bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of contrast-induced acute kidney injury on long-term major adverse cardiovascular events and kidney function after percutaneous coronary intervention: insights from a territory-wide cohort study in Hong Kong
Authors: Ng Andrew Kei-Yan , Ng Pauline Yeung , Ip April , Lam Lap-tin , Ling Ian Wood-Hay , Wong Alan Shing-Lung , Yap Desmond Yat-Hin , Siu Chung-Wah 
Published: October 2021

ABSTRACT

Background
The impact of contrast-induced acute kidney injury (CI-AKI) on long-term major adverse cardiovascular events (MACE) remains controversial.

Method
This was a retrospective cohort study from 14 hospitals under the Hospital Authority of Hong Kong between 2004 and 2017. Severe CI-AKI was defined as an increase in serum creatinine of &gt;50% from the baseline value, an absolute increase of &gt;1 mg/dL (88 μmol/L) or requiring dialysis after percutaneous coronary intervention (PCI). Mild CI-AKI was defined as an increase in serum creatinine of &gt;25% from the baseline value or an absolute increase of &gt;0.5 mg/dL (44 μmol/L) after PCI but not fulfilling the criteria for severe CI-AKI. The primary endpoint was MACE, defined as a composite outcome of all-cause mortality, non-fatal myocardial infarction after hospital discharge, stroke or any unplanned coronary revascularization, in a time-to-first-event analysis up to 5 years after PCI. The secondary endpoints were individual components of MACE and cardiovascular mortality.

Results
A total of 34 576 patients were analysed. After adjustment for cardiovascular risk factors, procedural characteristics and medication use, the risk of MACE at 5 years was significantly higher with mild CI-AKI {hazard ratio [HR], 1.18 [95% confidence interval (CI) 1.12–1.26); P &lt; 0.001} and severe CI-AKI [HR 1.92 (95% CI 1.78–2.07); P &lt; 0.001]. Severe CI-AKI was associated with higher adjusted risks of each secondary end point and the risks monotonically accrued over time.

Conclusions
Among patients undergoing a first-ever PCI, CI-AKI of any severity was associated with a higher adjusted risk of MACE at 5 years. Severe CI-AKI has a stronger association with MACE and its individual components, with an excess of early and late events.
Applications of Digital Microscopy and Densely Connected Convolutional Neural Networks for Automated Quantification of Babesia-Infected Erythrocytes
Authors: Durant Thomas J S , Dudgeon Sarah N , McPadden Jacob , Simpson Anisia , Price Nathan , Schulz Wade L , Torres Richard , Olson Eben M 
Published: October 2021

Abstract

Background
Clinical babesiosis is diagnosed, and parasite burden is determined, by microscopic inspection of a thick or thin Giemsa-stained peripheral blood smear. However, quantitative analysis by manual microscopy is subject to error. As such, methods for the automated measurement of percent parasitemia in digital microscopic images of peripheral blood smears could improve clinical accuracy, relative to the predicate method.

Methods
Individual erythrocyte images were manually labeled as “parasite” or “normal” and were used to train a model for binary image classification. The best model was then used to calculate percent parasitemia from a clinical validation dataset, and values were compared to a clinical reference value. Lastly, model interpretability was examined using an integrated gradient to identify pixels most likely to influence classification decisions.

Results
The precision and recall of the model during development testing were 0.92 and 1.00, respectively. In clinical validation, the model returned increasing positive signal with increasing mean reference value. However, there were 2 highly erroneous false positive values returned by the model. Further, the model incorrectly assessed 3 cases well above the clinical threshold of 10%. The integrated gradient suggested potential sources of false positives including rouleaux formations, cell boundaries, and precipitate as deterministic factors in negative erythrocyte images.

Conclusions
While the model demonstrated highly accurate single cell classification and correctly assessed most slides, several false positives were highly incorrect. This project highlights the need for integrated testing of machine learning-based models, even when models in the development phase perform well.
Community detection in social networks by incorporating the preferential selection
Authors: Meena Shyam Sundar , Tokekar Dr. Vrinda 
Published: October 2021

Abstract
In the last decade, online social networks (OSNs) have become popular among researchers. Now, almost a third of the world’s population uses it. The recent boom of technologies provides opportunities to improve the processing and mining of social data. The proposed approach detects communities in the OSNs using the concepts of a preferential selection of neighbours. The proposed work is evaluated on real-world datasets as well as computer-generated datasets. It is also compared with other state-of-the-art community detection algorithms for normalized mutual information and F1-measure values. The cumulative performance of the algorithm is found to be superior, which outperforms other state-of-the-art community detection algorithms.
Spectral density of random graphs: convergence properties and application in model fitting
Authors: Santos Suzana de Siqueira , Fujita André , Matias Catherine 
Published: October 2021

AbstractRandom graph models are used to describe the complex structure of real-world networks in diverse fields of knowledge. Studying their behaviour and fitting properties are still critical challenges that, in general, require model-specific techniques. An important line of research is to develop generic methods able to fit and select the best model among a collection. Approaches based on spectral density (i.e. distribution of the graph adjacency matrix eigenvalues) appeal to that purpose: they apply to different random graph models. Also, they can benefit from the theoretical background of random matrix theory. This work investigates the convergence properties of model fitting procedures based on the graph spectral density and the corresponding cumulative distribution function. We also review the convergence of the spectral density for the most widely used random graph models. Moreover, we explore through simulations the limits of these graph spectral density convergence results, particularly in the case of the block model, where only partial results have been established. random graphs, spectral density, model fitting, model selection, convergence.
Artificial intelligence in cardiology: the debate continues
Authors: Asselbergs Folkert W , Fraser Alan G 
Published: October 2021

AbstractIn 1955, when John McCarthy and his colleagues proposed their first study of artificial intelligence, they suggested that ‘every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it’. Whether that might ever be possible would depend on how we define intelligence, but what is indisputable is that new methods are needed to analyse and interpret the copious information provided by digital medical images, genomic databases, and biobanks. Technological advances have enabled applications of artificial intelligence (AI) including machine learning (ML) to be implemented into clinical practice, and their related scientific literature is exploding. Advocates argue enthusiastically that AI will transform many aspects of clinical cardiovascular medicine, while sceptics stress the importance of caution and the need for more evidence. This report summarizes the main opposing arguments that were presented in a debate at the 2021 Congress of the European Society of Cardiology. Artificial intelligence is an advanced analytical technique that should be considered when conventional statistical methods are insufficient, but testing a hypothesis or solving a clinical problem—not finding another application for AI—remains the most important objective. Artificial intelligence and ML methods should be transparent and interpretable, if they are to be approved by regulators and trusted to provide support for clinical decisions. Physicians need to understand AI methods and collaborate with engineers. Few applications have yet been shown to have a positive impact on clinical outcomes, so investment in research is essential.
Diagnostic and prognostic contribution of 99mTc-DPD scintigraphy in transthyretin V30M cardiac amyloidosis
Authors: Azevedo Coutinho M D C , Cortez-Dias N , Cantinho G , Goncalves S , Cunha N , Rodrigues T , Santos L , Conceicao I , Pinto F 
Published: October 2021

Abstract

Background
Early diagnosis and prognostic stratification of hereditary transthyretin amyloidosis (ATTR) are crucial. Previous findings suggested that 99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid (DPD) scintigraphy presents suboptimal accuracy to detect ATTR cardiomyopathy caused by V30M mutation, particularly in patients with onset of symptoms under 50 years of age. Furthermore, its prognostic value has never been evaluated in ATTR caused by this mutation.

Purpose
To assess the diagnostic value of DPD scintigraphy to detect cardiomyopathy in a large cohort of patients with ATTR-V30M mutation and to explore its prognostic value regarding mortality.

Methods
Of the 305 ATTR-V30M mutation carriers followed prospectively and who underwent DPD scintigraphy, 288 individuals [median age 46 (39–56); 49% male] without myocardial thickening attributable to other causes were enrolled in the study. Amyloid cardiomyopathy was defined by septal thickness ≥13mm not attributable to other causes plus at least one of the following criteria: (1) late heart-to-mediastinum (H/M) 123I-metaiodobenzylguanidine (MIBG) ratio &lt;1.60; (2) electrical heart disease (arrhythmia or cardiac conduction defect); or (3) amyloid infiltration documented in biopsy.

Results
Amyloid cardiomyopathy was identified in 41 (14.2%) patients and 44 (15.3%) individuals presented abnormal cardiac DPD uptake. Individuals with cardiac DPD retention had 27-fold higher likelihood of having amyloid cardiomyopathy (OR: 27.4; 95% CI 11.6–65.0; P&lt;0.001). However, DPD scintigraphy presented suboptimal accuracy to detect ATTR cardiomyopathy (89.9%) with limitations in sensitivity (56.1%), specificity (95.6%), positive predictive value (67.7%) and negative predictive value (92.9%).
During a mean follow-up 33.6±1.2 months, 16 patients died (5.6%). Mortality was 14 times higher in patients with amyloid cardiomyopathy (HR: 14.1; 95% CI 4.9–40.7; P&lt;0.001), 13 times higher in those with abnormal cardiac DPD uptake (HR: 12.59; 95% CI % 4.56–34.72; P&lt;0.001) and 10 times higher in those with H/M MIBG ratio &lt;1.60 (HR: 10.40; 95% CI 2.95–36.69; P&lt;0.001). The prognostic value of ventricular thickness and cardiac DPD uptake was additive: patients without septal thickening and no cardiac DPD retention had excellent prognosis (5-year mortality of 0.75%), while those with septal thickening and/or abnormal DPD retention presented 5-year mortality rates ranging from 39.9 to 53.3%.

Conclusions
DPD scintigraphy is valuable in the evaluation of ATTR-V30M mutation carriers, particularly for prognostic stratification purposes, identifying patients at higher risk of death.

Funding Acknowledgement
Type of funding sources: None.
Epicardial adipose tissue and nonvalvular atrial fibrillation
Authors: Arakelyan M , Golukhova E Z , Gromova O I , Bulaeva N I 
Published: October 2021

Abstract

Background
Several studies revealed the relationship between epicardial fat tissue (EF) and development of atrial fibrillation (AF). Though pathophysiological mechanisms are not clear enough, the anatomy and location EF as a part of visceral adiposity tissue could lead to proinflammatory and fibrotic changes in atrial myocardium.

Purpose
To evaluate the paracrine effects of EF and detect the association of tissue Doppler imaging (TDI) parameters, EF thickness by cardiac magnetic resonance tomography (CMR) and biochemical markers of fibrosis and inflammation in patients with nonvalvular AF without concomitant coronary artery disease.

Methods
Thirty-nine patients with idiopathic paroxysmal AF, normal or slightly enlarged left atria (LA) (mean LA diameter 4,5±0,6cm) were included. The mean age was 50,8±13,9 y.o., 19 (49%) were men. The absence of coronary lesions was confirmed by angiography in all cases. Besides standard ECG and ECHO, all patients underwent TDI and CMR with late gadolinium enhancement. EP thickness at anterior left ventricular (LV) wall was estimated by CMR. The myocardial fibrotic and proinflammatory biomarkers levels - matrix metalloproteinases (MMP-2, MMP-9), tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) were estimated. Kendall rank correlation coefficient was used. If the |τ| &gt;Tcr, the correlation ranked as statistically significant.

Results
The epicardial fat thickness was associated with TIMP-1 plasma level (τ=0,71; Tcr=0,18) and MMP-9 (τ=0,65; Tcr=0,16). Among clinical factors weight was slightly associated with fat thickness (τ=0,33; Tcr=0,26). Besides, we found correlation of MMP-9, TIMP-1 with E/e' by TDI (τ=0,65; Tcr=0,16 and τ=0,56; Tcr=0,21, relatively); and with maximal systolic strain of lateral LV wall (τ=−0,37; Tcr=0,18 and τ=−0,44; Tcr=0,16, relatively) and interventricular septum (τ=−0,36; Tcr=0,18 and τ=−0,44; Tcr=0,16, relatively).

Conclusion
The epicardial fat thickness by CMR is significantly associated with myocardial fibrosis markers (MMP-9, TIMP-1) in patients with AF without structural heart disease. The increasing levels of MMP-9 and TIMP-1 are associated with LV local contractility disturbances by TDI in patients with AF. This association demonstrates the paracrine effect of EF, which could lead to atrial remodeling and formation AF substrate even in patients without valvular and ischemic heart disease and with normal or slightly enlarged LA

Funding Acknowledgement
Type of funding sources: None.
Arrhythmic risk stratification in patients with clinically-suspected left ventricular arrhythmogenic cardiomyopathy
Authors: Peretto G , Villatore A , Basso C , Della Bella P , Sala S 
Published: October 2021

Abstract

Background
Arrhythmic risk of patients with left ventricular arrhythmogenic cardiomyopathy (LVAC) is unpredictable.

Purpose
To identify risk facors associated with major ventricular tachyarrhythmias (VTA) in clinically-suspected LVAC patients.

Methods
We enrolled 127 consecutive patients (69% males, age 46±13 y, LVEF 54±7%) with clinically-suspected LVAC. All patients presented with either major (VT, VF) or minor VTA (NSVT, frequent VEB), and underwent extensive diagnostic workup to rule-out alternative diagnoses. Medical treatment and ICD implant were clinically-driven. Prospective follow-up was obtained via sequential 24h-Holter ECG (2–4/y) with or without continuous arrhythmia monitoring (ICD or implantable loop recorders, ILR). The primary endpoint was occurrence of major VTA (VT/VF/ICD therapy) by 24-month follow-up.

Results
At presentation, 56 (44%) and 71 patients (56%) had, respectively, major and minor VTA. Variants in desmosomal genes were identified in 7 of the 9 patients with clinically-indicated genetic test. Delayed gadolinium enhancement (DGE, average 23±12% of the LV mass) had anteroseptal distribution in 43 cases (34%). Monitoring strategy included ICD (n=64), ILR (n=33), or sequential Holer ECGs (n=30). By 24-month follow-up, major VTA occurred in 32 patients (25%). At univariable anlysis, major VTA onset (HR 16.8, 95% CI 5.4–52.2, p&lt;0.001) and anteroseptal DGE (HR 3.0, 95% CI 1.3–6.9, p=0.010) were significantly associated with major VTA by 24-month follow-up. Among patients presenting with minor VTA, the only factor significantly associated with the primary endpoint was anteroseptal DGE (3/4 vs. 14/67, p=0.004).

Conclusion
Our preliminary experience suggests that, in patients with clinically-suspected LVAC, major VTA onset and anteroseptal DGE are relevant risk factors for major arrhythmic events by 24-month follow-up.

Funding Acknowledgement
Type of funding sources: None.
Frontal QRS/T angle can predict mortality in COVID-19 patients
Authors: Gunduz R , Yildiz B S 
Published: October 2021

Abstract

Aims
fQRS-T angle was investigated from general population including healthy people to patients who has hearth failure. It can predict mortality of myocarditis, ischemic cardiomyopathy, non-ischemic cardiomyopathy, idiopathic dilated cardiomyopathy and chronic heart failure in general population. There is no study in the literature that has been investigated for COVID-19 patients. The purpose of this retrospective multi-center study is to evaluate fQRS angle of COVID-19 patients for in-hospital mortality and need mechanical ventilation.

Methods and results
ECG was enrolled in 327 COVID-19 patients during admission and the fQRS angle calculated. Mechanical ventilation was needed for 119 patients and 110 of them died in hospital. Patients were divided into two groups according to their fQRS angle as fQRs&gt;90° and fQRS≤90°. Percentages of mortality and need of MV according to fQRS angle were found 67.8% and 66.1% respectively in fQRs&gt;90° group and 26.1%, 29.9% in fQRS≤90°group. Heart rate, SO2, fQRS, eGFR and CRP only were predictors for mortality in multivariable analysis. Mortality risk was increased 2.9-fold in univariate analysis and 1.6-fold in multivariate analysis for fQRS&gt;90 patient group in respect to fQRS≤90 group.

Conclusion
In conclusion, a wide fQRS angle (&gt;90°) was found as a predictor for mortality in-hospital and associated with the need for mechanical ventilation in COVID-19 patients.

Funding Acknowledgement
Type of funding sources: None. Mortality, need mechanical ventilationUnivariable and multivariable predictors
Usefulness of a smartphone-based event recorder for ambulatory patients presenting with palpitations
Authors: Salar Alcaraz M E , Buendia Santiago F , Flores Blanco P J , Cabrera Romero E , Fernandez Vazquez D , Vazquez Andres D J , Pascual Figal D A , Garcia Alberola A , Manzano Fernandez S 
Published: October 2021

Abstract

Background
Palpitations are a common complaint among patients seen by primary care physicians (16%). Recent technological advances have led to several novel electrocardiographic monitoring devices. AliveCor Kardia Mobile® (AliveCor, Inc., Mountain View, CA, USA) is a smartphone-based event recorder that allows take an electrocardiogram (ECG) recording during 30 seconds. The usefulness of this device has been studied in atrial fibrillation screening, however, its usefulness in the diagnosis of palpitations is not well known.

Objective
Evaluate the diagnostic yield of the AliveCor Kardia Mobile® device in unselected patients referred to the cardiologist for the study of palpitations.

Methods
Uni-centre retrospective study. From September 2018 to October 2020, consecutive patients with palpitations referred to cardiology department were included. After an initial evaluation it was decided monitoring ECG of these patients with this device if they had access to a compatible smartphone. They were instructed to record ECG when they had symptoms. ECG tracings and clinical characteristics were analysed.

Results
152 patients were included. Mean age 42±15 years, 68% female. Most of the patients did not have heart disease and about 25% had a history of anxiety-depressive syndrome (Table 1). After monitoring, 31 (20%) patients had rhythm disturbances during symptoms, 82 (54%) patients had no rhythm disturbances related to the symptoms and 39 (26%) patients had no symptoms. Table 2 shows the electrocardiographic findings. Patients with palpitations of arrhythmic origin were older and presented less anxiety/depression (Table 1). Age was the only independent predictor of palpitations of arrhythmic origin (OR, × year: 1.03, 95% CI 1.01–1.06; p=0.035).

Conclusions
The AliveCor Kardia Mobile® device is easy to use and diagnosed the aetiology of palpitations in a high proportion of patients (74%) referred for specialist evaluation.

Funding Acknowledgement
Type of funding sources: None.
Clustering of healthy lifestyle behaviors is associated with a lower incidence of adverse events in patients with newly diagnosed atrial fibrillation: a nationwide cohort study
Authors: Lee S R , Choi E K , Han K D , Oh S , Lip G Y H 
Published: October 2021

Abstract

Background
Although unhealthy or healthy lifestyle behaviors tend to be clustered, studies on the risk of clinical outcomes depending on how the lifestyle behaviors are managed after atrial fibrillation (AF) diagnosis remain limited.

Purpose
We aimed to evaluate the association between a cluster of healthy lifestyle behaviors and the risk of adverse outcomes in patients with AF.

Methods
Using the Korean National Insurance Service database, patients who were newly diagnosed as nonvalvular AF between 2009 and 2016 and received national health screening examination within 2-year after AF diagnosis were included. A healthy lifestyle behavior score (HLS) was calculated by assigning 1 point each for “non-current” smoking, for non-drinking, and for performing regular exercise from the self-reported questionnaire in health screening examinations. The primary outcome was defined as major adverse cardiovascular events (MACE), including ischemic stroke, myocardial infarction, and hospitalization for heart failure. The secondary outcomes included individual components of the primary composite outcome and all-cause death.

Results
A total of 208,662 patients were included and 7.1%, 22.7%, 58.6%, and 11.6% were HLS 0, 1, 2, and 3 group, respectively. After multivariable adjustment, patients with HLS 1, 2, and 3 were associated with lower risks of MACE compared to those with HLS 0 (adjusted hazard ratio [95% confidence interval]: 0.788 [0.762–0.855], 0.654 [0.604–0.708], and 0.579 [0.527–0.636], respectively) (Figure). Increased number of healthy lifestyle behaviors were associated with lower risks of ischemic stroke, hospitalization for heart failure, and all-cause death. The risk reduction of healthy lifestyle combinations was consistently observed in various subgroups, regardless of CHA2DS2-VASc score and oral anticoagulant use.

Conclusion
Increased number of healthy lifestyle behaviors were significantly associated with lower MACE and all-cause death risks in patients with new-onset AF. These findings support the promotion of a healthy lifestyle to reduce the risk of adverse events in AF patients.

Funding Acknowledgement
Type of funding sources: None.