Electrocardiographic Recordings Research Articles

A lightweight deep learning approach for detecting electrocardiographic lead misplacement

Objective. Electrocardiographic (ECG) lead misplacement can result in distorted waveforms and amplitudes, significantly impacting accurate interpretation. Although lead misplacement is a relatively low-probability event, with an incidence ranging from 0.4% to 4%, the large number of ECG records in clinical practice necessitates the development of an effective detection method. This paper aimed to address this gap by presenting a novel lead misplacement detection method based on deep learning models. Approach. We developed two novel lightweight deep learning model for limb and chest lead misplacement detection, respectively. For limb lead misplacement detection, two limb leads and V6 were used as inputs, while for chest lead misplacement detection, six chest leads were used as inputs. Our models were trained and validated using the Chapman database, with an 8:2 train-validation split, and evaluated on the PTB-XL, PTB, and LUDB databases. Additionally, we examined the model interpretability on the LUDB databases. Limb lead misplacement simulations were performed using mathematical transformations, while chest lead misplacement scenarios were simulated by interchanging pairs of leads. The detection performance was assessed using metrics such as accuracy, precision, sensitivity, specificity, and Macro F1-score. Main results. Our experiments simulated three scenarios of limb lead misplacement and nine scenarios of chest lead misplacement. The proposed two models achieved Macro F1-scores ranging from 93.42% to 99.61% on two heterogeneous test sets, demonstrating their effectiveness in accurately detecting lead misplacement across various arrhythmias. Significance. The significance of this study lies in providing a reliable open-source algorithm for lead misplacement detection in ECG recordings. The source code is available at https://github.com/wjcai/ECG_lead_check.

Characterization of heart rate variability in end-stage renal disease patients after kidney transplantation with recurrence quantification analysis.

Heart rate variability (HRV) is a noninvasive approach to studying the autonomic modulation of heart rate in experimental settings, such as active standing sympathetic stimulation. It is known that patients with end-stage renal disease during active standing have few changes in HRV dynamics, which are improved after hemodialysis. However, it is unknown whether the response to active standing is recovered after definitive treatment with kidney transplantation. This work aims to assess the change in HRV dynamics in the supine position and active standing through time and frequency-based metrics, as well as recurrence plot quantitative analysis (RQA). We studied HRV dynamics by obtaining 5-minute electrocardiographic recordings from kidney transplant recipients who underwent an active standing test. The mean duration of heartbeats and their standard deviation diminished in active standing, compared with the supine position. Also, the low-frequency component of HRV and the presence of diagonal and vertical structures in RQA were predominant. A larger estimated glomerular filtration rate was significantly correlated with broader HRV in the supine position and during active standing. The narrower HRV during active standing may indicate a sympathetic response to external stimuli, which is expected in a functional cardiovascular system, and may be influenced by renal function.

Electrocardiographic approach strategies in patients with Parkinson disease treated with deep brain stimulation.

Deep brain stimulation (DBS) is an interdisciplinary and reversible therapy that uses high-frequency electrical stimulation to correct aberrant neural pathways in motor and cognitive neurological disorders. However, the high frequency of the waves used in DBS can interfere with electrical recording devices (e.g., electrocardiogram, electroencephalogram, cardiac monitor), creating artifacts that hinder their interpretation. The compatibility of DBS with these devices varies and depends on factors such as the underlying disease and the configuration of the neurostimulator. In emergencies where obtaining an electrocardiogram is crucial, the need for more consensus on reducing electrical artifacts in patients with DBS becomes a significant challenge. Various strategies have been proposed to attenuate the artifact generated by DBS, such as changing the DBS configuration from monopolar to bipolar, temporarily deactivating DBS during electrocardiographic recording, applying frequency filters both lower and higher than those used by DBS, and using non-standard leads. However, the inexperience of medical personnel, variability in DBS models, or the lack of a controller at the time of approach limit the application of these strategies. Current evidence on their reproducibility and efficacy is limited. Due to the growing elderly population and the rising utilization of DBS, it is imperative to create electrocardiographic methods that are easily accessible and reproducible for general physicians and emergency services.

The Impact of Prenatal Alcohol Exposure on the Autonomic Nervous System and Cardiovascular System in Rats in a Sex-Specific Manner.

Fetal Alcohol Spectrum Disorder (FASD) is a consequence of prenatal alcohol exposure (PAE) associated with a range of effects, including dysmorphic features, prenatal and/or postnatal growth problems, and neurodevelopmental difficulties. Despite advances in treatment methods, there are still gaps in knowledge that highlight the need for further research. The study investigates the effect of PAE on the autonomic system, including sex differences that may aid in early FASD diagnosis, which is essential for effective interventions. During gestational days 5 to 20, five pregnant female Wistar rats were orally administered either glucose or ethanol. After 22 days, 26 offspring were born and kept with their mothers for 21 days before being isolated. Electrocardiographic recordings were taken on the 29th and 64th day. Heart rate variability (HRV) parameters were collected, including heart rate (HR), standard deviation (SD), standard deviation of normal-to-normal intervals (SDNN), and the root mean square of successive differences between normal heartbeats (RMSSD). Additionally, a biochemical analysis of basic serum parameters was performed on day 68 of the study. The study found that PAE had a significant impact on HRV. While electrolyte homeostasis remained mostly unaffected, sex differences were observed across various parameters in both control and PAE groups, highlighting the sex-specific effects of PAE. Specifically, the PAE group had lower mean heart rates, particularly among females, and higher SDNN and RMSSD values. Additionally, there was a shift towards parasympathetic activity and a reduction in heart rate entropy in the PAE group. Biochemical changes induced by PAE were also observed, including elevated levels of alanine transaminase (ALT) and aspartate aminotransferase (AST), especially in males, increased creatinine concentration in females, and alterations in lipid metabolism. PAE negatively affects the development of the autonomic nervous system, resulting in decreased heart rate and altered sympathetic activity. PAE also induces cardiovascular abnormalities with sex-specific effects, highlighting a relationship between PAE consequences and sex. Elevated liver enzymes in the PAE group may indicate direct toxic effects, while increased creatinine levels, particularly in females, may suggest an influence on nephrogenesis and vascular function. The reduced potassium content may be linked to hypothalamus-pituitary-adrenal axis overactivity.

Robust QRS detection based on simulated degenerate optical parametric oscillator-assisted neural network

Accurately detecting the depolarization QRS complex in the ventricles is a fundamental requirement for cardiovascular disease detection using electrocardiography (ECG). In contrast to traditional signal enhancement algorithms, emerging neural network approaches have shown promise for QRS detection because of their generalizability on complex data. However, the inevitable noise present during ECG recording leads to a decrease in the performance of neural networks. To enhance the robustness and performance of neural network-based QRS detectors, we propose a simulated degeneration unit (SDU)-assisted convolutional neural network (CNN). An SDU simulates the physical degeneration process of interfering optical pulses, which can effectively suppress in-band noise. Through comprehensive performance evaluations on three open-source databases, the SDU-enhanced CNN-based approach demonstrated better performance in detecting QRS complexes than other recently reported QRS detectors. Furthermore, real-world noise injection tests indicate that the optimal noise robustness boundary for the CNN equipped with SDU is 167–300% higher than that for the CNN without SDU.

Evaluation of a digital stethoscope for electrocardiographic recording in donkeys: Preliminary results

The digital stethoscope (DS) is a cost-effective single-lead digital stethoscope that allows simultaneous electrocardiographic (ECG) and phonocardiographic recordings on a smartphone. Despite its application in small animals and horses, there are currently no studies on its use in donkeys. The aim of this study was to evaluate the use of a new smartphone-based DS device in recording ECG tracings in donkeys. Standard base-apex lead ECG (sECG) and single-lead DS ECG (dECG) were simultaneously recorded for at least 30 s. Both sECG and dECG tracings were analysed by the same operator, recording heart rate, ECG waves and intervals, and the presence and duration of artefacts. Thirty-seven donkeys were included. The dECG tracings were interpretable in all the animals (100 %). The results showed perfect agreement between the sECG and dECG data for the classification of heart rhythm and P-wave polarity. Strong agreement was found in the evaluation of heart rate calculated manually and automatically by the smartphone app, QRS complex polarity, T wave polarity, and duration of the PR interval. However, no agreement was found in the evaluation of P wave duration, QRS complex duration and amplitude, and T wave duration and amplitude. In conclusion, although this is only a preliminary study, the DS was a valid, practical, and easy to use electrocardiographic tool for recording good-quality ECG tracings to assess the ECGs of donkeys in the field.

Polistemi Vera ve Esansiyel Trombositemi Tanısı Alan Hastalarda Elektrokardiyografik ve Ekokardiyografik Bulgularının Değerlendirilmesi

Background/Aims: Polycythemia vera (PV) and essential thrombocythemia (ET) are chronic myeloproliferative diseases. Along with the increase in myeloproliferative cell lines, they can cause various clinical outcomes such as arterial and venous thrombosis, pulmonary hypertension, and myocardial infarction. This study was designed to evaluate the cardiac effects of these diseases via electrocardiography and echocardiography. Methods: A total of 50 patients with a diagnosis of PV, 50 patients with a diagnosis of ET, and 50 healthy individuals as a control group were included in this study. Data on patient demographics were recorded in all subjects. All patients and control subjects had electrocardiography (ECG) recordings and routine transthoracic echocardiographic examination. Pulse wave velocity (PWV) was assessed with a Holter blood pressure device. Results: In total, 50 PV patients, 50 ET patients, and 50 control group were included in the study. The demographic characteristics of the PV, ET and control groups were similar. The PR interval was significantly shorter in control subjects than in PV and ET patients (p:0.007, p:0.024). Although the measured values were within normal limits, diastolic posterior wall thickness was significantly lower in the control group compared to PV and ET patients (p:0.019, p:0.009). PWV was significantly higher in ET patients compared to the control group (p:0.012). Conclusion: In this study, evaluating the effects of PV and ET on electrocardiography and transthoracic echocardiography; ECG parameters used to predict ventricular arrhythmias (QT, QTc, Tp-Te, Tp-Te/QT) and Pulmonary Artery Pressure showed no significant change, in opposition to existing literature. Nonetheless, similar to previous publications, PV and ET were found to negatively affect the diastolic function parameters on transthoracic echocardiography. While the aortic stiffness was significantly higher in ET patients compared to the control group, no significant difference was noted between PV patients and control subjects in terms of aortic stiffness.

Performance comparison of 6 in-hospital patient monitoring systems in the detection and alarm of ventricular cardiac arrhythmias

BackgroundPatient monitoring devices are critical in alerting potential cardiac arrhythmias during hospitalization; however, there are concerns of alarm fatigue due to high false alarm rates. ObjectiveTo evaluate sensitivity and false alarm rate of hospital-based continuous electrocardiographic (ECG) monitoring technologies. MethodsSix commonly-used multiparameter bedside monitoring systems available in the United States were evaluated: B125M (GE HealthCare), ePM10 and iPM12 (Mindray), Efficia and IntelliVue (Philips), and Life Scope (Nihon Kohden). Sensitivity was tested using ECG recordings containing 57 true ventricular tachycardia (VT) events. False positive rate testing used 205 patient-hours of ECG recordings containing no cardiac arrhythmias. Signals from ECG recordings were fed to devices simultaneously; high-severity arrhythmia alarms were tracked. Sensitivity to true VT events and false positive rates were determined. Differences were assessed using Fisher’s exact tests (sensitivity) and Z-tests (false positive rates). ResultsB125M raised 56 total alarms for 57 annotated VT events and had the highest sensitivity (98%, P<0.05), followed by iPM12 (84%), Life Scope (81%), Efficia (79%), ePM10 (77%), and IntelliVue (75%). B125M raised 20 false alarms, significantly lower (P<0.0001) than iPM12 (284), Life Scope (292), IntelliVue (304), ePM10 (324), and Efficia (493). The most common false alarm was VT, followed by non-sustained VT. ConclusionWe found significant performance differences among multiparameter bedside ECG monitoring systems using previously-collected recordings. B125M had the highest sensitivity in detecting true VT events and lowest false alarm rate. These results can assist in minimizing alarm fatigue and optimizing patient safety by careful selection of in-hospital continuous monitoring technology.

SleepMI: An AI-based screening algorithm for myocardial infarction using nocturnal electrocardiography

Myocardial infarction (MI) is a common cardiovascular disease, the early diagnosis of which is essential for effective treatment and reduced mortality. Therefore, novel methods are required for automatic screening or early diagnosis of MI, and many studies have proposed diverse conventional methods for its detection. In this study, we aimed to develop a sleep-myocardial infarction (sleepMI) algorithm for automatic screening of MI based on nocturnal electrocardiography (ECG) findings from diagnostic polysomnography (PSG) data using artificial intelligence (AI) models. The proposed sleepMI algorithm was designed using representation and ensemble learning methods and optimized via dropout and batch normalization. In the sleepMI algorithm, a deep convolutional neural network and light gradient boost machine (LightGBM) models were mixed to obtain robust and stable performance for screening MI from nocturnal ECG findings. The nocturnal ECG signal was extracted from 2,691 participants (2,331 healthy individuals and 360 patients with MI) from the PSG data of the second follow-up stage of the Sleep Heart Health Study. The nocturnal ECG signal was extracted 3 h after sleep onset and segmented at 30-s intervals for each participant. All ECG datasets were divided into training, validation, and test sets consisting of 574,729, 143,683, and 718,412 segments, respectively. The proposed sleepMI model exhibited very high performance with precision, recall, and F1-score of 99.38%, 99.38%, and 99.38%, respectively. The total mean accuracy for automatic screening of MI using a nocturnal single-lead ECG was 99.387%. MI events can be detected using conventional 12-lead ECG signals and polysomnographic ECG recordings using our model.

Heart Rate Variability-Based Prediction of Autonomic Dysreflexia After Spinal Cord Injury.

Autonomic dysreflexia (AD) is a common autonomic complication of spinal cord injury (SCI) characterized by a sudden increase is blood pressure triggered by peripheral stimulation, such as bladder distention. Iatrogenic AD events often occur during various medical procedures including urodynamic assessments (UDSs) used to evaluate lower urinary tract (LUT) function in individuals with SCI. To date, there are no established clinical practices that would allow early detection of the development of episodes of AD. Heart rate variability (HRV) is a reliable and non-invasive metric for evaluating autonomic regulation of the cardiovascular system, with demonstrated utility in people with SCI during UDSs. We aim to provide a comprehensive evaluation of cardiovascular function during UDS-induced AD using ultra-short-term HRV analysis and identify changes in cardiovascular dynamics to predict the onset of AD. We assessed cardiovascular data in a total of 24 participants with sensorimotor complete SCI above T6 (17 males, 7 females, median age = 43 [36-50] years) who experienced AD during UDS. We used continuous electrocardiographic recordings to evaluate HRV in 60 sec overlapping windows during filling cystometry. The mean of "normal-to-normal" heartbeats (meanNN), its standard deviation (SDNN), and the root mean square of successive differences (RMSSD) were calculated and used in all subsequent analyses. We found that SDNN and RMSSD diminished during the early phase of bladder filling and sharply increased during AD. Using the lowest point of statistical variability in heart rate (i.e., SDNN), we were able to predict AD events within 240 sec (percentile 25-percentile 75: 172-339 sec) before the first systolic blood pressure peak after AD onset (sensitivity = 0.667; specificity = 0.875). Our results indicated a temporary increase in sympathetic activity during the early phase of bladder filling, which is followed by an increase in parasympathetic outflow to the heart when AD occurs. These findings have significant clinical implications that extend beyond the context of UDS and demonstrate the importance of identifying early changes in HRV in order to accurately predict AD episodes in people living with SCI.

Interleukin-33/ST2 axis involvement in atrial remodeling and arrhythmogenesis

Interleukin (IL)-33, a cytokine involved in immune responses, can activate its receptor, suppression of tumorigenicity 2 (ST2), is elevated during atrial fibrillation (AF). However, the role of IL-33/ST2 signaling in atrial arrhythmia is unclear. This study explored the pathological effects of the IL-33/ST2 axis on atrial remodeling and arrhythmogenesis. Patch clamping, confocal microscopy, and Western blotting were used to analyze the electrical characteristics of and protein activity in atrial myocytes (HL-1) treated with recombinant IL-33 protein and/or ST2-neutralizing antibodies for 48 hrs. Telemetric electrocardiographic recordings, Masson's trichrome staining, and immunohistochemistry staining of the atrium were performed in mice receiving tail vein injections with nonspecific immunoglobulin (control), IL-33, and IL-33 combined with anti-ST2 antibody for 2 weeks. IL-33-treated HL-1 cells had a reduced action potential duration, lower L-type Ca2+ current, greater sarcoplasmic reticulum (SR) Ca2+ content, increased Na+/Ca2+ exchanger (NCX) current, elevation of K+ currents, and increased intracellular calcium transient. IL-33-treated HL-1 myocytes had greater activation of the calcium–calmodulin-dependent protein kinase II (CaMKII)/ryanodine receptor 2 (RyR2) axis and nuclear factor kappa B (NF-κB) / NLR family pyrin domain containing 3 (NLRP3) signaling than did control cells. IL-33 treated cells also had greater expression of Nav1.5, Kv1.5, NCX, and NLRP3 than did control cells. Pretreatment with neutralizing anti-ST2 antibody attenuated IL-33-mediated activation of CaMKII/RyR2 and NF-κB/NLRP3 signaling. IL-33-injected mice had more atrial ectopic beats and increased AF episodes, greater atrial fibrosis, and elevation of NF-κB/NLRP3 signaling than did controls or mice treated with IL-33 combined with anti-ST2 antibody. Thus, IL-33 recombinant protein treatment promotes atrial remodeling through ST2 signaling. Blocking the IL-33/ST2 axis might be an innovative therapeutic approach for patients with atrial arrhythmia and elevated serum IL-33.

Accuracy of Smartwatch Electrocardiographic Recording in the Acute Coronary Syndrome Setting: Rationale and Design of the ACS WATCH II Study.

Background: Acute Coronary Syndrome (ACS), with or without ST-segment elevation, is a major contributor to global mortality and morbidity. Swift diagnosis and treatment are vital for mitigating cardiac damage and improving long-term outcomes. The 12-lead electrocardiogram (ECG) currently serves as the gold standard for diagnosis in ACS with ST-segment elevation and may support the diagnosis in ACS without ST-segment elevation. However, the growing prevalence of smartwatches enables the acquisition of electrocardiographic data without traditional ECG equipment. While smaller studies support smartwatch ECG use, larger-scale validation within ACS remains lacking. The ACS WATCH II study aims to validate smartwatch ECG recordings for ACS. Methods: The primary objective is to validate smartwatch-obtained electrocardiographic data in patients presenting with ACS. Two cohorts of 120 patients each, presenting ACS with and without ST-segment elevation, will be assessed. Smartwatches will capture recordings of leads I, III, and V2 alongside standard ECGs. These leads, chosen due to a 97% ACS diagnosis sensitivity in previous studies, will undergo blind evaluation by two experienced external assessors against conventional ECG. Additionally, a control sample of 60 healthy individuals will be included. Conclusions: ACS WATCH II pioneers large-scale prospective validation of smartwatch ECG recordings in ACS patients. Additionally, it indirectly validates a swift diagnostic approach using three leads (I, III, and V2). This could expedite time-critical ACS diagnoses and simplify access through smartwatch-based diagnosis.

Cryoanesthesia in tambaqui Colossoma macropomum: Behavioral and electrocardiographic responses

Cryoanesthesia is a low-cost procedure that has advantages for use in fish, however, there are only a few studies dealing with the electrophysiological evaluation and its safety-related aspects. The relationship between behavior and electrocardiographic activity allows for the monitoring of functional changes in cardiac activity in fish submitted to low temperatures. This study aimed to describe the behavior and cardiac effects of cryoanesthesia in juvenile tambaqui (Colossoma macropomum) through electrocardiographic assessment. For this purpose, 27 juveniles of tambaqui (28.9 ± 4.2 g) were used and essayed into two experiments. Experiment 1: behavioral evaluation (n = 9) and Experiment 2: electrocardiographic recordings with control group (n = 9), and fish submitted to water at 5 °C in baths followed by subsequent recovery at a temperature of 26 ± 2 °C (n = 9). Each cardiac activity recording lasted 1200 s, after which fish were immediately transferred to a bath in water at 26 ± 2 °C, for 600 s. Heart rate, QRS amplitude, QRS complex duration and RR, PQ and QT intervals were analyzed. The results showed that four tracing patterns emerged which characterized the induction phases of cryoanesthesia throughout exposure to water at 5 °C. In phase 1, there was a decrease in the amplitude of the QRS complex. In phase 2, there was an increase in the amplitude of the QRS complex and maintenance of sinus rhythm. Phase 3 showed a gradual loss of cardiac function with the onset of an atrioventricular blockade. In phase 4, a cardiac arrest occurred, albeit reversible. Heart rate decreased as exposure time was longer at low temperatures. The fish recovered completely from cryoanesthesia after the increase in temperature, showing normal heartbeats, and QRS complex duration, QT, RR, and HR intervals being restored with maintenance of sinus rhythm, indicating recovery of fish hemodynamics. Overall, tambaqui juveniles at 5 °C showed a time-dependent and gradual reduction of motor activity with loss of postural reflex and immobility. Cardiac response was a function of temperature and progressed to a reversible cardiac arrest. During recovery, stages similar to those of induction were observed, but in the opposite direction, until recovery of the postural reflex. Cryoanesthesia can be used as an alternative method for the immobilization of C. macropomum.

Direct and indirect effects of adiposity on markers of autonomic nervous system activity in older adults.

Several cardiovascular disease (CVD) risk factors (e.g., hypertension, poor glycemic control) can affect and be affected by autonomic nervous system (ANS) activity. Since excess adiposity can influence CVD development through its effect on hypertension and diabetes mellitus, it is important to determine how adiposity and altered ANS activity are related. The present study employed structural equation modeling to investigate the relation between adiposity and ANS activity both directly and indirectly through biological variables typically associated with glycemic impairment and cardiac stress in older adults. Utilizing the Atherosclerosis Risk in Communities (ARIC) dataset, 1,145 non-smoking adults (74±4.8 yrs, 62.8% female) free from known CVD, hypertension, and diabetes and not currently taking beta-blockers were evaluated for fasting blood glucose (FBG), insulin, and HbA1c concentrations, waist circumference (WC), blood pressure (BP), and markers of ANS activity. WC was recorded just above the iliac crest and was used to reflect central adiposity. Resting 2-minute electrocardiograph recordings, pulse wave velocity, and ankle-brachial index data were used to assess the root mean square of successive differences in RR intervals (RMSSD) and the pre-ejection period (PEP), markers of parasympathetic and sympathetic activity, respectively. FBG, insulin, and HbA1c inferred a latent variable termed glycemic impairment (GI), whereas heart rate and diastolic BP inferred a latent variable termed cardiac stress (CS). The structural equation model fit was acceptable [root mean square error of approximation = 0.050 (90% CI = .036, .066), comparative fit index = .970, Tucker Lewis Index = 0.929], with adiposity having both significant direct (β = 0.208, p = 0.018) and indirect (β = -.217, p = .041) effects on PEP through GI. Adiposity displayed no significant direct effect on RMSSD. CS displayed a significant pathway (β = -0.524, p = 0.035) on RMSSD, but the indirect effect of WC on RMSSD through CS did not reach statistical significance (β = -0.094, p = 0.137). These results suggest that adiposity's relation to ANS activity is multifaceted, as increased central adiposity had opposing direct and indirect effects on markers of sympathetic activity in this population of older adults.

Registered nurses' knowledge and interpretation of ECG rhythms: A cross-sectional study.

Electrocardiographic (ECG) monitoring and recording are seen as the most commonly used non-invasive diagnostic tool to identify cardiac arrhythmia and myocardial damage in the clinical setting. There is an expectation that critical care nurses are ideally trained to interpret abnormalities and morphology in the ECG more proficiently than nurses from general ward areas. However, the ability to interpret and recognise ECG abnormalities is dependent on which critical care area nurses are currently working in and their level of experience. The aim of this study was to investigate registered nurses' knowledge in being able to identify and interpret select electrocardiographic rhythms. This was a cross-sectional study that evaluated registered nurses' knowledge of electrocardiogram rhythm identification and interpretation. A convenience sample of 105 registered nurses currently enrolled in a 2-year Master's programme leading to critical care specialism and advanced practice nurse award were recruited. A 20-item multiple choice questionnaire that provided examples of electrocardiogram rhythm (n=14) abnormalities and rhythm abnormalities caused by electrolyte disturbances (n=6) RESULTS: The study included registered nurses from critical care and general ward areas. The overall results were poor with only 55% of questions answered correctly. Coronary care nurses scored the highest in identifying ECG rhythms (12/20 ± 1.58; p < .001). When ECG abnormalities associated with electrolyte imbalances were analysed, both groups were unable to identify the effects of hypokalaemia and hypomagnesaemia effectively (p = .748). Length of time as a registered nurse (r = -0.304, p = .002) and length of time in current work environment were weakly correlated (r = -0.328, p = .001). Having a critical care background showed a positive relationship with nursing knowledge of ECG rhythm identification (r = 0.614, p < .001). The results of this study demonstrate that nurses have a poor knowledge of ECG rhythm identification and interpretation, a consistent finding from other work. A possible solution is a revamp of education and training associated with ECG recognition and morphology. Monitoring and assessing ECG morphology provide important details about cardio-electroconductive stability, especially with fluctuations in serum electrolyte levels seen in critical illness or trauma. For this, critical nurses must improve their proficiency through education/training or internal quality improvement activities in detecting abnormalities associated with ECG changes beyond those most easily recognizable rhythms such as atrial fibrillation or ventricular tachycardia.

Novel Entropy-Based Metrics for Long-Term Atrial Fibrillation Recurrence Prediction Following Surgical Ablation: Insights from Preoperative Electrocardiographic Analysis.

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia often treated concomitantly with other cardiac interventions through the Cox-Maze procedure. This highly invasive intervention is still linked to a long-term recurrence rate of approximately 35% in permanent AF patients. The aim of this study is to preoperatively predict long-term AF recurrence post-surgery through the analysis of atrial activity (AA) organization from non-invasive electrocardiographic (ECG) recordings. A dataset comprising ECGs from 53 patients with permanent AF who had undergone Cox-Maze concomitant surgery was analyzed. The AA was extracted from the lead V1 of these recordings and then characterized using novel predictors, such as the mean and standard deviation of the relative wavelet energy (RWEm and RWEs) across different scales, and an entropy-based metric that computes the stationary wavelet entropy variability (SWEnV). The individual predictors exhibited limited predictive capabilities to anticipate the outcome of the procedure, with the SWEnV yielding a classification accuracy (Acc) of 68.07%. However, the assessment of the RWEs for the seventh scale (RWEs7), which encompassed frequencies associated with the AA, stood out as the most promising individual predictor, with sensitivity (Se) and specificity (Sp) values of 80.83% and 67.09%, respectively, and an Acc of almost 75%. Diverse multivariate decision tree-based models were constructed for prediction, giving priority to simplicity in the interpretation of the forecasting methodology. In fact, the combination of the SWEnV and RWEs7 consistently outperformed the individual predictors and excelled in predicting post-surgery outcomes one year after the Cox-Maze procedure, with Se, Sp, and Acc values of approximately 80%, thus surpassing the results of previous studies based on anatomical predictors associated with atrial function or clinical data. These findings emphasize the crucial role of preoperative patient-specific ECG signal analysis in tailoring post-surgical care, enhancing clinical decision making, and improving long-term clinical outcomes.

Sorting ECGs by lag irreversibility

In this work we introduce the lag irreversibility function as a method to assess time-irreversibility in discrete time series. It quantifies the degree of time-asymmetry for the joint probability function of the state variable under study and the state variable lagged in time. We test its performance in a time-irreversible Markov chain model for which theoretical results are known. Moreover, we use our approach to analyze electrocardiographic recordings of four groups of subjects: healthy young individuals, healthy elderly individuals, and persons with two different disease conditions, namely, congestive heart failure and atrial fibrillation. We find that by studying jointly the variability of the amplitudes of the different waves in the electrocardiographic signals, one can obtain an efficient method to discriminate between the groups already mentioned. Finally, we test the accuracy of our method using the ROC analysis.

Predictive Model of All-Cause Death in Patients with Heart Failure using Heart Rate Variability.

Central Illustration : Predictive Model of All-Cause Death in Patients with Heart Failure using Heart Rate Variability. Short and long-duration heart rate variability (HRV) data from Holter monitoring could identify predictors of all-cause death in heart failure (HF) patients. To build a predictive model of all-cause death in patients with HF using HRV. Retrospective study including patients with suspected or confirmed HF who were admitted for decompensated HF or syncope that underwent Holter monitoring. In analysis of augmented sympathetic tonus, we evaluated the lowest HRV in nonoverlapping 10-minutes periods throughout 24h continuous electrocardiographic signal recording (short HRV variables). Variables with p<0.01 were included in a multivariate Cox regression model to determine the occurrence of the all-cause death. Variables with statistical significance in Cox regression were chosen to build the predictive model. P<0.05 was considered significant. A total of 116 patients were included, mean age of 71.9±16.3 years, 45.7% men, mean follow-up of 2.83±1.27 years. Thirty-nine deaths occurred (33.6%). By comparing survivors vs. non-survivors, the variables that showed statistical significance were lowest SDNN, lowest rMSSD, age and left ventricular ejection fraction (LVEF). In Cox regression, independent predictors of all-cause death were: age>69 years (HR 3.95, 95%CI 1.64-9.52); LVEF≤57% (HR 4.70, 95%CI 2.38-9.28) and lowest rMSSD≤12ms (HR 5.54, 95%CI 2.04-15.08). An integer value was assigned to each variable. Score<3 showed AUC=0.802 (95%CI 0.72-0.87). In HF patients hospitalized for decompensated HF or syncope, independent long-term predictors of all-cause death were age, LVEF, and 10-minutes rMSSD. These findings indicate that even brief moments of high sympathetic tone can impact survival, specifically in the elderly and patients with HF with reduced ejection fraction.

What Disrupts Flow in Office Work? The Impact of Frequency and Relevance of IT-Mediated Interruptions

Flow, the holistic sensation people experience when they act with total involvement, is a known driver for desired work outcomes like task performance. However, the increasing ubiquity of IT at work can disrupt employees’ flow. Thus, the impact of IT-mediated interruptions on flow warrants more attention in research and practice. We conducted a NeuroIS laboratory experiment focusing on a typical office work task—an invoice matching task (i.e., matching customer payments to invoices). We manipulated interruption frequency (low, high) and content relevance (irrelevant, relevant) to study the impact of interruptions on self-reported flow, its dimensions, and high-frequency heart rate variability (HF-HRV; calculated from electrocardiography recordings) as a proxy for parasympathetic nervous system (PNS) activation. We found that content relevance moderated the relationship between interruption frequency and self-reported flow and that these results vary along flow dimensions. Content relevance also moderated the relationship between interruption frequency and PNS activation. Furthermore, self-reported flow was positively associated with both perceived and objective task performance, while PNS activation was not related to either performance measure. Lastly, we found no relationship between PNS activation (measured by HF-HRV) and self-reported flow, contributing to an important debate in the NeuroIS literature on whether physiological evidence constitutes an alternative or a complement to self-reports. Overall, our findings indicate that frequent interruptions are not harmful per se. Rather, considering content relevance is critical for a more comprehensive understanding of the effects on self-reported flow, its dimensions, and the underlying physiology.

Precordial electrocardiographic recording and QT measurement from a novel wearable ring device

BackgroundThe availability of portable and wearable electrocardiography devices has increased secondary to technological development. Single-lead ECG recordings have been shown to reliably detect and characterize cardiac rhythms such as atrial fibrillation. Acquisition of precordial electrodes for full 12-lead ECG reconstruction from bipolar recordings is complicated by the absence of a body ground / Wilson central terminal electrode, however the extent of difference between standard precordial lead and those from a wearable bipolar ECG recorder has not been characterized. ObjectiveThis study characterizes precordial ECG lead set from sequential bipolar recordings from an ECG ring wearable device. MethodsIn 70 patients wearing an ECG device on their right finger, sequential precordial leads (CR1-CR6) were obtained along with chest electrodes (V1-V6). During acquisition of the modified precordial lead CR6 a full standardized 12 lead ECG capture was obtained.Using automated analysis software, signal quality was assessed, and the correlation values between the ring-derived ECG precordial leads and standard ECG leads were compared with QRS duration, QT width, and RR interval measurement. ResultsThere is high concordance in the morphology of precordial ECG leads obtained in a standard fashion and those recorded through an ECG ring. Morphologic alignment improved with increasing laterality of the precordial lead with chest to right arm ring recording (CR5, CR6) compared with anterior chest leads to right arm (CR1, CR2). Segmental measurements of QRS duration and QT segment were well aligned and of high correlation. ConclusionWearable ring based electrocardiographic technology is capable of high fidelity recording of precordial leads for non-simultaneous reconstruction of complete ECG sets. These correlate highly with surface-obtained QRS and QT duration measurement, which has significant implications for clinical applications. Uninterpretable tracings were primarily due to electrode noise from poor electrode contact.