The Normal Electrocardiogram: Resting 12-Lead and Electrocardiogram Monitoring in the Hospital

Approaches to panic attack symptoms in cardiology outpatients

Cardiologists' attitudes towards the patients with panic attack (PA) symptoms can be affected by many variables. This study was aimed to examine the practices and attitudes of cardiologists actively practicing in Turkey through an internet-based survey. An internet-based, cross-sectional, and observational survey was administered to actively practicing adult cardiologists. The sample size was calculated (minimum 135 participants). The survey draft was created by the conductor of the study and the final version of the survey items was decided by psychiatrists and cardiologists. Cronbach's alpha based on standardized items of the survey in the pilot (0.747) and final samples (0.742) was calculated. The survey, which included the characteristics on the landing page, was delivered to participants working in the Turkey via WhatsApp and Yahoo groups. All analyses were performed using IBM SPSS Statistics version 26.0. Ethical approval and informed consent was obtained. One hundred forty-five participants (87 males (60.00%) and 58 females (40.00%); 89 cardiology resident (61.37%) and 56 cardiology specialist (38.63%)) were included in the study. In patients presenting with symptoms of PA, when no cardiac/organic etiology was detected, 83 (57.24%) of the cardiologists directly referred the patients to psychiatry, while 62 (42.76%) of them started the treatment themselves. The most common symptom in patients presenting with non-cardiac PA symptoms was palpitations (86.20%). The number of cardiologists who had experience in starting escitalopram with a preliminary diagnosis of panic disorder (PD) was 50 (31.00%). Forty-three (29.7%) of cardiologists thought that antidepressants (ADs) were addictive. Thirty-five (24.1%) of cardiologists thought that ADs caused forgetfulness. According to 61 cardiologists, ADs should be used in the morning, while according to 64 cardiologists, ADs should be used in the evening. Forty-four (30.3%) cardiologists did not think benzodiazepines were addictive. The number of cardiologists who thought that patients who admitted to any physician other than cardiology with PA symptoms should be routinely referred to cardiology was 71 (49.00%). The difference between PA and PD was not known to any of the participants (n = 145). While gender had a limited effect on the findings, it was found that being cardiology specialist or not had a significant relationship with many variables. Binary logistic regression analysis was used to predict approach in the presence of non-cardiac PA symptoms and five variables (specialization status, routine echocardiogram examination, minimum usage time of ADs, association of ADs with addiction, and routine cardiology consultation by a non-cardiologist) were included given their contribution to the model (sensitivity = 86.70%, specificity = 83.90%; Beginning block - 2 Log likelihood 197.961; Block one - 2 Log likelihood 100.083a, Cox & Snell R2 = 0.491, Nagelkerke R2 = 0.659; Hosmer and Lemeshow Test p value 0.254; constant p = 0.001). Non-cardiac PA symptoms are detected in approximately one sixth of those who apply to cardiology outpatient clinics, and it is recommended that cardiologists refer these patients to psychiatry to be evaluated for PD and receive appropriate treatment. PD treatment is a teamwork, and collaboration between cardiology and psychiatry is an integral part of this process.

Invasive and non-invasive monitoring in the ICU

Effective invasive and non-invasive monitoring, when coupled with good clinical decision making, can improve outcomes for critically ill patients. When deciding on the best monitoring technique, it is important to consider the specific information that is needed to guide critical care management, while balancing the reliability of the data obtained and the risks of invasive monitor placement. Here, we review invasive and non-invasive options for hemodynamic and neurologic monitoring in the Surgical Intensive Care Unit. Understanding how each monitoring device functions, its indications, risks, and limitations is key when deciding how to monitor bedside physiologic data that guide clinical decision making. Level of evidence: Level IV.

Computational Modeling of Cardiac Electrophysiology with Human Realistic Heart-Torso Model

The electrocardiogram (ECG) has long been considered the non-invasive gold standard in diagnosing heart diseases. However, its connection with the cardiac molecular biology remains somewhat unclear. Therefore, modeling the electrophysiological behavior of the heart provides an important theoretical complement to clinically observable data. This study employed an electrophysiological model, integrating a bidomain model with the Fitzhugh-Nagumo (FHN) model, to compute an ECG and body surface potential maps (BSPMs). Parameters from previous studies were simulated individually for the cardiac domain. A specific set of parameters was selected based on comparisons of the morphology of the 12-lead ECG. The effect of the heart position relative to the torso on the 12-lead ECG was analyzed using a simplified whole-heart model to approximate the realistic heart position within the torso. Significant waveform changes were observed in leads VIII and aVL, as compared to other leads. This study employed a realistic heart-torso model, in contrast to earlier studies. External stimuli were incorporated into the original electrophysiological model to account for the electrical isolation between the atria and ventricles. The morphology of the simulated 12-lead ECG closely matched that of clinically observed data.

Practice and confidence in electrocardiogram interpretation among ICU nurses: A cross-sectional study

OBJECTIVES

This study aimed to determine practice and confidence in electrocardiogram (ECG) interpretation among intensive care unit (ICU) nurses in Fujian Province, China, and identify predictors of ECG interpretation practice.

RESEARCH METHODOLOGY/DESIGN

A quantitative cross-sectional study was conducted between October 2021 and December 2021 among 357 respondents.

SETTING

Conducted online at twenty-one hospitals in all nine cities of Fujian Province.

MAIN OUTCOME MEASURES

Purposive and convenient sampling techniques were employed in selecting hospitals and respondents, respectively. A validated and pre-tested Chinese version of the questionnaire was used in data collection. We conducted binary logistic regression to identify the predictors of ICU nurses' ECG interpretation practice, and linear regression to analyze the relationship between ECG interpretation practice and confidence. We considered statistically significant a p-value < 0.05.

RESULTS

The practice mean score of the respondents was 5.54 (SD = 2.26) out of 10 points, and only 2.2 % of nurses correctly interpreted all the patient ECG strips. Few ICU nurses (25.5 %) had good ECG interpretation practice, with a confidence mean score of 2.02 (SD = 0.99) out of 4 points in their overall ability to interpret patient ECG strips. Currently working unit in comparison to cardiac ICU (emergency ICU: AOR = 5.71, 95 % CI: 1.84-17.75); previous ECG training (AOR = 2.02, 95 % CI: 1.10-3.70); source of ECG training (university/school) (AOR = 2.02, 95 % CI: 1.12-3.65); and ECG knowledge (AOR = 16.18, 95 % CI: 7.43-35.25) were significantly associated with the ECG interpretation practice.

CONCLUSIONS

ICU nurses' ECG interpretation practice in the current study was relatively poor. An ECG education program is recommended to impart ICU nurses with basic ECG knowledge for enhancing good ECG interpretation practice and confidence in nursing care provision.

IMPLICATIONS FOR CLINICAL PRACTICE

Good ECG interpretation skills are paramount among ICU nurses for better patient outcomes. ECG knowledge among ICU nurses is an important predictor of effective ECG monitoring for cardiac arrhythmias. Therefore, frequent, continuouszgood practice and boost confidence in the provision of quality nursing care.

Telephone training to improve ECG quality in remote screening for atrial fibrillation

Objective.Self-recorded, single-lead electrocardiograms (ECGs) are increasingly used to diagnose arrhythmias. However, they can be of variable quality, affecting the reliability of interpretation. In this analysis of ECGs collected in atrial fibrillation screening studies, our aims were to: (i) determine the quality of ECGs when recorded unsupervised; and (ii) investigate whether telephone training improved ECG quality.Approach.Data was obtained from the Screening for Atrial Fibrillation with ECG to Reduce stroke programme, where participants recorded four single-lead ECG traces per day for three weeks using a handheld device. ECG quality was assessed by an automated algorithm, and participants who recorded >25% poor-quality ECGs from days 4-10 of screening were identified for training to improve ECG recording technique. Training was delivered when research team capacity permitted.Main results.13 741 participants recorded 1127 264 ECGs, of which 41 288 (3.7%) were poor-quality. Most participants (51.5%) did not record any poor-quality ECGs. 1,088 (7.9%) participants met the threshold for training. Of these, 165 participants received training and 923 did not. The median proportion of poor-quality ECGs per participant on days 1-3 was 41.7 (27.3-50.0)% for those who received training and 33.3 (25.0-45.5)% for those who did not. On days 11-21, the median proportions of poor-quality ECGs per participant were significantly lower (p< 0.001) for those who received training, 17.8 (5.0-31.6)%, and those who did not, 14.0 (4.8-30.2)%. Comparing these groups, the mean (95% confidence interval) reduction in proportion of poor-quality ECGs from days 1-3 to days 11-21 was 20.2 (16.8-23.5)% in those who received training and 16.0 (14.7-17.3)% in those who did not (p= 0.396).Significance.Most participants achieved adequate quality ECGs. For those that did not, ECG quality improved over time regardless of whether they received telephone training. Telephone training may therefore not be required to achieve improvements in ECG quality during screening.

Association between exposure to greenspace and ECG abnormalities in China: a nationwide longitudinal study

BACKGROUND

Greenspace is an important modifiable environmental factor that is associated with health and well-being. Although previous research has shown that exposure to greenspace is beneficial for cardiovascular diseases, studies have rarely focused on early subclinical health outcomes such as electrocardiogram (ECG) abnormality.

METHODS

We developed a longitudinal study using data from the China National Stroke Screening Survey (2013-2019). Monthly exposure to greenspace was assessed by the Normalized Difference Vegetation Index (NDVI) values. ECG abnormality was diagnosed by physicians based on the results of the 12-lead electrocardiogram. We used fixed-effects logistic regression with participant-specific intercepts to estimate the association between exposure to greenspace and ECG abnormalities.

RESULTS

A total of 132,108 visits from 61,029 participants with ≥ 2 ECG measurements were included. At baseline, the lag-1 month average NDVI value was 0.29 (SD = 0.15). In the fully adjusted model, per 0.1-unit increment in lag-1 month average NDVI value was associated with a 3.0% (95% CI -1.6 ∼ 7.4%) decreased risk of ECG abnormality. In urban areas, the decreased risk associated with per 0.1-unit increment in NDVI was 14.81% (95% CI 9.38 ∼ 19.92%).

CONCLUSION

Our study found that higher exposure to greenspace was associated with a decreased risk of ECG abnormality, especially in urban areas. Our findings suggested that monthly exposure to greenspace might be beneficial to cardiovascular health, and greenspace provision and maintenance could be considered an important public health intervention in urban planning.

Competency of Nurses on Electrocardiogram Monitoring and Interpretation in Selected Hospitals of Al-Ahsa, Saudi Arabia

PURPOSE

The ability of healthcare nurses to monitor and interpret electrocardiograms (ECGs) is essential for the identification of heart-related abnormalities and rapid treatment initiation. Lack of expertise of nurses in this competency may cause confusion and complications. The aims of this study were to assess the competency levels of nurses in monitoring and interpreting ECGs and to associate the knowledge with the demographic variables.

PATIENTS AND METHODS

A descriptive cross-sectional study design was used. A total of 156 nurses were selected from five hospitals located in Al-Ahsa, Saudi Arabia by computer generated simple randomization. A structured self-administered tool for knowledge and observational checklist for skills regarding ECG monitoring and interpretation was used. Tool validity and reliability were tested. Descriptive and inferential statistics, including the mean, standard deviation, and chi-square test, were applied. Statistical significance was set at p < 0.05.

RESULTS

Mean participant age was 32.59 ± 5.35 years, 30% of nurses had adequate knowledge, and the overall mean score was 17 ± 3.97. Seventy-two (46.2%) nurses correctly interpreted the ECG axis, and 76 (48.7%) could identify the Q-T interval on ECG strips. Significant associations of nurse knowledge level were detected with age (p < 0.0208), education (p < 0.0001), experience (p < 0.0001), nationality (p < 0.0002), and hospital type (p < 0.0018).

CONCLUSION

Most nurses had a low level of expertise in interpreting ECGs, and it will be crucial for them to improve their competence. Adequate training on ECG interpretation will enhance the proficiency of nurses and help provide appropriate care and life-saving measures to patients in emergency situations.

ICU nurses' knowledge and attitude towards electrocardiogram interpretation in Fujian province, China: a cross-sectional study

Introduction

The series of electrocardiograms (ECGs) can help track cardiac abnormalities in patients' conditions and make an earlier clinical decision. It is crucial for nurses working in critical care environments to acquire ECG knowledge for effective ECG monitoring and act accordingly in case of a change in patient condition. This study aimed at investigating intensive care unit (ICU) nurses' knowledge and attitude towards ECG interpretation in Fujian province, China. The study also analyzed the relationship between participants' demographic characteristics and level of ECG knowledge.

Methods

This study was done online at twenty-one hospitals in Fujian province using a quantitative cross-sectional design involving 357 registered nurses working in the ICU between October and December 2021. The selection of hospitals and potential participants involved purposive and convenient sampling methods, respectively. Binary logistic regression was carried out to determine factors that predict ICU nurses' knowledge of ECG interpretation, and a p-value <0.05 was deemed statistically significant.

Results

The majority of nurses (70.9%) demonstrated a low level of ECG knowledge. The mean score for ECG knowledge was 5.95 (SD = 2.14), with only 0.8% of ICU nurses answering all questions correctly. The majority portrayed positive attitude towards ECG interpretation; however, more than half (61.6%) believed that nurses should rely on a doctor's opinion about ECG interpretation. Previous ECG training (AOR = 3.98, 95% CI: 2.12-7.45); frequency of ECG interpretation in comparison with no frequency of ECG interpretation (1-3 times per day: AOR = 15.55, 95% CI: 6.33-38.18; 1-3 times per week: AOR = 18.10, 95% CI: 6.38-51.34); and current working unit in comparison to those working in cardiac ICU (general ICU: AOR = 0.45, 95% CI: 0.21-0.94; medical ICU; AOR = 0.28, 95% CI: 0.12-0.67; and surgical ICU; AOR = 0.05, 95% CI: 0.01-0.43) remained statistically significant after adjusting for confounders.

Conclusion

The present study revealed a low level of knowledge about ECG interpretation among ICU nurses. Although the participants demonstrated positive attitudes toward ECG interpretation, the negative attitude still existed. Nurses should acknowledge ECG interpretation as part of their duties and responsibilities in nursing care instead of merely relying on doctors' opinions.

A DENOISING METHOD OF DIAPHRAGM ELECTROMYOGRAM SIGNALS BASED ON DUAL-THRESHOLD FILTER

Diaphragmatic electromyography (EMGdi) signals can effectively reflect human respiratory process and effort, but simultaneously interfered by electrocardiogram (ECG) signals, leading to the limited application of EMGdi signals. Conventional denoising schemes for ECG cancellation from EMGdi signals are usually limited to the cases of irregular ECG signals. For this purpose, this paper proposes a denoising method of ECG signals by using a dual-threshold filter, which performs effectively in the scenarios of irregular ECG condition, such as arrhythmia. Specifically, we first employ wavelet transform to decompose EMGdi signals to wavelets of different frequencies, by which QRS complex detection is performed to determine the location of ECG signals. Then we propose to remove the ECG interference by reforming the interference range with the adjacent signals. Experimental results indicate that the proposed denoising method performs superior to the state-of-the-art schemes, especially for the cases of weak EMGdi signal scenarios.

Feasibility and Reliability of Smartwatch to Obtain Precordial Lead Electrocardiogram Recordings

The Apple Watch is capable of recording single-lead electrocardiograms (ECGs). To incorporate such devices in routine medical care, the reliability of such devices to obtain precordial leads needs to be validated. The purpose of this study was to assess the feasibility and reliability of a smartwatch (SW) to obtain precordial leads compared to standard ECGs. We included 100 participants (62 male, aged 62.8 ± 13.1 years) with sinus rhythm and recorded a standard 12-lead ECG and the precordial leads with the Apple Watch. The ECGs were quantitively compared. A total of 98 patients were able to record precordial leads without assistance. A strong correlation was observed between the amplitude of the standard and SW-ECGs’ waves, in terms of P waves, QRS-complexes, and T waves (all p-values < 0.01). A significant correlation was observed between the two methods regarding the duration of the ECG waves (all p-values < 0.01). Assessment of polarity showed a significant and a strong concordance between the ECGs’ waves in all six leads (91–100%, all p-values < 0.001). In conclusion, 98% of patients were able to record precordial leads using a SW without assistance. The SW is feasible and reliable for obtaining valid precordial-lead ECG recordings as a validated alternative to a standard ECG.

Baseline Corrected QT Interval Dispersion Is Useful to Predict Effectiveness of Metoprolol on Pediatric Postural Tachycardia Syndrome

OBJECTIVES

The study was designed to explore the role of baseline-corrected QT interval dispersion (QTcd) in predicting the effectiveness of metoprolol on pediatric postural tachycardia syndrome (POTS).

METHODS

There were two groups in the study, the discovery group and the validation group. The children with POTS in the discovery group were treated with oral metoprolol, with the completed necessary medical records, head-up tilt test (HUTT), blood chemistry, and 12-lead ECG before treatment at the pediatrics of Peking University First Hospital, China. According to whether the symptom score (SS) was reduced by more than 2 points after administration with oral metoprolol as compared with that before treatment, the children with POTS were separated into responders and non-responders. The demographic characteristics, hemodynamic indicators, and the QTcd of the two groups were compared, and the estimate of the baseline QTcd in predicting the treatment response to metoprolol was tested through a receiver operating characteristic (ROC) analysis. Other 24 children suffering from POTS who were, administrated with metoprolol at the pediatrics of Peking University First Hospital were included in the validation group. The sensitivity, specificity, and accuracy of the baseline QTcd in the prediction of the effectiveness of metoprolol on POTS were validated in children.

RESULTS

The pre-treatment baseline QTcd in responders treated with metoprolol was longer than that of the non-responders in the discovery group [(66.3 ± 20.3) ms vs. (45.7 ± 19.9) ms, p = 0.001]. The baseline QTcd was negatively correlated with SS after metoprolol treatment (r = -0.406, p = 0.003). The cut-off value of baseline QTcd for the prediction of the effectiveness of metoprolol on pediatric POTS was 47.9 ms, yielding a sensitivity of 78.9% and a specificity of 83.3%, respectively. The validation group showed that the sensitivity, specificity, and accuracy of the baseline QTcd ≥ 47.9 ms before treatment for estimating the effectiveness of metoprolol on POTS in children were 73.7, 80.0, and 75.0%, respectively.

CONCLUSION

Baseline QTcd is effective for predicting the effectiveness of metoprolol on pediatric POTS.

Investigation on the Prediction of Cardiovascular Events Based on Multi-Scale Time Irreversibility Analysis

Investigation of the risk factors associated with cardiovascular disease (CVD) plays an important part in the prevention and treatment of CVD. This study investigated whether alteration in the multi-scale time irreversibility of sleeping heart rate variability (HRV) was a risk factor for cardiovascular events. The D-value, based on analysis of multi-scale increments in HRV series, was used as the measurement of time irreversibility. Eighty-four subjects from an open-access database (i.e., the Sleep Heart Health Study) were included in this study. None of them had any CVD history at baseline; 42 subjects had cardiovascular events within 1 year after baseline polysomnography and were classed as the CVD group, and the other 42 subjects in the non-CVD group were age matched with those in the CVD group and had no cardiovascular events during the 15-year follow-up period. We compared D-values of sleeping HRV between the CVD and non-CVD groups and found that the D-values of the CVD group were significantly lower than those of the non-CVD group on all 10 scales, even after adjusting for gender and body mass index. Moreover, we investigated the performance of a machine learning model to classify CVD and non-CVD subjects. The model, which was fed with a feature space based on the D-values on 10 scales and trained by a random forest algorithm, achieved an accuracy of 80.8% and a positive prediction rate of 86.7%. These results suggest that the decreased time irreversibility of sleeping HRV is an independent predictor of cardiovascular events that could be used to assist the intelligent prediction of cardiovascular events.

Modes of death and clinical outcomes in adult patients with hypertrophic cardiomyopathy in Thailand

Background

There are limited data about modes of death and major adverse cardiovascular events (MACEs) in patients with hypertrophic cardiomyopathy (HCM) in South East Asian population. The aim of the study was to examine modes of death and clinical outcomes in Thai patients with HCM.

Methods

Between January 1, 2009 and December 31, 2013, 166 consecutive patients with HCM diagnosed in our institution were evaluated. Five patients were excluded because of non-Thai ethnic groups (n = 3) and diagnosis of myocardial infarction at initial presentation documented by coronary angiography (n = 2). The final study population consisted of 161 patients with HCM. HCM-related deaths included: (1) sudden cardiac death (SCD) – death due to sudden cardiac arrest or unexpected sudden death; (2) heart failure – death due to refractory heart failure; or (3) stroke - death due to embolic stroke associated with atrial fibrillation. MACEs included: (1) SCD, sudden unexpected aborted cardiac arrest, fatal, or nonfatal ventricular arrhythmia (ventricular fibrillation or sustained ventricular tachycardia); (2) heart failure (fatal or non-fatal), or heart transplantation; or (3) stroke - fatal or non-fatal embolic stroke associated with atrial fibrillation.

Results

One hundred and sixty-one Thai patients with HCM (age 66 ± 16 years, 58% female) were enrolled. Forty-two patients (26%) died over a median follow-up period of 6.8 years including 25 patients (16%) with HCM-related deaths (2%/year). The HCM-related deaths included: heart failure (52% of HCM-related deaths; n = 13), SCD (44% of HCM-related deaths; n = 11), and stroke (4% of HCM-related deaths, n = 1). The SCDs occurred in 6.8% of patients (1%/year). Eighty-four major MACEs occurred in 65 patients (41, 5%/year). The MACEs included: 40 heart failures in which 2 patients underwent heart transplants; 22 SCDs and nonfatal ventricular arrhythmias; and 22 fatal or nonfatal strokes.

Conclusions

The most common mode of death in adult patients with HCM in Thailand was heart failure followed by SCD. About one-third of the patients experiencing heart failure died during the 6.8 years of follow-up. SCDs occurred in 7% of patients (1%/year), predominantly in the fourth decade or later.