Heart rate variability as early marker of multiple organ dysfunction syndrome in septic patients

Non-invasive ventral cervical magnetoneurography as a proxy of in vivo lipopolysaccharide-induced inflammation

Maintenance of autonomic homeostasis is continuously calibrated by sensory fibers of the vagus nerve and sympathetic chain that convey compound action potentials (CAPs) to the central nervous system. Lipopolysaccharide (LPS) intravenous challenge reliably elicits a robust inflammatory response that can resemble systemic inflammation and acute endotoxemia. Here, we administered LPS intravenously in nine healthy subjects while recording ventral cervical magnetoneurography (vcMNG)-derived CAPs at the rostral Right Nodose Ganglion (RNG) and the caudal Right Carotid Artery (RCA) with optically pumped magnetometers (OPM). We observed vcMNG RNG and RCA neural firing rates that tracked changes in TNF-α levels in the systemic circulation. Further, endotype subgroups based on high and low IL-6 responders segregate RNG CAP frequency (at 30-120 min) and based on high and low IL-10 response discriminate RCA CAP frequency (at 0-30 min). These vcMNG tools may enhance understanding and management of the neuroimmune axis that can guide personalized treatment based on an individual's distinct endophenotype.

Suppression by central adenosine A3 receptors of the cholinergic defense against cardiovascular aberrations of sepsis: role of PI3K/MAPKs/NFκB signaling

Introduction: Despite the established role of peripheral adenosine receptors in sepsis-induced organ dysfunction, little or no data is available on the interaction of central adenosine receptors with sepsis. The current study tested the hypothesis that central adenosine A3 receptors (A3ARs) modulate the cardiovascular aberrations and neuroinflammation triggered by sepsis and their counteraction by the cholinergic antiinflammatory pathway. Methods: Sepsis was induced by cecal ligation and puncture (CLP) in rats pre-instrumented with femoral and intracisternal (i.c.) catheters for hemodynamic monitoring and central drug administration, respectively. Results: The CLP-induced hypotension, reduction in overall heart rate variability (HRV) and sympathovagal imbalance towards parasympathetic predominance were abolished by i.v. nicotine (100 μg/kg) or i.c. VUF5574 (A3AR antagonist, 2 µg/rat). In addition, the selective A3AR agonist, 3-iodobenzyl-5'-N-methylcarboxamidoadenosine IB-MECA, 4 µg/rat, i.c.) exaggerated the hypotension and cardiac autonomic dysfunction induced by sepsis and opposed the favorable nicotine actions against these septic manifestations. Immunohistochemically, IB-MECA abolished the nicotine-mediated downregulation of NFκB and NOX2 expression in rostral ventrolateral medullary areas (RVLM) of brainstem of septic rats. The inhibitory actions of IB-MECA on nicotine responses disappeared after i.c. administration of PD98059 (MAPK-ERK inhibitor), SP600125 (MAPK-JNK inhibitor) or wortmannin (PI3K inhibitor). Moreover, infliximab (TNFα inhibitor) eliminated the IB-MECA-induced rises in RVLM-NFκB expression and falls in HRV, but not blood pressure. Conclusion: Central PI3K/MAPKs pathway mediates the A3AR counteraction of cholinergic defenses against cardiovascular and neuroinflammatory aberrations in sepsis.

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.

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.

Autonomic dysfunction as a predictor of infection in neurocritical care unit: a prospective cohort study

PURPOSE

Infection in the neurocritical care unit ( NCCU) can cause significant mortality and morbidity. Autonomic nervous system plays an important role in defense against infection. Autonomic dysfunction causing inflammatory dysregulation can potentiate infection. We aimed to study the relationship between autonomic dysfunction and occurrence of infection in neurologically ill patients.

METHODS

Fifty one patients who were on mechanical ventilation were prospectively enrolled in this study. Autonomic dysfunction was measured for three consecutive days on admission to NCCU using Ansiscope. Patients were followed up for seven days to see the occurrence of infection. Infection was defined as per centre of disease control definition.

RESULTS

A total of 386 patients were screened for eligibility. 68 patients satisfied the eligibility criteria and 51 patients were finally included in the study. The incidence of infection was 74.5%. The commonest infection was pulmonary infection (38.8%) followed by urinary tract infection (33.3%), blood stream infection(14.8%), central nervous system infection (11.1%) and wound site infection (3.7%). The degree of autonomic dysfunction (AD) percentage was more in infection group (37.7% (25.2-49.7)) compared to non infection group (23.5% (18-33.5)) and maximal on day 3 (P = 0.02). Patients with increasing trend of AD% from day 1 to day 3 had the highest infection rates. The length of NCCU stay (20(10-23) days and mortality (42.1%) was higher in infection group (p < 0.001).

CONCLUSION

AD assessment can be used as a tool to predict development of infection in NCCU. This can help triage and institute early investigation and treatment.

Heart rate complexity helps mortality prediction in the intensive care unit: A pilot study using artificial intelligence

BACKGROUND

In intensive care units (ICUs), accurate mortality prediction is crucial for effective patient management and resource allocation. The Simplified Acute Physiology Score II (SAPS-2), though commonly used, relies heavily on comprehensive clinical data and blood samples. This study sought to develop an artificial intelligence (AI) model utilizing key hemodynamic parameters to predict ICU mortality within the first 24 h and assess its performance relative to SAPS-2.

METHODS

We conducted an analysis of select hemodynamic parameters and the structure of heart rate curves to identify potential predictors of ICU mortality. A machine-learning model was subsequently trained and validated on distinct patient cohorts. The AI algorithm's performance was then compared to the SAPS-2, focusing on classification accuracy, calibration, and generalizability.

MEASUREMENTS AND MAIN RESULTS

The study included 1298 ICU admissions from March 27th, 2015, to March 27th, 2017. An additional cohort from 2022 to 2023 comprised 590 patients, resulting in a total dataset of 1888 patients. The observed mortality rate stood at 24.0%. Key determinants of mortality were the Glasgow Coma Scale score, heart rate complexity, patient age, duration of diastolic blood pressure below 50 mmHg, heart rate variability, and specific mean and systolic blood pressure thresholds. The AI model, informed by these determinants, exhibited a performance profile in predicting mortality that was comparable, if not superior, to the SAPS-2.

CONCLUSIONS

The AI model, which integrates heart rate and blood pressure curve analyses with basic clinical parameters, provides a methodological approach to predict in-hospital mortality in ICU patients. This model offers an alternative to existing tools that depend on extensive clinical data and laboratory inputs. Its potential integration into ICU monitoring systems may facilitate more streamlined mortality prediction processes.

Test-retest reliability of short- and long-term heart rate variability in individuals with spinal cord injury

STUDY DESIGN

Cross-sectional.

OBJECTIVES

To investigate test-retest reliability of heart rate variability (HRV) metrics in SCI without restriction of activity over long (24-h) and shorter durations (5-min, 10-min, 1-h, 3-h and 6-h).

SETTINGS

University hospital in Khon Kaen, Thailand.

METHODS

Forty-five participants (11 with tetraplegia and 34 with paraplegia) underwent two 24-h recordings of RR-intervals to derive time and frequency HRV metrics. Relative reliability was assessed by intraclass correlation coefficient (ICC) and absolute reliability by coefficient of variation (CV) and Bland-Altman limits of agreement (LoA).

RESULTS

For 5- and 10-min durations, eight of eleven HRV metrics had moderate to excellent reliability (ICC 0.40-0.76); the remaining three were poor (ICC < 0.4). HRV values from 1-h and 3-h durations showed moderate to excellent reliability (ICC of 0.46-0.81), except for 1-h reliability of ULF and TP (ICC of 0.06 and 0.30, respectively). Relative reliability was excellent (ICC of 0.77-0.92) for 6-h and 24-h durations in all HRV metrics. Absolute reliability improved as recording duration increased (lower CVs and narrower LoAs). Participants with high AD risk (SCI level at or above T6) showed lower test-retest reliability of HF and LF values than participants with low AD risk.

CONCLUSION

Relative reliability of HRV was excellent for 6-h and 24-h. The best absolute reliability values were for 24-h duration. Time-domain outcomes were more reliable than frequency domain outcomes. Participants with high risk of AD, particularly those with tetraplegia, showed lower reliability, especially for HF and LF.

The validity and applications of the analgesia nociception index: a narrative review

Pain refers to the subjective, unpleasant experience that is related to illness or injury. In contrast to pain, nociception refers to the physiological neural processing of noxious stimuli, such as intra-operative surgical stimuli. One novel device, the Analgesia Nociception Index (ANI), aims to objectively measure intra-operative nociception by analyzing the heart rate variability in patients undergoing surgery. Through this method of nociceptive monitoring, the ANI device aims to provide an objective, continuous evaluation of patient comfort levels and allow anesthesiologists to better manage surgical stress and patient analgesia, perhaps with even better efficacy than current practices used to assess nociception. Additionally, ANI may have clinical application in settings outside of the operating room, such as in the intensive care unit. In this narrative review, we compiled and summarized the findings of many studies that have investigated ANI's validity and applications in different clinical settings. Currently, the literature appears mostly supportive of ANI's ability to detect nociception in both surgical and non-surgical settings. However, the ability for ANI to provide clinical benefits, such as decreased intra-operative opioid use, post-operative opioid use, and post-operative pain compared to standard practices appear controversial. Because of the wide variety of methodology, clinical settings, patient populations, and limitations in these studies, more investigation of ANI is needed before any firm conclusions can be drawn on its clinical benefits.

HEART RATE VARIABILITY PARAMETERS WERE NOT ASSOCIATED WITH 30-DAY ALL-CAUSE MORTALITY IN INTENSIVE CARE UNIT PATIENTS WITH OR WITHOUT ATRIAL FIBRILLATION: A RETROSPECTIVE STUDY OF THE MIMIC-IV DATABASE

ABSTRACT

Objective: Our study aims to evaluate the association between heart rate variability (HRV) and short- and long-term prognosis in patients admitted to intensive care unit (ICU). Methods and Results: Adult patients continuously monitored for over 24 h in ICUs from the the American Medical Information Mart for Intensive Care (MIMIC)-IV Waveform Database were recruited in our study. Twenty HRV-related variables (8 time domain, 6 frequency domain, and 6 nonlinear variables) were calculated based on RR intervals. The association between HRV and all-cause mortality was assessed. Ninety-three patients met the inclusion criteria and were classified into atrial fibrillation (AF) and sinus rhythm (SR) groups, which were further divided into 30-day survivor group and nonsurvivor\groups based on their survival status. The 30-day all-cause mortality rates in AF and SR groups were 36.3% and 14.6%, respectively. All the time domain, frequency domain, and nonlinear HRV parameters did not differ significantly between survivors and nonsurvivors with or without AF (all P > 0.05). Presence of renal failure, malignancy, and elevated blood urea nitrogen level were associated with increased 30-day all-cause mortality in SR patients, while presence of sepsis, infection, higher platelet count, and magnesium level were associated with increased 30-day all-cause mortality in AF patients. Conclusions: Heart rate variability variables were not associated with increased 30-day all-cause mortality in ICU patients with or without AF.

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.

Autonomic and circulatory alterations persist despite adequate resuscitation in a 5-day sepsis swine experiment

Autonomic and vascular failures are common phenotypes of sepsis, typically characterized by tachycardia despite corrected hypotension/hypovolemia, vasopressor resistance, increased arterial stiffness and decreased peripheral vascular resistance. In a 5-day swine experiment of polymicrobial sepsis we aimed at characterizing arterial properties and autonomic mechanisms responsible for cardiovascular homeostasis regulation, with the final goal to verify whether the resuscitation therapy in agreement with standard guidelines was successful in restoring a physiological condition of hemodynamic profile, cardiovascular interactions and autonomic control. Twenty pigs were randomized to polymicrobial sepsis and protocol-based resuscitation or to prolonged mechanical ventilation and sedation without sepsis. The animals were studied at baseline, after sepsis development, and every 24 h during the 3-days resuscitation period. Beat-to-beat carotid blood pressure (BP), carotid blood flow, and central venous pressure were continuously recorded. The two-element Windkessel model was adopted to study carotid arterial compliance, systemic vascular resistance and characteristic time constant τ. Effective arterial elastance was calculated as a simple estimate of total arterial load. Cardiac baroreflex sensitivity (BRS) and low frequency (LF) spectral power of diastolic BP were computed to assess autonomic activity. Sepsis induced significant vascular and autonomic alterations, manifested as increased arterial stiffness, decreased vascular resistance and τ constant, reduced BRS and LF power, higher arterial afterload and elevated heart rate in septic pigs compared to sham animals. This compromised condition was persistent until the end of the experiment, despite achievement of recommended resuscitation goals by administered vasopressors and fluids. Vascular and autonomic alterations persist 3 days after goal-directed resuscitation in a clinically relevant sepsis model. We hypothesize that the addition of these variables to standard clinical markers may better profile patients' response to treatment and this could drive a more tailored therapy which could have a potential impact on long-term outcomes.

Predicting Time to Death After Withdrawal of Life-Sustaining Measures Using Vital Sign Variability: Derivation and Validation

To develop a predictive model using vital sign (heart rate and arterial blood pressure) variability to predict time to death after withdrawal of life-supporting measures.

Role of autonomic system imbalance in neurogenic pulmonary oedema

Neurogenic pulmonary oedema (NPE) is a life-threatening complication that develops rapidly and dramatically after an injury to the central nervous system (CNS). The autonomic system imbalance produced by severe brain damage may play an important role in the development of NPE. Activation of the sympathetic nervous system and inhibition of the vagus nerve system are essential prerequisites for autonomic system imbalance. The more severe the damage, the more pronounced the phenomenon. Sympathetic hyperactivity is associated with increased release of catecholamines from peripheral sympathetic nerve endings, which can cause dramatic changes in haemodynamics and cause pulmonary oedema. On the other hand, the abnormal inflammatory response caused by vagus nerve inhibition may also play an important role in the pathogenesis of NPE. The perspective of autonomic system imbalance seems to perfectly integrate the existing pathogenesis of NPE and can explain the entire development progression of NPE.

The Interplay between Autonomic Nervous System and Inflammation across Systemic Autoimmune Diseases

The autonomic nervous system (ANS) and the immune system are deeply interrelated. The ANS regulates both innate and adaptive immunity through the sympathetic and parasympathetic branches, and an imbalance in this system can determine an altered inflammatory response as typically observed in chronic conditions such as systemic autoimmune diseases. Rheumatoid arthritis, systemic lupus erythematosus, and systemic sclerosis all show a dysfunction of the ANS that is mutually related to the increase in inflammation and cardiovascular risk. Moreover, an interaction between ANS and the gut microbiota has direct effects on inflammation homeostasis. Recently vagal stimulation techniques have emerged as an unprecedented possibility to reduce ANS dysfunction, especially in chronic diseases characterized by pain and a decreased quality of life as well as in chronic inflammation.

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.

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.

Relationship Between Heart Rate Variability and Pulse Rate Variability Measures in Patients After Coronary Artery Bypass Graft Surgery

Background: Heart rate variability (HRV) and pulse rate variability (PRV) measures are two kinds of physiological indices that can be used to evaluate the autonomic nervous function of healthy subjects and patients with various kinds of illness.

Purpose: In this study, we compared the agreement and linear relationship between electrocardiographic signals (ECG)-derived HRV and photoplethysmographic signals (PPG)-derived right hand PRV (R-PRV) and left hand PRV (L-PRV) measures in 14 patients over 1 year after coronary artery bypass graft (CABG) surgery.

Method: The ECG and PPG signals of the patient were recorded simultaneously for 10 min in a supine position. The last 512 stationary RR intervals (RRI) and peak-to peak intervals (PPI) of pulse wave were derived for data analysis. Bland-Altman plot was used to assess the agreement among HRV and both hand PRV measures, while linear regression analysis was used to examine the relationship among corresponding measures of HRV, R-PRV, and L-PRV.

Result: The results revealed significant differences in total power (TP), very low-frequency power (VLF), low-frequency power (LF), high-frequency power (HF), and normalized VLF (VLFnorm) among HRV, R-PRV, and L-PRV. Bland-Altman plot analysis showed good agreements in almost all measures between R-PRV and L-PRV, except insufficient agreement was found in LF/HF. Insufficient agreements were found in root mean square successive difference (RMSSD), normalized HF (HFnorm), and LF/HF indices between HRV and L-PRV, and in VLFnorm, HFnorm, and LF/HF indices between HRV and R-PRV. Linear regression analysis showed that the HRV, R-PRV, and L-PRV measures were all highly correlated with one another (r = 0.94 ~ 1; p < 0.001).

Conclusion: Though PRV measures of either hand are not surrogates of HRV measures, they might still be used to evaluate the autonomic nervous functions of CABG patients due to the moderate to good agreements in most time-domain and frequency-domain HRV measures and the strong and positive correlations among HRV and both hands PRV measures in CABG patients.

Comprehensive Mechanism, Novel Markers and Multidisciplinary Treatment of Severe Acute Pancreatitis-Associated Cardiac Injury - A Narrative Review

Acute pancreatitis (AP) is one of the common acute abdominal inflammatory diseases in clinic with acute onset and rapid progress. About 20% of the patients will eventually develop into severe acute pancreatitis (SAP) characterized by a large number of inflammatory cells infiltration, gland flocculus flaky necrosis and hemorrhage, finally inducing systemic inflammatory response syndrome (SIRS) and multiple organ dysfunction syndrome (MODS). Pancreatic enzyme activation, intestinal endotoxemia (IETM), cytokine activation, microcirculation disturbance, autonomic nerve dysfunction and autophagy dysregulation all play an essential role in the occurrence and progression of SAP. Organ dysfunction is the main cause of early death in SAP. Acute kidney injury (AKI) and acute lung injury (ALI) are common, while cardiac injury (CI) is not, but the case fatality risk is high. Many basic studies have observed obvious ultrastructure change of heart in SAP, including myocardial edema, cardiac hypertrophy, myocardial interstitial collagen deposition. Moreover, in clinical practice, patients with SAP often presented various abnormal electrocardiogram (ECG) and cardiac function. Cases complicated with acute myocardial infarction and pericardial tamponade have also been reported and even result in stress cardiomyopathy. Due to the molecular mechanisms underlying SAP-associated cardiac injury (SACI) remain poorly understood, and there is no complete, unified treatment and sovereign remedy at present, this article reviews reports referring to the pathogenesis, potential markers and treatment methods of SACI in recent years, in order to improve the understanding of cardiac injury in severe pancreatitis.

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.

Early Warning of Infection in Patients Undergoing Hematopoietic Stem Cell Transplantation Using Heart Rate Variability and Serum Biomarkers

Early warning of infection is critical to reduce the risk of deterioration and mortality, especially in neutropenic patients following hematopoietic stem cell transplantation (HCT). Given that heart rate variability (HRV) is a sensitive and early marker for infection, and that serum inflammatory biomarkers can have high specificity for infection, we hypothesized their combination may be useful for accurate early warning of infection. In this study, we developed and evaluated a composite predictive model using continuous HRV with daily serum biomarker measurements to provide risk stratification of future deterioration in HCT recipients. A total of 116 ambulatory outpatients about to undergo HCT consented to collection of prospective demographic, clinical (daily vital signs), HRV (continuous electrocardiography [ECG] monitoring, laboratory [daily serum samples frozen at -80 °C]), and infection outcome variables (defined as the time of escalation of antibiotics), all from 24 hours pre-HCT to the onset of infection or 14 days post-HCT. Indications for antibiotic escalation were adjudicated as "true infection" or not by 2 blinded HCT clinicians. A composite time series of 8 HRV metrics was created for each patient, and the probability of deterioration within the next 72 hours was estimated using logistic regression modeling of composite HRV and serum biomarkers using a rule-based naïve Bayes model if the HRV-based probability exceeded a median threshold. Thirty-five patients (30%) withdrew within <24 hours owing to intolerability of ECG monitoring, leaving 81 patients, of whom 48 (59%) had antibiotic escalation adjudicated as true infection. The combined HRV and biomarker (TNF-α, IL-6, and IL-7) predictive model began increasing at ∼48 hours on average before the diagnosis of infection, could distinguish between high risk of impending infection (>90% incidence of subsequent infection within 72 hours), average risk (∼50%), and low risk (<10%), with an area under the receiver operating characteristic curve of 0.87. However, given that prophylactic predictive ECG monitoring and daily serum collection proved challenging for many patients, further refinement in measurement is necessary for further study.

Cholinergic System and Its Therapeutic Importance in Inflammation and Autoimmunity

Neurological and immunological signals constitute an extensive regulatory network in our body that maintains physiology and homeostasis. The cholinergic system plays a significant role in neuroimmune communication, transmitting information regarding the peripheral immune status to the central nervous system (CNS) and vice versa. The cholinergic system includes the neurotransmitter\ molecule, acetylcholine (ACh), cholinergic receptors (AChRs), choline acetyltransferase (ChAT) enzyme, and acetylcholinesterase (AChE) enzyme. These molecules are involved in regulating immune response and playing a crucial role in maintaining homeostasis. Most innate and adaptive immune cells respond to neuronal inputs by releasing or expressing these molecules on their surfaces. Dysregulation of this neuroimmune communication may lead to several inflammatory and autoimmune diseases. Several agonists, antagonists, and inhibitors have been developed to target the cholinergic system to control inflammation in different tissues. This review discusses how various molecules of the neuronal and non-neuronal cholinergic system (NNCS) interact with the immune cells. What are the agonists and antagonists that alter the cholinergic system, and how are these molecules modulate inflammation and immunity. Understanding the various functions of pharmacological molecules could help in designing better strategies to control inflammation and autoimmunity.

Is the heart rate variability monitoring using the analgesia nociception index a predictor of illness severity and mortality in critically ill patients with COVID-19? A pilot study

Introduction

The analysis of heart rate variability (HRV) has proven to be an important tool for the management of autonomous nerve system in both surgical and critically ill patients. We conducted this study to show the different spectral frequency and time domain parameters of HRV as a prospective predictor for critically ill patients, and in particular for COVID-19 patients who are on mechanical ventilation. The hypothesis is that most severely ill COVID-19 patients have a depletion of the sympathetic nervous system and a predominance of parasympathetic activity reflecting the remaining compensatory anti-inflammatory response.

Materials and methods

A single-center, prospective, observational pilot study which included COVID-19 patients admitted to the Surgical Intensive Care Unit was conducted. The normalized high-frequency component (HFnu), i.e. ANIm, and the standard deviation of RR intervals (SDNN), i.e. Energy, were recorded using the analgesia nociception index monitor (ANI). To estimate the severity and mortality we used the SOFA score and the date of discharge or date of death.

Results

A total of fourteen patients were finally included in the study. ANIm were higher in the non-survivor group (p = 0.003) and were correlated with higher IL-6 levels (p = 0.020). Energy was inversely correlated with SOFA (p = 0.039) and fewer survival days (p = 0.046). A limit value at 80 of ANIm, predicted mortalities with a sensitivity of 100% and specificity of 85.7%. In the case of Energy, a limit value of 0.41 ms predicted mortality with all predictive values of 71.4%.

Conclusion

A low autonomic nervous system activity, i.e. low SDNN or Energy, and a predominance of the parasympathetic system, i.e. low HFnu or ANIm, due to the sympathetic depletion in COVID-19 patients are associated with a worse prognosis, higher mortality, and higher IL-6 levels.

Low Heart Rate Variability Predicts Stroke and Other Complications in the First Six Postoperative Months After a Hip Fracture Operation

Background: One-year mortality after hip fractures is underestimated and is reported as 25%. An improved risk stratifying could contribute to a better follow up of these patients. Heart Rate Variability (HRV) is an easy point-of-care investigation and is been used in cardiology, endocrinology, and perioperative care. This observational study intended to explore relevant associations between HRV parameters and 6-months mortality and morbidity after a hip fracture. Methods: One hundred and sixty-five patients admitted to two hospitals were included, and short-time HRV measurements (5 min, and 10 min at the two hospitals, respectively) were obtained. Mortality data were gathered by means of the Norwegian central address register. Patients, close relatives of patients, and in some cases their general physicians or nursery home physicians were interviewed 6 months postoperatively regarding the incidence of pneumonia, cardiac events, or stroke. Results: One and hundred fifty-seven (95.2%) patients were followed up after 6 months post-surgery. Twenty-one (13%) died during this period. Twenty patients (13%) developed pneumonia, eight (5 %) stroke, and four (2%) myocardial infarction. No HRV parameter was associated with 6-month general mortality. However, patients who developed stroke had significantly lower High Frequency Power (HF, p < 0.001) and lower Very Low Frequency Power (VLF, p = 0.003) at inclusion compared to patients without complications. Patients who developed pneumonia had at the inclusion lower root mean square of successive differences (RMSSD, p = 0.044). Patients with a history of coronary heart disease (n = 41) showed a mortality of 7%. Mortality in this group was associated with standard deviation of beat-to-beat intervals (SDNN, p = 0.006), Total Power (TP, p = 0.009), HF (p = 0.026), and Low Frequency Power (LF, p = 0.012). Beta-blocker intake was associated with lower heart rate, but not with differences in HRV parameters. Conclusion: In this exploratory study, we present for the first-time significant associations between different preoperative HRV parameters and stroke, myocardial infarction, and pneumonia during a 6-month period after hip fracture. HRV might be a simple and effective tool to identify patients at risk that would warrant better follow-up.

Heart rate variability measures for prediction of severity of illness and poor outcome in ED patients with sepsis

INTRODUCTION

This study evaluates the utility of heart rate variability (HRV) for assessment of severity of illness and poor outcome in Emergency Department (ED) patients with sepsis. HRV measures evaluated included low frequency (LF) signal, high frequency (HF) signal, and deviations in LF and HF signal from age-adjusted reference values.

METHODS

This was a prospective, observational study. Seventy-two adult ED patients were assessed within 6 h of arrival.

RESULTS

Severity of illness as defined by sepsis subtype correlated with decreased LF signal (sepsis: 70.68 ± 22.95, severe sepsis: 54.00 ± 28.41, septic shock: 45.54 ± 23.31, p = 0.02), increased HF signal (sepsis: 27.87 ± 19.42, severe sepsis: 44.63 ± 27.29, septic shock: 47.66 ± 20.98, p = 0.01), increasingly negative deviations in LF signal (sepsis: 0.41 ± 24.53, severe sepsis: -21.43 ± 30.09, septic shock -30.39 ± 26.09, p = 0.005) and increasingly positive deviations in HF signal (sepsis: -1.86 ± 21.09, severe sepsis: 20.07 ± 29.03, septic shock: 23.6 ± 24.17, p = 0.004). Composite poor outcome correlated with decreased LF signal (p = 0.008), increased HF signal (p = 0.03), large negative deviations in LF signal (p = 0.004) and large positive deviations in HF signal (p = 0.02). Deviations in LF and HF signal from age-adjusted reference values correlated with individual measures of poor outcome with greater consistency than LF or HF signal.

DISCUSSION

Accounting for the influence of age on baseline HRV signal improves the predictive value of HRV measures in ED patients with sepsis.

Delirium in patients with hip fracture is associated with increased heart rate variability

BACKGROUND

Heart rate variability (HRV) is a method to assess the autonomic nervous system and reflects possibly central brain states. HRV has previously not been examined in patients with hip fracture and delirium.

AIMS

To explore HRV parameters in hip fracture patients with and without delirium.

METHODS

Patients admitted to Oslo University Hospital with hip fracture and sinus rhythm in electrocardiogram (ECG) were included. Delirium was diagnosed using the confusion assessment method. HRV was assessed preoperatively after a relaxing period of five minutes, by measuring an ECG signal over 5 min. Parameters in time domain (the standard deviation of the QRS distances-SDNN) and frequency domain (total power (TP), low frequency (LF), high frequency (HF) and LF/HF ratio) were calculated.

RESULTS

Seventy-five patients were included in the study, and 21 of them had subsyndromal delirium and were excluded from the analysis. Fifty-four patients with a mean age of 83.5 years (SD 8.6, 78% females) were included. Twenty-six patients (48%) had preoperative delirium, 11 (20%) developed delirium postoperatively, whereas 17 (31%) never developed delirium. SDNN, TP and HF values were significantly higher in patients with delirium compared to patients without delirium, and LF and LF/HF were lower. Patients developing postoperative delirium had decreased LF and increased HF before symptom onset.

DISCUSSION

Increased SDNN, TP and HF and decreased LF values might reflect an abnormal stress response in delirium.

CONCLUSION

HRV measurements in patients with hip fractures provide additional information beyond heart rate and might be used to identify relevant pathophysiological factors in delirium.

Complex dynamics of skin sympathetic nerve activities as a prognostic predictor for critically ill patients

BACKGROUND

The skin sympathetic nerve activity (SKNA) is a new method to measure sympathetic nerve activity by using conventional ECG electrodes. We developed a novel approach to analyze the complexity of SKNA time series under different time scales and showed its prognostic significance in patients receiving critical care.

METHODS

This study measured SKNA in patients admitted to an intensive care unit (ICU). Each recording is 10-minute long with 10000Hz sampling rate. Multi-scale fluctuation analysis (MSFA) was developed to quantify the variation within each time scale after removing the linear trend. The prognostic value of SKNA was combined with traditional prognostics scoring system to improve the predictive values.

RESULTS

155 patients were recruited. After 30 and 90 days, 30 and 48 patients expired. MSFA was significantly higher in survival group than mortality group for 30-day (0.487 ± 0.185 vs 0.401 ± 0.045, p = 0.018) and 90-day (0.499 ± 0.196 vs 0.414 ± 0.061, p = 0.001) follow-up. Sequential Organ Failure Assessment (SOFA) score was significantly lower in the survival group compared to the expired group for 30-day and 90-day (4.1 ± 2.9 vs. 5.5 ± 4.1, p = 0.032 and 3.9 ± 3.0 vs. 5.4 ± 3.5, p = 0.012). The Kaplan-Meier survival analysis showed MSFA lower than 0.401 (log-rank test:4.96, p = 0.03) or with SOFA score lower than 5 (log-rank test:5.49, p = 0.019) have a significantly higher mortality rate. A multivariate Cox regression model showed that the MSFA is an independent predictor for 30-day mortality (HR = 2.35, 1.08-5.09, p = 0.031) and 90-day mortality (HR = 1.96, 1.08-3.58, p = 0.027).

CONCLUSION

MSFA was a significant prognostic predictor for critically ill patients. MSFA adding to SOFA score could help improve risk prediction.

Prognostic value of measuring heart rate variability at the time of hospital admission in horses with colic

OBJECTIVE

To evaluate the prognostic value of measuring heart rate variability (HRV) in horses with colic at the time of admission to a referral hospital.

ANIMALS

51 horses > 1 year of age with colic (41 that survived [survivors] and 10 that died or were euthanized [nonsurvivors]).

PROCEDURES

HRV was recorded within 1 hour after admission by use of heart rate sensors with horses restrained in stocks. A 5-minute recording period was analyzed to obtain HRV measurements (eg, SD of R-R intervals [SDRR], root mean square of successive differences between R-R intervals [RMSSD], and geometric SDs determined from Poincaré plots [SD1 and SD2]). Variables associated with outcome (survival vs nonsurvival) were identified. Measurements were compared among diagnostic categories for colic (obstructive, inflammatory, or ischemic).

RESULTS

SDRR and RMSSD were significantly higher in survivors (median [25th to 75th percentile], 91.0 milliseconds [78.9 to 114.6 milliseconds] and 64.8 milliseconds [40.9 to 78.4 milliseconds], respectively) than in nonsurvivors (50.7 milliseconds [29.1 to 69.2 milliseconds] and 33.4 milliseconds [12.6 to 47.9 milliseconds], respectively). Similarly, SD1 and SD2 were significantly higher in survivors (48.3 milliseconds [28.9 to 60.9 milliseconds] and 111.3 milliseconds [93.0 to 146.6 milliseconds], respectively) than in nonsurvivors (23.7 milliseconds [8.9 to 33.9 milliseconds] and 65.1 milliseconds [33.7 to 91.9 milliseconds], respectively). The SDRR and SD2 were significantly higher for horses with obstructive colic than for horses with ischemic colic.

CONCLUSIONS AND CLINICAL RELEVANCE

Analysis of HRV in horses with colic may provide information on the underlying cause and be helpful in identifying horses less likely to survive.

Heart rate variability: Measurement and emerging use in critical care medicine

Variation in the time interval between consecutive R wave peaks of the QRS complex has long been recognised. Measurement of this RR interval is used to derive heart rate variability. Heart rate variability is thought to reflect modulation of automaticity of the sinus node by the sympathetic and parasympathetic components of the autonomic nervous system. The clinical application of heart rate variability in determining prognosis post myocardial infarction and the risk of sudden cardiac death is well recognised. More recently, analysis of heart rate variability has found utility in predicting foetal deterioration, deterioration due to sepsis and impending multiorgan dysfunction syndrome in critically unwell adults. Moreover, reductions in heart rate variability have been associated with increased mortality in patients admitted to the intensive care unit. It is hypothesised that heart rate variability reflects and quantifies the neural regulation of organ systems such as the cardiovascular and respiratory systems. In disease states, it is thought that there is an 'uncoupling' of organ systems, leading to alterations in 'inter-organ communication' and a clinically detectable reduction in heart rate variability. Despite the increasing evidence of the utility of measuring heart rate variability, there remains debate as to the methodology that best represents clinically relevant outcomes. With continuing advances in technology, our understanding of the physiology responsible for heart rate variability evolves. In this article, we review the current understanding of the physiological basis of heart rate variability and the methods available for its measurement. Finally, we review the emerging use of heart rate variability analysis in intensive care medicine and conditions in which heart rate variability has shown promise as a potential physiomarker of disease.

Augmentation of Dispersion Entropy for Handling Missing and Outlier Samples in Physiological Signal Monitoring

Entropy quantification algorithms are becoming a prominent tool for the physiological monitoring of individuals through the effective measurement of irregularity in biological signals. However, to ensure their effective adaptation in monitoring applications, the performance of these algorithms needs to be robust when analysing time-series containing missing and outlier samples, which are common occurrence in physiological monitoring setups such as wearable devices and intensive care units. This paper focuses on augmenting Dispersion Entropy (DisEn) by introducing novel variations of the algorithm for improved performance in such applications. The original algorithm and its variations are tested under different experimental setups that are replicated across heart rate interval, electroencephalogram, and respiratory impedance time-series. Our results indicate that the algorithmic variations of DisEn achieve considerable improvements in performance while our analysis signifies that, in consensus with previous research, outlier samples can have a major impact in the performance of entropy quantification algorithms. Consequently, the presented variations can aid the implementation of DisEn to physiological monitoring applications through the mitigation of the disruptive effect of missing and outlier samples.

Linking Big Data and Prediction Strategies: Tools, Pitfalls, and Lessons Learned

OBJECTIVES

Modern critical care amasses unprecedented amounts of clinical data-so called "big data"-on a minute-by-minute basis. Innovative processing of these data has the potential to revolutionize clinical prognostics and decision support in the care of the critically ill but also forces clinicians to depend on new and complex tools of which they may have limited understanding and over which they have little control. This concise review aims to provide bedside clinicians with ways to think about common methods being used to extract information from clinical big datasets and to judge the quality and utility of that information.

DATA SOURCES

We searched the free-access search engines PubMed and Google Scholar using the MeSH terms "big data", "prediction", and "intensive care" with iterations of a range of additional potentially associated factors, along with published bibliographies, to find papers suggesting illustration of key points in the structuring and analysis of clinical "big data," with special focus on outcomes prediction and major clinical concerns in critical care.

STUDY SELECTION

Three reviewers independently screened preliminary citation lists.

DATA EXTRACTION

Summary data were tabulated for review.

DATA SYNTHESIS

To date, most relevant big data research has focused on development of and attempts to validate patient outcome scoring systems and has yet to fully make use of the potential for automation and novel uses of continuous data streams such as those available from clinical care monitoring devices.

CONCLUSIONS

Realizing the potential for big data to improve critical care patient outcomes will require unprecedented team building across disparate competencies. It will also require clinicians to develop statistical awareness and thinking as yet another critical judgment skill they bring to their patients' bedsides and to the array of evidence presented to them about their patients over the course of care.

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.

Spectral analysis of heart rate variability for trauma outcome prediction: an analysis of 210 ICU multiple trauma patients

PURPOSE

This study aimed to test and compare short-term spectral HRV indices with most used trauma scorings in outcome prediction of multiple trauma, and then to explore the efficacy of their combined application.

METHODS

A prospective study was conducted for patients with blunt multiple trauma admitted to an emergency intensive care unit (ICU) between January 2016 and December 2017. Short-term spectral HRV indices on admission were measured, including normalized low-frequency power (nLF), normalized high-frequency power (nHF), and the nLF/nHF ratio. Injury severity score (ISS), new injury severity score (NISS), and revised trauma score (RTS) were evaluated for each patient, as well as probability of survival (Ps) by trauma and injury severity score (TRISS) model. The primary outcome was 30-day mortality and secondary outcomes were incidence of multiple organ dysfunction syndrome (MODS) and length of ICU stay.

RESULTS

Two hundred and ten patients were recruited. The nLF/nHF ratio, RTS, and Ps_(TRISS) were independent predictors of 30-day mortality, while nLF/nHF, NISS and RTS were independent predictors of MODS. The area under the receiver operating characteristic (ROC) curve (AUC) of nLF/nHF for 30-day mortality prediction was 0.924, comparable to RTS (0.951) and Ps_(TRISS) (0.892). AUC of nLF/nHF-RTS combination was 0.979, significantly greater than that of each alone. Combination of nLF/nHF and Ps_(TRISS) showed an increased AUC (0.984) compared to each of them. The nLF/nHF ratio presented a similar AUC (0.826) to NISS (0.818) or RTS (0.850) for MODS prediction. AUC of nLF/nHF-RTS combination was 0.884, significantly greater than that of nLF/nHF. Combination of nLF/nHF and NISS showed a greater AUC (0.868) than each alone. The nLF/nHF ratio, NISS, RTS, and Ps_(TRISS) were correlated with length of ICU stay for survivors, with correlation coefficients 0.476, 0.617, - 0.588, and - 0.539.

CONCLUSIONS

These findings suggest that the short-term spectral analysis of HRV might be a potential early tool to assess injury severity and predict outcome of multiple trauma. Combination of nLF/nHF and conventional trauma scores can provide more accuracy in outcome prediction of multiple trauma.

Spectral Analysis of Heart Rate Variability: Time Window Matters

Spectral analysis of heart rate variability (HRV) is a valuable tool for the assessment of cardiovascular autonomic function. Fast Fourier transform and autoregressive based spectral analysis are two most commonly used approaches for HRV analysis, while new techniques such as trigonometric regressive spectral (TRS) and wavelet transform have been developed. Short-term (on ECG of several minutes) and long-term (typically on ECG of 1–24 h) HRV analyses have different advantages and disadvantages. This article reviews the characteristics of spectral HRV studies using different lengths of time windows. Short-term HRV analysis is a convenient method for the estimation of autonomic status, and can track dynamic changes of cardiac autonomic function within minutes. Long-term HRV analysis is a stable tool for assessing autonomic function, describe the autonomic function change over hours or even longer time spans, and can reliably predict prognosis. The choice of appropriate time window is essential for research of autonomic function using spectral HRV analysis.

Heart rate variability as a marker of recovery from critical illness in children

Objectives

The purpose of this study was to Identify whether changes in heart rate variability (HRV) could be detected as critical illness resolves by comparing HRV from the time of pediatric intensive care unit (PICU) admission with HRV immediately prior to discharge. We also sought to demonstrate that HRV derived from electrocardiogram (ECG) data from bedside monitors can be calculated in critically-ill children using a real-time, streaming analytics platform.

Methods

This was a retrospective, observational pilot study of 17 children aged 0 to 18 years admitted to the PICU of a free-standing, academic children’s hospital. Three time-domain measures of HRV were calculated in real-time from bedside monitor ECG data and stored for analysis. Measures included: root mean square of successive differences between NN intervals (RMSSD), percent of successive NN interval differences above 50 ms (pNN50), and the standard deviation of NN intervals (SDNN).

Results

HRV values calculated from the first and last 24 hours of PICU stay were analyzed. Mixed effects models demonstrated that all three measures of HRV were significantly lower during the first 24 hours compared to the last 24 hours of PICU admission (p<0.001 for all three measures). In models exploring the relationship between time from admission and log HRV values, the predicted average HRV remained consistently higher in the last 24 hours of PICU stay compared to the first 24 hours.

Conclusion

HRV was significantly lower in the first 24 hours compared to the 24 hours preceding PICU discharge, after resolution of critical illness. This demonstrates that it is feasible to detect changes in HRV using an automated, streaming analytics platform. Continuous tracking of HRV may serve as a marker of recovery in critically ill children.

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.

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.

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 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.

A novel heart rate variability based risk prediction model for septic patients presenting to the emergency department

A quick, objective, non-invasive means of identifying high-risk septic patients in the emergency department (ED) can improve hospital outcomes through early, appropriate management. Heart rate variability (HRV) analysis has been correlated with mortality in critically ill patients. We aimed to develop a Singapore ED sepsis (SEDS) predictive model to assess the risk of 30-day in-hospital mortality in septic patients presenting to the ED. We used demographics, vital signs, and HRV parameters in model building and compared it with the modified early warning score (MEWS), national early warning score (NEWS), and quick sequential organ failure assessment (qSOFA) score.Adult patients clinically suspected to have sepsis in the ED and who met the systemic inflammatory response syndrome (SIRS) criteria were included. Routine triage electrocardiogram segments were used to obtain HRV variables. The primary endpoint was 30-day in-hospital mortality. Multivariate logistic regression was used to derive the SEDS model. MEWS, NEWS, and qSOFA (initial and worst measurements) scores were computed. Receiver operating characteristic (ROC) analysis was used to evaluate their predictive performances.Of the 214 patients included in this study, 40 (18.7%) met the primary endpoint. The SEDS model comprises of 5 components (age, respiratory rate, systolic blood pressure, mean RR interval, and detrended fluctuation analysis α2) and performed with an area under the ROC curve (AUC) of 0.78 (95% confidence interval [CI]: 0.72-0.86), compared with 0.65 (95% CI: 0.56-0.74), 0.70 (95% CI: 0.61-0.79), 0.70 (95% CI: 0.62-0.79), 0.56 (95% CI: 0.46-0.66) by qSOFA (initial), qSOFA (worst), NEWS, and MEWS, respectively.HRV analysis is a useful component in mortality risk prediction for septic patients presenting to the ED.

High-frequency power of heart rate variability can predict the outcome of thoracic surgical patients with acute respiratory distress syndrome on admission to the intensive care unit: a prospective, single-centric, case-controlled study

BACKGROUND

The morbidity and mortality of acute respiratory distress syndrome (ARDS) remains high, and the strategic focus of ARDS research has shifted toward identifying patients at high risk of mortality early in the course of illness. This study intended to identify the heart rate variability (HRV) measure that can predict the outcome of patients with ARDS on admission to the surgical intensive care unit (SICU).

METHODS

Patients who had lung or esophageal cancer surgery were included either in the ARDS group (n = 21) if they developed ARDS after surgery or in the control group (n = 11) if they did not. The ARDS patients were further stratified into survivors and non-survivors subgroups according to their outcomes. HRV measures of the patients were used for statistical analysis.

RESULTS

The mean RR interval (mRRI), high-frequency power (HFP) and product of low-/high-frequency power ratio tidal volume and tidal volume (LHR*VT) were significantly lower (p < 0.05), while the normalized HFP to VT ratio (nHFP/VT) was significantly higher in the ARDS patients (p = 0.011). The total power (TP), low-frequency power (LFP), HFP and HFP/VT were all significantly higher in the non-survived ARDS patients, whereas Richmond Agitation-Sedation Scale (RASS) was significantly lower in the non-survived ARDS patients. After adjustment for RASS, age and gender, firth logistic regression analysis identified the HFP, TP as the significant independent predictors of mortality for ARDS patients.

CONCLUSIONS

The vagal modulation of thoracic surgical patients with ARDS was enhanced as compared to that of non-ARDS patients, and the non-survived ARDS patients had higher vagal activity than those of survived ARDS patients. The vagal modulation-related parameters such as TP and HFP were independent predictors of mortality in patients with ARDS on admission to the SICU, and the HFP was found to be the best predictor of mortality for those ARDS patients. Increased vagal modulation might be an indicator for poor prognosis in critically ill patients following thoracic surgery.

Prediction and early detection of delirium in the intensive care unit by using heart rate variability and machine learning

OBJECTIVE

Delirium is an important syndrome found in patients in the intensive care unit (ICU), however, it is usually under-recognized during treatment. This study was performed to investigate whether delirious patients can be successfully distinguished from non-delirious patients by using heart rate variability (HRV) and machine learning.

APPROACH

Electrocardiography data of 140 patients was acquired during daily ICU care, and HRV data were analyzed. Delirium, including its type, severity, and etiologies, was evaluated daily by trained psychiatrists. HRV data and various machine learning algorithms including linear support vector machine (SVM), SVM with radial basis function (RBF) kernels, linear extreme learning machine (ELM), ELM with RBF kernels, linear discriminant analysis, and quadratic discriminant analysis were utilized to distinguish delirium patients from non-delirium patients.

MAIN RESULTS

HRV data of 4797 ECGs were included, and 39 patients had delirium at least once during their ICU stay. The maximum classification accuracy was acquired using SVM with RBF kernels. Our prediction method based on HRV with machine learning was comparable to previous delirium prediction models using massive amounts of clinical information.

SIGNIFICANCE

Our results show that autonomic alterations could be a significant feature of patients with delirium in the ICU, suggesting the potential for the automatic prediction and early detection of delirium based on HRV with machine learning.

Effects of Tai Chi Exercise on Cancer-Related Fatigue in Patients With Nasopharyngeal Carcinoma Undergoing Chemoradiotherapy: A Randomized Controlled Trial

CONTEXT

Tai Chi exercise has been shown to improve cancer-related fatigue (CRF) and autonomic nervous system (ANS) balance in some cancer patients or survivors; however, such effects are yet to be verified in nasopharyngeal carcinoma (NPC) patients undergoing chemoradiotherapy.

OBJECTIVES

To explore the effects of Tai Chi exercise on CRF in NPC patients undergoing chemoradiotherapy and then to evaluate ANS information indicated by heart rate variability parameters and their association with CRF.

METHODS

A randomized controlled trial of Tai Chi exercise was conducted from January 2014 to August 2015. Participants in the Tai Chi group practiced Tai Chi a one-hour session, five sessions/week during chemoradiotherapy. Participants in the control group received usual care. The primary end points were scores of the multidimensional fatigue symptom inventory-short form (MFSI-SF). Secondary end points were heart rate variability parameters, including normalized low-frequency (nLF) power, normalized high-frequency (nHF) power, and the nLF/nHF ratio, and their association with CRF.

RESULTS

One hundred fourteen patients were recruited in this study, and 83 patients completed the trial. The Tai Chi group and the control group had comparable baseline characteristics. After chemoradiotherapy, the Tai Chi group exhibited lower MFSI-SF total score and three negative subscale (general, physical, and emotional fatigue) scores and higher vigor score compared with the control group (P < 0.01 for all). The nLF/nHF ratio was significantly lower in the Tai Chi group compared to the control group after chemoradiotherapy. The MFSI-SF total score was markedly correlated with the nLF/nHF ratio.

CONCLUSION

Tai Chi exercise is conducive to alleviate CRF in NPC patients undergoing chemoradiotherapy. The improvement in ANS balance might fit into the process of Tai Chi for CRF management in this population.

Beyond HRV: attractor reconstruction using the entire cardiovascular waveform data for novel feature extraction

Advances in monitoring technology allow blood pressure waveforms to be collected at sampling frequencies of 250-1000 Hz for long time periods. However, much of the raw data are under-analysed. Heart rate variability (HRV) methods, in which beat-to-beat interval lengths are extracted and analysed, have been extensively studied. However, this approach discards the majority of the raw data.

OBJECTIVE

Our aim is to detect changes in the shape of the waveform in long streams of blood pressure data.

APPROACH

Our approach involves extracting key features from large complex data sets by generating a reconstructed attractor in a three-dimensional phase space using delay coordinates from a window of the entire raw waveform data. The naturally occurring baseline variation is removed by projecting the attractor onto a plane from which new quantitative measures are obtained. The time window is moved through the data to give a collection of signals which relate to various aspects of the waveform shape.

MAIN RESULTS

This approach enables visualisation and quantification of changes in the waveform shape and has been applied to blood pressure data collected from conscious unrestrained mice and to human blood pressure data. The interpretation of the attractor measures is aided by the analysis of simple artificial waveforms.

SIGNIFICANCE

We have developed and analysed a new method for analysing blood pressure data that uses all of the waveform data and hence can detect changes in the waveform shape that HRV methods cannot, which is confirmed with an example, and hence our method goes 'beyond HRV'.

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.

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

INTRODUCTION

One in five patients with sepsis deteriorates within 48 hours after hospital admission. Regrettably, a clear tool for the early detection of deterioration is still lacking. The SepsiVit study aims to determine whether continuous heart rate variability (HRV) measurement can provide an early warning for deterioration in patients presenting with suspected infection or sepsis to the emergency department (ED).

METHODS AND ANALYSIS

The protocol of a prospective observational study in the ED. We will include 171 adult medical patients presenting with suspected infection or sepsis and at least two systemic inflammatory response syndrome criteria. Patients with known pregnancy, cardiac transplantation or not admitted to our hospital are excluded.High sample frequency ECG signals (500 Hz), respiratory rate, blood pressure and peripheral oxygen saturation will be recorded continuously during the first 48 hours of hospitalisation using a bedside patient monitor (Philips IntelliVue MP70). Primary endpoint is patient deterioration, defined as the development of organ dysfunction, unplanned intensive care unit admission or in-hospital mortality. The ECG data will be used for offline HRV analysis. We will compare the HRV between two groups (deterioration/no deterioration) and analyse whether HRV provides an early warning for deterioration. Furthermore, we will create a multivariate predictive model for deterioration based on heart rate, respiratory rate and HRV. As planned secondary analyses, we (1) perform a subgroup analysis for patients with pneumosepsis and urosepsis and (2) determine whether HRV using lower sample frequencies (1 Hz or less) suffices to predict deterioration.

ETHICS AND DISSEMINATION

The Institutional Review Board of the University Medical Center Groningen granted a waiver for the study (METc 2015/164). Results will be disseminated through international peer-reviewed publications and conference presentations. A lay summary of the results will be provided to the study participants.

TRIAL REGISTRATION NUMBER

NTR6168; Pre-results.

Blood pressure variability as an indicator of sepsis severity in adult emergency department patients

STUDY OBJECTIVE

Quantify the correlation between blood pressure variability (BPV) and markers of illness severity: serum lactate (LAC) or Sequential Organ Failure Assessment (SOFA) scores.

METHODS

We performed a secondary analysis of data from a prospective, observational study evaluating fluid resuscitation on adult, septic, ED patients. Vital signs and fluid infusion volumes were recorded every 15min during the 3h following ED arrival. BPV was assessed via average real variability (ARV): the average of the absolute differences between consecutive BP measurements. ARV was calculated for the time periods before and after 3 fluid infusion milestones: 10-, 20-, and 30-mL/kg total body weight (TBW). Spearman's rho correlation coefficient analysis was utilized. A p-value<0.05 was considered statistically significant.

RESULTS

Forty patients were included. Mean fluid infusion was 33.7mL/kg TBW (SD 22.1). All patients received fluid infusion≥10mL/kg TBW, 25 patients received fluid infusion>20mL/kg TBW, and 16 patients received fluid infusion>30mL/kg TBW. Mean initial LAC was 4.0mmol/L (SD 3.2). Mean repeat LAC was 3.1mmol/L (SD 3.2), obtained an average of 6.6h (SD 5.3) later. Mean SOFA score was 7.0 (SD 4.4). BPV correlated with both follow-up LAC (r=0.564; p=0.023) and SOFA score (r=0.544; p=0.024) among the cohort that received a fluid infusion>20-mL/kg TBW.

CONCLUSION

With the finding of a positive correlation between BPV and markers of illness severity (LAC and SOFA scores), this pilot study introduces BPV analysis as a real-time, non-invasive tool for continuous sepsis monitoring in the ED.

Panic disorder and cardiovascular diseases: an overview

The association between panic disorder (PD) and cardiovascular diseases (CVD) has been extensively studied in recent years and, although some studies have shown anxiety disorders co-existing or increasing the risk of heart disease, no causal hypothesis has been well established. Thus, a critical review was performed of the studies that evaluated the association between PD and cardiovascular diseases; synthesizing the evidence on the mechanisms mediators that theoretically would be the responsible for the causal pathway between PD and CVD, specifically. This overview shows epidemiological studies, and discusses biological mechanisms that could link PD to CVD, such as pleiotropy, heart rate variability, unhealthy lifestyle, atherosclerosis, mental stress, and myocardial perfusion defects. This study tried to provide a comprehensive narrative synthesis of previously published information regarding PD and CVD and open new possibilities of clinical management and pathophysiological understanding. Some epidemiological studies have indicated that PD could be a risk factor for CVD, raising morbidity and mortality in PD, suggesting an association between them. These studies argue that PD pathophysiology could cause or potentiate CVD. However, there is no evidence in favour of a causal relationship between PD and CVD. Therefore, PD patients with suspicions of cardiovascular symptoms need redoubled attention.