BACKGROUND AND OBJECTIVE

COVID-19 has been associated with cardiac injury, often detectable through electrocardiographic (ECG) changes. This study seeks to characterize the cardiovascular and electrocardiographic profiles of adult patients diagnosed with COVID-19.

This study included adult patients with confirmed COVID-19 from June 2021 to June 2022. Clinical profiles and 12-lead ECG tracings were obtained from electronic medical records and reviewed independently by three cardiologists. Descriptive analysis was performed to summarize the cardiovascular and electrocardiographic findings in this population.

The study included 998 COVID-19 patients (mean age: 50 years; 53.7% male). The most common comorbidities were hypertension, diabetes, and dyslipidemia. A majority (31.36%) presented with severe COVID-19 infection. The most frequent significant ECG abnormalities observed at admission were sinus tachycardia (22.8%), and atrial fibrillation (11.02%). Additional ischemic findings included ST segment depression (2.91%), T-wave inversion (1.70%), and ST segment elevation (2.71%).

The baseline ECG findings among COVID-19 patients were predominantly normal; however, significant abnormalities were also identified. The most frequent abnormalities included sinus tachycardia, atrial fibrillation, and ischemic changes, all of which may have clinical implications.

In the field of medicine and cardiology, there is perhaps no other condition or situation that stimulates an adrenalin rush for the healthcare team than a patient presenting with wide QRS complex tachycardia. These cases may be potentially fatal and are usually associated with worse outcomes. While the real-world experience in the evaluation and management of these cases can be chaotic situations, a careful, systematic and organized scrutiny of the electrocardiographic tracing is key to obtaining a correct diagnosis and proceeding with the right therapeutic management. An understanding of the physiological mechanisms of arrhythmia, the appreciation of scientific basis for electrocardiographic features and recognition of different criteria for diagnosis provides endless opportunities and “teachable moments” in medicine. For both learners and teachers, the academic discussion of these points and features can be an exciting journey and electrifyingly educational experience. This article provides a simplified yet beautifully complicated approach to diagnosing wide complex tachycardia.

The electrocardiographic analysis of heart blocks provides great opportunities for the discussion of mechanisms of electrical cardiac conduction, serving as “teachable moments” in medicine. Recognition of heart blocks can sometimes be a challenge as they can present in many forms, different severities and levels of blocks that present as varied patterns on electrocardiographic tracing. The ultimate key to correct diagnosis rests on adequate understanding of normal electrophysiology of the electrical system of the heart. While it is vital to recognize the pattern, we should always know and understand the physiology behind the pattern. This article presents a detailed analysis of a case of heart block which can easily be misinterpreted on first look. The case is featured not for its rarity but for the interesting concepts in cardiac electrophysiology that are highlighted. Navigation of the different elements of tracing can be an adventure and a great learning experience enjoyed by both students and experts.
Heart Block ; Electrocardiography

OBJECTIVES

The study aimed to determine the association of electrocardiographic (ECG) abnormalities and in-hospital mortality of patients with coronavirus disease 2019 (COVID-19) infection admitted in a tertiary care hospital in the Philippines.

We conducted a retrospective study of confirmed COVID-19–infected patients. Demographic and clinical characteristics and clinical outcomes were extracted from the medical records. Electrocardiographic analysis was derived from the 12-lead electrocardiogram recorded upon admission. The frequencies and distributions of various clinical characteristics were described, and the ECG abnormalities associated with in-hospital mortality were investigated.

A total of 163 patients were included in the study; most were female (52.7%) with a median age of 55 years. Sinus rhythm with any ECG abnormality (65%), nonspecific ST and T-wave changes (35%), and sinus tachycardia (22%) were the frequently reported ECG findings. The presence of any ECG abnormality was detected in 78.5% of patients, and it was significantly associated with in-hospital mortality (P = 0.038). The analysis revealed a statistically significant association between in-hospital mortality and having atrial fibrillation or flutter (P = 0.002), supraventricular tachycardia (P = 0.011), ventricular tachycardia (P = 0.011), third-degree atrioventricular block (P = 0.011), T-wave inversion (P = 0.005), and right ventricular hypertrophy (P = 0.011).

The presence of any ECG abnormality in patients with COVID-19 infection was associated with in-hospital mortality. Electrocardiographic abnormalities that were associated with mortality were atrial fibrillation or flutter, supraventricular tachycardia, ventricular tachycardia, third-degree atrioventricular block, T-wave inversion, and right ventricular hypertrophy.

Fetal electrocardiogram (ECG) signals provide important clinical information for early diagnosis and intervention of fetal abnormalities. In this paper, we propose a new method for fetal ECG signal extraction and analysis. Firstly, an improved fast independent component analysis method and singular value decomposition algorithm are combined to extract high-quality fetal ECG signals and solve the waveform missing problem. Secondly, a novel convolutional neural network model is applied to identify the QRS complex waves of fetal ECG signals and effectively solve the waveform overlap problem. Finally, high quality extraction of fetal ECG signals and intelligent recognition of fetal QRS complex waves are achieved. The method proposed in this paper was validated with the data from the PhysioNet computing in cardiology challenge 2013 database of the Complex Physiological Signals Research Resource Network. The results show that the average sensitivity and positive prediction values of the extraction algorithm are 98.21% and 99.52%, respectively, and the average sensitivity and positive prediction values of the QRS complex waves recognition algorithm are 94.14% and 95.80%, respectively, which are better than those of other research results. In conclusion, the algorithm and model proposed in this paper have some practical significance and may provide a theoretical basis for clinical medical decision making in the future.
Algorithms ; Neural Networks, Computer ; Electrocardiography ; Databases, Factual ; Fetus

OBJECTIVE: To use the low-cost anesthesia monitor for realizing anesthesia depth monitoring, effectively assist anesthesiologists in diagnosis and reduce the cost of anesthesia operation. METHODS: Propose a monitoring method of anesthesia depth based on artificial intelligence. The monitoring method is designed based on convolutional neural network (CNN) and long and short-term memory (LSTM) network. The input data of the model include electrocardiogram (ECG) and pulse wave photoplethysmography (PPG) recorded in the anesthesia monitor, as well as heart rate variability (HRV) calculated from ECG, The output of the model is in three states of anesthesia induction, anesthesia maintenance and anesthesia awakening. RESULTS: The accuracy of anesthesia depth monitoring model under transfer learning is 94.1%, which is better than all comparison methods. CONCLUSIONS The accuracy of this study meets the needs of perioperative anesthesia depth monitoring and the study reduces the operation cost.
Artificial Intelligence ; Neural Networks, Computer ; Heart Rate ; Electrocardiography ; Photoplethysmography/methods* ; Anesthesia

OBJECTIVE: To investigate whether Suxiao Jiuxin Pills (SJP), a Chinese herbal remedy, is an anti-ventricular fibrillation (VF) agent. METHODS: VF was induced by isoproterenolol (ISO) intraperitoneal injection followed by electrical pacing in mice and rabbits. The effects of SJP on the L-type calcium channel current (CaV1.2), voltage-dependent sodium channel current (I_Na), rapid and slow delayed rectifier potassium channel current (I_Kr and I_Ks, respectively) were studied by whole-cell patch-clamp method. Computer simulation was implemented to incorporate the experimental data of SJP effects on the CaV1.2 current into the action potential (AP) and pseudo-electrocardiography (pseudo-ECG) models. RESULTS: SJP prevented VF induction and reduced VF durations significantly in mice and rabbits. Patch-clamp experiments revealed that SJP decreased the peak amplitude of the CaV1.2 current with a half maximal concentration (IC₅₀) value of 16.9 mg/L (SJP-30 mg/L, -32.8 ± 6.1 pA; Verapamil, -16.2 ±1.8 pA; vs. control, -234.5 ±16.7 pA, P<0.01, respectively). The steady-state activation curve, inactivation curve, and the recovery from inactivation of the CaV1.2 current were not shifted significantly. Specifically, SJP did not altered I_Na, I_Kr, and I_Ks currents significantly (SJP vs. control, P>0.05). Computer simulation showed that SJP-reduced CaV1.2 current shortened the AP duration, transiting VF into sinus rhythm in pseudo-ECG. CONCLUSION SJP reduced VF via inhibiting the CaV1.2 current with in vivo, in vitro, and in silico studies, which provide experimental basis for SJP anti-VF clinical application.
Animals ; Rabbits ; Mice ; Calcium ; Computer Simulation ; Arrhythmias, Cardiac ; Electrocardiography

INTRODUCTION: MyDiagnostick is an atrial fibrillation (AF) screening tool that has been validated in the Caucasian population in the primary care setting. METHODS: In our study, we compared MyDiagnostick with manual pulse check for AF screening in the community setting. RESULTS: In our cohort of 671 candidates from a multi-ethnic Asian population, AF prevalence was found to be 1.78%. Of 12 candidates, 6 (50.0%) had a previous history of AF and another 6 (50.0%) were newly diagnosed with AF. Candidates found to have AF during the screening were older (72.0 ± 11.7 years vs. 56.0 ± 13.0 years, P < 0.0001) and had a higher CHADSVASC risk score (2.9 ± 1.5 vs. 1.5 ± 1.1, P = 0.0001). MyDiagnostick had a sensitivity of 100.0% and a specificity of 96.2%. In comparison, manual pulse check had a sensitivity of 83.3% and a specificity of 98.9%. CONCLUSION MyDiagnostick is a simple AF screening device that can be reliably used by non-specialist professionals in the community setting. Its sensitivity and specificity are comparable and validated across various studies performed in different population cohorts.
Humans ; Atrial Fibrillation/diagnosis* ; Heart Rate ; Sensitivity and Specificity ; Risk Factors ; Electrocardiography ; Mass Screening

INTRODUCTION: Despite the challenges related to His bundle pacing (HBP), recent data suggest an improved success rate with experience. As a non-university, non-electrophysiology specialised centre in Singapore, we report our experiences in HBP using pacing system analyser alone. METHODS: Data of 28 consecutive patients who underwent HBP from August 2018 to February 2019 was retrospectively obtained. The clinical and technical outcomes of these patients were compared between two timeframes of three months each. Patients were followed up for 12 months. RESULTS: Immediate technical success was achieved in 21 (75.0%) patients (mean age 73.3 ± 10.7 years, 47.6% female). The mean left ventricular ejection fraction was 53.9% ± 12.1%. The indications for HBP were atrioventricular block (n = 13, 61.9%), sinus node dysfunction (n = 7, 33.3%) and upgrade from implantable cardioverter-defibrillator to His-cardiac resynchronisation therapy (n = 1, 4.8%). No significant difference was observed in baseline characteristics between Timeframe 1 and Timeframe 2. Improvements pertaining to mean fluoroscopy time were achieved between the two timeframes. There was one HBP-related complication of lead displacement during Timeframe 1. All patients with successful HBP achieved non-selective His bundle (NSHB) capture, whereas only eight patients had selective His bundle (SHB) capture. NSHB and SHB capture thresholds remained stable at the 12-month follow-up. CONCLUSION Permanent HBP is feasible and safe, even without the use of an electrophysiology recording system. This was successfully achieved in 75% of patients, with no adverse clinical outcomes during the follow-up period.
Humans ; Female ; Middle Aged ; Aged ; Aged, 80 and over ; Male ; Bundle of His ; Follow-Up Studies ; Stroke Volume ; Retrospective Studies ; Treatment Outcome ; Cardiac Pacing, Artificial/adverse effects* ; Electrocardiography ; Ventricular Function, Left/physiology*

Humans ; Wolff-Parkinson-White Syndrome/diagnosis* ; Electrocardiography ; Athletes