, and 1 × 10⁶ cells, at 6 h post-CLP, respectively). All experiments, including the assessment of echocardiographic parameters and heart rate variability, were performed 24 h after CLP. WJ-MSC treatment attenuated diastolic dysfunction and restored baroreflex sensitivity. WJ-MSCs also increased cardiac sympathetic and cardiovagal activity. WJ-MSCs reduced leukocyte infiltration and proinflammatory cytokines, effects that were abolished by administration of a selective α7nAChR antagonist (MLA). In addition, WJ-MSC treatment also diminished apoptosis in the lungs and spleen. In cardiac and splenic tissue, WJ-MSCs downregulated α7nAChR expression, as well as reduced the phospho-STAT3-to-total STAT3 ratio in the spleen. WJ-MSCs appear to protect against sepsis-induced organ injury by reducing systemic inflammation, at least in part, via a mechanism that is dependent on an activated CAP.

Serum glial fibrillary acidic protein and ubiquitin C-terminal hydrolase-L1 for diagnosis of sepsis-associated encephalopathy and outcome prognostication

PURPOSE

We investigated the role of serum Glial Fibrillary Acidic Protein (GFAP) and Ubiquitin C-Terminal Hydrolase-L1 (UCH-L1) in diagnosis of sepsis-associated encephalopathy(SAE), predicting prognosis and long-term quality of life with patients of sepsis.

MATERIALS AND METHODS

This is a prospective single center study entailed 105 patients whosuffered from sepsis from Jan 2015 to Aug 2016. Serum concentrations of GFAP and UCH-L1 for diagnosis of SAE and predicting prognosis and long-term quality of life with patients of sepsis were analyzed.

RESULTS

The serum concentrations of GFAP and UCH-L1 were higher in SAE group than in no-SAE group (p < .001). GFAP and UCH-L1 produced an AUC of 0.824 and 0.812 respectively for diagnosis of SAE with optimal cut-off values 0.532 ng/ml and 7.72 ng/ml respectively. The optimal cut-off values of GFAP and UCH-L1 to distinguish patients with survivors from non-survivors were 0.536 ng/ml and 8.06 ng/ml with an area under the curve of 0.773 and 0.746. Patients with a higher GFAP levels had worse long-term usual activities and patients with a higher UCH-L1 levels had more long-term pain (P = .026).

CONCLUSIONS

Serum concentrations GFAP and UCH-L1 early elevated and associated with sepsis-associated encephalopathy, poor prognosis and quality of life.

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.

Cerebral Autoregulation-Guided Optimal Blood Pressure in Sepsis-Associated Encephalopathy: A Case Series

BACKGROUND

Impaired cerebral autoregulation and cerebral hypoperfusion may play a critical role in the high morbidity and mortality in patients with sepsis-associated encephalopathy (SAE). Bedside assessment of cerebral autoregulation may help individualize hemodynamic targets that optimize brain perfusion. We hypothesize that near-infrared spectroscopy (NIRS)-derived cerebral oximetry can identify blood pressure ranges that enhance autoregulation in patients with SAE and that disturbances in autoregulation are associated with severity of encephalopathy.

METHODS

Adult patients with acute encephalopathy directly attributable to sepsis were followed using NIRS-based multimodal monitoring for 12 consecutive hours. We used the correlation in time between regional cerebral oxygen saturation and mean arterial pressure (MAP) to determine the cerebral oximetry index (COx) as a measure of cerebral autoregulation. Autoregulation curves were constructed for each patient with averaged COx values sorted by MAP in 3 sequential 4-hour periods; the optimal pressure (MAP_OPT), defined as the MAP associated with most robust autoregulation (lowest COx), was identified in each period. Severity of encephalopathy was measured with Glasgow coma scale (GCS).

RESULTS

Six patients with extracranial sepsis met the stringent criteria specified, including no pharmacological sedation or neurologic premorbidity. Optimal MAP was identified in all patients and ranged from 55 to 115 mmHg. Additionally, MAP_OPT varied within individual patients over time during monitoring. Disturbed autoregulation, based on COx, was associated with worse neurologic status (GCS < 13) both with and without controlling for age and severity of sepsis (adjusted odds ratio [OR]: 2.11; 95% confidence interval [CI]: 1.77-2.52; P < .001; OR: 2.97; 95% CI: 1.63-5.43; P < .001).

CONCLUSIONS

In this high-fidelity group of patients with SAE, continuous, NIRS-based monitoring can identify blood pressure ranges that improve autoregulation. This is important given the association between cerebral autoregulatory function and severity of encephalopathy. Individualizing blood pressure goals using bedside autoregulation monitoring may better preserve cerebral perfusion in SAE than current practice.

Autonomic Nervous System Dysfunction in Pediatric Sepsis

The autonomic nervous system (ANS) plays a major role in maintaining homeostasis through key adaptive responses to stress, including severe infections and sepsis. The ANS-mediated processes most relevant during sepsis include regulation of cardiac output and vascular tone, control of breathing and airway resistance, inflammation and immune modulation, gastrointestinal motility and digestion, and regulation of body temperature. ANS dysfunction (ANSD) represents an imbalanced or maladaptive response to injury and is prevalent in pediatric sepsis. Most of the evidence on ANSD comes from studies of heart rate variability, which is a marker of ANS function and is inversely correlated with organ dysfunction and mortality. In addition, there is evidence that other measures of ANSD, such as respiratory rate variability, skin thermoregulation, and baroreflex and chemoreflex sensitivity, are associated with outcomes in critical illness. The relevance of understanding ANSD in the context of pediatric sepsis stems from the fact that it might play an important role in the pathophysiology of sepsis, is associated with outcomes, and can be measured continuously and noninvasively. Here we review the physiology and dysfunction of the ANS during critical illness, discuss methods for measuring ANS function in the intensive care unit, and review the diagnostic, prognostic, and therapeutic value of understanding ANSD in pediatric sepsis.

Disruption of Brain-Heart Coupling in Sepsis

PURPOSE

To investigate heart rate and EEG variability and their coupling in patients with sepsis and determine their relationship to sepsis severity and severity of sepsis-associated brain dysfunction.

METHODS

Fifty-two patients with sepsis were prospectively identified, categorized as comatose (N = 30) and noncomatose (N = 22), and compared with 11 control subjects. In a 30-minute EEG and electrocardiogram recording, heart rate variability and EEG variability (measured by the variability of relative power in a modified alpha band = RAP) and their coupled oscillations were quantified using linear (least-square periodogram and magnitude square coherence) and nonlinear (Shannon entropy and mutual information) measures. These measures were compared between the three groups and correlated with outcome, adjusting for severity of sepsis.

RESULTS

Several measures of heart rate variability and EEG variability and of their coupled oscillations were significantly lower in patients with sepsis compared with controls and correlated with outcome. This correlation was not independent when adjusting for severity of sepsis.

CONCLUSIONS

Sepsis is associated with lower variability of both heart rate and RAP on EEG and reduction of their coupled oscillations. This uncoupling is associated with the severity of encephalopathy. Combined EEG and electrocardiogram monitoring may be used to gain insight in underlying mechanisms of sepsis and quantify brainstem or thalamic dysfunction.

Heart rate elevations during early sepsis predict death in fluid-resuscitated rats with fecal peritonitis

BACKGROUND

In sepsis, early outcome prediction would allow investigation of both adaptive mechanisms underlying survival and maladaptive mechanisms resulting in death. The aim of this study was to test whether early changes in heart rate monitored by telemetry could predict outcome in a long-term rat model of fecal peritonitis.

METHODS

Male Wistar rats (n = 24) were instrumented with a central venous line for administration of fluids, antibiotics and analgesics. A telemetry transmitter continuously collected electrocardiogram signals. Sepsis was induced by intraperitoneal injection of fecal slurry, and the animals were observed for 48 h. Additional animals underwent arterial cannulation at baseline (n = 9), 4 h (n = 16), or 24 h (n = 6) for physiology and laboratory measurements.

RESULTS

48-h mortality was 33% (8/24), with all deaths occurring between 4 and 22 h. Septic animals were characterized by lethargy, fever, tachycardia, positive blood cultures, and elevated cytokine (IL-1, IL-6, TNF alpha) levels. An increase in heart rate ≥ 50 bpm during the first 4 h of sepsis predicted death with sensitivity and specificity of 88% (p = 0.001).

CONCLUSIONS

In this long-term rat sepsis model, prognostication could be made early by telemetry-monitored changes in heart rate. This model enables the study of underlying mechanisms and the assessment of any differential effects of novel therapies in predicted survivors or non-survivors.

Proposed mechanisms of relative bradycardia

Relative bradycardia is the term used to describe the mechanism where there is dissociation between pulse and temperature. This finding is important to recognize since it may provide further insights into the potential underlying causes of disease. There is no known proposed mechanism to explain this phenomenon. We hypothesize that relative bradycardia is the central mechanism reflecting and influenced potentially by the direct pathogenic effect on the sinoatrial node as well as cross-talk between the autonomic nervous system and immune system. Cardiac pacemaker cells may act as a target for inflammatory cytokines leading to alteration in heart rate dynamics or their responsiveness to neurotransmitters during systemic inflammation. These factors account for the important role of how the host response to infectious and non-infectious causes influences the appearance of relative bradycardia. We propose several methods that may be useful to confirm the proposed theoretical framework to further enhance our understanding of this paradoxical phenomenon. This includes measuring, during the episode of relative bradycardia, proinflammatory and anti-inflammatory cytokines, monitoring heart rate variability (HRV), and assessing underlying comorbidities and outcomes in patients with the same disease.

Association between autonomic control indexes and mortality in subjects admitted to intensive care unit

This study checks whether autonomic markers derived from spontaneous fluctuations of heart period (HP) and systolic arterial pressure (SAP) and from their interactions with spontaneous or mechanical respiration (R) are associated with mortality in patients admitted to intensive care unit (ICU). Three-hundred consecutive HP, SAP and R values were recorded during the first day in ICU in 123 patients. Population was divided into survivors (SURVs, n = 83) and non-survivors (NonSURVs, n = 40) according to the outcome. SURVs and NonSURVs were aged- and gender-matched. All subjects underwent modified head-up tilt (MHUT) by tilting the bed back rest segment to 60°. Autonomic control indexes were computed using time-domain, spectral, cross-spectral, complexity, symbolic and causality techniques via univariate, bivariate and conditional approaches. SAP indexes derived from time-domain, model-free complexity and symbolic approaches were associated with the endpoint, while none of HP variability markers was. The association was more powerful during MHUT. Linear cross-spectral and causality indexes were useless to separate SURVs from NonSURVs, while nonlinear bivariate symbolic markers were successful. When indexes were combined with clinical scores, only SAP variance provided complementary information. Cardiovascular control variability indexes, especially when derived after an autonomic challenge such as MHUT, can improve mortality risk stratification in ICU.

Heart-Rate Variability-More than Heart Beats?

Heart-rate variability (HRV) is frequently introduced as mirroring imbalances within the autonomous nerve system. Many investigations are based on the paradigm that increased sympathetic tone is associated with decreased parasympathetic tone and vice versa. But HRV is probably more than an indicator for probable disturbances in the autonomous system. Some perturbations trigger not reciprocal, but parallel changes of vagal and sympathetic nerve activity. HRV has also been considered as a surrogate parameter of the complex interaction between brain and cardiovascular system. Systems biology is an inter-disciplinary field of study focusing on complex interactions within biological systems like the cardiovascular system, with the help of computational models and time series analysis, beyond others. Time series are considered surrogates of the particular system, reflecting robustness or fragility. Increased variability is usually seen as associated with a good health condition, whereas lowered variability might signify pathological changes. This might explain why lower HRV parameters were related to decreased life expectancy in several studies. Newer integrating theories have been proposed. According to them, HRV reflects as much the state of the heart as the state of the brain. The polyvagal theory suggests that the physiological state dictates the range of behavior and psychological experience. Stressful events perpetuate the rhythms of autonomic states, and subsequently, behaviors. Reduced variability will according to this theory not only be a surrogate but represent a fundamental homeostasis mechanism in a pathological state. The neurovisceral integration model proposes that cardiac vagal tone, described in HRV beyond others as HF-index, can mirror the functional balance of the neural networks implicated in emotion-cognition interactions. Both recent models represent a more holistic approach to understanding the significance of HRV.

Patient-Specific Classification of ICU Sedation Levels From Heart Rate Variability

OBJECTIVE

To develop a personalizable algorithm to discriminate between sedation levels in ICU patients based on heart rate variability.

DESIGN

Multicenter, pilot study.

SETTING

Several ICUs at Massachusetts General Hospital, Boston, MA.

PATIENTS

We gathered 21,912 hours of routine electrocardiogram recordings from a heterogenous group of 70 adult ICU patients. All patients included in the study were mechanically ventilated and were receiving sedatives.

MEASUREMENTS AND MAIN RESULTS

As "ground truth" for developing our method, we used Richmond Agitation Sedation Scale scores grouped into four levels denoted "comatose" (-5), "deeply sedated" (-4 to -3), "lightly sedated" (-2 to 0), and "agitated" (+1 to +4). We trained a support vector machine learning algorithm to calculate the probability of each sedation level from heart rate variability measures derived from the electrocardiogram. To estimate algorithm performance, we calculated leave-one-subject out cross-validated accuracy. The patient-independent version of the proposed system discriminated between the four sedation levels with an overall accuracy of 59%. Upon personalizing the system supplementing the training data with patient-specific calibration data, consisting of an individual's labeled heart rate variability epochs from the preceding 24 hours, accuracy improved to 67%. The personalized system discriminated between light- and deep-sedation states with an average accuracy of 75%.

CONCLUSIONS

With further refinement, the methodology reported herein could lead to a fully automated system for depth of sedation monitoring. By enabling monitoring to be continuous, such technology may help clinical staff to monitor sedation levels more effectively and to reduce complications related to over- and under sedation.

Decreases in heart rate variability are associated with postoperative complications in hip fracture patients

Background

To explore relevant associations between deviations in linear and nonlinear heart rate variability (HRV) scores, and short-term morbidity and mortality in patients undergoing hip-surgery after a fracture.

Methods

165 patients with hip fractures being admitted for surgery at two hospitals were included in a prospective cohort study. A short-term ECG was recorded within 24 hours of arrival. 15 patients had to be excluded due to insufficient quality of the ECG recordings. 150 patients were included in the final analysis. Linear parameters were calculated in time domain: standard deviation of NN intervals (SDNN), root mean square of successive differences (rMSSD); and frequency domain: Total Power (TP), High Frequency Power (HF), Low Frequency Power (LF), Very Low Frequency Power (VLF), and the ratio of LF/HF. Postoperative outcome was evaluated at the time of discharge. This included occurrence of pneumonia, overall infection rate, stroke, myocardial infarction, and all-cause mortality.

Results

Patients experiencing complications had significantly lower rMSSD (p = 0.04), and TP (p = 0.03) preoperatively. Postoperative infections were predicted by decreased VLF preoperatively (p = 0.04). There was a significant association between pneumonia and LF/HF<1 (p = 0.03). The likelihood ratio to develop pneumonia when LF/HF < 1 was 6,1.

Conclusion

HRV seems to reflect the general frailty of the patient with hip fracture and might be used to identify patients in need of increased surveillance or prophylactic treatment.

Heart rate variability in critical care medicine: a systematic review

BACKGROUND

Heart rate variability (HRV) has been used to assess cardiac autonomic activity in critically ill patients, driven by translational and biomarker research agendas. Several clinical and technical factors can interfere with the measurement and/or interpretation of HRV. We systematically evaluated how HRV parameters are acquired/processed in critical care medicine.

METHODS

PubMed, MEDLINE, EMBASE and the Cochrane Central Register of Controlled Trials (1996-2016) were searched for cohort or case-control clinical studies of adult (>18 years) critically ill patients using heart variability analysis. Duplicate independent review and data abstraction. Study quality was assessed using two independent approaches: Newcastle-Ottowa scale and Downs and Black instrument. Conduct of studies was assessed in three categories: (1) study design and objectives, (2) procedures for measurement, processing and reporting of HRV, and (3) reporting of relevant confounding factors.

RESULTS

Our search identified 31/271 eligible studies that enrolled 2090 critically ill patients. A minority of studies (15; 48%) reported both frequency and time domain HRV data, with non-normally distributed, wide ranges of values that were indistinguishable from other (non-critically ill) disease states. Significant heterogeneity in HRV measurement protocols was observed between studies; lack of adjustment for various confounders known to affect cardiac autonomic regulation was common. Comparator groups were often omitted (n = 12; 39%). This precluded meaningful meta-analysis.

CONCLUSIONS

Marked differences in methodology prevent meaningful comparisons of HRV parameters between studies. A standardised set of consensus criteria relevant to critical care medicine are required to exploit advances in translational autonomic physiology.

Heart rate variability as predictor of mortality in sepsis: A prospective cohort study

Background

Sepsis is a serious medical condition with increasing prevalence and high mortality. The role of the autonomic nervous system in pathophysiology of sepsis has been increasingly researched. The objective of this study is to evaluate the Heart rate variability (HRV) as a predictor of mortality in septic patients.

Methods

This was a prospective cohort of patients diagnosed with sepsis. Patient recruitment was carried out at ICU in tertiary university hospital between March 2012 and February 2014. Clinical data and laboratory exams were collected at admission. Each patient underwent a 20-minute Holter and a 24-hour Holter on the first day of enrollment. The primary outcome was the 28-day all-cause mortality.

Results

A total of 63 patients were included. Patients were categorized into nonsurvivor group (n = 16) or survivor group (n = 47) depending on this endpoint. Survivors were younger (48.6 years vs. 63.0 years), had better renal function and lower values in severity scores (APACHE II and SOFA) compared to nonsurvivors. In the 20-minute Holter, SDNN, Total Power, VLF Power, LF Power and LF/HF of nonsurvivors were significantly lower than those of survivors (p = <0.001, p = 0.003, p = 0.002, p = 0.006, p = 0.009 respectively). ROC curve of SDNN was built, showing area under the curve of 0.772 (0.638–0.906) for mortality. The value of 17ms was chosen as best SDNN cutoff to discriminate survivors and nonsurvivors. In the Cox proportional regression, adjusted for SOFA score and for APACHE II, a SDNN ≤ 17ms was associated with a greater risk of death, with hazard ratios of 6.3 (1.4–28.0; p = 0.015) and 5.5 (1,2–24,8; p = 0.027), respectively. The addition of the dichotomized SDNN to the SOFA model reduced AIC and increased the concordance statistic and the R², indicating that predictive power of the SDNN + SOFA model is better than predictive power of SOFA only.

Conclusions

Several HRV parameters are reduced in nonsurviving septic patients. SDNN ≤17 is a risk factor for death in septic patients, even after adjusting for severity scores.

Automatic Classification of Sedation Levels in ICU Patients Using Heart Rate Variability

OBJECTIVE

To explore the potential value of heart rate variability features for automated monitoring of sedation levels in mechanically ventilated ICU patients.

DESIGN

Multicenter, pilot study.

SETTING

Several ICUs at Massachusetts General Hospital, Boston, MA.

PATIENTS

Electrocardiogram recordings from 40 mechanically ventilated adult patients receiving sedatives in an ICU setting were used to develop and test the proposed automated system.

MEASUREMENTS AND MAIN RESULTS

Richmond Agitation-Sedation Scale scores were acquired prospectively to assess patient sedation levels and were used as ground truth. Richmond Agitation-Sedation Scale scores were grouped into four levels, denoted "unarousable" (Richmond Agitation- Sedation Scale = -5, -4), "sedated" (-3, -2, -1), "awake" (0), "agitated" (+1, +2, +3, +4). A multiclass support vector machine algorithm was used for classification. Classifier training and performance evaluations were carried out using leave-oneout cross validation. An overall accuracy of 69% was achieved for discriminating between the four levels of sedation. The proposed system was able to reliably discriminate (accuracy = 79%) between sedated (Richmond Agitation-Sedation Scale < 0) and nonsedated states (Richmond Agitation-Sedation Scale > 0).

CONCLUSIONS

With further refinement, the methodology reported herein could lead to a fully automated system for depth of sedation monitoring. By enabling monitoring to be continuous, such technology may help clinical staff to monitor sedation levels more effectively and to reduce complications related to over- and undersedation.

Progression and variability of physiologic deterioration in an ovine model of lung infection sepsis

In this study, a lung infection model of pneumonia in sheep (n = 12) that included smoke inhalation injury followed by methicillin-resistant Staphylococcus aureus placement into the lungs was used to investigate hemodynamic and pulmonary dysfunctions during the course of sepsis progression. To assess the variability in disease progression, animals were retrospectively divided into survivor (n = 6) and nonsurvivor (n = 6) groups, and a range of physiological indexes reflecting hemodynamic and pulmonary function were estimated and compared to evaluate variability in dynamics underlying sepsis development. Blood pressure and heart rate variability analyses were performed to assess whether they discriminated between the survivor and nonsurvivor groups early on and after intervention. Results showed hemodynamic deterioration in both survivor and nonsurvivor animals during sepsis along with a severe oxygenation disruption (decreased peripheral oxygen saturation) in nonsurvivors separating them from survivor animals of this model. Variability analysis of beat-to-beat heart rate and blood pressure reflected physiologic deterioration during infection for all animals, but these analyses did not discriminate the nonsurvivor animals from survivor animals.NEW & NOTEWORTHY Variable pulmonary response to injury results in varying outcomes in a previously reported animal model of lung injury and methicillin-resistant Staphylococcus aureus-induced sepsis. Heart rate and blood pressure variability analyses were investigated to track the varying levels of physiologic deterioration but did not discriminate early nonsurvivors from survivors.

Heart-rate variability depression in porcine peritonitis-induced sepsis without organ failure

Depression of heart-rate variability (HRV) in conditions of systemic inflammation has been shown in both patients and experimental animal models and HRV has been suggested as an early indicator of sepsis. The sensitivity of HRV-derived parameters to the severity of sepsis, however, remains unclear. In this study we modified the clinically relevant porcine model of peritonitis-induced sepsis in order to avoid the development of organ failure and to test the sensitivity of HRV to such non-severe conditions. In 11 anesthetized, mechanically ventilated and instrumented domestic pigs of both sexes, sepsis was induced by fecal peritonitis. The dose of feces was adjusted and antibiotic therapy was administered to avoid multiorgan failure. Experimental subjects were screened for 40 h from the induction of sepsis. In all septic animals, sepsis with hyperdynamic circulation and increased plasma levels of inflammatory mediators developed within 12 h from the induction of peritonitis. The sepsis did not progress to multiorgan failure and there was no spontaneous death during the experiment despite a modest requirement for vasopressor therapy in most animals (9/11). A pronounced reduction of HRV and elevation of heart rate developed quickly (within 5 h, time constant of 1.97 ± 0.80 h for HRV parameter TINN) upon the induction of sepsis and were maintained throughout the experiment. The frequency domain analysis revealed a decrease in the high-frequency component. The reduction of HRV parameters and elevation of heart rate preceded sepsis-associated hemodynamic changes by several hours (time constant of 11.28 ± 2.07 h for systemic vascular resistance decline). A pronounced and fast reduction of HRV occurred in the setting of a moderate experimental porcine sepsis without organ failure. Inhibition of parasympathetic cardiac signaling probably represents the main mechanism of HRV reduction in sepsis. The sensitivity of HRV to systemic inflammation may allow early detection of a moderate sepsis without organ failure. Impact statement A pronounced and fast reduction of heart-rate variability occurred in the setting of a moderate experimental porcine sepsis without organ failure. Dominant reduction of heart-rate variability was found in the high-frequency band indicating inhibition of parasympathetic cardiac signaling as the main mechanism of heart-rate variability reduction. The sensitivity of heart-rate variability to systemic inflammation may contribute to an early detection of moderate sepsis without organ failure.

Perioperative Near-Infrared Spectroscopy Monitoring in Neonates With Congenital Heart Disease: Relationship of Cerebral Tissue Oxygenation Index Variability With Neurodevelopmental Outcome

OBJECTIVES

To evaluate the value of perioperative cerebral near-infrared spectroscopy monitoring using variability analysis in the prediction of neurodevelopmental outcomes in neonates undergoing surgery for congenital heart disease.

DESIGN

Retrospective cohort study.

SETTING

Urban, academic, tertiary-care children's hospital.

PATIENTS

Neonates undergoing surgery with cardiopulmonary bypass for congenital heart disease.

INTERVENTIONS

Perioperative monitoring of continuous cerebral tissue oxygenation index by near-infrared spectroscopy and subsequent neurodevelopmental testing at 6, 15, and 21 months of age.

MEASUREMENTS AND MAIN RESULTS

We developed a new measure, cerebral tissue oxygenation index variability, using the root mean of successive squared differences of averaged 1-minute cerebral tissue oxygenation index values for both the intraoperative and first 24-hours postoperative phases of monitoring. There were 62 neonates who underwent cerebral tissue oxygenation index monitoring during surgery for congenital heart disease and 44 underwent subsequent neurodevelopmental testing (12 did not survive until testing and six were lost to follow-up). Among the 44 monitored patients who underwent neurodevelopmental testing, 20 (45%) had abnormal neurodevelopmental indices. Patients with abnormal neurodevelopmental indices had lower postoperative cerebral tissue oxygenation index variability when compared with patients with normal indices (p = 0.01). Adjusting for class of congenital heart disease and duration of deep hypothermic circulatory arrest, lower postoperative cerebral tissue oxygenation index variability was associated with poor neurodevelopmental outcome (p = 0.02).

CONCLUSIONS

We found reduced postoperative cerebral tissue oxygenation index variability in neonatal survivors of congenital heart disease surgery with poor neurodevelopmental outcomes. We hypothesize that reduced cerebral tissue oxygenation index variability may be a surrogate for impaired cerebral metabolic autoregulation in the immediate postoperative period. Further research is needed to investigate clinical implications of this finding and opportunities for using this measure to drive therapeutic interventions.

Monitoring Severity of Multiple Organ Dysfunction Syndrome: New Technologies

OBJECTIVE

To describe new technologies (biomarkers and tests) used to assess and monitor the severity and progression of multiple organ dysfunction syndrome in children as discussed as part of the Eunice Kennedy Shriver National Institute of Child Health and Human Development MODS Workshop (March 26-27, 2015).

DATA SOURCES

Literature review, research data, and expert opinion.

STUDY SELECTION

Not applicable.

DATA EXTRACTION

Moderated by an experienced expert from the field, investigators developing and assessing new technologies to improve the care and understanding of critical illness presented their research and the relevant literature.

DATA SYNTHESIS

Summary of presentations and discussion supported and supplemented by relevant literature.

CONCLUSIONS

There are many innovative tools and techniques with the potential application for the assessment and monitoring of severity of multiple organ dysfunction syndrome. If the reliability and added value of these candidate technologies can be established, they hold promise to enhance the understanding, monitoring, and perhaps, treatment of multiple organ dysfunction syndrome in children.

Neuroanatomy and Physiology of Brain Dysfunction in Sepsis

Sepsis-associated encephalopathy (SAE), a complication of sepsis, is often complicated by acute and long-term brain dysfunction. SAE is associated with electroencephalogram pattern changes and abnormal neuroimaging findings. The major processes involved are neuroinflammation, circulatory dysfunction, and excitotoxicity. Neuroinflammation and microcirculatory alterations are diffuse, whereas excitotoxicity might occur in more specific structures involved in the response to stress and the control of vital functions. A dysfunction of the brainstem, amygdala, and hippocampus might account for the increased mortality, psychological disorders, and cognitive impairment. This review summarizes clinical and paraclinical features of SAE and describes its mechanisms at cellular and structural levels.

Mechanical ventilatory modes and cardioventilatory phase synchronization in acute respiratory failure patients

Cardioventilatory phase synchronization was studied in ten critically ill patients admitted in intensive care unit (ICU) for acute respiratory failure under two mechanical ventilatory modes: (i) pressure controlled ventilation (PCV); (ii) pressure support ventilation (PSV). The two modalities were administered to the same patient in different times in a random order. Cardioventilatory phase interactions were typified by plotting the relative position of a heartbeat, detected from the electrocardiogram and collected in n groups, within m ventilatory cycles as a function of the progressive cardiac beat number via the synchrogram. n:m phase synchronized patterns were detected by computing the variability of each phase group. The percent duration of the recording featuring phase synchronization was assessed as a measure of the strength of phase synchrony and tested against situations of full phase desynchronization between cardiac and ventilatory rhythms. Indexes quantifying the variability of the cardiac and ventilatory activities were computed as well. Findings proved that: (i) a significant presence of n:m phase synchronized patterns was detected in PCV; (ii) the strength of n:m phase synchronization was stronger during PCV than PSV; (iii) different strengths of cardioventilatory phase synchronization detected during PCV and PSV were found in presence of similar heart and ventilatory rates and alike variability. We conclude that mechanical ventilation can induce a significant presence of cardioventilatory phase synchronized patterns and this amount depends on the mode of mechanical ventilation. Future studies should test the eventual link of the level of phase coordination between heart and mechanical ventilation to a clinical outcome to understand whether featuring a certain degree of cardioventilatory phase synchronization is beneficial for the critical patient in ICU.

Characterization of Brain-Heart Interactions in a Rodent Model of Sepsis

Loss of heart rate variability (HRV) and autonomic dysfunction are associated with poor outcomes in critically ill patients. Neuronal networks comprising brainstem and hypothalamus are involved in the “flight-or-fight” response via control over the autonomic nervous system and circulation. We hypothesized that sepsis-induced inflammation in brain regions responsible for autonomic control is associated with sympathovagal imbalance and depressed contractility. Sepsis was induced by fecal slurry injection in fluid-resuscitated rats. Sham-operated animals served as controls. Echocardiography-derived peak velocity (PV) was used to separate septic animals into good (PV ≥0.93 m/s, low 72-h mortality) and bad (PV <0.93, high 72-h mortality) prognosis. Cytokine protein levels were assessed by ELISA. All experiments were performed at 24 h post-insult. Increased levels of inflammation and oxidative injury were observed in the hypothalamus (TNF-α, IL-10, nitrite and nitrate and carbonyl groups) and brainstem (IL-1, IL-6, IL-10, nitrite and nitrate and carbonyl groups) of the septic animals (p < 0.05 vs. sham), but not in the pre-frontal cortex, an area not directly implicated in control of the autonomic nervous system. Good prognosis septic animals had increased sympathetic output and increased left ventricular contractility (p < 0.05 vs. sham). There was a significant inverse correlation between high frequency power (a marker of parasympathetic outflow) and contractility (r = −0.73, p < 0.05). We found no correlation between the degree of inflammation or injury to autonomic centers and cardiovascular function. In conclusion, control of autonomic centers and cardiac function in our long-term rodent model of sepsis was related to clinical severity but not directly to the degree of inflammation.

Heart Rate Variability in Porcine Progressive Peritonitis-Induced Sepsis

Accumulating evidence suggests that heart rate variability (HRV) alterations could serve as an indicator of sepsis progression and outcome, however, the relationships of HRV and major pathophysiological processes of sepsis remain unclear. Therefore, in this experimental study HRV was investigated in a clinically relevant long-term porcine model of severe sepsis/septic shock. HRV was analyzed by several methods and the parameters were correlated with pathophysiological processes of sepsis. In 16 anesthetized, mechanically ventilated, and instrumented domestic pigs of either gender, sepsis was induced by fecal peritonitis. Experimental subjects were screened up to the refractory shock development or death. ECG was continuously recorded throughout the experiment, afterwards RR intervals were detected and HRV parameters computed automatically using custom made measurement and analysis MATLAB routines. In all septic animals, progressive hyperdynamic septic shock developed. The statistical measures of HRV, geometrical measures of HRV and Poincaré plot analysis revealed a pronounced reduction of HRV that developed quickly upon the onset of sepsis and was maintained throughout the experiment. The frequency domain analysis demonstrated a decrease in the high frequency component and increase in the low frequency component together with an increase of the low/high frequency component ratio. The reduction of HRV parameters preceded sepsis-associated hemodynamic changes including heart rate increase or shock progression. In a clinically relevant porcine model of peritonitis-induced progressive septic shock, reduction of HRV parameters heralded sepsis development. HRV reduction was associated with a pronounced parasympathetic inhibition and a shift of sympathovagal balance. Early reduction of HRV may serve as a non-invasive and sensitive marker of systemic inflammatory syndrome, thereby widening the therapeutic window for early interventions.

Spontaneous breathing trial in T-tube negatively impact on autonomic modulation of heart rate compared with pressure support in critically ill patients

INTRODUCTION

Spontaneous breathing with a conventional T-piece (TT) connected to the tracheal tube orotraqueal has been frequently used in clinical setting to weaning of mechanical ventilation (MV), when compared with pressure support ventilation (PSV). However, the acute effects of spontaneous breathing with TT versus PSV on autonomic function assessed through heart rate variability (HRV) have not been fully elucidated.

OBJECTIVE

The purpose of this study was to examine the acute effects of spontaneous breathing in TT vs PSV in critically ill patients.

METHOD

Twenty-one patients who had received MV for ≥ 48 h and who met the study inclusion criteria for weaning were assessed. Eligible patients were randomized to TT and PSV. Cardiorespiratory responses (respiratory rate -ƒ, tidal volume-V_T , mean blood pressure (MBP) and diastolic blood pressure (DBP), end tidal dioxide carbone (P_ET CO₂ ), peripheral oxygen saturation (SpO₂ ) and HRV indices in frequency domain (low-LF, high frequency (HF) and LF/HF ratio were evaluated.

RESULTS

TT increased ƒ (20 ± 5 vs 25 ± 4 breaths/min, P<0.05), MBP (90 ± 14 vs 94 ± 18 mmHg, P<0.05), HR (90 ± 17 vs 96 ± 12 beats/min, P<0.05), P_ET CO₂ (33 ± 8 vs 48 ± 10 mmHg, P<0.05) and reduced SpO₂ (98 ± 1.6 vs 96 ± 1.6%, P<0.05). In addition, LF increased (47 ± 18 vs 38 ± 12 nu, P<0.05) and HF reduced (29 ± 13 vs 32 ± 16 nu, P<0.05), resulting in higher LF/HF ratio (1.62 ± 2 vs 1.18 ± 1, P<0.05) during TT. Conversely, V_T increased with PSV (0.58 ± 0.16 vs 0.50 ± 0.15 L, P<0.05) compared with TT.

CONCLUSION

Acute effects of TT mode may be closely linked to cardiorespiratory mismatches and cardiac autonomic imbalance in critically ill patients.

Autonomic nervous system activity as risk predictor in the medical emergency department: a prospective cohort study

OBJECTIVES

To evaluate heart rate deceleration capacity, an electrocardiogram-based marker of autonomic nervous system activity, as risk predictor in a medical emergency department and to test its incremental predictive value to the modified early warning score.

DESIGN

Prospective cohort study.

SETTING

Medical emergency department of a large university hospital.

PATIENTS

Five thousand seven hundred thirty consecutive patients of either sex in sinus rhythm, who were admitted to the medical emergency department of the University of Tübingen, Germany, between November 2010 and March 2012.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Deceleration capacity of heart rate was calculated within the first minutes after emergency department admission. The modified early warning score was assessed from respiratory rate, heart rate, systolic blood pressure, body temperature, and level of consciousness as previously described. Primary endpoint was intrahospital mortality; secondary endpoints included transfer to the ICU as well as 30-day and 180-day mortality. One hundred forty-two patients (2.5%) reached the primary endpoint. Deceleration capacity was highly significantly lower in nonsurvivors than survivors (2.9 ± 2.1 ms vs 5.6 ± 2.9 ms; p < 0.001) and yielded an area under the receiver-operator characteristic curve of 0.780 (95% CI, 0.745-0.813). The modified early warning score model yielded an area under the receiver-operator characteristic curve of 0.706 (0.667-0.750). Implementing deceleration capacity into the modified early warning score model led to a highly significant increase of the area under the receiver-operator characteristic curve to 0.804 (0.770-0.835; p < 0.001 for difference). Deceleration capacity was also a highly significant predictor of 30-day and 180-day mortality as well as transfer to the ICU.

CONCLUSIONS

Deceleration capacity is a strong and independent predictor of short-term mortality among patients admitted to a medical emergency department.

[Use of biomarkers in sepsis. Update and perspectives]

Sepsis and related complications are a challenge for intensive care medicine. Despite many advances in antibiotic therapy sepsis remains one of the most common diseases of patients in intensive care units and is designated as the main cause of death in critically ill patients. Persisting sepsis leads to impaired immunity, resulting in immunosuppression. Unspecific predictive signs complicate an early diagnosis; however, an early initiation of adequate therapy is of crucial importance for the prognosis. Scoring systems can be applied for the initial evaluation but are controversially discussed concerning the monitoring of disease progression and therapy as well as outcome prediction. Biomarkers are considered as a complementary approach.

Are there new approaches for diagnosis, therapy guidance and outcome prediction of sepsis?

Beside many efforts to improve outcome, sepsis is still one of the most frequent causes of death in critically ill patients. It is the most common condition with high mortality in intensive care units. The complexity of the septic syndrome comprises immunological aspects - i.e., sepsis induced immunosuppression - but is not restricted to this fact in modern concepts. So far, exact mechanisms and variables determining outcome and mortality stay unclear. Since there is no typical risk profile, early diagnosis and risk stratification remain difficult, which hinders rapid and effective treatment initiation. Due to the heterogeneous nature of sepsis, potential therapy options should be adapted to the individual. Biomarkers like C-reactive protein and procalcitonin are routinely used as complementary tools in clinical decision-making. Beyond the acute phase proteins, a wide bunch of promising substances and non-laboratory tools with potential diagnostic and prognostic value is under intensive investigation. So far, clinical decision just based on biomarker assessment is not yet feasible. However, biomarkers should be considered as a complementary approach.

Usefulness of α7 nicotinic receptor messenger RNA levels in peripheral blood mononuclear cells as a marker for cholinergic antiinflammatory pathway activity in septic patients: results of a pilot study

BACKGROUND

Stimulation of the vagus nerve in the so-called cholinergic antiinflammatory pathway (CAP) attenuates systemic inflammation, improving survival in animal sepsis models via α7 nicotinic acetylcholine receptors on immunocompetent cells. Because the relevance of this regulatory pathway is unknown in human sepsis, this pilot study assessed whether the α7 gene expression level in septic patients' peripheral blood mononuclear cells (PBMC) might be used to assess CAP activity and clinical outcome.

METHODS

The PBMCs α7 messenger RNA levels were determined by real-time quantitative reverse-transcription polymerase chain reaction in 33 controls and 33 patients at enrollment and after their hospital discharge. Data were analyzed to find significant associations between α7 level, vagally mediated heart rate variability as an indirect reflection of CAP activity, serum concentrations of different inflammation markers, and clinical course.

RESULTS

Septic patients' α7 levels were significantly increased and returned to control values after recovery. These α7 levels correlated directly with the vagal heart input and inversely with the magnitude of the patient's inflammatory state, disease severity, and clinical outcome.

CONCLUSIONS

This study reveals that the PBMC α7 gene expression level is a clinically relevant marker for CAP activity in sepsis: the higher the α7 expression, the better the inflammation control and the prognosis.

From data patterns to mechanistic models in acute critical illness

The complexity of the physiologic and inflammatory response in acute critical illness has stymied the accurate diagnosis and development of therapies. The Society for Complex Acute Illness was formed a decade ago with the goal of leveraging multiple complex systems approaches to address this unmet need. Two main paths of development have characterized the society's approach: (i) data pattern analysis, either defining the diagnostic/prognostic utility of complexity metrics of physiologic signals or multivariate analyses of molecular and genetic data and (ii) mechanistic mathematical and computational modeling, all being performed with an explicit translational goal. Here, we summarize the progress to date on each of these approaches, along with pitfalls inherent in the use of each approach alone. We suggest that the next decade holds the potential to merge these approaches, connecting patient diagnosis to treatment via mechanism-based dynamical system modeling and feedback control and allowing extrapolation from physiologic signals to biomarkers to novel drug candidates. As a predicate example, we focus on the role of data-driven and mechanistic models in neuroscience and the impact that merging these modeling approaches can have on general anesthesia.

On heart rate variability and autonomic activity in homeostasis and in systemic inflammation

Analysis of heart rate variability (HRV) is a promising diagnostic technique due to the noninvasive nature of the measurements involved and established correlations with disease severity, particularly in inflammation-linked disorders. However, the complexities underlying the interpretation of HRV complicate understanding the mechanisms that cause variability. Despite this, such interpretations are often found in literature. In this paper we explored mathematical modeling of the relationship between the autonomic nervous system and the heart, incorporating basic mechanisms such as perturbing mean values of oscillating autonomic activities and saturating signal transduction pathways to explore their impacts on HRV. We focused our analysis on human endotoxemia, a well-established, controlled experimental model of systemic inflammation that provokes changes in HRV representative of acute stress. By contrasting modeling results with published experimental data and analyses, we found that even a simple model linking the autonomic nervous system and the heart confound the interpretation of HRV changes in human endotoxemia. Multiple plausible alternative hypotheses, encoded in a model-based framework, equally reconciled experimental results. In total, our work illustrates how conventional assumptions about the relationships between autonomic activity and frequency-domain HRV metrics break down, even in a simple model. This underscores the need for further experimental work towards unraveling the underlying mechanisms of autonomic dysfunction and HRV changes in systemic inflammation. Understanding the extent of information encoded in HRV signals is critical in appropriately analyzing prior and future studies.