Virtual Reality Simulation for the Acquisition and Retention of Electrocardiogram Interpretation Skills: A Randomized Controlled Trial Among Undergraduate Medical Students.

Introduction The electrocardiogram (ECG) is one of the most important tools in diagnosing cardiac abnormalities, particularly arrhythmias and myocardial infarction. It is one of the certifiable competencies for final-year medical undergraduate students. We determined virtual reality's effectiveness in acquiring and retaining ECG interpretation skills among medical students compared to traditional teaching. Methods One hundred and forty students were randomized into two groups. Seventy-one students (immersion group) were trained using virtual reality simulation to acquire and retain interpretation skills of normal and abnormal ECG. Sixty-nine students (traditional group) were trained in the classroom using chalk and board. The primary outcome of change in acquiring knowledge of the interpretation of ECG was determined by comparing pre and post-test scores. The secondary outcome of retention of knowledge was determined by comparing pre-test and second post-test scores conducted after eight weeks of intervention. The p-value of <0.05 was considered significant. Results Out of 140 students, 50 (35.7%) were males and 90 (64.3%) were female. The mean age of the students was 22.1 (SD 1.1), with 69.3% of them between the ages of 21 and 22 years. Mean pre-test scores for the interpretation of normal ECG among immersion and traditional groups were 9.8 (SD 8.4) and 8.3 (SD 7.5), respectively, and post-test scores for the acquisition of knowledge were 24.3 (SD 5.5) and 24.8 (SD 6.3), respectively. The post-test scores for retention skills were 25.3 (SD 5.6) and 20.7 (SD 6.9) respectively (p<0.001). The mean pre-test scores for the interpretation of abnormal ECG of both groups were 7.0 (SD 6) and 8.3 (SD 6.6), respectively. Mean post-test scores for acquiring knowledge to interpret abnormal ECG were 23.5 (SD 6.2) and 17.7 (SD 9), respectively (p<0.001), and mean post-test scores for retention of interpretation skills of abnormal ECG were 19.2 (SD - 6.9) and 13.3 (SD 10.2) respectively (p=0.001). The pairwise comparison of the immersion group indicates that all the combinations that changed in score from the pre to post-intervention time points, from pre-to-retention time, and from the post-to-retention time were significant (p<0.001). Conclusion Virtual reality teaching had a better impact on acquiring and retaining the skill for interpreting normal and abnormal electrocardiograms.

Novel interpretable Feature set extraction and classification for accurate atrial fibrillation detection from ECGs.

OBJECTIVE: We present a novel method for detecting atrial fibrillation (AFib) by analyzing Lead II electrocardiograms (ECGs) using a unique set of features. METHODS: For this purpose, we used specific signal processing techniques, such as proper orthogonal decomposition, continuous wavelet transforms, discrete cosine transform, and standard cross-correlation, to extract 48 features from the ECGs. Thus, our approach aims to more effectively capture AFib signatures, such as beat-to-beat variability and fibrillatory waves, than traditional metrics. Moreover, our features were designed to be physiologically interpretable. Subsequently, we incorporated an XGBoost-based ECG classifier to train and evaluate it using the publicly available 'Training' dataset of the 2017 PhysioNet Challenge, which includes 'Normal,' 'AFib,' 'Other,' and 'Noisy' ECG categories. RESULTS: Our method achieved an accuracy of 96 % and an F1-score of 0.83 for 'AFib' detection and 80 % accuracy and 0.85 F1-score for 'Normal' ECGs. Finally, we compared our method's performance with the top-classifiers from the 2017 PhysioNet Challenge, namely ENCASE, Random Forest, and Cascaded Binary. As reported by Clifford et al., 2017, these three best performing models scored 0.80, 0.83, 0.82, in terms of F1-score for 'AFib' detection, respectively. CONCLUSION: Despite using significantly fewer features than the competition's state-of-the-art ECG detection algorithms (48 vs. 150-622), our model achieved a comparable F1-score of 0.83 for successful 'AFib' detection. SIGNIFICANCE: The interpretable features specifically designed for 'AFib' detection results in our method's adaptability in clinical settings for real-time arrhythmia detection and is even effective with short ECGs (<10 heartbeats).

Cardiac Damage After SARS-CoV2 Infection.

COVID-19 is a viral disease that can manifest acutely in the respiratory tract and other organs. In this study, we aimed to investigate potential long-term damage to the heart from COVID-19. For this study, we divided 97 consecutive unselected COVID-19 patients aged 18-80 years at a cardiology practice in Cologne, Germany, into two groups based on the severity of their infection. We performed a resting ECG and a resting transthoracic echocardiography three and six months after SARS-CoV2 infection. The key discriminator determining disease severity was bed confinement or hospital admission. Group 1 included patients with less severe COVID-19, whereas group 2 contained more severe cases. Heart rate as the primary ECG endpoint was lower by a statistically significant amount for the entire study population (p=0.024), subdivided by gender (pwomen <0.001, pmen <0.001) and in group 1 p =0.003 compared to three months. QTc time and repolarization disturbances as primary ECG endpoints and the echocardiographic primary endpoints, left ventricular ejection fraction, and left ventricular end-diastolic diameter (LVEDD), showed no relevant difference between the subgroups at three and six months or between the measurements taken at each point. In contrast, LVEDD normalized to body surface area was statistically significantly lower at six months in women in group 1 compared to group 2 (p=0.048) and in the overall study population at six months compared with the data after three months (p=0.034). E/E' was statistically lower at six months than at three months in the whole population (p=0.004) and in women (p=0.031). All measured echocardiographic and electrocardiographic mean values were within the normal range in all groups and follow-up controls. Overall, the prospective study conducted showed no significant evidence of long-term cardiac damage from COVID-19 disease, as evidenced by electrocardiographic and echocardiographic examinations at three and six months after infection.

Vectorcardiography signs of a failing Fontan: Heart rate, PR interval, RtQRSvm, QRSvm and SPQRS-T angle as noninvasive markers of late Fontan complications and mortality.

BACKGROUND: Limited data exists on interpreting vectorcardiography (VCG) parameters in the Fontan population. OBJECTIVE: The purpose of this study was to demonstrate the associations between ECG/VCG parameters and Fontan failure (FF). METHODS/RESULTS: 107 patients with a Fontan operation after 1990 and without significant ventricular pacing were included. FF and Fontan survival (FS) groups were compared. The average follow-up after Fontan operation was 11.8 years ±7.1 years. 14 patients had FF (13.1%) which was defined as having protein-losing-enteropathy (1.9%), plastic bronchitis (2.8%), Fontan takedown (1.9%), heart transplant (5.6%), NYHA class III-IV (2.8%) or death (0.9%). A 12­lead ECG at last follow up or prior to FF was assessed for heart rate, PR interval, QRS duration, Qtc and left/right sided precordial measures (P-wave, QRS and T-wave vector magnitudes, spatial P-R and QRS-T angles). Transthoracic echocardiogram evaluated atrioventricular valve regurgitation and ventricular dysfunction at FF or last follow up. A cox multivariate regression analysis adjusted for LV dominance, ventricular dysfunction, HR, PR, QTc, Pvm, QRSvm, SPQRST-angle, RtPvm, RtQRSvm and RtTvm. Ventricular dysfunction, increased heart rate and prolonged PR interval were significantly associated to FF at the multivariate analysis. ROC analysis and Kaplan-meier analysis revealed an increased total mortality associated with a heart rate > 93 bpm, PR interval > 155 mv, QRSvm >1.91 mV, RtQRSvm >1.8 mV and SPQRST angle >92.3 mV with p values <0.001 to 0.018. CONCLUSION: We demonstrate the importance of ECG/VCG monitoring in the Fontan population and suggest specific indicators of late complications and mortality.

A robust deep learning system for screening of obstructive sleep apnea using T-F spectrum of ECG signals.

Obstructive sleep apnea (OSA) is a non-communicable sleep-related medical condition marked by repeated disruptions in breathing during sleep. It may induce various cardiovascular and neurocognitive complications. Electrocardiography (ECG) is a useful method for detecting numerous health-related disorders. ECG signals provide a less complex and non-invasive solution for the screening of OSA. Automated and accurate detection of OSA may enhance diagnostic performance and reduce the clinician's workload. Traditional machine learning methods typically involve several labor-intensive manual procedures, including signal decomposition, feature evaluation, selection, and categorization. This article presents the time-frequency (T-F) spectrum classification of de-noised ECG data for the automatic screening of OSA patients using deep convolutional neural networks (DCNNs). At first, a filter-fusion algorithm is used to eliminate the artifacts from the raw ECG data. Stock-well transform (S-T) is employed to change filtered time-domain ECG into T-F spectrums. To discriminate between apnea and normal ECG signals, the obtained T-F spectrums are categorized using benchmark Alex-Net and Squeeze-Net, along with a less complex DCNN. The superiority of the presented system is measured by computing the sensitivity, specificity, accuracy, negative predicted value, precision, F1-score, and Fowlkes-Mallows index. The results of comparing all three utilized DCNNs reveal that the proposed DCNN requires fewer learning parameters and provides higher accuracy. An average accuracy of 95.31% is yielded using the proposed system. The presented deep learning system is lightweight and faster than Alex-Net and Squeeze-Net as it utilizes fewer learnable parameters, making it simple and reliable.

Wearable Ring-Shaped Biomedical Device for Physiological Monitoring through Finger-Based Acquisition of Electrocardiographic, Photoplethysmographic, and Galvanic Skin Response Signals: Design and Preliminary Measurements.

Wearable health devices (WHDs) are rapidly gaining ground in the biomedical field due to their ability to monitor the individual physiological state in everyday life scenarios, while providing a comfortable wear experience. This study introduces a novel wearable biomedical device capable of synchronously acquiring electrocardiographic (ECG), photoplethysmographic (PPG), galvanic skin response (GSR) and motion signals. The device has been specifically designed to be worn on a finger, enabling the acquisition of all biosignals directly on the fingertips, offering the significant advantage of being very comfortable and easy to be employed by the users. The simultaneous acquisition of different biosignals allows the extraction of important physiological indices, such as heart rate (HR) and its variability (HRV), pulse arrival time (PAT), GSR level, blood oxygenation level (SpO2), and respiratory rate, as well as motion detection, enabling the assessment of physiological states, together with the detection of potential physical and mental stress conditions. Preliminary measurements have been conducted on healthy subjects using a measurement protocol consisting of resting states (i.e., SUPINE and SIT) alternated with physiological stress conditions (i.e., STAND and WALK). Statistical analyses have been carried out among the distributions of the physiological indices extracted in time, frequency, and information domains, evaluated under different physiological conditions. The results of our analyses demonstrate the capability of the device to detect changes between rest and stress conditions, thereby encouraging its use for assessing individuals' physiological state. Furthermore, the possibility of performing synchronous acquisitions of PPG and ECG signals has allowed us to compare HRV and pulse rate variability (PRV) indices, so as to corroborate the reliability of PRV analysis under stationary physical conditions. Finally, the study confirms the already known limitations of wearable devices during physical activities, suggesting the use of algorithms for motion artifact correction.

Dextrocardia With Situs Inversus in a COVID-19 Patient.

With an estimated incidence of one in 10,000 to one in 50,000 patients, Situs inversus totalis (SIT) is a rare innate anomaly, portraying a mirror image of the normal anatomy, as the cardiac position and abdominal viscera are completely inverted. Despite the fact that physicians and researchers have been dealing with the SARS-CoV-2 pandemic for three years, there is a lack of published data examining the potential effects of anatomic variations on coronavirus disease 2019 (COVID-19) infection. This study aimed to contribute to this domain by presenting a rare case of a COVID-19 infection coexisting with SIT as one of the very few cases reporting the simultaneous presence of the two pathologies. We sought to present this case of COVID-19 in a quinquagenarian female, in whom SIT was an incidental radiological finding. The reversed anatomy did not seem to affect the clinical progression of the virus. However, due to the lack of scientific evidence, the potential long-term effects, if any, of COVID-19 on SIT cannot be predicted. The recognition of the mirror pattern will offer a personalized treatment plan, reducing the risk of severe complications and management mishaps.

Cardiac Abnormalities in a Predictive Mouse Model of Chagas Disease.

Chronic Chagas cardiomyopathy (CCC) results from infection with the protozoan parasite Trypanosoma cruzi and is a prevalent cause of heart disease in endemic countries. We previously found that cardiac fibrosis can vary widely in C3H/HeN mice chronically infected with T. cruzi JR strain, mirroring the spectrum of heart disease in humans. In this study, we examined functional cardiac abnormalities in this host:parasite combination to determine its potential as an experimental model for CCC. We utilised electrocardiography (ECG) to monitor T. cruzi-infected mice and determine whether ECG markers could be correlated with cardiac function abnormalities. We found that the C3H/HeN:JR combination frequently displayed early onset CCC indicators, such as sinus bradycardia and right bundle branch block, as well as prolonged PQ, PR, RR, ST, and QT intervals in the acute stage. Our model exhibited high levels of cardiac inflammation and enhanced iNOS expression in the acute stage, but denervation did not appear to have a role in pathology. These results demonstrate the potential of the C3H/HeN:JR host:parasite combination as a model for CCC that could be used for screening new compounds targeted at cardiac remodelling and for examining the potential of antiparasitic drugs to prevent or alleviate CCC development and progression.

Memory T-Waves: An Uncharted Territory in T-Wave Inversions.

T-wave inversions on electrocardiograms (ECGs) can present a diagnostic challenge due to their association with various underlying causes. One less-explored cause is memory T-waves, a phenomenon characterized by T-wave inversions, often seen in chest and inferior leads, following a period of abnormal ventricular conduction. In this case report, we discuss the intriguing case of an 80-year-old woman who recently underwent percutaneous coronary intervention (PCI) for a myocardial infarction and subsequently developed memory T-waves. We are also discussing how important it can be to understand and recognize memory T-waves, as it will avoid further unnecessary tests and longer hospital stays.

Cardiac Electromechanical Activity in Healthy Cats and Cats with Cardiomyopathies.

Optimal heart function depends on perfect synchronization between electrical and mechanical activity. In this pilot study, we aimed to investigate the electromechanical activity of the heart in healthy cats and cats with cardiomyopathy with phonocardiography (PCG) synchronized to an electrocardiography (ECG) pilot device. We included 29 cats (12 healthy cats and 17 cats diagnosed with cardiomyopathy) and performed a clinical examination, PCG synchronized with ECG and echocardiography. We measured the following durations with the pilot PCG device synchronized with ECG: QRS (ventricular depolarization), QT interval (electrical systole), QS1 interval (electromechanical activation time (EMAT)), S1S2 (mechanical systole), QS2 interval (electrical and mechanical systole) and electromechanical window (end of T wave to the beginning of S2). The measured parameters did not differ between healthy cats and cats with cardiomyopathy; however, in cats with cardiomyopathy, EMAT/RR, QS2/RR and S1S2/RR were significantly longer than in healthy cats. This suggests that the hypertrophied myocardium takes longer to generate sufficient pressure to close the mitral valve and that electrical systole, i.e., depolarization and repolarization, and mechanical systoles are longer in cats with cardiomyopathy. The PCG synchronized with the ECG pilot device proved to be a valuable tool for evaluating the electromechanical activity of the feline heart.

Comparison of dipole-based and potential-based ECGI methods for premature ventricular contraction beat localization with clinical data.

Introduction: Localization of premature ventricular contraction (PVC) origin to guide the radiofrequency ablation (RFA) procedure is one of the prominent clinical goals of non-invasive electrocardiographic imaging. However, the results reported in the literature vary significantly depending on the source model and the level of complexity in the forward model. This study aims to compare the paced and spontaneous PVC localization performances of dipole-based and potential-based source models and corresponding inverse methods using the same clinical data and to evaluate the effects of torso inhomogeneities on these performances. Methods: The publicly available EP solution data from the EDGAR data repository (BSPs from a maximum of 240 electrodes) with known pacing locations and the Bratislava data (BSPs in 128 leads) with spontaneous PVCs from patients who underwent successful RFA procedures were used. Homogeneous and inhomogeneous torso models and corresponding forward problem solutions were used to relate sources on the closed epicardial and epicardial-endocardial surfaces. The localization error (LE) between the true and estimated pacing site/PVC origin was evaluated. Results: For paced data, the median LE values were 25.2 and 13.9 mm for the dipole-based and potential-based models, respectively. These median LE values were higher for the spontaneous PVC data: 30.2-33.0 mm for the dipole-based model and 28.9-39.2 mm for the potential-based model. The assumption of inhomogeneities in the torso model did not change the dipole-based solutions much, but using an inhomogeneous model improved the potential-based solutions on the epicardial-endocardial ventricular surface. Conclusion: For the specific task of localization of pacing site/PVC origin, the dipole-based source model is more stable and robust than the potential-based source model. The torso inhomogeneities affect the performances of PVC origin localization in each source model differently. Hence, care must be taken in generating patient-specific geometric and forward models depending on the source model representation used in electrocardiographic imaging (ECGI).

Tablet-Based Wearable Patch Sensor Design for Continuous Cardiovascular System Monitoring in Postoperative Settings.

Meticulous monitoring for cardiovascular systems is important for postoperative patients in postanesthesia or the intensive care unit. The continuous auscultation of heart and lung sounds can provide a valuable information for patient safety. Although numerous research projects have proposed the design of continuous cardiopulmonary monitoring devices, they primarily focused on the auscultation of heart and lung sounds and mostly served as screening tools. However, there is a lack of devices that could continuously display and monitor the derived cardiopulmonary parameters. This study presents a novel approach to address this need by proposing a bedside monitoring system that utilizes a lightweight and wearable patch sensor for continuous cardiovascular system monitoring. The heart and lung sounds were collected using a chest stethoscope and microphones, and a developed adaptive noise cancellation algorithm was implemented to remove the background noise corrupted with those sounds. Additionally, a short-distance ECG signal was acquired using electrodes and a high precision analog front end. A high-speed processing microcontroller was used to allow real-time data acquisition, processing, and display. A dedicated tablet-based software was developed to display the acquired signal waveforms and the processed cardiovascular parameters. A significant contribution of this work is the seamless integration of continuous auscultation and ECG signal acquisition, thereby enabling the real-time monitoring of cardiovascular parameters. The wearability and lightweight design of the system were achieved through the use of rigid-flex PCBs, which ensured patient comfort and ease of use. The system provides a high-quality signal acquisition and real-time monitoring of the cardiovascular parameters, thus proving its potential as a health monitoring tool.

An Interesting Case of Weakness and Atrial Tachycardia in the Emergency Department: Thinking Beyond Hearts and Minds.

Thyrotoxic periodic paralysis is a rare but life-threatening presentation of hyperthyroidism that manifests with sudden, painless episodes of muscle weakness due to hypokalemia. We present the case of a middle-aged Middle Eastern female who attended our Emergency Department with sudden onset weakness to the lower limbs, resulting in her inability to walk. She had a power of 1/5 in the lower limbs, and subsequent investigations showed a low potassium level, and primary hyperthyroidism secondary to Grave's disease was diagnosed. A 12-lead electrocardiogram showed atrial flutter with a variable block, along with U waves. The patient reverted to sinus rhythm following administration of potassium replacement and was also treated with Propanalol and Carbimazole. The patient made a full neurological recovery.  Emergency physicians and all frontline healthcare workers should be aware that electrolyte problems can cause paralysis. Furthermore, hypokalemic periodic paralysis can be caused by an undiagnosed thyrotoxic state. Be aware that if left untreated, hypokalemia can cause serious atrial and ventricular arrhythmias. Achieving a euthyroid state and blunting hyperadrenergic stimulation, in addition to replacing potassium, all help to fully reverse muscle weakness.

Electrocardiographic QRS Findings Upon Admission Can Predict Prognosis of Acute Myocardial Infarction Caused by Occlusion of Left Main Coronary Artery.

BACKGROUND: Acute myocardial infarction (AMI) caused by left main coronary artery (LMCA) occlusion is associated with a severe clinical course and catastrophic consequences. HYPOTHESIS: We sought to clarify ECG predictors of prognosis in AMI caused by LMCA occlusion. METHODS: We examined 20 consecutive patients with AMI caused by LMCA occlusion that was treated by primary stenting. The patients were assigned to either a group that survived (S) and was discharged from hospital, or a group that did not survive (NS) and died in hospital. We compared ECG findings upon admission, angiographic findings, laboratory data and clinical outcomes. RESULTS: The rate of having Thrombolysis In Myocardial Infarction (TIMI) grade > 2 coronary flow before PCI and of achieving TIMI grade 3 after PCI was significantly lower in the NS than the S group (14.3% vs. 83.3%, p = 0.003 and 35.7% vs. 100%, p = 0.008). The ECG findings showed longer QRS interval in the NS than in the S group (150.5 ± 37.9 vs. 105.2 ± 15.4, p = 0.022). A QRS interval ≥ 120 msec predicted in-hospital mortality with sensitivity, specificity and positive and negative predictive values of 78.5%, 100%, 100% and 66.7%, respectively, in this population. CONCLUSIONS: The QRS duration upon admission was a good predictor of in-hospital mortality among patients with AMI caused by LMCA occlusion. This ECG sign could be useful in the emergency clinical setting.

Cross-Domain Transfer of EEG to EEG or ECG Learning for CNN Classification Models.

Electroencephalography (EEG) is often used to evaluate several types of neurological brain disorders because of its noninvasive and high temporal resolution. In contrast to electrocardiography (ECG), EEG can be uncomfortable and inconvenient for patients. Moreover, deep-learning techniques require a large dataset and a long time for training from scratch. Therefore, in this study, EEG-EEG or EEG-ECG transfer learning strategies were applied to explore their effectiveness for the training of simple cross-domain convolutional neural networks (CNNs) used in seizure prediction and sleep staging systems, respectively. The seizure model detected interictal and preictal periods, whereas the sleep staging model classified signals into five stages. The patient-specific seizure prediction model with six frozen layers achieved 100% accuracy for seven out of nine patients and required only 40 s of training time for personalization. Moreover, the cross-signal transfer learning EEG-ECG model for sleep staging achieved an accuracy approximately 2.5% higher than that of the ECG model; additionally, the training time was reduced by >50%. In summary, transfer learning from an EEG model to produce personalized models for a more convenient signal can both reduce the training time and increase the accuracy; moreover, challenges such as data insufficiency, variability, and inefficiency can be effectively overcome.

Evaluation of Index of Cardiac Electrophysiological Balance in Patients With Myotonic Dystrophy Type 1.

BACKGROUND: Myotonic dystrophy type 1(MD1), which is characterized by decreased muscle tone, progressive muscle weakness, and cardiac involvement, is an autosomal dominant and progressive congenital muscle disease. Cardiac involvement more often manifests as conduction abnormalities and arrhythmias (such as supraventricular or ventricular). Approximately one-third of MD1-related deaths occur due to cardiac causes. The index of cardiac-electrophysiological balance (ICEB) is a current parameter calculated as QT interval/QRS duration. The increase in this parameter has been associated with malignant ventricular arrhythmias. In this study, our aim was to compare the ICEB values ​​of MD1 patients and the normal population. MATERIAL AND METHOD: A total of 62 patients were included in our study. They were divided into two groups - 32 MD patients and 30 controls. The demographic, clinical, laboratory, and electrocardiographic parameters of the two groups were compared. RESULTS: The median age of the study population was 24 (20-36 IQR), and 36 (58%) of these patients were female. Body mass index was higher in the control group (p = 0.037). While in the MD1 group creatinine kinase was significantly higher (p <0.001), In the control group creatinine, aspartate aminotransferase, alanine aminotransferase, calcium, and lymphocyte levels were significantly higher (p=0.031, p= 0.003, p=0.001, p=0.002, p=0.031, respectively). ICEB [3.96 (3.65-4.46) vs 3.74 (3.49-3.85) p=0.015] and corrected ICEB (ICEBc) [4.48 (4.08-4.92) vs 4.20 (4.03-4.51) p = 0.048] were significantly higher in the MD1 group. CONCLUSION: In our study, ICEB was found to be higher in MD1 patients than in the control group. Increased ICEB and ICEBc values ​​in MD1 patients may precipitate ventricular arrhythmias in the future. Close monitoring of these parameters can be helpful in predicting possible ventricular arrhythmias and in risk stratification.

Electrocardiographic Findings in Children With Growth Hormone Deficiency.

Introduction It has been shown that cardiac functions begin to deteriorate in growth hormone (GH) deficiency even in childhood. However, little is known about how GH deficiency affects arrhythmogenesis. The aim of this study was to evaluate the parameters of P wave dispersion (Pd), QT dispersion (QTd), corrected QT (QTc) dispersion (QTcd), T wave peak-to-end (Tp-e) interval, Tp-e/QT ratio, and Tp-e/QTc ratio in children with GH deficiency. This study also aimed to evaluate the relationship of these parameters with insulin-like growth factor 1 (IGF-1) and insulin-like growth factor binding protein 3 (IGFBP-3). Method In the study, records of children diagnosed with GH deficiency in Adana City Training and Research Hospital Pediatric Endocrine Outpatient Clinic between September 2021 and December 2022 were retrospectively reviewed. The control group consisted of children in the same age group who applied to the Emergency Outpatient Clinic with a complaint of chest pain and no pathological finding was detected. The electrocardiograms (ECGs) of all patients were retrospectively evaluated. Results There were a total of 82 children in the study, 41 of whom were diagnosed with GH deficiency and 41 in the healthy control group. The age and male/female ratio of children with GH deficiency were similar to those in the control group (p>0.05). There were 27 (66%) children with complete GH deficiency and 14 (34%) children with partial GH deficiency. P wave dispersion was similar in both GH-deficient children and control group children. It was also similar in children with complete and partial GH deficiency (p>0.05). QT and QTc dispersions were found to be increased in children with GH deficiency, although not statistically significant, compared to the control group (p>0.05). Tp-e interval, Tp-e/QTmax (longest QT interval), and Tp-e/QTcmax (longest QTc interval) ratios were increased in children with GH deficiency compared to the control group (p=0.001, p=0.003, and p=0.001, respectively). QT and QTc dispersion, Tp-e interval, Tp-e/QTmax, and Tp-e/QTcmax ratios were found to be increased in children with complete GH deficiency compared to children with partial GH deficiency, but the difference was not significant (p>0.05). No correlation was found between these ECG parameters and IGF-1, IGFBP-3, and peak GH levels after stimulation tests (p>0.05). Conclusion We found in our study that the Tp-e interval was longer and Tp-e/QT and Tp-e/QTc ratios were increased in children with GH deficiency. These results suggest that the risk of ventricular arrhythmias in children with GH deficiency may start to increase from childhood. However, further prospective studies are needed to confirm our results.

Electrocardiography Assessment of Sympatico-Vagal Balance during Resting and Pain Using the Texas Instruments ADS1299.

Sympatico-vagal balance is essential for regulating cardiac electrophysiology and plays an important role in arrhythmogenic conditions. Various noninvasive methods, including electrocardiography (ECG), have been used for clinical assessment of the sympatico-vagal balance. This study aimed to use a custom-designed wearable device to record ECG and ECG-based cardiac function biomarkers to assess sympatico-vagal balance during tonic pain in healthy controls. Nineteen healthy volunteers were included for the ECG measurements using the custom-designed amplifier based on the Texas Instruments ADS1299. The ECG-based biomarkers of the sympatico-vagal balance, (including heart rate variability, deceleration capacity of the heart rate, and periodic repolarization dynamic), were calculated and compared between resting and pain conditions (tonic pain). The custom-designed device provided technically satisfactory ECG recordings. During exposure to tonic pain, the periodic repolarization dynamics increased significantly (p = 0.02), indicating enhancement of sympathetic nervous activity. This study showed that custom-designed wearable devices can potentially be useful in healthcare as a new telemetry technology. The ECG-based novel biomarkers, including periodic repolarization dynamic and deceleration capacity of heart rate, can be used to identify the cold pressor-induced activation of sympathetic and parasympathetic systems, making it useful for future studies on pain-evoked biomarkers.

Clinical Implications of Cardiac Symptoms and Electrocardiographic Abnormalities for Advanced Liver Fibrosis in Patients with Nonalcoholic Fatty Liver Disease.

Background and Objectives: Advanced liver fibrosis in patients with nonalcoholic fatty liver disease (NAFLD) can be a major predictor of cardiovascular disease (CVD) events and cardiac complications. However, the clinical significance of cardiac symptoms and abnormal electrocardiography (ECG) findings in patients with NAFLD associated with advanced liver fibrosis is unclear. Therefore, our study was aimed to evaluate the clinical implications based on the association between cardiac symptoms with ECG abnormalities for advanced liver fibrosis in patients with NAFLD. Materials and Methods: Of 31,795 participants who underwent health checkups, 6293 were diagnosed with NAFLD using ultrasound and inclusion criteria in a retrospective cross-sectional study. Advanced liver fibrosis was assessed based on a low NAFLD fibrosis score (NFS) and fibrosis-4 index (Fib-4) cut-off values (COVs). Cardiac data were assessed using a cardiac symptom questionnaire and 12-lead electrocardiography (ECG). Results: Among 6293 NAFLD patients with NAFLD, 304 (4.8%) experienced cardiac symptoms. NFS and Fib-4 indicated higher rates of advanced fibrosis in the cardiac-symptomatic group than in the non-symptomatic group (NFS: 7.3 vs. 4.1%; Fib-4: 7.8 vs. 3.7%; both p < 0.001). Cardiac symptoms were independently associated with advanced liver fibrosis using a step-wise-adjusted model and NFS and Fib-4 (final adjusted odds ratio (aOR), 1.40; 95% CI, 1.06-1.85; p = 0.018 for NFS; aOR, 1.67; 95%, 1.30-2.15; p < 0.001 for Fib-4). Cardiac symptoms with abnormal ECG findings independently predicted advanced liver fibrosis (aOR, 2.43; 95% CI, 1.72-3.39; p < 0.001 for NFS; aOR, 3.02; 95% CI, 2.19-4.15; p < 0.001 for Fib-4). Conclusions: Patients who have had cardiac symptoms and some ECG abnormalities may have a higher association with advanced liver fibrosis.