Journal of electrocardiology最新文献

{"title":"Estimating very low ejection fraction from the 12 Lead ECG among patients with acute heart failure","authors":"Sunita Pokhrel Bhattarai PhD, RN ,&nbsp;Dillon J. Dzikowicz PhD, RN, PCCN ,&nbsp;Ying Xue DNSc, RN ,&nbsp;Robert Block MD, MPH, FACP, FNLA ,&nbsp;Rebecca G. Tucker PhD, RN, ACNPC ,&nbsp;Shilpa Bhandari BCS ,&nbsp;Victoria E. Boulware BSN, RN ,&nbsp;Breanne Stone BSN, RN ,&nbsp;Mary G. Carey PhD RN, FAHA FAAN","doi":"10.1016/j.jelectrocard.2025.153878","DOIUrl":"10.1016/j.jelectrocard.2025.153878","url":null,"abstract":"<div><h3>Background</h3><div>Identifying patients with low left ventricular ejection fraction (LVEF) in the emergency department using an electrocardiogram (ECG) may optimize acute heart failure (AHF) management. We aimed to assess the efficacy of 527 automated 12‑lead ECG features for estimating LVEF among patients with AHF.</div></div><div><h3>Method</h3><div>Medical records of patients &gt;18 years old and AHF-related ICD codes, demographics, LVEF %, comorbidities, and medication were analyzed. Least Absolute Shrinkage and Selection Operator (LASSO) identified important ECG features and evaluated performance.</div></div><div><h3>Results</h3><div>Among 851 patients, the mean age was 74 years (IQR:11), male 56 % (<em>n</em> = 478), and the median body mass index was 29 kg/m² (IQR:1.8). A total of 914 echocardiograms and ECGs were matched; the time between ECG-Echocardiogram was 9 h (IQR of 9 h); ≤30 % LVEF (16.45 %, <em>n</em> = 140). Lasso demonstrated 42 ECG features important for estimating LVEF ≤30 %. The predictive model of LVEF ≤30 % showed an area under the curve (AUC) of 0.86, a 95 % confidence interval (CI) of 0.83 to 0.89, a specificity of 54 % (50 % to 57 %), and a sensitivity of 91 (95 % CI: 88 % to 96 %), accuracy 60 % (95 % CI:60 % to 63 %) and, negative predictive value of 95 %.</div></div><div><h3>Conclusions</h3><div>An explainable machine learning model with physiologically feasible predictors may help screen patients with low LVEF in AHF.</div></div>","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"89 ","pages":"Article 153878"},"PeriodicalIF":1.3,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143039313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The crucial role of image quality in AI-enabled ECG digitization and interpretation of occlusion myocardial infarction","authors":"Robert Herman ,&nbsp;Stephen W. Smith","doi":"10.1016/j.jelectrocard.2025.153873","DOIUrl":"10.1016/j.jelectrocard.2025.153873","url":null,"abstract":"","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"89 ","pages":"Article 153873"},"PeriodicalIF":1.3,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143006472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Residual-attention deep learning model for atrial fibrillation detection from Holter recordings","authors":"Md Moklesur Rahman ,&nbsp;Massimo Walter Rivolta ,&nbsp;Martino Vaglio ,&nbsp;Pierre Maison-Blanche ,&nbsp;Fabio Badilini ,&nbsp;Roberto Sassi","doi":"10.1016/j.jelectrocard.2025.153876","DOIUrl":"10.1016/j.jelectrocard.2025.153876","url":null,"abstract":"<div><h3>Background</h3><div>Detecting subtle patterns of atrial fibrillation (AF) and irregularities in Holter recordings is intricate and unscalable if done manually. Artificial intelligence-based techniques can be beneficial. In fact, with the rapid advancement of AI, deep learning (DL) demonstrated the capability to identify AF from ECGs with significant performance. However, further development and validation on larger cohorts is still needed.</div></div><div><h3>Purpose</h3><div>The main purpose of this study was to develop a Residual-attention DL model by considering a large cohort of 2‑lead Holter recordings.</div></div><div><h3>Methods</h3><div>We developed a residual DL model by collecting a large dataset of 661 Holter recordings, which was labeled manually by an expert cardiologist. The DL model leveraged attention mechanisms, allowing it to capture long-range dependencies and intricate temporal relationships crucial for identifying subtle patterns indicative of AF.</div></div><div><h3>Results</h3><div>Experimental results demonstrated that our model achieved a sensitivity (detection of AF) of <span><math><mi>Se</mi><mo>=</mo><mn>0.928</mn></math></span> and a specificity of <span><math><mi>Sp</mi><mo>=</mo><mn>0.915</mn></math></span>, with an AUC-ROC of <span><math><mi>AUC</mi><mo>=</mo><mn>0.967</mn></math></span> on our dataset. Additionally, when evaluated with an external test dataset, specifically IRIDIA-AF, our DL model obtained <span><math><mi>Se</mi><mo>=</mo><mn>0.942</mn></math></span>, <span><math><mi>Sp</mi><mo>=</mo><mn>0.932</mn></math></span>, and <span><math><mi>AUC</mi><mo>=</mo><mn>0.965</mn></math></span>. Finally, when compared under similar experimental conditions with other state-of-the-art models, our DL model achieved slightly better performance overall.</div></div><div><h3>Conclusion</h3><div>The Residual-attention DL model we proposed offers a promising solution for AF detection. The validation on external datasets contributes to its potential for deployment in clinical settings, providing clinicians with a valuable decision support system.</div></div>","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"89 ","pages":"Article 153876"},"PeriodicalIF":1.3,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143006470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ECG challenge: Intermittent wide QRS complexes in heterotaxy syndrome","authors":"Stefan Kurath-Koller M.D., Ph.D ,&nbsp;Martin Manninger M.D., Ph.D ,&nbsp;Daniel Scherr M.D. ,&nbsp;Hannes Sallmon M.D.","doi":"10.1016/j.jelectrocard.2025.153877","DOIUrl":"10.1016/j.jelectrocard.2025.153877","url":null,"abstract":"<div><div>We report wide QRS complexes appearing in conjunction with prolonged R-R intervals in a 5- year old patient with situs ambiguous and mirror image dextrocardia, who had undergone ASD and VSD closure at of the age of one. We present differential diagnoses of intermittent spontaneous QRS widening and refer to ECG lead positioning in mirror image dextrocardia patients.</div></div>","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"89 ","pages":"Article 153877"},"PeriodicalIF":1.3,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142978840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of P-wave parameter changes after radiofrequency ablation and cryoballoon ablation for paroxysmal atrial fibrillation: An observational cohort study","authors":"Ibrahim Antoun PhD ,&nbsp;Xin Li PhD ,&nbsp;Zakkariya Vali FRCP ,&nbsp;Ahmed Abdelrazik MSc ,&nbsp;Riyaz Somani PhD ,&nbsp;G. André Ng PhD","doi":"10.1016/j.jelectrocard.2024.153863","DOIUrl":"10.1016/j.jelectrocard.2024.153863","url":null,"abstract":"<div><h3>Background</h3><div>Pulmonary vein isolation (PVI) for paroxysmal atrial fibrillation (PAF) can be performed using one-shot cryoballoon ablation (cryo) or point-by-point radiofrequency ablation (RF). This study compares the changes in P-wave parameters between both ablation methods.</div></div><div><h3>Methods</h3><div>This single-centre retrospective study included contact force RF and second-generation cryo for PAF between 2018 and 2019. Procedure success was defined by freedom of ECG-documented AF at 12 months. Digital 12‑leads ECGs with 1–50 hertz bandpass filters were monitored directly during the procedure. Corrected P-wave duration (PWDc), P-wave voltage (PWV), P-wave dispersion (PWDisp), and P-wave terminal force in V1 (PTFV1) were measured and compared between RF and cryo. Additional ablations outside pulmonary veins were excluded.</div></div><div><h3>Results</h3><div>The final analysis included 226 patients, and the freedom of AF rate was similar at the 12-month follow-up between RF and cryo (76 % vs 74 %, <em>P</em> = 0.12). PWDc and PWV increased and decreased, respectively in both arms. PTFV1 decreased in RF (−3.3 mm.s to −4.6 mm.s, <em>P</em> &lt; 0.001) and cryo (−3.4 mm.s to −5.3 mm.s,<em>P</em> = 0.002). There were similar changes after RF and cryo in PWDc (F_{11, 1032} = 0.80, <em>P</em> = 0.85), PWV (F_{11, 1032} = 0.19,<em>P</em> = 0.06), and PWDisp (F_{11, 1032} = 0.16,<em>P</em> = 0.34) and PTFV1 (<em>P</em> = 0.39). Increased PWDc was correlated with failure of RF (hazard ratio [2.3], 95 % confidence interval [CI]: 1.4–5.9, <em>p</em> = 0.01) and cryo (HR: 2.1, 95 % CI (1.3–4.6), <em>p</em> = 0.02). Results were similar when patients on antiarrhythmic drugs were excluded.</div></div><div><h3>Conclusion</h3><div>RF and cryo caused similar freedom of AF rate at 12 months in PAF and similar P-wave parameter changes.</div></div>","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"89 ","pages":"Article 153863"},"PeriodicalIF":1.3,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142949878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In the face of confounders: Atrial fibrillation detection – Practitioners vs. ChatGPT","authors":"Yuval Avidan MD ,&nbsp;Vsevolod Tabachnikov MD ,&nbsp;Orel Ben Court MD ,&nbsp;Razi Khoury MD ,&nbsp;Amir Aker MD","doi":"10.1016/j.jelectrocard.2024.153851","DOIUrl":"10.1016/j.jelectrocard.2024.153851","url":null,"abstract":"<div><h3>Introduction</h3><div>Atrial fibrillation (AF) is the most common arrhythmia in clinical practice, yet interpretation concerns among healthcare providers persist. Confounding factors contribute to false-positive and false-negative AF diagnoses, leading to potential omissions. Artificial intelligence advancements show promise in electrocardiogram (ECG) interpretation. We sought to examine the diagnostic accuracy of ChatGPT-4omni (GPT-4o), equipped with image evaluation capabilities, in interpreting ECGs with confounding factors and compare its performance to that of physicians.</div></div><div><h3>Methods</h3><div>Twenty ECG cases, divided into Group A (10 cases of AF or atrial flutter) and Group B (10 cases of sinus or another atrial rhythm), were crafted into multiple-choice questions. Total of 100 practitioners (25 from each: emergency medicine, internal medicine, primary care, and cardiology) were tasked to identify the underlying rhythm. Next, GPT-4o was prompted in five separate sessions.</div></div><div><h3>Results</h3><div>GPT-4o performed inadequately, averaging 3 (±2) in Group A questions and 5.40 (±1.34) in Group B questions. Upon examining the accuracy of the total ECG questions, no significant difference was found between GPT-4o, internists, and primary care physicians (<em>p</em> = 0.952 and = 0.852, respectively). Cardiologists outperformed other medical disciplines and GPT-4o (<em>p</em> &lt; 0.001), while emergency physicians followed in accuracy, though comparison to GPT-4o only indicated a trend (<em>p</em> = 0.068).</div></div><div><h3>Conclusion</h3><div>GPT-4o demonstrated suboptimal accuracy with significant under- and over-recognition of AF in ECGs with confounding factors. Despite its potential as a supportive tool for ECG interpretation, its performance did not surpass that of medical practitioners, underscoring the continued importance of human expertise in complex diagnostics.</div></div>","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"88 ","pages":"Article 153851"},"PeriodicalIF":1.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142818416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying early left atrial dysfunction in COPD patients using ECG morphology-voltage-P wave duration score","authors":"Uğur Küçük MD (Assistant Professor) ,&nbsp;Pınar Mutlu MD (Assistant Professor) ,&nbsp;Arzu Mirici MD (Professor) ,&nbsp;Uğur Özpınar MD ,&nbsp;Selin Beyza Özpınar MD","doi":"10.1016/j.jelectrocard.2024.153854","DOIUrl":"10.1016/j.jelectrocard.2024.153854","url":null,"abstract":"<div><h3>Background</h3><div>Chronic Obstructive Pulmonary Disease (COPD) is associated with left atrial (LA) dyfunction, which may contribute to adverse cardiovascular outcomes. This study investigates the predictive value of lately identified morphology-voltage-P wave duration electrocardiography (MVP ECG) score for detecting early LA dysfunction in COPD patients.</div></div><div><h3>Methods</h3><div>In this cross-sectional study, 101 COPD patients were enrolled. All patients underwent speckle tracking echocardiography and were classified into two groups based on their LA functions.</div></div><div><h3>Results</h3><div>Our findings demonstrate significant variations in Peak Atrial Longitudinal Strain (PALS) values among COPD patients, with a mean PALS of 28.74 ± 1.81 % for the group with normal LA function and 18.44 ± 1.87 % for the group with abnormal LA function (<em>p</em> &lt; 0.001). Despite similar LA diameters across groups, these variations indicate subclinical LA pathogenesis. ROC curve analysis indicated that an MVP ECG score greater than 2.5 predicted abnormal LA function with a sensitivity of 65 % and a specificity of 91 % (area under the curve [AUC]: 0.873; <em>p</em> &lt; 0.001), suggesting its utility in identifying atrial damage and remodeling.</div></div><div><h3>Conclusions</h3><div>The MVP ECG score shows promise as a tool for early detection of atrial remodeling in COPD patients.</div></div>","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"88 ","pages":"Article 153854"},"PeriodicalIF":1.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142894713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevalence and severity of QT prolongation and other ECG abnormalities in takotsubo syndrome","authors":"Andrei D. Margulescu MD, PhD ,&nbsp;Diluka Amila Premawardhana ,&nbsp;Dewi E. Thomas MD","doi":"10.1016/j.jelectrocard.2024.153848","DOIUrl":"10.1016/j.jelectrocard.2024.153848","url":null,"abstract":"<div><h3>Background</h3><div>The prevalence and severity of QT interval prolongation (long QT, LQT) in takotsubo syndrome (TS) is not well described.</div></div><div><h3>Methods</h3><div>This is a retrospective cohort study of all patients admitted in our Centre between January 2019 and December 2023 with confirmed TS. QT interval corrected for heart rate (QTc) (Bazzett formula) was measured manually in all available ECGs. Presence of other ECG abnormalities (T-wave inversion (TWI), ST segment elevation (STE), ST segment depression (STD)) were also recorded.</div></div><div><h3>Results</h3><div>Fifty-eight patients were included, all women (68 ± 11 years). Fifty-six patients (96.6 %) had classical, apical ballooning form of TS. Symptoms included chest pain (93.1 %), dyspnoea (10.3 %), and others (5.2 %). Triggers were present in 70.7 % of patients. Three-hundred-and-thirty ECGs were analysed. LQT was infrequent in the first 3 h after symptom onset (23.5 % of patients), and was only mild. However, between 24 and 48 h after symptom onset, 90.9 % of patients developed LQT, which was severe (≥500 ms) in 63.6 % of patients. LQT prevalence decreased afterwards but QTc did not return to normal in 40.0 % of patients, and remained severely prolonged in 11.4 % of patients beyond 96 h. ECG was normal in 40.5 % of patients in the first 6 h. TWI was the predominant ECG change, and its prevalence increased from 16.7 % within the first 6 h to 76.9 % after 7 days. STE was present in 31.4 % of patients in the first 96 h, but was rare in isolation. Isolated STD did not occur.</div></div><div><h3>Conclusion</h3><div>LQT is almost universally seen in patients with TS within the first 96 h after symptom onset, and is severe in the majority. ECGs abnormalities in TS are highly dynamic, but ECGs are frequently normal in the first 6 h after symptom onset. Patients should be monitored for at least 96 h after symptom onset, and until QTc falls below 500 ms.</div></div>","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"88 ","pages":"Article 153848"},"PeriodicalIF":1.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142769347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Case presentation of acute ischemia induced ST-depression masking Brugada syndrome ECG pattern in a relatively young patient","authors":"Kristina Torngren MD ,&nbsp;Aleksei Savelev MD ,&nbsp;Erik Ljungström MD, PhD ,&nbsp;Pyotr G. Platonov MD, PhD (Professor)","doi":"10.1016/j.jelectrocard.2024.153853","DOIUrl":"10.1016/j.jelectrocard.2024.153853","url":null,"abstract":"<div><div>ECG in Brugada syndrome (BrS) is characterized by a ST-segment elevation in the right precordial leads. Overlap between ST-segment changes in BrS and ischemia may lead to diagnostic challenges.</div><div>We report a case of a male patient presented with recurrent chest pain episodes and ST elevation in the right precordial leads consistent with Brugada ECG pattern type 1 and was clinically diagnosed with BrS at the age of 30 years. During follow up the patient developed acute myocardial infarction with pronounced ST depression in the right precordial leads, masking the Brugada pattern of the baseline ECG.</div></div>","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"88 ","pages":"Article 153853"},"PeriodicalIF":1.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142864534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neurocardiology: Major mechanisms and effects","authors":"Cees A. Swenne Ph.D. ,&nbsp;Vladimir Shusterman M.D., Ph.D.","doi":"10.1016/j.jelectrocard.2024.153836","DOIUrl":"10.1016/j.jelectrocard.2024.153836","url":null,"abstract":"<div><div>Neurocardiology is a broad interdisciplinary specialty investigating how the cardiovascular and nervous systems interact. In this brief introductory review, we describe several key aspects of this interaction with specific attention to cardiovascular effects.</div><div>The review introduces basic anatomy and discusses physiological mechanisms and effects that play crucial roles in the interaction of the cardiovascular and nervous systems, namely: the cardiac neuraxis, the taxonomy of the nervous system, integration of sensory input in the brainstem, influences of the autonomic nervous system (ANS) on heart and vasculature, the neural pathways and functioning of the arterial baroreflex, receptors and ANS effects in the walls of blood vessels, receptors and ANS effects in excitable cells in the heart, ANS effects on heart rate and sympathovagal balance, endo-epicardial inhomogeneity, ANS effects with a balanced vagal and sympathetic stimulation, sympathovagal interaction, arterial baroreflex, baroreflex sensitivity and heart rate variability, arrhythmias and the arterial baroreflex, the cardiopulmonary baroreflex, the exercise pressor reflex, exercise-recovery hysteresis, mental stress, cardiac-cardiac reflexes, the cardiac sympathetic afferent reflex (CSAR), and neuromodulation. Also, the potential role of the discussed mechanisms in cardiovascular disorders will be touched upon.</div></div>","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"88 ","pages":"Article 153836"},"PeriodicalIF":1.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142824345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}