bluuebunny/crossref_metadata_2025 huggingface dataset:
Standardization of transthoracic impedance values for estimating heart failure and its utility
Authors: Nose D , Ibayashi Y , Arimura T , Matsui T , Matsuda Y , Otsuka T , Yasumoto K , Sugimoto M , Miura S
Published: October 2024

Background

The use of intrathoracic impedance for examining pleural effusion in heart failure patients has been explored previously. However, due to concerns about its accuracy and complexity, transthoracic impedance values have had limitations in quantifying extravascular lung water. Our dual objectives were to clarify the relationship between intrathoracic conditions and percutaneous transthoracic impedance values, and to establish a basic model for a new machine learning-based estimation system for assessing intrathoracic conditions in patients with heart failure.

Methods

First, we developed a live porcine congested lung model that induced pleural effusion by substantial fluid loading, and then longitudinally evaluated its correlation with percutaneous transthoracic impedance values. Second, we conducted multi-frequency bioelectrical impedance analysis to simultaneously collect electrical, physical, and hematological data from 63 hospitalized heart failure patients and 82 healthy volunteers

Results

In the porcine model, pleural effusion correlated with a concurrent decrease in SpO2 and a gradual decrease in impedance. We indexed and generated features from the measured values and developed an intrathoracic estimation model based on electrical measurements and clinical findings using a decision tree-based machine learning approach. Among the 286 features collected per individual, the model used 16 features. Notably, the model demonstrated high accuracy in discriminating patients with pleural effusion, achieving an AUC of 0.905 (95% CI: 0.870-0.940) in cross-validation, significantly outperforming the conventional frequency-based method.

Conclusions

Transthoracic impedance values, when indexed, reflect intrathoracic conditions and improve estimation. Our results highlighted the potential of machine learning and thoracic impedance measurement for accurate estimation of pleural effusion. This approach provides an effective means of assessing intrathoracic conditions.

Figure: The upper figure shows the relationship between impedance values and pleural effusion in the congested lung model. On these results, human data were collected to construct the estimation model. The lower illustrates the accuracy of the model and provides a comprehensive view of the system.
AI-based cluster analysis enables outcomes prediction among patients with increased LVM
Authors: Loutati R , Kolben Y , Luria D , Amir O , Biton Y
Published: October 2024

Background

The traditional classification of left ventricular hypertrophy (LVH) solely based on left ventricular geometry disregards associated comorbidities and clinical characteristics. We aimed to identify unique clinical phenotypes of LVH using unsupervised cluster analysis and explore their association with clinical outcomes.

Methods

From UK Biobank (UKBB) participants with available left ventricular mass (LVM) estimations, we identified those meeting CMR-based criteria for increased LVM: LVM index ≥ 72 g/m2 for males and LVM index ≥ 55 g/m2 for females. Baseline demographic, clinical, and laboratory data were collected. Using Ward's method, patients were clustered based on 27 variables. The primary outcome was a composite of all-cause mortality with heart failure (HF) admissions, ventricular arrhythmia, and atrial fibrillation (AF). Cox proportional hazard model and Kaplan-Meier survival analysis were applied.

Results

Among CMR-assessed UKBB participants, 4,255 individuals exhibited increased LVM, with an average age of 64 ± 7 years; 2,447 (58%) were females. Cluster analysis identified four distinct subgroups. Over a median 5-year follow-up (IQR: 4-6), 100 patients (2%) died, 118 (2.8%) were hospitalized due to HF, 29 (0.7%) were hospitalized due to VA, and 208 (5%) were hospitalized due to AF. Univariate Cox analysis revealed that compared to the 1st cluster (n=1,578), patients in the 2nd (n=1,296), 3rd (n=824) and 4th (n=557) clusters had 60%, 104%, and 164% increased risk of a major event, respectively (95% CI 1.2-2.16, p<.001 for cluster 2; 95% CI 1.49-2.78, p<.001 for cluster 3; 95% CI 1.92-3.62, p<.001 for cluster 4). Each cluster manifested different phenotypes: cluster 2 comprised mainly overweight females, with the highest prevalence of chronic lung disease; cluster 3, predominantly composed of males, had the highest burden of comorbidities and cardiovascular risk factors; and cluster 4, mostly males, presented with the most abnormal cardiac measures, including left ventricular end-diastolic volume (LVEDV), left ventricular end-systolic volume (LVESV), and left ventricular ejection fraction (LVEF).

Conclusions

Unsupervised cluster analysis identified four subgroups among patients with increased LVM. These subgroups bear notable relevance to overall mortality risk and clinical outcomes. This phenotypic classification holds promise in offering valuable insights regarding clinical course and outcomes in LVH patients.
An explainable AI for trustworthy detection of atrial fibrillation on reduced lead ECGs in mobile applications
Authors: Hammer A , Goettling M , Malberg H , Linke A , Schmidt M
Published: October 2024

Introduction

Artificial intelligence (AI), particularly deep learning (DL), has demonstrated high performance in various diagnostic problems, including the detection of paroxysmal atrial fibrillation (AF) from electrocardiograms (ECGs). In mobile applications, these approaches can help to detect AF at an early stage and thus prevent possible secondary diseases. However, due to their black-box nature, DL approaches lack explainability and interpretability. Furthermore, 12-lead ECGs are the clinical standard, but mobile devices usually only provide 1–3 leads, which are similar but not identical to Einthoven leads and differ in morphology.

Purpose

We apply a recently introduced explainable ECG analysis architecture (xECGArch) to single-lead ECGs to verify its performance in mobile applications. xECGArch can learn rhythmic and morphological characteristics using two parallel convolutional neural networks of different dimensions (Fig. 1). When combined with methods from explainable AI, the classification can be traced back to rhythmic and morphological characteristics.

Methods

We used a subset of 9 854 ECGs (n(AF) = n(non-AF) = 4 927) from 4 public databases (Chapman-Shaoxing, CPSC2018, Georgia, and PTB-XL). Noise was removed using a cascade of high-pass filtering at 0.3 Hz and discrete wavelet transform. For each lead, we trained xECGArch on single-lead ECGs of 10 s length to classify AF vs. non-AF using 90% of the ECGs with 5-fold cross-validation and tested it on the remaining randomly selected ECGs (n(AF) = 507, n(non-AF) = 479). Consistent data splitting was ensured for all leads. Model explanations were generated using deep Taylor decomposition.

Results

Both models achieved minimum 91.1% accuracy for each ECG lead (Fig. 1). On lead I, the morphology model outperformed the rhythm model with 92.8% vs. 91.5% accuracy, while the rhythm model slightly outperformed the morphology model on leads II and III with 94.2%–95.0% accuracy vs. 91.1%–94.0%. Both models achieved maximum accuracy of 95.0% (rhythm) and 94.0% (morphology) on lead II. By combining both models, xECGArch reached 93.7%–95.1% accuracy. The model explanations confirm that the rhythm model primarily considers QRS complexes as relevant, while the morphology model focuses on fibrillatory waves (Fig. 1).

Conclusions

Both rhythm and morphology models achieved reliable results across all leads, competing with the state-of-the-art for automatic AF detection from single-lead ECGs. The combination of both models in xECGArch further increased the accuracy. xECGArch is based on the medical reading of ECGs by considering rhythm and morphology characteristics and is therefore interpretable by design. The model explanations are consistent with the diagnostic criteria for AF (Fibrillatory waves and absolute arrhythmia) across leads. With high accuracy on different single-lead ECGs and improved interpretability, xECGArch provides a trustworthy method for ECG analysis in mobile applications.
Accuracy of the Apple Watch in detecting atrial fibrillation among patients undergoing 24-hour Holter monitoring
Authors: Inocian E , Junia A , Cordovez M G , Katada K , Paday L M W
Published: October 2024

Background

As direct-to-consumer wearable devices like the Apple Watch become more common, an increasing number of patients arrive at clinics with reports of irregular rhythms captured on their devices.

Purpose

This study sought to assess the accuracy of a commonly used smart wearable device (Apple Watch) in detecting atrial fibrillation.

Methods

We enrolled 140 patients referred for 24-hour Holter monitoring in a Cardiovascular Center. Following thorough disclosure, participants were instructed to wear an Apple Watch provided by the researchers in addition to the Holter monitor to facilitate comparison. The Apple Watch was selected due to its widespread usage among patients. Participants were instructed to record an ECG using the Apple Watch hourly, or more frequently while awake. The objective of the study was to evaluate the sensitivity and specificity of the irregular rhythm notification and ECG-based detection features of the Apple Watch in comparison to the conventional 24-hour Holter monitoring for atrial fibrillation detection.

Results

The irregular rhythm notification feature of the Apple Watch exhibited a low sensitivity of 21.4% but achieved a high specificity of 100% in detecting atrial fibrillation. Meanwhile, the ECG-based detection feature of the Apple Watch analyzed from 1,295 ECGs captured by the participants when compared in real-time to their ECG rhythms recorded by the Holter monitor, revealed a high level of agreement with a sensitivity of 100% and a specificity of 99.1%.

Conclusion

The low sensitivity of the irregular notification feature of the Apple watch in detecting atrial fibrillation cautions against relying solely on it to rule out atrial fibrillation as the cause of a patient’s symptoms. Nevertheless, the high concordance of manually taken Apple watch ECGs positions the device as a reliable tool for detecting atrial fibrillation through its ECG-based detection feature.
Low conduction velocity is a key factor for localisation of reentrant drivers for atrial fibrillation
Authors: Ogbomo-Harmitt S , King A , Aslanidi O
Published: October 2024

Background

Atrial Fibrillation (AF) is a prevalent cardiac arrhythmia globally, associated with heightened risks of stroke, dementia, and heart failure. Catheter ablation, the sole curative therapy for AF, yields suboptimal success rates for persistent AF cases. Understanding the mechanisms and dynamics of AF remains challenging, hindering treatment advancements. Novel ablation strategies aimed at targeting substrates harbouring AF reentrant drivers (RD), such as low-voltage ablation and rotor-based ablation, have yet to demonstrate superiority over the gold standard ablation strategy – pulmonary vein isolation.

Purpose

The purpose of the study is to integrate in-silico 3D left atrial (LA) simulations and explainable artificial intelligence (AI) to pinpoint key factors for RD localisation in persistent AF, aiming to improve the mechanistic understanding of AF and help develop a more effective ablation strategy.

Methods

3D LA models were derived from magnetic resonance images of 41 patients and combined with atrial cell electrophysiology models. Persistent AF was initiated in each patient-specific LA model with fast pacing, and five functional features (action potential duration (APD), conduction velocity (CV), wavelength, APD spatial gradient, CV spatial gradient, and wavelength spatial gradient) and three structural features (fibrotic density, fibrotic entropy, and image intensity ratio) were evaluated. A random forest AI model was trained to classify phase singularities corresponding to the RDs (PS-RD) in five distinct tissue classes (total LA tissue, healthy tissue, fibrotic border zone, dense fibrotic tissue, and PS-RD tissue) based on the functional and structural features. Shapley additive explanations (SHAP) analysis was then used to find the most influential feature in the AI model’s decision process.

Results

Simulations of the patient-specific LA models revealed that RDs were typically localised in regions with the lowest atrial CV, which often coincided with patches of dense fibrotic tissue. In a five-fold cross-validation, the random forest AI model achieved high accuracy in classifying PS-RD regions: a mean ROC AUC of 0.99 ± 0.010, a mean F1 score of 0.86 ± 0.034, a mean recall of 0.95 ± 0.058, and a mean precision score of 0.79 ± 0.085. The further SHAP analysis revealed that low CV was the key determinant in classifying the PS-RD regions.

Conclusion

Our study combined AF computational modelling and explainable AI to identify the key factors in RD localisation. Both the computational and AI models concluded that low CV was the most important determinant in localising RDs. These findings provide mechanistic evidence for the efficacy of ablation strategies that target low CV atrial areas for persistent AF patients.
To monitor or not after detected AF, this is a question: report from the consumer-led screening programme of long-term extension mAFA cohort
Authors: Guo Y
Published: October 2024

Background

The consumer-led screening for atrial fibrillation (AF) is evolving with the widespread availability of wearables. Nonetheless, what the long-term impact on the individual's behavior of rhythm monitoring after detected AF is unclear.

Objective

To investigate the long-term impact on health behavior for the individuals using wearables for cardiac rhythm.

Methods

In the mobile technology supported screening and integrated care in atrial fibrillation (mobile atrial fibrillation application, mAFA programme), the general population freely decided to enter the screening programm with wristbands or watches across China. At least 14-day monitoring was proposed, the individuals with detected AF can consider to receive the mAFA App for AF care. The adherence of rhythm monitoring after detected AF with wearables was calculated, while the multinomial logistics regression model was utilised to analyze the independent factors associated with the adherence.

Results

There were 4337172 individuals entered into AF screening programme using wearables between Oct, 2018 and Feb 14, 2024. Among them, 22224 individuals (0.5%, 22224/4337172, mean age, SD, 55, 16 years old, male 82.4%) were monitored with AF episodes. There were 21223 individuals remaining the wearables use for rhythm monitoring after first AF identification. The time (days, median, interquartile ) using wearables for monitoring the pulse rhythm were 465 (130, 889) days. The time to first identified AF (days, median, interquartile) were 16 (1, 176) days. The continuing monitoring time since first identified AF (days, median, interquartile) were 290 (54, 668) days.

The adherence of cardiac rhythm monitoring after detected AF with wearables (Figure): 96.0% individuals continued the rhythm monitoring using wearables during 30 days, 58.8% in 2 years, and 35.7% in 3 years and over.

In the adjusted multinomial logistics regression model, the palpitation, hypertension, obstructive sleep apnea, heart failure, age and mAFA use were independently associated with the adherence for the individuals remaining the wearables use for rhythm monitoring after detected AF (all p<0.05).

Conclusions

The general population at risk were likely to receive long-term rhythm monitoring after detected AF, and the mAFA use, with the self-care support, was an independent factor for the continuing monitoring.
Traditional dual-chamber right ventricular pacing versus conduction system pacing in the US medicare population
Authors: Vijayaraman P , Longacre C , Kron J , Subzposh F , Zimmerman P , Butler K , Crossley G H , Ellenbogen K A
Published: October 2024

Introduction

Conduction system pacing (CSP) has emerged as an alternative therapy to traditional right ventricular (RV) pacing. However, the majority of CSP studies reflect small cohorts or single-center experience.

Purpose

This analysis aimed to compare CSP to dual chamber (DC) RV pacing in a large, population-based cohort utilizing data from the Micra Coverage with Evidence Development (CED) study.

Methods

Medicare administrative claims data were used to identify patients implanted with a DC RV pacemaker. Lead placement data from Medtronic’s device registration system was used to identify patients with treated with CSP (N=6,197) using a 3830 catheter-delivered lead or DC RV (non-3830 lead, non-CSP placement) (N=16,989) at the same centers. CSP patients were stratified into left bundle branch area pacing (LBBAP) (N=4,738) and His-bundle pacing (HBP) (N=1,459). Incident heart failure hospitalizations (iHFH), all-cause mortality, complication rates and reinterventions at 6 months were analyzed.

Results

CSP (LBBAP and HBP) patients with a 3830 catheter-delivered lead experienced significantly lower rates of iHFH (HR: 0.70, P=0.02) and all-cause mortality at 6 months compared with DC RV patients (HR: 0.66, P<.0001) (figure). There was no difference in complications (HR: 0.89, P=0.06) or need for reintervention (HR: 0.83, P=0.08) with LBBAP compared to DC RV, though HBP patients experienced significantly higher rates of complications (HR: 1.41, P=0.001) compared to LBBAP.

Conclusion

Patients treated with CSP with a 3830 catheter-delivered lead experienced significant all-cause mortality and HFH benefits compared to DC RV pacing. LBBAP had lower complications compared to HBP. These real-world results in a large cohort of Medicare patients align with findings in small clinical studies demonstrating the benefits of LBBAP. Future research will focus on understanding patient selection for CSP.Figure
Echo triaging works. How to use international guidelines
Authors: Kipourou K , Jimeno M , Keskin Meric B , Chester R , Barron A J , Rahman Haley S , Baltabaeva A
Published: October 2024

Introduction

Transthoracic echocardiography (TTE) is the first-choice non-invasive imaging modality for the assessment of cardiac structure and function due to its wide availability, speed, cost-effectiveness and reproducibility. Therefore, there is exponential increase in demand in TTE across all specialties in medicine and surgery. Hence, it is important to carefully triage patients according to current international guidelines.

Purpose

To reduce inappropriate TTE scans by using guideline driven indications in triaging echo scans in the UK tertiary hospital.

Methods

Strict list of guidelines driven indications adapted to local practice was used for triaging echo requests which included both inpatient and outpatient TTEs. The 4 objectives: appropriateness, completeness of requests as well as impact of performed studies on the follow-up and patient management plan were assessed before and after implementation of new triaging tool. To ensure similar working and staff environment was sustained we studied the pattern of referrals in the same month of the year- September. The triage process was conducted by accredited physiologists.

The same month was chosen to reflect true change of practice. Change in patient management and follow up were evaluated for a minimum duration of 6-months.

Results

Overall there were 1112 TTEs performed in September 2022 and 1081 - in September 2023. Prospective TTE referral triaging began in March 2023. We have studied and analyzed above criteria retrospectively. In 2022 there were 18% inappropriate requests; 37% of requests lacked sufficient clinical information and 10% of studies did not lead to change in management plan according to clinical letters. There was also high proportion of inappropriate requests for inpatients (9%). Within 6 months of implementation there was a significant improvement in the appropriateness (82% vs. 99%, p<0.001), with increase in supply of adequate clinical information (63.4% vs. 86.1%, p<0.001). However, there was no significant change using TTE study results in changing patient management (10%). All inpatients had 100% appropriate requests.

Conclusion

The implementation of triage criteria resulted in a significant improvement in TTE referrals: both in appropriateness and completeness of requests. However, some clinicians did not use echo in patient management plan. Future research on lack of use of TTE results in clinical practice might help to utilize the limited echo capacity to full.
The impact of daily step count with mobile health apps on clinical outcomes among general population
Authors: Takeji Y , Nomura A , Takamura M , Tabuchi T
Published: October 2024

Background/Introduction

Numerous studies have investigated the correlation between daily step count and the reduction of all-cause mortality and cardiovascular events. However, the optimal daily step count for the general population remains controversial.

Purpose

This study aims to assess cardiovascular risk based on individual step counts using a large cohort that includes step count data from mHealth Apps (Kencom), health checkups databases, and Japanese insurance claims databases.

Methods

We analyzed data from 85,204 users registered with Kencom between January 2016 and September 2021. The mean step count during one year before and after baseline data collection was used to define each individual's step count. We divided participants into low (N=45,539) and high (N=39,665) step count groups based on their mean step counts. Additionally, we categorized users into five groups based on their step counts (<4000; 4000-5999; 6000-7999; 8000-9999; and ≥10000) to evaluate cardiovascular events. The primary outcome was the occurrence of cardiovascular events, including myocardial infarction, stroke, angina pectoris, heart failure, and atrial fibrillation, as classified by the International Classification of Diseases and Related Health Problems, 10th Revision (ICD-10). The cumulative incidence was estimated over 5 years.

Results

The high step count group was generally younger and predominantly male. No significant differences in cardiovascular risk factors such as hypertension, dyslipidemia, diabetes mellitus, and current smoking status were found between the two groups. Stratifying baseline characteristics by step count revealed significant differences among the five groups, with the exception of sex. The cumulative incidence of cardiovascular events was significantly lower in the high step count group compared to the low step count group (6.5% vs. 7.5%, log-rank P=0.005, Figure 1). After adjusting for confounding factors, the risk reduction of the high step count group remained significant (HR: 0.92, 95% CI: 0.87-0.98, P=0.005). Among the five step count groups, the incidence of primary outcome significantly differed, with only Group 5 (≥10000 steps) showing a significant reduction in the risk of cardiovascular events compared to Group 1 (<4000 steps) after adjustment (HR: 0.87, 95% CI: 0.77-0.99, P=0.03). Subgroup analyses based on sex indicated that the risk reduction was significant in males in Group 5 but not in females.

Conclusion

The risk of cardiovascular events was higher in the low step count group compared to the high step count group. After adjusting for confounders, only the highest step count group (≥10,000 steps/day) showed a significant reduction in cardiovascular event risk compared to the lowest step count group.
Comparison between smartphone 6-lead ECGs and 12-lead ECGs in athletes
Authors: Davis A , Orchard J W , Mcghie D , Driscoll T , Puranik R , Orchard J J
Published: October 2024

Introduction

Athletes occasionally experience transient arrythmias that are difficult to capture using traditional methods. Smartphone electrocardiogram (ECG) technology presents an innovative method of capturing transient arrythmias. A 6-lead (6L) smartphone device that measures leads I, II, III, aVR, aVL, and aVF, has been shown to be accurate in some populations but has limited evidence in athletes. A previous pilot study comparing 6L with 12L readings in athletes showed good correlations.

Purpose

To assess the accuracy of the 6L device in athletes by comparing the 6L with a 12-lead (12L) ECG in a larger sample size under real-world conditions.

Methods

From 2020-2023, athletes (n=217, mean age 18.0±3.8 years, 40% female) had a resting supine 12L ECG as part of cardiac screening and a seated 30s 6L reading within 2 hours of the 12L. Manual measurements of RR, QT, PR intervals, and QRS duration in the 6L and 12L ECGs were completed by a cardiologist using EPS Digital Calipers in lead II. A subset (n=30) was measured by 4 expert cardiologists and the mean was taken. Each measurement was calculated as an average of at least 6 consecutive beats in the 6L and 12L. Bland-Altman analysis was used to assess the quantitative agreement between heart rate (HR), QTc interval (Bazett), PR interval and QRS duration in the 6L and 12L. ECGs were analysed for agreement of QRS axis (normal, left and right axis deviation defined by the International Criteria for Athlete ECG Interpretation[1]).

Results

The 6L readings for HR were 5.0±11.0bpm faster than the 12L; 6L readings for other measurements were shorter than the 12L. QTc had the largest difference, with the 6L on average 14.2±27.4ms shorter than the 12L reading. For QTc, 5.5% of readings were >60ms different, mostly due to baseline interference in the 6L traces. PR intervals were 13.9±16.3ms shorter in the 6L than the 12L. QRS duration measurements were similar, with 6L readings being 0.8±10.2ms shorter than the 12L reading. There was 96.8% agreement on QRS axis classification between 6L and 12L.

Conclusion

The 6L readings had fair agreement with the 12L ECG, although the standard deviations were higher than measured in the pilot study, suggesting less consistent accuracy of the 6L. Most 6L measures (excluding HR) were slightly shorter than the 12L, consistent with studies in other populations. QRS axis categories were very similar. Given the change from supine to seated, it is unsurprising that HR was higher in the 6L. Our previous work showed good correlation between 6L and 12L readings and excellent utility of the portable 6L device for detecting transient arrhythmias in athletes. This larger study confirms most of those findings but adds caution that baseline interference is not uncommon in real-world 6L readings, meaning that QTc may be difficult to accurately measure.
A novel device for electrocardiographic imaging
Authors: Galizia Brito V , Gallego Sanchez V , Pozo Ocampo F , Gallego Bravo P , Exposito Pineda C , Grande Morales C , Torrebella Segui J , Datino Romaniega T , Cabrera Rodriguez J A
Published: October 2024

Background

Electrocardiographic imaging (ECGi) is a non-invasive imaging tool that allows 3D visualization and characterization of the electrical activity of the heart from measurements on the body surface by solving the so called "inverse problem of electrocardiography". This method helps overcome the limitations of the conventional12-lead ECG in diagnosing and locating heart arrythmias. We developed a textile 34-electrode imageless device (with no need for MRI or CT-scan).

Purpose

We aim to evaluate the feasibility and safety of the use of a novel textile imageless 34-electrode device for recording ECGi for identification of electrical activity of the heart.

Methods and results

The performance of a prototype data acquisition system (DAS) was evaluated in 158 individuals. Tests were conducted in three hospitals. The mean age was 43.32 years old (±17.44); mean height 167.31cm (±18.33); mean weight 70kg (±15.68). Almost 88% of the patients were in sinus rhythm. The relative frequencies of the targeted pathologies are listed in Figure 1. The collection of cardiac signals and posterior representation in virtual reality of a stereoscopic, holographic 3D-360º map, was achieved in 100% of the patients. Figure 2 shows the textile hardware with the silver dry electrodes and a screenshot of the software with an example of a voltage map in a patient in sinus rhythm. There were no adverse effects reported. The DAS is composed of 34 electrodes, being their distribution representative of the electrical activity on the torso. Several studies have discussed the minimum number of electrodes on the torso of the patient required to characterize the heart potentials from the electrical potentials on the torso surface through the inverse problem (1,2). We highlight that the representativeness condition of the electrical activity on the torso is crucial to appropriately estimate cardiac activity with the minimum number of leads on the DAS.

Conclusion

The use of a novel textile imageless 34-electrode device for recording ECGi for identification of electrical activity of the heart is feasible and safe.Targeted rhythmHardware and software
Cardiovascular mortality rate between 2018 and 2022 in Kyrgyz Republic
Authors: Abdurasulova A , Habib Beigh H , Abibillaev D , Kydyralieva R
Published: October 2024

Background

Cardiovascular diseases (CVD) are the number one cause of death in low- and middle-income countries (LMICs), including Kyrgyz Republic. According to official statistics, CVD ranks first in the structure of overall mortality, accounting for more than half (52.1% according to 2022 data) of all deaths.

Purpose

to analyze the cardiovascular mortality rate in the Kyrgyz Republic, from 2018 to 2022.

Methods

Medical and statistical information on mortality from CVD in the population was obtained from the Centre for Electronic Health (CEH) of the Ministry of Health. To conduct a comparative analysis, relative indicators per 100 thousand population were calculated. A retrospective epidemiological study of mortality from CVD including different nosological forms over period for 2018–2022 was conducted, calculating the rate of increase (decrease). An analysis of the epidemiological situation of the disease in nine administrative-territorial units of the Kyrgyz Republic was also carried out with the calculation of the average 5-year mortality ratefor the period from 2018 to 2022.

Results

Despite the decrease in morbidity, a high proportion of mortality from CVD remains in all years, more than 50%. In terms of the percentage indicator for recent years, all this time it has maintained the highest position, in contrast to diseases of other organs and systems. In the last decade, from 2012 until 2020, there was a gradual decrease in the mortality rate. Since 2020, we have seen a sharp increase in the CVD mortality rate per 100 thousand population by 19.6% compared to 2018, by 19.4% since 2019, which is associated with the influence of Covid-19 pandemic, in 2021 this indicator amounted to 297.6 cases, in 2022 - 234.5. The main contribution to population death from CVD is made by coronary heart disease (65.90%), including acute myocardial infarction, cerebrovascular diseases (21.4%), arterial hypertension (5.9%). If we analyze the mortality rate from CVD by nine administrative-territorial units, the highest rates in 2022 are observed in the Chui and Talas regions, 291.9 and 266.3 per 100 thousand population respectively; the lowest in the Osh region (207.3), Osh city (196.1) and Bishkek (208.6), which is explained by the better organization of health services in these areas.

Conclusion

CVD remains the main cause of mortality in the population of the Kyrgyz Republic. Although over the past year there has been a good decline in this indicator, in almost all regions, particularly the greatest successes have been achieved in Naryn and Issyk-Kul regions. In connection with the above, there is requirement for a clear identification of priorities when determining the strategy of treatment and preventive interventions. It is necessary to create an effective National system of care for patients with CVD with a focus on emergency cardiac care and prevention issues.
Cardiovascular risk factors and disease mortality among asian american subgroups
Authors: Aggarwal R , Wadhera R , Szarek M , Bhatt D
Published: October 2024

Background

Asian Americans are the fastest growing racial group in the United States. Although Asian subgroups have distinct cardiovascular (CV) risk profiles, they are often aggregated together for public health surveillance.

Purpose

We provide the first comprehensive national estimates of CV and CV risk factor mortality in Asian American subgroups to assess differences in CV risk.

Methods

We used CDC WONDER, which captures all death certificates in the US (2018-2020), as well as the American Community Survey for demographic data. Adults aged ≥18 years were included. Estimates of age-adjusted overall CV mortality, as well as heart disease, hypertension, and stroke-related mortality, were determined by ICD-10 codes. To compare the contribution of each cause of mortality among subgroups with different baseline all-cause mortality rates, proportional mortality rates were determined by race. Proportional mortality was defined as the mortality rate of each condition divided by the all-cause mortality for that race group. Differences in proportional mortality by race and ethnicity, compared with White American adults, were assessed with age-sex adjusted linear regression.

Results

The US population consisted of 12,950,565 Asian Americans (53.7% female). Among the Asian American subgroups, 25.4% were Asian Indian, 28.5% Chinese, 19.7% Filipino, 5.3% Japanese, 9.6% Korean, and 11.8% Vietnamese. A total of 160,282,147 adults were White. Age-adjusted baseline mortality rates are shown in the Table.

Compared with White adults, Asian Indian (34.5% vs 29.3%; adjusted difference 5.2%, [95% CI: 1.8%, 8.6%], P=0.009) and Filipino (32.8% vs 29.3%; adjusted difference 3.5%, [95% CI: 0.1%, 6.9%], P=0.04) adults had significantly higher proportional mortality from all CV causes. Asian Indian (26.0% vs 22.6%; adjusted difference 3.2%, [95% CI: 0.3%, 6.2%], P=0.04) adults had higher proportional mortality from heart disease than White adults, while Korean (17.3% vs 22.6%; adjusted difference -5.2%, [95% CI: -8.1%, -2.2%], P=0.01) and Vietnamese (17.5% vs 22.6%; adjusted difference -5.1%, [95% CI: -8.0%, -2.1%], P=0.01) adults had lower proportional mortality.

Every Asian American subgroup had higher proportional mortality from hypertension causes compared with White adults, except for Asian Indians (Figure). In addition, every Asian American subpopulation had higher proportional mortality from stroke compared with White adults (Figure).

Conclusions

CV risk factor and disease-related mortality varies substantially among Asian American subgroups. Public health efforts targeted to address CV health disparities among the diverse group of Asian Americans are needed.
Environmental impact analysis of ajmaline challenge protocols: a comparative assessment of carbon footprint reduction in Brugada Syndrome diagnosis
Authors: Oliveira C , Tinoco M , Calvo L , Santos L , Pinho A , Moreira H , Palma P , Rocha M , Marques C , Cabrita A , Pestana G , Madeira M , Adao L , Lebreiro A
Published: October 2024

Background

Climate change is an urgent public health crisis that significantly impacts disease development and health outcomes. The 2022 Lancet Countdown Report revealed that healthcare contributes with 5.2% of global emissions, prompting a call for environmentally conscious approaches. In this context, we explored the environmental impact of different ajmaline challenge protocols, aiming to contribute to a more sustainable medical landscape.

Purpose

This study aims to compare the carbon footprint of two ajmaline challenge protocols commonly used in diagnosing Brugada syndrome, an inherited cardiac disorder associated with sudden cardiac death.

Methods

We performed a retrospective and observational analysis of adult patients (pts) who underwent ajmaline testing between March 2020 and June 2023 in two hospitals. In Group A (infusion protocol), 1mg/kg of ajmaline diluted in 50 mL of 5% glucose solution was infused in 10 minutes, up to the target dose, until a positive result or termination criteria ensued. In Group B (bolus protocol), 10 mg of ajmaline were administered every 2 minutes, again up to the target dose of 1mg/kg (maximum of 100 mg) or test interruption was indicated. Greenhouse gas emissions resulting from material processing were estimated based on life cycle analyses of each product's composition. Material consumption, waste production, and direct measurement of weights were considered.

Results

A total of 101 pts were included, 49 pts in group A with a mean age of 47.3±14.3 years old and 52 patients in group B with a mean age of 43.9±16.6 years-old. No complications were observed in either group. Test performance was not evaluated, since both protocols have been previously validated.

Group A, utilizing the infusion method, exhibited a higher environmental impact, producing 18.19 kg CO2eq, compared to 6.23 kg CO2eq (p<0.001) in Group B (bolus protocol). Group B not only demonstrated a 66% reduction in CO2eq emissions but also used significantly less plastic (16g vs 102g per test) and glass (1.58 kg vs 1,79Kg), emphasizing its environmental superiority.

Conclusions

Shifting from infusion to bolus in ajmaline challenge protocols results in a substantial reduction in carbon footprint. Our findings emphasize the potential impact of adopting more dematerialized approaches in cardiac testing, urging healthcare professionals to embrace sustainable practices. Despite the study's limited sample size, the global adoption of such environmentally friendly strategies promises significant positive effects on healthcare's environmental footprint.
Gender disparities in short-term outcomes of STEMI patients: the influence of universal health coverage
Authors: Qalby N , Qanitha A , Arsyad D S , Appelman J E A , Cramer M J , Doevendans P A F M , Muzakkir A F
Published: October 2024

Background

Even after the event, individuals recovering from ST-elevation myocardial infarction (STEMI) face lingering risks, including potential subsequent events and mortality. The introduction of Universal Health Coverage (UHC) seeks to enhance healthcare outcomes for all segments of the population.

Purpose

This study evaluates the effect of UHC on 30-day mortality in post-STEMI patients, focusing on medication access and treatment disparities. Using a gender-stratified approach, we analyze changes before and after UHC implementation to provide insights into the difference in therapy between genders and how gender influences healthcare outcomes for post-STEMI patients.

Methods

Analyzing two cohorts, Cohort 1 (211 STEMI patients, 2013-2014 pre-UHC) and Cohort 2 (365 STEMI patients, 2018-2020 post-UHC), this study employed the chi-square test to determine differences between genders and the Kaplan–Meier log-rank test to compare survival rates.

Results

Comparing pre- and post-UHC, we observed a significant increase in both medication and reperfusion therapy (p<0.001). However, even in both periods, women continued to have lower rates of medication and reperfusion compared to men (Men vs Women: Before UHC 14.3% vs 0%; After UHC 58.5% vs 47.9%). Within 30 days after the STEMI event, we noted a reduction in mortality rates across genders before and after UHC implementation, yet the decrease was less pronounced in women compared to men (Before UHC: Men 13.0%, Women 22.0%; After UHC: Men 8.2%, Women 18.3%).

Conclusion

UHC led to improvements in medication and reperfusion therapy for STEMI patients. Despite this progress, persistent gender disparities were observed, with women consistently having lower treatment rates. While mortality rates reduced for both genders, the decrease was less pronounced in women, especially after the implementation of UHC. These findings emphasize the need for targeted interventions to address gender-specific healthcare discrepancies within the scope of comprehensive health coverage.Baseline characteristicsMortality outcomes within 30 Days
The genetic architecture of exercise-induced ventricular ectopy
Authors: Van Duijvenboden S , Nicholson G , Smith-Byrne K , Portas L , Atkins J , Ramirez J , Orini M , Young W J , Tinker A , Lambiase P D , Munroe P B , Doherty A
Published: October 2024

Background

Previously, we have shown that the frequency of exercise-induced premature ventricular contractions (PVCs) during and after exercise are associated with increased risk of major adverse cardiovascular events in asymptomatic individuals from the UK Biobank study1. The underlying mechanisms are, however, unclear. Several electrocardiographic markers associated with arrhythmogenesis have a known hereditary component, but the genetic underpinnings of exercise-induced ventricular ectopy have not been investigated.

Purpose

Our aim was to explore the genetic basis of premature ventricular ectopy during and after exercise and unveil plausible candidate genes and biological mechanisms.

Methods

We conducted a genome-wide association study (GWAS) for PVC frequency during exercise and recovery in >44,000 asymptomatic individuals of European ancestry without known cardiovascular disease from the UK Biobank study. As the distribution of PVC frequency is highly skewed (e.g. absence of negative values and excess of zero values), we first applied Gaussian transformation. Simulation studies were performed to justify that this approach would lead to valid inference. In the GWAS model, we included sex, age, UK Biobank genotyping array, and the first 10 genetic principal components as covariates. Statistical power was boosted by joint analysis of exercise and recovery PVC traits using multi-trait analysis of GWAS (MTAG)2. Genetic risk scores were constructed in independent samples from UK Biobank (N=341,948) and were tested for association with heart failure and life-threatening ventricular arrhythmias.

Results

We identified 4 loci for PVC frequency during exercise, and 1 locus for PVC frequency during recovery (Picture 1). Candidate genes included CRIM1, FLNC, and BAG3 for which mutations have been linked in the pathogenesis of (arrhythmogenic) cardiomyopathy. Subjects in the top 10% of the genetic risk scores had a significantly higher risk of heart failure and life-threatening ventricular arrhythmias compared to the bottom 90%, (odds ratio (OR) (95% confidence interval): 1.14 (1.08 – 1.20), p < 0.001; and 1.13 (1.02 – 1.24), p < 0.001, respectively).

Conclusions

Ventricular ectopic burdens during exercise and recovery have a significant heritable component. Candidate genes highlight a possible shared genetic background with inherited cardiomyopathy and a genetic risk score was associated with heart failure and ventricular arrhythmias. These findings substantial advance our understanding of the genetic basis of exercise-induced ventricular ectopy in a population-based cohort without cardiovascular disease.Miami plot of ventricular ectopic burden
Effects of the restrictive cardiomyopathy-associated cardiac troponin I K178E mutation on cAMP signalling at the myofilament
Authors: Gee Olmedilla M , Chao Y C , Zaccolo M
Published: October 2024

Background

Catecholaminergic stimulation of cardiac β-adrenergic receptors (β-ARs) and subsequent cAMP signalling control cardiac inotropy and lusitropy. cAMP signalling is known to be compartmentalised to optimise sympathetic control by producing heterogeneous cAMP signals and protein kinase A (PKA) activation at distinct subcellular sites. This signalling may be disrupted in diseases such as restrictive cardiomyopathy (RCM) characterised by diastolic dysfunction, which is associated with certain mutations including the K178E missense mutation in cardiac troponin I (TPNI). The impaired ventricular relaxation associated with this mutation is thought to arise from myofilament calcium hypersensitivity, which can be modulated by PKA-dependent TPNI phosphorylation. However, a detailed understanding of the pathological effects mediated by the K178E-TPNI mutation is lacking.

Purpose

This study aims to determine whether the K178E-TPNI mutation alters local cAMP/PKA signalling at TPNI, potentially affecting myofilament calcium sensitivity and cardiac myocyte relaxation.

Methods

Real-time imaging of cAMP was carried out using the Fluorescence Resonance Energy Transfer (FRET)-based sensor CUTie (cAMP Universal Tag for imaging experiments) [1] fused to wild type (WT)- or K178E-TPNI. The sensors were expressed by transfection in neonatal rat ventricular myocytes (NRVMs) and FRET-changes were recorded at the myofilament on application of the β-AR stimulant isoproterenol (ISO). We further assessed the involvement of cAMP hydrolysing phosphodiesterases (PDEs) in the regulation of cAMP levels selectively at TPNI.

Results

The peak FRET-change and FRET-change after 5mins on ISO application were significantly higher in NRVMs expressing the mutant compared to the WT sensor, as was the rate of cAMP accumulation. A strong trend showed that the rise in FRET following PDE4 inhibition was larger in NRVMs expressing the WT compared to the mutant sensor, suggesting the involvement of this isoform in degrading cAMP locally at TPNI and reduced PDE4 activity in the presence of the K178E mutation. Co-immunoprecipitation analysis in HEK293 cells demonstrated interaction between WT-TPNI and a PDE4D isoform, and a weaker interaction of this isoform with the K178E-TPNI mutant.

Conclusions

This study shows that the K178E-TPNI mutation attenuates the TPNI/PDE4D interaction and alters the magnitude and kinetics of the local cAMP response at the myofilament. This mechanistic insight may aid the development of therapeutics targeting the TPNI/PDE4D interaction to treat RCM-associated diastolic dysfunction.The TPNI-CUTie SensorFRET Response Trace
Comparison of ICD implantation approach in children. The IChilDren study
Authors: Cledel A , Maltret A , Waldmann V , Marquie C , Koutbi L , Jesel L , Bordachar P , Blangy H , Maury P , Martins R , Amedro P , Probst V , Gourraud J B
Published: October 2024

Background

Without dedicated device, implantable cardioverter defibrillators (ICD) implantation in children is a real challenge for physicians. Types of implantation include transvenous, surgical and subcutaneous-ICD approach, but with a lack of reliable data comparing their respective efficacy and safety.

Objective

We here aim to compare the results of these 3 ICD implantation approaches in children.

Methods

Consecutive children (<16yo) implanted with an ICD from 2005 to 2021 in 19 french tertiary centers of the French Pediatric and Congenital heart disease network, were retrospectively enrolled in the study. The primary endpoints were the occurrence of lead failure, device infection or inappropriate shock.

Results

Among 306 patients (mean age 12,6 yo), 34% received a transvenous ICD, 28% a S-ICD and 38% a surgical ICD. During a median follow-up of 4.7 years, endpoints occurred in 24.2% of the total population, more often in the surgical group (p<0.05). After adjustment for age, ICD type and stratification by heart disease, there was an excess risk of lead failure or infection with the surgical ICD compared with the S-ICD (HR 7.54, 95% CI 1.73;32.91, p<0.05). However, when inappropriate shocks were included, the difference was reduced (HR 2.28, 95% CI 1.03;5.04, p>0.05). In addition, no significant difference between transvenous and surgical ICDs was observed in the multivariate analysis.

Conclusions

We demonstrate a high rate of complication in children implanted with an ICD. The transvenous and surgical approaches are quite similar. S-ICD appears as a promising approach with the lowest serious adverse event rate. Limitation of inappropriate shock remain the main challenge of this technique.Late complications