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

Discriminatory ability of perioperative heart rate variability in predicting postoperative complications in major urologic surgery: a prospective cohort study

We aimed to determine if continuous perioperative heart rate variability (HRV) monitoring could improve risk stratification compared to a short preoperative measurement in radical cystectomy patients. Electrocardiography (ECG) recordings were collected continuously preoperatively to discharge in 83 patients. Two, 5-min ECG signal segments (preoperative and at 24-h post ECG placement) were analyzed offline to extract HRV metrics. HRV metric discriminatory ability to identify patients with 30-day postoperative complications were analyzed using receiver operating characteristics curves. Sixty participants were included for analysis of which 27 (45%) developed a complication within 30 days postoperative. HRV was reduced in patients with complications. Postoperative standard deviation NN intervals and root mean square of successive differences had area under the curves (AUC) of 0.67 (95% CI 0.54 to 0.81) and 0.68 (95% CI 0.54 to 0.82), respectively. Significant discriminatory abilities were also reported for postoperative frequency metrics of absolute low frequency (LF) [AUC = 0.65 (95% CI 0.51 to 0.79)] and high frequency (HF) powers [AUC = 0.69 (95% CI 0.55 to 0.83)] and total power [AUC = 0.66 (95% CI 0.53 to 0.80)]. Postoperative acquired HRV metrics demonstrated improved discriminatory ability. Our findings suggest that longer-term perioperative HRV monitoring presents with superior ability to stratify complication risk.

Development of Prediction Model for Intensive Care Unit Admission Based on Heart Rate Variability: A Case-Control Matched Analysis

This study aimed to develop a predictive model for intensive care unit (ICU) admission by using heart rate variability (HRV) data. This retrospective case-control study used two datasets (emergency department [ED] patients admitted to the ICU, and patients in the operating room without ICU admission) from a single academic tertiary hospital. HRV metrics were measured every 5 min using R-peak-to-R-peak (R-R) intervals. We developed a generalized linear mixed model to predict ICU admission and assessed the area under the receiver operating characteristic curve (AUC). Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated from the coefficients. We analyzed 610 (ICU: 122; non-ICU: 488) patients, and the factors influencing the odds of ICU admission included a history of diabetes mellitus (OR [95% CI]: 3.33 [1.71-6.48]); a higher heart rate (OR [95% CI]: 3.40 [2.97-3.90] per 10-unit increase); a higher root mean square of successive R-R interval differences (RMSSD; OR [95% CI]: 1.36 [1.22-1.51] per 10-unit increase); and a lower standard deviation of R-R intervals (SDRR; OR [95% CI], 0.68 [0.60-0.78] per 10-unit increase). The final model achieved an AUC of 0.947 (95% CI: 0.906-0.987). The developed model effectively predicted ICU admission among a mixed population from the ED and operating room.

Early heart rate fluctuation and outcomes in critically ill patients with sepsis: A retrospective cohort study of the MIMIC-IV database

Background

Heart rate (HR) abnormalities are common in critically ill patients, but the significance of HR fluctuation in sepsis remains unclear. We aimed to assess the association of HR fluctuation with intensive care unit (ICU) mortality, hospital mortality, and 28-day mortality in patients with sepsis and identify the cutoff value of HR fluctuation associated with the lowest risk of death.

Methods

We conducted a retrospective cohort study using the medical information mart for the intensive care IV database. HR fluctuation, defined as the difference between maximum and minimum HR within the first 24 h of ICU admission, was analyzed for its association with outcomes using restricted cubic spline and multivariable Cox regression models.

Results

Among 24,419 eligible patients with sepsis, HR fluctuation showed a J-shaped association with ICU mortality, hospital mortality, and 28-day mortality. The high HR fluctuation group (≥ 35 bpm) had a significantly increased risk of ICU mortality ([hazard ratio, 95% confidence interval] 1.12,1.02-1.22, P = 0.013), hospital mortality (1.10,1.02-1.19, P = 0.013), and 28-day mortality (1.11,1.03-1.20, P = 0.007) compared to the control group (HR fluctuation 25-34 bpm). The low HR fluctuation group (< 25 bpm) showed no significant difference in the risk of mortality compared to the control group.

Conclusions

Our large-sample study suggests that early high HR fluctuation is indicative of poor prognosis in critically ill patients with sepsis. Early HR fluctuation may serve as a readily available "high-risk alert system" influencing therapeutic decision-making.

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.

Electrocardiogram monitoring as a predictor of neurological and survival outcomes in patients with out-of-hospital cardiac arrest: a single-center retrospective observational study

Introduction

This study hypothesized that monitoring electrocardiogram (ECG) waveforms in patients with out-of-hospital cardiac arrest (OHCA) could have predictive value for survival or neurological outcomes. We aimed to establish a new prognostication model based on the single variable of monitoring ECG waveforms in patients with OHCA using machine learning (ML) techniques.

Methods

This observational retrospective study included successfully resuscitated patients with OHCA aged ≥ 18 years admitted to an intensive care unit in Japan between April 2010 and April 2020. Waveforms from ECG monitoring for 1 h after admission were obtained from medical records and examined. Based on the open-access PTB-XL dataset, a large publicly available 12-lead ECG waveform dataset, we built an ML-supported premodel that transformed the II-lead waveforms of the monitoring ECG into diagnostic labels. The ECG diagnostic labels of the patients in this study were analyzed for prognosis using another model supported by ML. The endpoints were favorable neurological outcomes (cerebral performance category 1 or 2) and survival to hospital discharge.

Results

In total, 590 patients with OHCA were included in this study and randomly divided into 3 groups (training set, n = 283; validation set, n = 70; and test set, n = 237). In the test set, our ML model predicted neurological and survival outcomes, with the highest areas under the receiver operating characteristic curves of 0.688 (95% CI: 0.682-0.694) and 0.684 (95% CI: 0.680-0.689), respectively.

Conclusion

Our ML predictive model showed that monitoring ECG waveforms soon after resuscitation could predict neurological and survival outcomes in patients with OHCA.

Heart Rate Variability for Outcome Prediction in Intracerebral and Subarachnoid Hemorrhage: A Systematic Review

This systematic review presents clinical evidence on the association of heart rate variability with outcome prediction in intracerebral and subarachnoid hemorrhages. The literature search led to the retrieval of 19 significant studies. Outcome prediction included functional outcome, cardiovascular complications, secondary brain injury, and mortality. Various aspects of heart rate recording and analysis, based on linear time and frequency domains and a non-linear entropy approach, are reviewed. Heart rate variability was consistently associated with poor functional outcome and mortality, while controversial results were found regarding the association between heart rate variability and secondary brain injury and cardiovascular complications.

Norepinephrine dose, lactate or heart rate: what impacts prognosis in sepsis and septic shock? Results from a prospective, monocentric registry

OBJECTIVE

The study comprehensively investigates the prognostic value of norepinephrine (NE) dose, lactate and heart rate in patients with sepsis and septic shock.

BACKGROUND

Limited data regarding the prognostic value of NE dose, lactate and heart rate in patients meeting the sepsis-3 criteria is available.

METHODS

Consecutive patients with sepsis and septic shock from 2019 to 2021 were included. The prognostic value of NE dose, lactate and heart rate was tested for 30-day all-cause mortality. Statistical analyses included univariable t-tests, Spearman's correlations, C-statistics, Kaplan-Meier analyses, as well as one-factorial repeated measures analysis of variance (ANOVA) and Cox proportional regression analyses.

RESULTS

339 patients with sepsis or septic shock were included. With an area under the curve (AUC) of up to 0.638 and 0.685, NE dose and lactate revealed moderate prognostic accuracy for 30-day all-cause mortality, whereas heart rate was not associated with prognosis. Very high NE doses (i.e. > 1.0 mcg/kg/min) (HR = 2.938; 95% CI 1.933 - 4.464; p = .001) and lactate levels (i.e. ≥ 4 mmol/l) (HR = 2.963; 95% CI 2.095 - 4.191; p = .001) on admission were associated with highest risk of death. Finally, increasing NE doses and lactate levels from day 1 to 3 indicated increased risk of death, which was consistent after multivariable adjustment.

CONCLUSION

Both very high NE doses and lactate levels - but not heart rate - were associated with increased risk of 30-d all-cause mortality in patients with sepsis and septic shock.

Comment on: "exercise training and cardiac autonomic function following coronary artery bypass grafting: a systematic review and meta-analysis"

BACKGROUND

Low cardiorespiratory fitness is associated with poor prognosis in individuals with coronary artery disease and after coronary artery bypass grafting surgery. Thus, we comment about a meta-analysis that adds important information about the effect of exercise training on cardiac autonomic function in individuals following coronary artery bypass grafting surgery.

MAIN BODY

The study by Kushwaha et al. showed positive effects for heart rate variability and heart rate recovery in subjects after coronary artery bypass grafting surgery in response to acute physical training. These data are relevant, since heart rate variability is an independent predictor of for all-cause and cardiovascular mortality for individuals with cardiovascular disorders. Additionally, attenuated heart rate recovery is associated with increased risk for the same outcomes. Moreover, we summarize the quantitative data from studies that compared the effect of physical training in comparison with control group in cardiorespiratory fitness in adults following coronary artery bypass grafting.

CONCLUSIONS

Our findings suggest that improvements in peak oxygen consumption result in an additional benefit in adults following coronary artery bypass grafting. Considered that, the increased cardiorespiratory fitness is an independent predictor of longer survival in coronary artery disease.

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.

Prediction of intrapartum fever using continuously monitored vital signs and heart rate variability

Objectives

Neonatal early onset sepsis (EOS), bacterial infection during the first seven days of life, is difficult to diagnose because presenting signs are non-specific, but early diagnosis before birth can direct life-saving treatment for mother and baby. Specifically, maternal fever during labor from placental infection is the strongest predictor of EOS. Alterations in maternal heart rate variability (HRV) may precede development of intrapartum fever, enabling incipient EOS detection. The objective of this work was to build a predictive model for intrapartum fever.

Methods

Continuously measured temperature, heart rate, and beat-to-beat RR intervals were obtained from wireless sensors on women (n = 141) in labor; traditional manual vital signs were taken every 3-6 hours. Validated measures of HRV were calculated in moving 5-minute windows of RR intervals: standard deviation of normal-to-normal intervals (SDNN) and root mean square of successive differences (RMSSD) between normal heartbeats.

Results

Fever (>38.0 °C) was detected by manual or continuous measurements in 48 women. Compared to afebrile mothers, average SDNN and RMSSD in febrile mothers decreased significantly (p < 0.001) at 2 and 3 hours before fever onset, respectively. This observed HRV divergence and raw recorded vitals were applied to a logistic regression model at various time horizons, up to 4-5 hours before fever onset. Model performance increased with decreasing time horizons, and a model built using continuous vital signs as input variables consistently outperformed a model built from episodic vital signs.

Conclusions

HRV-based predictive models could identify mothers at risk for fever and infants at risk for EOS, guiding maternal antibiotic prophylaxis and neonatal monitoring.

Wearable Technologies for Pediatric Patients with Surgical Infections—More than Counting Steps?

Reliable vital sign assessments are crucial for the management of patients with infectious diseases. Wearable devices enable easy and comfortable continuous monitoring across settings, especially in pediatric patients, but information about their performance in acutely unwell children is scarce. Vital signs were continuously measured with a multi-sensor wearable device (Everion^®, Biofourmis, Zurich, Switzerland) in 21 pediatric patients during their hospitalization for appendicitis, osteomyelitis, or septic arthritis to describe acceptance and feasibility and to compare validity and reliability with conventional measurements. Using a wearable device was highly accepted and feasible for health-care workers, parents, and children. There were substantial data gaps in continuous monitoring up to 24 h. The wearable device measured heart rate and oxygen saturation reliably (mean difference, 2.5 bpm and 0.4% SpO₂) but underestimated body temperature by 1.7 °C. Data availability was suboptimal during the study period, but a good relationship was determined between wearable device and conventional measurements for heart rate and oxygen saturation. Acceptance and feasibility were high in all study groups. We recommend that wearable devices designed for medical use in children be validated in the targeted population to assure future high-quality continuous vital sign assessments in an easy and non-burdening way.

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.

The mechanistic and prognostic implications of heart rate variability analysis in patients with cirrhosis

Chronic liver damage leads to scarring of the liver tissue and ultimately a systemic illness known as cirrhosis. Patients with cirrhosis exhibit multi-organ dysfunction and high mortality. Reduced heart rate variability (HRV) is a hallmark of cirrhosis, reflecting a state of defective cardiovascular control and physiological network disruption. Several lines of evidence have revealed that decreased HRV holds prognostic information and can predict survival of patients independent of the severity of liver disease. Thus, the aim of this review is to shed light on the mechanistic and prognostic implications of HRV analysis in patients with cirrhosis. Notably, several studies have extensively highlighted the critical role systemic inflammation elicits in conferring the reduction in patients' HRV. It appears that IL-6 is likely to play a central mechanistic role, whereby its levels also correlate with manifestations, such as autonomic neuropathy and hence the partial uncoupling of the cardiac pacemaker from autonomic control. Reduced HRV has also been reported to be highly correlated with the severity of hepatic encephalopathy, potentially through systemic inflammation affecting specific brain regions, involved in both cognitive function and autonomic regulation. In general, the prognostic ability of HRV analysis holds immense potential in improving survival rates for patients with cirrhosis, as it may indeed be added to current prognostic indicators, to ultimately increase the accuracy of selecting the recipient most in need of liver transplantation. However, a network physiology approach in the future is critical to delineate the exact mechanistic basis by which decreased HRV confers poor prognosis.

The Association between Inflammatory Biomarkers and Cardiovascular Autonomic Dysfunction after Bacterial Infection

Heart rate variability (HRV) is a known measure of cardiac autonomic function. A cardiovascular autonomic dysfunction (CAD), measured as changes in HRV, is usually presented after an infectious process. The aim of the present study is to assess the association between serum inflammatory markers and CAD. For this purpose, 50 volunteers (13 of them recovering from an infection) were recruited and followed-up for 6 weeks. Their serum inflammatory biomarkers (CRP, IL1, IL4, IL6, IL10, and TNFalpha) were quantified throughout those weeks, along with their HRV resting, in response to the Valsalva maneuver, metronome breathing, standing and sustained handgrip. The correlation of within-subject changes in both HRV and inflammatory biomarkers was assessed to evaluate the concurrent changes. An inverse within-subject correlation was found between CRP and HRV in response to the Valsalva maneuver (rho (95% CI): −0.517 (−0.877 to −0.001); p = 0.032) and HRV standing (rho (95% CI): −0.490 (−0.943 to −0.036); p = 0.034). At the beginning, increased values of CRP are found along with reduced levels of HRV. Then, the CRP was reduced, accompanied by an improvement (increase) in HRV. These results suggest that CRP is a potential marker of CAD. Whether it is the cause, the consequence or a risk indicator non-causally associated is still to be determined.

Biomarkers Predicting Tissue Pharmacokinetics of Antimicrobials in Sepsis: A Review

The pathophysiology of sepsis alters drug pharmacokinetics, resulting in inadequate drug exposure and target-site concentration. Suboptimal exposure leads to treatment failure and the development of antimicrobial resistance. Therefore, we seek to optimize antimicrobial therapy in sepsis by selecting the right drug and the correct dosage. A prerequisite for achieving this goal is characterization and understanding of the mechanisms of pharmacokinetic alterations. However, most infections take place not in blood but in different body compartments. Since tissue pharmacokinetic assessment is not feasible in daily practice, we need to tailor antibiotic treatment according to the specific patient’s pathophysiological processes. The complex pathophysiology of sepsis and the ineffectiveness of current targeted therapies suggest that treatments guided by biomarkers predicting target-site concentration could provide a new therapeutic strategy. Inflammation, endothelial and coagulation activation markers, and blood flow parameters might be indicators of impaired tissue distribution. Moreover, hepatic and renal dysfunction biomarkers can predict not only drug metabolism and clearance but also drug distribution. Identification of the right biomarkers can direct drug dosing and provide timely feedback on its effectiveness. Therefore, this might decrease antibiotic resistance and the mortality of critically ill patients. This article fills the literature gap by characterizing patient biomarkers that might be used to predict unbound plasma-to-tissue drug distribution in critically ill patients. Although all biomarkers must be clinically evaluated with the ultimate goal of combining them in a clinically feasible scoring system, we support the concept that the appropriate biomarkers could be used to direct targeted antibiotic dosing.

Association between circadian variation of heart rate and mortality among critically ill patients: a retrospective cohort study

Background

Heart rate (HR) related parameters, such as HR variability, HR turbulence, resting HR, and nighttime mean HR have been recognized as independent predictors of mortality. However, the influence of circadian changes in HR on mortality remains unclear in intensive care units (ICU). The study is designed to evaluate the relationship between the circadian variation in HR and mortality risk among critically ill patients.

Methods

The present study included 4,760 patients extracted from the Multiparameter Intelligent Monitoring in Intensive Care II database. The nighttime mean HR/daytime mean HR ratio was adopted as the circadian variation in HR. According to the median value of the circadian variation in HR, participants were divided into two groups: group A (≤ 1) and group B (> 1). The outcomes included ICU, hospital, 30-day, and 1-year mortalities. The prognostic value of HR circadian variation was investigated by multivariable logistic regression models and Cox proportional hazards models.

Results

Patients in group B (n = 2,471) had higher mortality than those in group A (n = 2,289). Multivariable models revealed that the higher circadian variation in HR was associated with ICU mortality (odds ratio [OR], 1.393; 95% confidence interval [CI], 1.112–1.745; P = 0.004), hospital mortality (OR, 1.393; 95% CI, 1.112–1.745; P = 0.004), 30-day mortality (hazard ratio, 1.260; 95% CI, 1.064–1.491; P = 0.007), and 1-year mortality (hazard ratio, 1.207; 95% CI, 1.057–1.378; P = 0.005), especially in patients with higher SOFA scores.

Conclusions

The circadian variation in HR might aid in the early identification of critically ill patients at high risk of associated with ICU, hospital, 30-day, and 1-year mortalities.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12871-022-01586-9.

Effectiveness of Different Physiotherapy Protocols in Children in the Intensive Care Unit: A Randomized Clinical Trial

PURPOSE

This study aimed to investigate the effectiveness of different physical therapy protocols on the autonomic modulation of heart rate, time of invasive mechanical ventilation (IMV), and length of hospital stay.

METHODS

This was a randomized clinical study with 20 children on IMV in an intensive care unit (ICU), between July 2018 and September 2019. The control group (n = 10) performed the hospital's physical therapy protocol and the experimental group (n = 10) performed the physical therapy protocol based on physical exercise.

RESULTS

Higher values of heart rate variability were found in the experimental group, both in individual and intergroup analyses. There was a significant reduction in the time of IMV and ICU stay.

CONCLUSION

There was an improvement in heart rate variability, reduced time on mechanical ventilation and length of stay in the ICU in individuals who performed the study protocol.

Impact of Ivabradine on renal function in septic patient with early renal impairment

Background

Acute kidney injury (AKI) with sepsis increases mortality significantly. The pathophysiology of AKI during sepsis is complex and multifactorial. Lower heart rate is associated with better survival in patients with multiple organ dysfunction syndrome (MODS), a disease mostly caused by sepsis. In our study, we hypnotized that use of ivardrabine as heart rate reducing agent in septic patient with renal impairment may improve renal function.

Results

Fifty patients with sepsis with early renal impairment were divided in 1: 1 ratio to receive Ivabradine (group I) or not (group C). The average age of the included patients was almost 45 years, chest disorders were the main cause of sepsis in both groups. There were statistically significant differences between both groups in terms of reduction of heart rate group (I) (68.13 ± 3.34) versus (group C) (87.04 ± 3.23) and (P < 0.001) also, improvement in eGFR by Cystatin c in group (I) (103.32 ± 6.96) versus (group C) (96.25 ± 6.36) and (P < 0.001) also vasopressor dosage consumption (P < 0.001). As regards secondary outcomes, there were no statistically significant differences between study’s groups in terms of length of hospital stay (P = 0.390), need for hemodialysis (P = 0.384), and mortality (P = 1.000).

Conclusions

We concluded that Ivabradine as an adjuvant therapy in septic patients with renal impairment is promising agent to reduce such impairment.

Trial registration

Pan African Clinical Trial Registry: Identification number for the registry is PACTR201911806644230.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42077-021-00162-6.

The biology of stress in cancer: Applying the biobehavioral framework to adolescent and young adult oncology research

The stress response influences the development and trajectory of cancer through a host of complex neuroimmune mechanisms. Basic, translational, and clinical research has elucidated these biobehavioral connections and offers a new paradigm for scientific investigation and patient care. Using a biobehavioral approach could offer new diagnostic and therapeutic opportunities in oncology, and this approach will be particularly impactful for adolescent and young adult (AYA) patients with cancer. To date, nearly all biobehavioral oncology research has been done in the adult population. And yet, AYAs have traditionally poorer mental health and cancer-related outcomes, and thus represent a population that could benefit from parallel psychosocial and biomedical intervention. Future biobehavioral work in oncology should focus on the AYA population, integrating new cancer therapies and technology into the next generation of research.

•

Translational research efforts are clarifying the role of stress in cancer biology and patient outcomes.

•

AYAs have poorer cancer-related and mental health outcomes, but nearly all biobehavioral oncology studies are in adults.

•

Future work in immunotherapy, digital health technology, and interdisciplinary cooperation will advance the field.

•

A translational biobehavioral approach brings the paradigm of precision medicine to psychosocial care in cancer.

Investigating components of pranayama for effects on heart rate variability

OBJECTIVE

Traditional Indian breath control practices of Pranayama have been shown to increase indices of heart rate variability (HRV) that are generally held to reflect parasympathetic nervous system (PNS) tone. To our knowledge, individual components of pranayama have not been separately evaluated for impact on HRV. The objective of this study was to isolate five components of a pranayama practice and evaluate their impact on HRV.

METHODS

In a crossover clinical trial, 46 healthy adults were allocated to complete five activities in random order, over five separate visits: 1) sitting quietly; 2) self-paced deep breathing; 3) externally-paced deep breathing; 4) self-paced Sheetali/Sheetkari pranayama; and 5) externally paced Sheetali/Sheetkari pranayama RESULTS: Our final sample included 25 participants. There was a significant increase in a time-domain index of HRV, the root mean square successive differences between RR intervals (RMSSD), during the five interventions. The change in logRMSSD ranged from 0.2 to 0.5 (p < .01 in all conditions by paired t-test). Greater increases were evident during externally-paced breathing than during self-paced breathing (mean pre-during logRMSSD change of 0.50 vs. 0.36, p = .02) or sitting quietly (mean, 0.17 ms; p = .005 and 0.02 when comparing Activities 3 and 5 to Activity 1 by random intercept model with Tukey correction for multiple comparisons). Lastly, pre-during increase in RMSSD was greater for Sheetali/Sheetkari vs. deep breathing, when controlling for respiration rate, though not significantly different (p = .07 in random intercept model) CONCLUSIONS: RMSSD increased with paced breathing, deep breathing, and Sheetali/Sheetkari pranayama, reinforcing evidence of a physiologic mechanism of pranayama.

TRIAL REGISTRATION

NCT03280589 https://www.clinicaltrials.gov/ct2/show/NCT03280589?term=sheetali&draw=2&rank=1.

Heart rate n-variability (HRnV) measures for prediction of mortality in sepsis patients presenting at the emergency department

Sepsis is a potentially life-threatening condition that requires prompt recognition and treatment. Recently, heart rate variability (HRV), a measure of the cardiac autonomic regulation derived from short electrocardiogram tracings, has been found to correlate with sepsis mortality. This paper presents using novel heart rate n-variability (HRnV) measures for sepsis mortality risk prediction and comparing against current mortality prediction scores. This study was a retrospective cohort study on patients presenting to the emergency department of a tertiary hospital in Singapore between September 2014 to April 2017. Patients were included if they were above 21 years old and were suspected of having sepsis by their attending physician. The primary outcome was 30-day in-hospital mortality. Stepwise multivariable logistic regression model was built to predict the outcome, and the results based on 10-fold cross-validation were presented using receiver operating curve analysis. The final predictive model comprised 21 variables, including four vital signs, two HRV parameters, and 15 HRnV parameters. The area under the curve of the model was 0.77 (95% confidence interval 0.70–0.84), outperforming several established clinical scores. The HRnV measures may have the potential to allow for a rapid, objective, and accurate means of patient risk stratification for sepsis severity and mortality. Our exploration of the use of wealthy inherent information obtained from novel HRnV measures could also create a new perspective for data scientists to develop innovative approaches for ECG analysis and risk monitoring.

Impact of acute antioxidant supplementation on vascular function and autonomic nervous system modulation in young adults with PTSD

Posttraumatic stress disorder (PTSD) has been associated with an increase in risk of cardiovascular disease (CVD). The goal of this study was to determine if peripheral vascular dysfunction, a precursor to CVD, was present in young adults with PTSD, and if an acute antioxidant (AO) supplementation could modify this potential PTSD-induced vascular dysfunction. Thirteen individuals with PTSD were recruited for this investigation and were compared with 35 age- and sex-matched controls (CTRL). The PTSD group participated in two visits, consuming either a placebo (PTSD-PL) or antioxidants (PTSD-AO; vitamins C and E; α-lipoic acid) before their visits, whereas the CTRL subjects only participated in one visit. Upper and lower limb vascular functions were assessed via flow-mediated dilation and passive leg movement technique. Heart rate variability was utilized to assess autonomic nervous system modulation. The PTSD-PL condition, when compared with the CTRL group, reported lower arm and leg microvascular function as well as sympathetic nervous system (SNS) predominance. After acute AO supplementation, arm, but not leg, microvascular function was improved and SNS predominance was lowered to which the prior difference between PTSD group and CTRL was no longer significant. Young individuals with PTSD demonstrated lower arm and leg microvascular function as well as greater SNS predominance when compared with age- and sex-matched controls. Furthermore, this lower vascular/autonomic function was augmented by an acute AO supplementation to the level of the healthy controls, potentially implicating oxidative stress as a contributor to this blunted vascular/autonomic function.

Application of a Diagnostic Methodology of Cardiac Systems Based on the Proportions of Entropy in Normal Patients and with Different Pathologies

Introduction

Dynamical systems theory, probability, and entropy were the substrate for the development of the diagnostic and predictive methodology of adult heart dynamics.

Objective

To apply a previously developed methodology from dynamical systems, probability, and entropy in both normal and pathological subjects.

Methods

Electrocardiographic records were selected from 30 healthy subjects and 200 with different pathologies, with a length of least 18 h. Numerical attractors from dynamical attractors and the probability of occurrence of ordered pairs of consecutive heart rates were built. A calculation of entropy and its proportions was performed and statistical analysis was conducted.

Results

The normal patients' heart dynamics were evaluated according to the methodology of entropy proportions, highlighting that there are differences in normal patients with different pathologies. There was maximal level of sensitivity, specificity, and diagnostic agreement.

Conclusion

Proportional entropy constitutes a diagnostic and predictive method of heart systems, and may be useful as a tool to objectively diagnose and perform the follow-up of normal and pathological cases.

Cardiovascular Responses During Sepsis

Sepsis is the life-threatening organ dysfunction arising from a dysregulated host response to infection. Although the specific mechanisms leading to organ dysfunction are still debated, impaired tissue oxygenation appears to play a major role, and concomitant hemodynamic alterations are invariably present. The hemodynamic phenotype of affected individuals is highly variable for reasons that have been partially elucidated. Indeed, each patient's circulatory condition is shaped by the complex interplay between the medical history, the volemic status, the interval from disease onset, the pathogen, the site of infection, and the attempted resuscitation. Moreover, the same hemodynamic pattern can be generated by different combinations of various pathophysiological processes, so the presence of a given hemodynamic pattern cannot be directly related to a unique cluster of alterations. Research based on endotoxin administration to healthy volunteers and animal models compensate, to an extent, for the scarcity of clinical studies on the evolution of sepsis hemodynamics. Their results, however, cannot be directly extrapolated to the clinical setting, due to fundamental differences between the septic patient, the healthy volunteer, and the experimental model. Numerous microcirculatory derangements might exist in the septic host, even in the presence of a preserved macrocirculation. This dissociation between the macro- and the microcirculation might account for the limited success of therapeutic interventions targeting typical hemodynamic parameters, such as arterial and cardiac filling pressures, and cardiac output. Finally, physiological studies point to an early contribution of cardiac dysfunction to the septic phenotype, however, our defective diagnostic tools preclude its clinical recognition. © 2021 American Physiological Society. Compr Physiol 11:1605-1652, 2021.

The Vagal Autonomic Pathway of COVID-19 at the Crossroad of Alzheimer's Disease and Aging: A Review of Knowledge

Coronavirus Disease 2019 (COVID-19) pandemic-triggered mortality is significantly higher in older than in younger populations worldwide. Alzheimer's disease (AD) is related to aging and was recently reported to be among the major risk factors for COVID-19 mortality in older people. The symptomatology of COVID-19 indicates that lethal outcomes of infection rely on neurogenic mechanisms. The present review compiles the available knowledge pointing to the convergence of COVID-19 complications with the mechanisms of autonomic dysfunctions in AD and aging. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is prone to neuroinvasion from the lung along the vagus nerve up to the brainstem autonomic nervous centers involved in the coupling of cardiovascular and respiratory rhythms. The brainstem autonomic network allows SARS-CoV-2 to trigger a neurogenic switch to hypertension and hypoventilation, which may act in synergy with aging- and AD-induced dysautonomias, along with an inflammatory "storm". The lethal outcomes of COVID-19, like in AD and unhealthy aging, likely rely on a critical hypoactivity of the efferent vagus nerve cholinergic pathway, which is involved in lowering cardiovascular pressure and systemic inflammation tone. We further discuss the emerging evidence supporting the use of 1) the non-invasive stimulation of vagus nerve as an additional therapeutic approach for severe COVID-19, and 2) the demonstrated vagal tone index, i.e., heart rate variability, via smartphone-based applications as a non-serological low-cost diagnostic of COVID-19. These two well-known medical approaches are already available and now deserve large-scale testing on human cohorts in the context of both AD and COVID-19.

Risk factors and outcomes of sepsis-associated delirium in intensive care unit patients: A secondary data analysis

OBJECTIVE

To identify the risk factors of sepsis-associated delirium and determine their effect on intensive care unit adult patient outcomes.

DESIGN

A secondary analysis of data from system development studies.

SETTING

Korean intensive care unit patients in a university hospital who were diagnosed with sepsis.

METHODS

The risk factors for sepsis-associated delirium were classified into patient factors and sepsis clinical features and were analysed using hierarchical logistic regression analysis. Outcomes included in-hospital mortality, 30-day in-hospital mortality, duration of mechanical ventilation, length of stay in the intensive care unit, length of hospital stay, total medical expenses, discharge placement, re-hospitalisation and visits to the emergency department after discharge.

RESULTS

The risk factor for sepsis-associated delirium including patients aged 65 ≥years, dependent activity and high nursing needs (patient factors), low level of consciousness, tachypnoea, and thrombocytopaenia (clinical features of sepsis). Use of vasopressors/inotropes and albumin decreased the risk of sepsis-associated delirium. Mechanical ventilation duration was prolonged and discharge to skilled nursing facilities was increased by sepsis-associated delirium.

CONCLUSIONS

The risk factors for sepsis-associated delirium increased as the severity of condition for patients with sepsis increased. Early identification of risk factors associated with sepsis-associated delirium may improve patient outcomes.

Brainstem dysfunction in critically ill patients

The brainstem conveys sensory and motor inputs between the spinal cord and the brain, and contains nuclei of the cranial nerves. It controls the sleep-wake cycle and vital functions via the ascending reticular activating system and the autonomic nuclei, respectively. Brainstem dysfunction may lead to sensory and motor deficits, cranial nerve palsies, impairment of consciousness, dysautonomia, and respiratory failure. The brainstem is prone to various primary and secondary insults, resulting in acute or chronic dysfunction. Of particular importance for characterizing brainstem dysfunction and identifying the underlying etiology are a detailed clinical examination, MRI, neurophysiologic tests such as brainstem auditory evoked potentials, and an analysis of the cerebrospinal fluid. Detection of brainstem dysfunction is challenging but of utmost importance in comatose and deeply sedated patients both to guide therapy and to support outcome prediction. In the present review, we summarize the neuroanatomy, clinical syndromes, and diagnostic techniques of critical illness-associated brainstem dysfunction for the critical care setting.

Organ Dysfunction in Sepsis: An Ominous Trajectory From Infection To Death

Sepsis is a highly complex and lethal syndrome with highly heterogeneous clinical manifestations that makes it difficult to detect and treat. It is also one of the major and most urgent global public health challenges. More than 30 million people are diagnosed with sepsis each year, with 5 million attributable deaths and long-term sequalae among survivors. The current international consensus defines sepsis as a life-threatening organ dysfunction caused by a dysregulated host response to an infection. Over the past decades substantial research has increased the understanding of its pathophysiology. The immune response induces a severe macro and microcirculatory dysfunction that leads to a profound global hypoperfusion, injuring multiple organs. Consequently, patients with sepsis might present dysfunction of virtually any system, regardless of the site of infection. The organs more frequently affected are kidneys, liver, lungs, heart, central nervous system, and hematologic system. This multiple organ failure is the hallmark of sepsis and determines patients' course from infection to recovery or death. There are tools to assess the severity of the disease that can also help to guide treatment, like the Sequential Organ Failure Assessment (SOFA) score. However, sepsis disease process is vastly heterogeneous, which could explain why interventions targeted to directly intervene its mechanisms have shown unsuccessful results and predicting outcomes with accuracy is still elusive. Thus, it is required to implement strong public health strategies and leverage novel technologies in research to improve outcomes and mitigate the burden of sepsis and septic shock worldwide.

A Personalized Signature and Chronotherapy-Based Platform for Improving the Efficacy of Sepsis Treatment

Sepsis remains a major therapeutic challenge and is associated with a high rate of morbidity and mortality. It is a dynamic condition in which multiple parameters change over time, rendering it difficult to overcome the various injurious responses, which worsen the prognosis in these patients. The prognosis of sepsis is associated with a disbalance of compensatory responses to infectious triggers, part of which can be deleterious. Marked inter- and intra-patient variability characterizes the mechanisms that underlie sepsis progression and determine the response to therapy. In this paper, we review some of the data on the use of chronopharmacological approaches for the treatment of patients with sepsis and discuss the role of the autonomic nervous system in the mechanisms associated with immune response and chronotherapy in these patients. We describe the implementation of an individualized platform that is based on the personalized autonomic nervous system, immune, and chronobiology-derived parameters for generating a patient-tailored therapeutic regimen. The notion of overcoming the deleterious compensatory response in a highly dynamic system in sepsis is presented to ensure an improved response to current therapies.

Validation of a wearable biosensor device for vital sign monitoring in septic emergency department patients in Rwanda

Objective

Critical care capabilities needed for the management of septic patients, such as continuous vital sign monitoring, are largely unavailable in most emergency departments (EDs) in low- and middle-income country (LMIC) settings. This study aimed to assess the feasibility and accuracy of using a wireless wearable biosensor device for continuous vital sign monitoring in ED patients with suspected sepsis in an LMIC setting.

Methods

This was a prospective observational study of pediatric (≥2 mon) and adult patients with suspected sepsis at the Kigali University Teaching Hospital ED. Heart rate, respiratory rate and temperature measurements were continuously recorded using a wearable biosensor device for the duration of the patients’ ED course and compared to intermittent manually collected vital signs.

Results

A total of 42 patients had sufficient data for analysis. Mean duration of monitoring was 32.8 h per patient. Biosensor measurements were strongly correlated with manual measurements for heart rate (r = 0.87, p < 0.001) and respiratory rate (r = 0.75, p < 0.001), although were less strong for temperature (r = 0.61, p < 0.001). Mean (SD) differences between biosensor and manual measurements were 1.2 (11.4) beats/min, 2.5 (5.5) breaths/min and 1.4 (1.0)°C. Technical or practical feasibility issues occurred in 12 patients (28.6%) although were minor and included biosensor detachment, connectivity problems, removal for a radiologic study or exam, and patient/parent desire to remove the device.

Conclusions

Wearable biosensor devices can be feasibly implemented and provide accurate continuous heart rate and respiratory rate monitoring in acutely ill pediatric and adult ED patients with sepsis in an LMIC setting.

Myalgic encephalomyelitis/chronic fatigue syndrome: From pathophysiological insights to novel therapeutic opportunities

Myalgic encephalomyelitis (ME) or chronic fatigue syndrome (CFS) is a common and disabling condition with a paucity of effective and evidence-based therapies, reflecting a major unmet need. Cognitive behavioural therapy and graded exercise are of modest benefit for only some ME/CFS patients, and many sufferers report aggravation of symptoms of fatigue with exercise. The presence of a multiplicity of pathophysiological abnormalities in at least the subgroup of people with ME/CFS diagnosed with the current international consensus "Fukuda" criteria, points to numerous potential therapeutic targets. Such abnormalities include extensive data showing that at least a subgroup has a pro-inflammatory state, increased oxidative and nitrosative stress, disruption of gut mucosal barriers and mitochondrial dysfunction together with dysregulated bioenergetics. In this paper, these pathways are summarised, and data regarding promising therapeutic options that target these pathways are highlighted; they include coenzyme Q₁₀, melatonin, curcumin, molecular hydrogen and N-acetylcysteine. These data are promising yet preliminary, suggesting hopeful avenues to address this major unmet burden of illness.

Significant reduction in heart rate variability is a feature of acute decompensation of cirrhosis and predicts 90-day mortality

BACKGROUND

Heart rate variability (HRV) is reduced in cirrhosis and in conditions of systemic inflammation. Whether HRV is associated with cirrhosis decompensation and development of acute-on-chronic liver failure (ACLF) is unknown.

AIMS

To (a) validate wireless remote HRV monitoring in cirrhosis decompensation; (b) determine if severely reduced HRV is a surrogate for inflammation and progression of cirrhosis decompensation; (c) assess if measuring HRV determines prognosis in cirrhosis decompensation.

METHODS

One hundred and eleven patients at risk of cirrhosis decompensation at two clinical sites were monitored for HRV. Standard deviation of all normal beat-beat intervals (SDNN) reflecting HRV was assessed using remote monitoring (Isansys Lifetouch) and/or Holter ECG recording. Clinical outcomes and major prognostic scores were recorded during 90-day follow-up.

RESULTS

Reduced HRV denoted by lower baseline SDNN, correlated with severity of decompensation (median 14 (IQR 11-23) vs 33 (25-42); P < 0.001, decompensated patients vs stable outpatient cirrhosis). Furthermore, SDNN was significantly lower in patients developing ACLF compared to those with only decompensation (median 10 (IQR9-12) vs 16 (11-24); P = 0.02), and correlated inversely with MELD and Child-Pugh scores, and C-reactive protein (all P < 0.0001) and white cell count (P < 0.001). SDNN predicted disease progression on repeat measures and appeared an independent predictor of 90-day mortality (12 patients). An SDNN cut-off of 13.25 ms had a 98% negative predictive value.

CONCLUSIONS

This study demonstrates that remote wireless HRV monitoring identifies cirrhosis patients at high risk of developing ACLF and death, and suggests such monitoring might guide the need for early intervention in such patients. Clinical Trial number: NIHR clinical research network CPMS ID 4949.

Association mapping in biomedical time series via statistically significant shapelet mining

Motivation

Most modern intensive care units record the physiological and vital signs of patients. These data can be used to extract signatures, commonly known as biomarkers, that help physicians understand the biological complexity of many syndromes. However, most biological biomarkers suffer from either poor predictive performance or weak explanatory power. Recent developments in time series classification focus on discovering shapelets, i.e. subsequences that are most predictive in terms of class membership. Shapelets have the advantage of combining a high predictive performance with an interpretable component-their shape. Currently, most shapelet discovery methods do not rely on statistical tests to verify the significance of individual shapelets. Therefore, identifying associations between the shapelets of physiological biomarkers and patients that exhibit certain phenotypes of interest enables the discovery and subsequent ranking of physiological signatures that are interpretable, statistically validated and accurate predictors of clinical endpoints.

Results

We present a novel and scalable method for scanning time series and identifying discriminative patterns that are statistically significant. The significance of a shapelet is evaluated while considering the problem of multiple hypothesis testing and mitigating it by efficiently pruning untestable shapelet candidates with Tarone's method. We demonstrate the utility of our method by discovering patterns in three of a patient's vital signs: heart rate, respiratory rate and systolic blood pressure that are indicators of the severity of a future sepsis event, i.e. an inflammatory response to an infective agent that can lead to organ failure and death, if not treated in time.

Availability and implementation

We make our method and the scripts that are required to reproduce the experiments publicly available at https://github.com/BorgwardtLab/S3M.

Supplementary information

Supplementary data are available at Bioinformatics online.

Towards precision critical care management of blood pressure in hemorrhagic stroke patients using dynamic linear models

Finding optimal blood pressure (BP) target and BP treatment after acute ischemic or hemorrhagic strokes is an area of controversy and a significant unmet need in the critical care of stroke victims. Numerous large prospective clinical trials have been done to address this question but have generated neutral or conflicting results. One major limitation that may have contributed to so many neutral or conflicting clinical trial results is the "one-size fit all" approach to BP targets, while the optimal BP target likely varies between individuals. We address this problem with the Acute Intervention Model of Blood Pressure (AIM-BP) framework: an individualized, human interpretable model of BP and its control in the acute care setting. The framework consists of two components: one, a model of BP homeostasis and the various effects that perturb it; and two, a parameter estimator that can learn clinically important model parameters on a patient by patient basis. By estimating the parameters of the AIM-BP model for a given patient, the effectiveness of antihypertensive medication can be quantified separately from the patient's spontaneous BP trends. We hypothesize that the AIM-BP is a sufficient framework for estimating parameters of a homeostasis perturbation model of a stroke patient's BP time course and the AIM-BP parameter estimator can do so as accurately and consistently as a state-of-the-art maximum likelihood estimation method. We demonstrate that this is the case in a proof of concept of the AIM-BP framework, using simulated clinical scenarios modeled on stroke patients from real world intensive care datasets.

Heart rate variability and inflammatory markers in neonates with hypoxic-ischemic encephalopathy

To examine heart rate variability (HRV) and inflammatory markers as predictors for neurological injury in neonates undergoing therapeutic hypothermia for hypoxic-ischemic encephalopathy (HIE). We hypothesized that HRV would differentiate between infants with no/mild injury and infants with moderate/severe injury observed on MRI. Because HRV can be associated with the inflammatory cascade, cytokine concentrations were compared with the severity of brain injury indicated by MRI. Further, we studied the effect of temperature, sex, and mechanical ventilation on HRV. HRV was prospectively collected on neonates with HIE using spectral analysis for low and high frequency components (n = 16). A subset (n = 10) of neonates had serum available for inflammatory cytokine analysis obtained during cooling. Neonates were stratified into no/mild or moderate/severe injury based on MRI obtained after rewarming. Differences in HRV were identified; lower low frequency power predicted more injury on MRI. Additionally, in neonates with HIE after cooling procedure, HRV differed by gender. Elevated RANTES (CCL5) and decreased GM-CSF (Granulocyte-macrophage colony-stimulating factor) at 96 hours predicted less severe injury. In this small study, HRV differs between no/mild and moderate/severe injury in neonates with HIE. With further study, this may aid the clinician in real-time decision making. HRV differs by gender. Finally, inflammatory biomarkers may help elucidate the pathophysiology of HIE.

Combining Heart Rate Variability with Disease Severity Score Variables for Mortality Risk Stratification in Septic Patients Presenting at the Emergency Department

The emergency department (ED) serves as the first point of hospital contact for many septic patients, where risk-stratification would be invaluable. We devised a combination model incorporating demographic, clinical, and heart rate variability (HRV) parameters, alongside individual variables of the Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation II (APACHE II), and Mortality in Emergency Department Sepsis (MEDS) scores for mortality risk-stratification. ED patients fulfilling systemic inflammatory response syndrome criteria were recruited. National Early Warning Score (NEWS), Modified Early Warning Score (MEWS), quick SOFA (qSOFA), SOFA, APACHE II, and MEDS scores were calculated. For the prediction of 30-day in-hospital mortality, combination model performed with an area under the receiver operating characteristic curve of 0.91 (95% confidence interval (CI): 0.88–0.95), outperforming NEWS (0.70, 95% CI: 0.63–0.77), MEWS (0.61, 95% CI 0.53–0.69), qSOFA (0.70, 95% CI 0.63–0.77), SOFA (0.74, 95% CI: 0.67–0.80), APACHE II (0.76, 95% CI: 0.69–0.82), and MEDS scores (0.86, 95% CI: 0.81–0.90). The combination model had an optimal sensitivity and specificity of 91.4% (95% CI: 81.6–96.5%) and 77.9% (95% CI: 72.6–82.4%), respectively. A combination model incorporating clinical, HRV, and disease severity score variables showed superior predictive ability for the mortality risk-stratification of septic patients presenting at the ED.

Which heart rate variability index is an independent predictor of mortality in cirrhosis?

BACKGROUND

Liver cirrhosis is associated with reduced heart rate variability (HRV), which indicates impaired integrity of cardiovascular control in this patient population. There are several different indices for HRV quantification. The present study was designed to: 1) determine which of the HRV indices is best at predicting mortality in patients with cirrhosis; 2) verify if such ability to predict mortality is independent of the severity of hepatic failure.

METHODS

Ten minutes electrocardiogram was recorded in 74 patients with cirrhosis. Heart rate fluctuations were quantified using statistical, geometrical and non-linear analysis. The patients were followed-up for 18months and information was collected on the occurrence of death/liver transplantation.

RESULTS

During the follow-up period, 24 patients (32%) died or were transplanted for hepatic decompensation. Cox's regression analysis showed that SDNN (total HRV), cSDNN (corrected SDNN), SD1 (short-term HRV), SD2 (long-terms HRV) and spectral indices could predict survival in these patients. However, only SD2 and cSDNN were shown to be independent of MELD in predicting survival. The prognostic value of HRV indices was independent of age, gender, use of beta blockers, and the aetiology of liver disease.

CONCLUSION

Two HRV indices were identified that could predict mortality in patients with cirrhosis, independently of MELD. These indices are potentially useful tools for survival prediction.

Predicting adverse hemodynamic events in critically ill patients

PURPOSE OF REVIEW

The art of predicting future hemodynamic instability in the critically ill has rapidly become a science with the advent of advanced analytical processed based on computer-driven machine learning techniques. How these methods have progressed beyond severity scoring systems to interface with decision-support is summarized.

RECENT FINDINGS

Data mining of large multidimensional clinical time-series databases using a variety of machine learning tools has led to our ability to identify alert artifact and filter it from bedside alarms, display real-time risk stratification at the bedside to aid in clinical decision-making and predict the subsequent development of cardiorespiratory insufficiency hours before these events occur. This fast evolving filed is primarily limited by linkage of high-quality granular to physiologic rationale across heterogeneous clinical care domains.

SUMMARY

Using advanced analytic tools to glean knowledge from clinical data streams is rapidly becoming a reality whose clinical impact potential is great.

Myalgic encephalomyelitis or chronic fatigue syndrome: how could the illness develop?

A model of the development and progression of chronic fatigue syndrome (myalgic encephalomyelitis), the aetiology of which is currently unknown, is put forward, starting with a consideration of the post-infection role of damage-associated molecular patterns and the development of chronic inflammatory, oxidative and nitrosative stress in genetically predisposed individuals. The consequences are detailed, including the role of increased intestinal permeability and the translocation of commensal antigens into the circulation, and the development of dysautonomia, neuroinflammation, and neurocognitive and neuroimaging abnormalities. Increasing levels of such stress and the switch to immune and metabolic downregulation are detailed next in relation to the advent of hypernitrosylation, impaired mitochondrial performance, immune suppression, cellular hibernation, endotoxin tolerance and sirtuin 1 activation. The role of chronic stress and the development of endotoxin tolerance via indoleamine 2,3-dioxygenase upregulation and the characteristics of neutrophils, monocytes, macrophages and T cells, including regulatory T cells, in endotoxin tolerance are detailed next. Finally, it is shown how the immune and metabolic abnormalities of chronic fatigue syndrome can be explained by endotoxin tolerance, thus completing the model.

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.

Noninvasive measurements of hemodynamic, autonomic and endothelial function as predictors of mortality in sepsis: A prospective cohort study

Background and aim

Sepsis is associated with marked alterations in hemodynamic responses, autonomic dysfunction and impaired vascular function. However, to our knowledge, analysis of noninvasive markers to identify greater risk of death has not yet been investigated. Thus, our aim was to explore the prognostic utility of cardiac output (CO), stroke volume (SV), indices of vagal modulation (RMSSD and SD1), total heart rate variability (HRV) indices and FMD of brachial artery (%FMD), all measured noninvasively, in the first 24 hours of the diagnosis of sepsis.

Methods

60 patients were recruited at ICU between 2015 and 2017 and followed by 28 days. CO, SV, RR intervals were measurement. Doppler ultrasound was used to assess brachial artery FMD and the hyperemic response were obtained (%FMD). Patients were divided by survivors (SG) and nonsurvivors groups (NSG).

Results

A total of 60 patients were analysed (SG = 21 and NSG = 39). Survivors were younger (41±15 years vs. 55±11 years) and used less vasoactive drugs. As expected, APACHE and SOFA scores were lower in NSG compared to SG. In addition, higher SD1, triangular index, % FMD, velocity baseline and hyperemia flow velocity as well as lower HR values were observed in the SG, compared to NSG (P<0.05). Interestingly, RMSSD and SD1 indices were independent predictors of %FMD, ΔFMD and FMD_peak. RMSSD threshold of 10.8ms and %FMD threshold of -1 were optimal at discriminatomg survivors and nonsurvivors.

Conclusion

Noninvasive measurements of autonomic and endotelial function may be important markers of sepsis mortality, which can be easily obtained in the early stages of sepsis at the bedside.

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.

Short-term heart rate variability as a predictor of long-term survival in patients with chronic hemodialysis: A prospective cohort study

BACKGROUND

Heart rate variability (HRV), a non-invasive measurement of the sympathetic-vagal balance, has been demonstrated as a predictor of long-term survival in various patient populations. However, its predictive value in patients with end-stage renal disease (ESRD) has not been evaluated in a long-term follow-up study.

METHODS

Prospective data collected for 41 patients with chronic hemodialysis (age 59 ± 10 years, men 51.3%, diabetes mellitus 31%, and duration of dialysis 64 ± 50 months) who underwent a 5-minute electrocardiogram (ECG) recording as a baseline for frequency domain HRV analysis.

RESULTS

During a median follow-up of 150.2 months from 2003 to 2014, 15 (35.7%) patients died (3 due to cardiac causes and 12 due to non-cardiac causes). The Cox proportional hazards model suggested that the low frequency versus high frequency signal (LF/HF) of a high ratio for the HRV and diabetes mellitus were two independent predictors of mortality (hazard ratios 3.028 and 3.494; p = 0.033 and 0.022, respectively). Less reduction in MAP during dialysis showed borderline significance of long-term survival than those with larger drop (p = 0.058).

CONCLUSION

A short ECG recording and an analysis of the frequency domain of the HRV is clinically predictive of the long-term survival of patients with chronic hemodialysis.

Association between dysfunction of autonomic nervous system activity and mortality in schizophrenia

BACKGROUND

Patients with schizophrenia have a higher mortality risk than the general population. Additionally, the autonomic nervous system (ANS) activity of patients with schizophrenia is lower and more dysfunctional than that of the general population. Nonetheless, the association between ANS dysfunction and mortality in schizophrenia is unclear. The aim of this study was to investigate the association between ANS activity and mortality in schizophrenia and to evaluate the predictive values of heart rate variability for long-term survival.

METHODS

This study involves the 10-year follow-up of a sample population consisting of 59 Japanese inpatients with schizophrenia between 60 and 70 years of age from 2007 to 2016. The ANS activity of all patients was evaluated using heart rate variability in 2007.

RESULTS

Fifty-three participants could be followed up because they stayed in the hospital during the follow-up period. Of these patients, 11 died during follow-up. Their mean age at death was 70.55 ± 3.45 years. The parasympathetic activity of nonsurvivors was significantly lower than that of survivors, and multiple logistic regression analysis showed a significant association between death and parasympathetic activity.

CONCLUSION

We suggest that decreased parasympathetic activity could be associated with 10-year all-cause mortality in older schizophrenic patients.

Heart rate variability as predictor of mortality in sepsis: A systematic review

BACKGROUND

Autonomic dysregulation is one of the recognized pathophysiological mechanisms in sepsis, generating the hypothesis that heart rate variability (HRV) can be used to predict mortality in sepsis.

METHODS

This was a systematic review of studies evaluating HRV as a predictor of death in patients with sepsis. The search was performed by independent researchers in PubMed, LILACS and Cochrane, including papers in English, Portuguese or Spanish, indexed until August 20th, 2017 with at least 10 patients. Study quality was assessed by Newcastle-Ottawa Scale. To analyze the results, we divided the articles between those who measured HRV for short-term recordings (≤ 1 hour), and those who did long-term recordings (≥ 24 hours).

RESULTS

Nine studies were included with a total of 536 patients. All of them were observational studies. Studies quality varied from 4 to 7 stars in Newcastle-Ottawa Scale. The mortality rate in the studies ranged from 8 to 61%. Seven studies performed HRV analysis in short-term recordings. With the exception of one study that did not explain which group had the lowest results, all other studies showed reduction of several HRV parameters in the non-survivors in relation to the surviving septic patients. SDNN (Standard deviation of the Normal to Normal interval), TP (Total Power), VLF (Very Low Frequency Power), LF (Low Frequency Power), LF/HF (Low Frequency Power / High Frequency Power), nLF (Normalized Low Frequency Power), α1/α2 (short-term and long-term fractal scaling coefficients from DFA) and r-MSSD (Square root of the squared mean of the difference of successive NN-intervals) of the non-survivor group were reduced in relation to the survivors in at least one study. Two studies found that SDNN is associated with mortality in sepsis, even after adjusting for possible confounding factors. Three studies performed HRV analysis using long-term recordings. Only one of these studies found difference between surviving and non-surviving groups, and even so, in only one HRV parameter: LogHF.

CONCLUSIONS

Several HRV parameters are reduced in nonsurviving septic patients in short-term recording. Two studies have found that SDNN is associated with mortality in sepsis, even after adjusting for possible confounding factors.

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.

Electrocardiomatrix facilitates qualitative identification of diminished heart rate variability in critically ill patients shortly before cardiac arrest

BACKGROUND

Although heart rate variability (HRV) has diagnostic and prognostic value for the assessment of cardiac risk, HRV analysis is not routinely performed in a hospital setting. Current HRV analysis methods are primarily quantitative; such methods are sensitive to signal contamination and require extensive post hoc processing.

METHODS AND RESULTS

Raw electrocardiogram (ECG) data from the Sleep Heart Health Study was transformed into electrocardiomatrix (ECM), in which sequential cardiac cycles are aligned, in parallel, along a shared axis. Such juxtaposition facilitates the visual evaluation of beat-to-beat changes in the R-R interval without sacrificing the morphology of the native ECG signal. Diminished HRV, verified by traditional methods, was readily identifiable. We also examined data from a cohort of hospitalized patients who suffered cardiac arrest within 24 h of data acquisition, all of whom exhibited severely diminished HRV that were visually apparent on ECM display.

CONCLUSIONS

ECM streamlines the identification of depressed HRV, which may signal deteriorating patient condition.

[Septic cardiomyopathy: pathophysiology and potential new therapeutic approaches]

Sepsis is the leading cause of death in critically ill patients, and its incidence continues to rise. Sepsis was defined as a systemic inflammatory response syndrome with an identifiable focus of infection, but therapeutic strategies aimed at eliminating the inflammatory response have only modest clinical benefit. The development of a failure of one or more organs poses a major threat to the survival of patients with sepsis, and mortality in sepsis is most often attributed to multiple organ dysfunction. Accordingly, sepsis has been recently redefined as life-threatening organ dysfunction due to a dysregulated host response to infection. Cardiac dysfunction is a well-recognized important component of septic multiple organ failure and can compromise the balance between oxygen supply and demand, ultimately leading to the development of multiple organ failure. The existence of cardiac dysfunction in sepsis is associated with much higher mortality when compared with septic patients without heart problems. Dobutamine, a β₁-selective adrenoceptor agonist, has been used in septic shock for many years as an only inotrope, but limited clinical outcome measures have been provided as to advisability of the usefulness of dobutamine in septic shock management. Here we provide an overview on the possible mechanisms underlying intrinsic myocardial depression during sepsis and discuss the perspective of several inotropes for sepsis-associated cardiac dysfunction.

Heart rate variability: implications for perioperative anesthesia care

PURPOSE OF REVIEW

Heart rate variability (HRV) is a measure of the balance between both the parasympathetic and sympathetic nervous system and may provide useful information for anesthesia care providers. HRV may offer predictive information about critically ill and operative patients. Further, HRV collection provides real-time information of patient autonomic nervous system status and may allow tailoring of the analgesia for patients in the ICU and operating room.

RECENT FINDINGS

Reduced and abnormal resting HRV predict sudden and nonsudden cardiac death. Recent evidence shows that decreased HRV correlates with worsened outcomes in both trauma patients and patients with sepsis, as well as the risk of developing hypotension after induction of general anesthesia and placement of intrathecal local anesthesia. In addition, HRV appears to provide an accurate assessment of the nociception-analgesia balance in deeply sedated ICU patients and those under general anesthesia.

SUMMARY

No study has assessed the prognostic value of preoperative HRV in patients presenting for surgery. Use of HRV for patient risk stratification and intraoperative analgesia management may allow tailored perioperative care and improved outcomes. If intraoperative HRV data leads to decreased perioperative opioid use, opioid-related adverse events, a serious perioperative issue, may be decreased.

CLINICAL TRIALS REGISTRATION

Not applicable.