Mortality Prediction of ICU Cardiovascular Patient: Time-Series Analysis

It is estimated that millions of deaths occur annually, which can be prevented when early diagnosis and correct treatment are provided in the intensive care unit (ICU). In addition to monitoring and treating patients, the physician of the ICU has the task of predicting the outcome of patients and identifying them. They are also responsible for the separation of patients who use special ICUs. Because not necessarily all patients hospitalized in ICU benefit from this unit, and hospitalization in a few cases will only lead to an easier death. Therefore, developing an intelligent method that can help doctors predict the condition of patients in the ICU is very useful. This paper aims to predict the mortality of cardiovascular patients hospitalized in the ICU using cardiac signals. In the proposed method, the condition of patients is predicted 30 minutes before death using various features extracted from the electrocardiogram (ECG) and heart rate variability (HRV) signals and intelligent methods. The paper's results showed that combining morphological, linear, and nonlinear features can predict the mortality of patients with accuracy and sensitivity of 96.7±6.7% and 94.1±5.8%, respectively. As a result, accurate classification of diseases and correct prediction of patients by reducing unnecessary monitoring can help optimize ICU beds' use. According to new and advanced techniques and technologies, it is possible to predict and treat many diseases in ICU, leading to longer patient survival

Sleep-time predictors of cardiovascular complications in surgical peripheral arterial disease

ABSTRACT Patients with peripheral arterial disease (PAD) undergoing surgical revascularisation are in high risk of postoperative cardiovascular complications and death, due to advancing age and multiple comorbidities in the population. In addition, PAD needing surgery represents a severe form of systemic atherosclerosis but the exact underlying pathophysiology of acute myocardial infarction (AMI) in these patients is unclear and predicting outcome especially in the long-term is challenging. Obstructive sleep apnoea (OSA) is increasingly common in the general population and independently associated with various manifestations of cardiovascular disease or their risk factors; OSA is highly prevalent in patients with coronary artery disease (CAD), stroke, hypertension and diabetes. To expand this knowledge, we determined the prevalence and severity (in terms of the apnoeahypopnoea index, AHI) of OSA in surgical PAD as well as its impact on the incidence of major adverse cardiovascular and cerebrovascular events (MACCE) in this patient group. Heart rate variability (HRV) reflects fluctuations in sympathetic and parasympathetic activation responsible for neurocirculatory control in various physiological and pathophysiological situations. Depressed HRV is associated with increased cardiovascular morbidity and mortality following AMI and major surgery. In this study, the alterations of nocturnal HRV and their association with the severity of OSA and incidence of MACCE in patients with PAD was assessed, including the fractal correlation properties of HRV. HRV in a control group of 15 healthy subjects was also examined. Patients scheduled for sub-inguinal vascular surgery (n=84, age 67±9 years) underwent polysomnography and HRV analyses. OSA was detected in 86% of patients and in 56% it was moderate or severe. Age, male gender, depressed left ventricular function and decreasing high density lipoprotein/cholesterol ratio (HDL/Chol) predicted the presence and severity of OSA. The latter two remained significant after adjusting for age and gender. OSA with AHI ≥20/hour, used as a cut-off in the outcome analyses, predicted a higher risk of MACCE (p=0.001) along with pre-existing CAD (p=0.001), decreasing HDL/Chol (p=0.048) and <4 years history of PAD (p=0.018). HRV was altered in patients with PAD when compared to controls but the time domain measures were mostly unchanged. In the frequency domain, low frequency power was generally lower, high frequency power was mostly higher and fractal correlation was consistently lower. Very low frequency power was increased the most in patients with AHI 10-20/hour when compared to <10/hour while those with AHI ≥20/hour had lower fractal correlation in the morning. Patients suffering a MACCE had lower high frequency power during S3-4 and rapid eye movement sleep. In conclusion, OSA is associated with worsening atherosclerosis and predicts MACCE after vascular surgery. HRV alterations, although associated with PAD, have limited predictive value. Keywords: atherosclerosis, peripheral arterial disease, sleep apnoea, heart rate variabilityTIIVISTELMÄ Unenaikaiset sydänkomplikaatioiden ennustetekijät kirurgista hoitoa vaativassa perifeerisessä valtimotaudissa Perifeeristä valtimotautia sairastavilla potilailla on suuri leikkauksenjälkeisten sydänkomplikaatioiden riski johtuen yhä iäkkäämmästä väestöstä sekä lukuisista rinnakkaissairauksista. Lisäksi perifeerinen valtimotauti merkitsee vaikea-asteista yleistynyttä ateroskleroosia, mutta sydäninfarktin tarkka syntymekanismi näillä potilailla on epäselvä ja erityisesti pitkän aikavälin ennusteen arviointi on haastavaa. Obstruktiivinen uniapnea yleistyy väestössä ja sillä on itsenäinen yhteys useisiin sydän- ja verisuonisairauksiin ja niiden riskitekijöihin; uniapnea on erittäin yleinen sepelvaltimotauti-, aivohalvaus-, verenpainetauti- ja diabetespotilailla. Tämän tietopohjan laajentamiseksi tässä tutkimuksessa määritettiin uniapnean esiintyvyys ja vaikeusaste (määrittäjänä apnea-hypopneaindeksi, AHI) vaikea-asteista yleistynyttä ateroskleroosia sairastavilla potilailla sekä sen vaikutus vakavien sydän- ja aivotapahtumien ilmaantuvuuteen. Sydämen sykevaihtelu kuvastaa autonomisen hermoston toiminnan muutoksia, jotka puolestaan vastaavat verenkierron säätelystä erilaisissa fysiologisissa ja patofysiologisissa tilanteissa. Alentunut sykevaihtelu on yhteydessä lisääntyneeseen kardiovaskulaariseen sairastuvuuteen ja kuolleisuuteen sairastetun sydäninfarktin tai suuren leikkauksen jälkeen. Tässä tutkimuksessa arvioitiin yöllisen sydämen sykevaihtelun muutosten yhteyttä uniapnean vaikeusasteeseen sekä vakavien sydän- ja aivotapahtumien ilmaantuvuuteen, mukaan lukien sykevaihtelun fraktaalikorrelaatio-ominaisuudet. Tutkimuksessa analysoitiin sykevaihtelu myös 15 terveen henkilön vertailuryhmältä. Nivustason alapuoliseen verisuonileikkaukseen meneville potilaille (n=84, ikä 67±9 vuotta) tehtiin unipolygrafia ja sykevaihteluanalyysi. Uniapnea todettiin 86 %:lla potilaista ja 56 %:lla se oli kohtalainen tai vaikea. Ikä, miessukupuoli, heikentynyt vasemman kammion toiminta ja alentunut HDL-kolesterolin suhde kokonaiskolesteroliin ennustivat uniapneaa ja sen vaikeutumista; 2 viimeksi mainittua säilyivät merkitsevinä ikä- ja sukupuolivakioinnin jälkeen. AHI ≥20/tunti, joka valittiin kynnysarvoksi päätetapahtumaanalyyseihin, ennusti merkitsevästi vakavia sydän- ja aivotapahtumia (p=0.001). Muita merkitseviä tekijöitä olivat sepelvaltimotauti (p=0.001), alentunut HDL-suhde (p=0.048) ja lyhyt (alle 4 vuotta) perifeerisen valtimotaudin kesto ennen leikkaushoidon tarvetta (p=0.018). Sykevaihtelu oli muuttunut valtimotautipotilailla verrattuna kontrolleihin, mutta aikakenttäparametrit säilyivät lähes ennallaan. Pienitaajuuksinen sykevaihtelu oli yleisesti vähäisempää, suuritaajuuksinen enimmäkseen voimakkaampaa ja fraktaalikorrelaatio johdonmukaisesti heikompaa. Hyvin pienitaajuuksinen vaihtelu oli eniten lisääntynyt AHI 10-20/tunti -alaryhmässä verrattuna AHI <10/tunti -ryhmään, mutta AHI ≥20/tunti -potilailla aamun fraktaalikorrelaatio oli heikompaa. Potilaiden, jotka saivat vakavia sydän- ja aivotapahtumia, suuritaajuusvaihtelu oli heikompaa syvän unen ja vilkeunen aikana. Johtopäätöksinä todetaan, että uniapnea on yhteydessä vaikeutuvaan valtimotautiin sekä ennustaa vakavia sydän- ja aivotapahtumia verisuonileikkauksen jälkeen sykevaihtelun muutosten ennustearvon ollessa tässä aineistossa hyvin rajallinen. Avainsanat: ateroskleroosi, perifeerinen valtimotauti, uniapnea, sykevaihtel

Heart Rate Variability as a Biomarker for Predicting Stroke, Post-stroke Complications and Functionality

© The Author(s) 2018. Background: Heart rate variability (HRV) is a non-invasive measure of the function of the autonomic nervous system, and its dynamic nature may provide a means through which stroke and its associated complications may be predicted, monitored, and managed. Objective: The objective of this review is to identify and provide a critique on the most recent uses of HRV in stroke diagnosis/management and highlight areas that warrant further research. Methods: The MEDLINE, CINAHL, and OVID MEDLINE databases were canvassed using a systematic search strategy, for articles investigating the use of HRV in stroke diagnosis and management. Initial paper selections were based on title alone, and final paper inclusion was informed by a full-text critical appraisal. Results: The systematic search returned 98 records, of which 51 were unique. Following screening, 22 records were included in the final systematic review. The included papers provided some information regarding predicting incident stroke, which largely seems to be best predicted by time- and frequency-domain HRV parameters. Furthermore, post-stroke complications and functionality are similarly predicted by time- and frequency-domain parameters, as well as non-linear parameters in some instances. Conclusions: Current research provides good evidence that HRV parameters may have utility as a biomarker for stroke and for post-stroke complications and/or functionality. Future research would benefit from the integration of non-linear, and novel parameters, the hybridisation of HRV parameters, and the expansion of the utilisation of predictive regression and hazard modelling

Heart Rate Fractality Disruption as a Footprint of Subthreshold Depressive Symptoms in a Healthy Population

Psychopathology (and depression in particular) is a cardiovascular risk factor independent from any co-occurring pathology. This link is traced back to the mind-heart-body connection, whose underlying mechanisms are still not completely known. To study psychopathology in relation to the heart, it is necessary to observe the autonomic nervous system, which mediates among the parts of that connection. Its gold standard of evaluation is the study of heart rate variability (HRV). To investigate whether any association exists between the HRV parameters and sub-threshold depressive symptoms in a sample of healthy subjects

Complex systems and the technology of variability analysis

Characteristic patterns of variation over time, namely rhythms, represent a defining feature of complex systems, one that is synonymous with life. Despite the intrinsic dynamic, interdependent and nonlinear relationships of their parts, complex biological systems exhibit robust systemic stability. Applied to critical care, it is the systemic properties of the host response to a physiological insult that manifest as health or illness and determine outcome in our patients. Variability analysis provides a novel technology with which to evaluate the overall properties of a complex system. This review highlights the means by which we scientifically measure variation, including analyses of overall variation (time domain analysis, frequency distribution, spectral power), frequency contribution (spectral analysis), scale invariant (fractal) behaviour (detrended fluctuation and power law analysis) and regularity (approximate and multiscale entropy). Each technique is presented with a definition, interpretation, clinical application, advantages, limitations and summary of its calculation. The ubiquitous association between altered variability and illness is highlighted, followed by an analysis of how variability analysis may significantly improve prognostication of severity of illness and guide therapeutic intervention in critically ill patients

Physiological time-series investigations of cardiovascular regulation in healthy young adults during physical exercise.

Physiological parameters may be recorded non-invasively to gain information on cardiovascular function which can then characterise populations with various pathologies. Physical exercise produces specific autonomic nervous system (ANS) changes. There has been no comprehensive profiling of cardiovascular function during exercise or simultaneous characterisation of the influence of exercise on cardiac ventricular function and electrical activity. This work aims to address that, using a combination of physiological parameters. Between-lead agreement for ambulatory electrocardiographic (EGG) depolarisation-repolarisation (QT) interval was quantified during rest and exercise. In contrast to cardiac interval (RR) data, between-lead bias and limits of agreement for QT interval data should be quantified when reporting results from an ambulatory EGG system and between-gender QT differences should also be accounted for. EGG electrode location appears to significantly affect QT-RR hysteresis, the shortening of the post-exercise QT interval relative to that at similar heart rates during exercise or pre-exercise rest, further emphasising the need for standardisation of EGG electrode placement. Sample entropy (SampEn) measures data complexity. Few studies have compared SampEn of RR data (SampEn-RR) during exercise, whilst none have examined SampEn for the corresponding QT interval (SampEn-QT). Fractal analysis assesses data correlation and scaling structures. Detrended fluctuation analysis (DFA) provides a scaling exponent (a) which describes these properties. This has not been quantified for RR interval data during post-exercise recovery and has not been reported for QT interval data. Differences in a magnitudes for RR and QT data suggest that these quantities have different fractal properties. Exercise perturbs the resting QT-RR relationship via hysteresis. The QT variability index (QTVI) quantifies the relative autonomic influence on the atrial and ventricular myocardium during rest and exercise. QTVI is a consistent measure of cardiac ventricular function and as such appears to be a more useful index than other parameters based on RR or QT interval alone

Fractal Analysis of Cardiovascular Signals Empowering the Bioengineering Knowledge

The cardiovascular system is composed of a complex network of vessels, where highly uniform hierarchical branching structures are regulated by the anatomy and local flow requirements. Arteries bifurcate many times before they become capillaries where the scaling factor of vessel length, diameter and angle between two children branches is established at each level of recurrence. This behaviour can be easily described using a fractal scaling principle. Moreover, it was observed that the basic pattern of blood distribution is also fractal, imposed both by the anatomy of the vascular tree and the local regulation of vascular tone. In this chapter, arterial physiology was analysed, where waveform complexity of arterial pressure time series was related to arterial stiffness changes, pulse pressure variations and the presence wave reflection. Fractal dimension was used as a nonlinear measure, giving place to a ‘holistic approach of fractal dimension variations throughout the arterial network’, both in health and disease

Cardiorespiratory Function in Young Adults With a History of Covid-19 Infection

Objective. Respiratory complications may persist several months into the recovery period following COVID-19 infection. This study evaluated respiratory function and oxygen saturation variability between young adults with a history of COVID-19 infection and controls. Associations between cardiorespiratory function with potential biobehavioral correlates of COVID-19 infection were also explored.Methods. 57 adults ages 18 to 65 participated in this study (24 COVID+, 33 Control). Spirometry was used to assess pulmonary function volumes of forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), FEV1/FVC and peak expiratory flow (PEF). Exhaled nitric oxide (FeNO) was measured using the NiOX VERO, a handheld electrochemical nitric oxide analyzer and taken as a proxy of airway inflammation. Systemic inflammation levels were assessed using salivary concentrations of inflammatory biomarkers. Oxygen saturation variability was quantified via extended continuous oxygen saturation (SpO2) monitoring using linear and nonlinear analyses. Network physiology analysis was conducted to evaluate cardiorespiratory control between SpO2, heart rate (HR), respiratory rate and skin temperature signals measured by continuous ambulatory monitoring with an Equivital EQO2 LifeMonitor. Physical activity levels and sedentary time were assessed using 9-day accelerometry. COVID-19 symptom severity was assessed by participant self-report via questionnaires. Results. No group differences were observed for pulmonary function of FVC (COVID+: 4.22±1.01, C: 4.43±1.06 L, p=.663), FEV1 (COVID+: 3.45±0.72, C: 3.57±0.92 L, p=.865), PEF (COVID+: 349.63±105.54, C: 373.73±140.61 L/min, p=.370), or FeNO (COVID+: 16.61±13.04, C: 20.03±20.11 ppb, p=.285). Linear and nonlinear oxygen saturation variability did not differ between adults with a history of COVID-19 infection and controls with no history of infection (p\u3e0.05). Cardiorespiratory function measured using network analysis of did not differ between recovering COVID-19 individuals and controls (p\u3e0.05). Sedentary time was inversely associated with FEV1 (r=-.392, p=.040), PEF (r=-.579, p=.003), and IL-6 concentrations (r=- .370, p=.049). COVID-19 disease severity was inversely associated with FVC (r=-.461, p=.012) and FEV1 (r=-.365, p=.040). Number of symptoms was inversely associated with FVC (r=-.404, p=.025). Conclusions. Pulmonary function, inflammation levels and oxygen saturation variability were similar between individuals with a history of COVID-19 infection and controls without a history of COVID-19 infection. Network interactions between regulatory components of the cardiorespiratory system were also similar between recovering COVID-19 individuals and controls. Findings suggest that cardiorespiratory function and dynamic control of SpO2 may not be impaired following COVID-19 infection in young adults. Moreover, increased sedentary time and disease severity may have negative effects on pulmonary function in individuals recovering from COVID-19

Higuchi Fractal Dimension of Heart Rate Variability During Percutaneous Auricular Vagus Nerve Stimulation in Healthy and Diabetic Subjects

Analysis of heart rate variability (HRV) can be applied to assess the autonomic nervous system (ANS) sympathetic and parasympathetic activity. Since living systems are non-linear, evaluation of ANS activity is difficult by means of linear methods. We propose to apply the Higuchi fractal dimension (HFD) method for assessment of ANS activity. HFD measures complexity of the HRV signal. We analyzed 45 RR time series of 84 min duration each from nine healthy and five diabetic subjects with clinically confirmed long-term diabetes mellitus type II and with diabetic foot ulcer lasting more than 6 weeks. Based on HRV time series complexity analysis we have shown that HFD: (1) discriminates healthy subjects from patients with diabetes mellitus type II; (2) assesses the impact of percutaneous auricular vagus nerve stimulation (pVNS) on ANS activity in normal and diabetic conditions. Thus, HFD may be used during pVNS treatment, to provide stimulation feedback for on-line regulation of therapy in a fast and robust way

Do retinal microvascular abnormalities shed light on the pathophysiology of lacunar stroke?

Background. Lacunar strokes account for 25% of all ischaemic stroke but the exact nature of the causative cerebral small vessel abnormality remains unknown. Pathological studies are technically difficult and brain imaging cannot adequately characterise the cerebral small vessels. The retinal blood vessels are of similar size and physiology to the cerebral small vessels and may act as a surrogate marker for these cerebral small vessels. We therefore investigated retinal microvascular abnormalities in lacunar stroke. Methods. We performed a systematic review of retinal microvascular abnormalities in lacunar stroke to clarify associations and identify where further research was required. We then established a cohort of patients presenting with lacunar stroke with cortical stroke controls to investigate differences in retinal microvascular abnormalities between stroke subtypes. All patients had MRI brain at presentation and digital retinal photography of both eyes. We investigated the prevalence of retinopathy (hard and soft exudates or haemorrhages/microaneurysms), focal arteriolar narrowing and arteriovenous nicking . We developed, validated and used novel semi-automated techniques for measuring retinal arteriolar and venular widths, retinal arteriolar geometry (branching co-efficients (change in arteriolar cross sectional area across a bifurcation) and branching angles) and fractal dimensions (reflecting branching complexity) of the vasculature. We also assessed MRI parameters in lacunar stroke. We used multivariable analysis to correct for baseline imbalances in vascular risk factors. Results. From the systematic review we demonstrated that retinal microvascular abnormalities are associated with incident and prevalent stroke but that in general, strokes were inadequately characterised and there were no data regarding retinal microvascular abnormalities in ischaemic stroke subtypes. We recruited 253 patients, 129 lacunar strokes and 124 cortical strokes, mean age 68 years. We found no difference in the prevalence of retinopathy, arteriovenous nicking, focal arteriolar narrowing or arteriolar widths between lacunar and cortical stroke subtypes. We found that venules were wider in lacunar stroke. We found no differences in arteriolar branching co-efficients or arteriolar branching angles between lacunar and cortical strokes but found that deep white matter white matter hyperintensities on MRI were associated with increased branching co-efficients and periventricular white matter hyperintensities associated with decreased branching co-efficients. We found that the fractal dimension of the vascular tree was decreased in lacunar stroke. Furthermore we found that enlarged perivascular spaces on MRI are associated with lacunar stroke and white matter disease. Conclusions. We have clearly demonstrated that retinal microvascular abnormalities differ between lacunar and cortical stroke suggesting that a distinct small vessel vasculopathy may cause lacunar stroke. We have also identified MR markers of lacunar stroke. These results suggest that venular disease (a hitherto underresearched area) may play a role in the pathophysiology of lacunar stroke. Retinal microvascular abnormalities can act as markers for cerebral small vessel disease. We plan collaborative analyses with colleagues who have performed similar studies to further assess retinal abnormalities in lacunar stroke