bluuebunny/crossref_metadata_2025 huggingface dataset:
The carbon footprint of total knee replacements
Authors: McGain Forbes , Wickramarachchi Kasun , Aye Lu , Chan Brandon G. , Sheridan Nicole , Tran Phong , McAlister Scott
Published: October 2024

Objective Detailed quantifications of the environmental footprint of operations that include surgery, anaesthesia, and engineering are rare. We examined all such aspects to find the greenhouse gas emissions of an operation. Methods We undertook a life cycle assessment of 10 patients undergoing total knee replacements, collecting data for all surgical equipment, energy requirements for cleaning, and operating room energy use. Data for anaesthesia were sourced from our prior study. We used life cycle assessment software to convert inputs of energy and material use into outputs in kg CO2e emissions, using Monte Carlo analyses with 95% confidence intervals. Results The average carbon footprint was 131.7 kg CO2e, (95% confidence interval: 117.7–148.5 kg CO2e); surgery was foremost (104/131.7 kg CO2e, 80%), with lesser contributions from anaesthesia (15.0/131.7 kg CO2e, 11%), and engineering (11.9/131.7 kg CO2e, 9%). The main surgical sources of greenhouse gas emissions were: energy used to disinfect and steam sterilise reusable equipment (43.4/131.7 kg CO2e, 33%), single-use equipment (34.2/131.7 kg CO2e, 26%), with polypropylene alone 13.7/131.7 kg CO2e (11%), and the knee prosthesis 19.6 kg CO2e (15%). For energy use, the main contributors were: gas heating (6.7 kg CO2e) and heating, cooling, and fans (4 kg CO2e). Conclusions The carbon footprint of a total knee replacement was equivalent to driving 914 km in a standard 2022 Australian car, with surgery contributing 80%. Such data provide guidance in reducing an operation’s carbon footprint through prudent equipment use, more efficient steam sterilisation with renewable electricity, and reduced single-use waste.
Strong coupling from inclusive semileptonic decay of charmed mesons*
Authors: Wu 吴 Jinfei 金飞 , Lou 娄 Xinchou 辛丑 , Che 车 Yuzhi 逾之 , Li 李 Gang 刚 , Huang 黄 Yanping 燕萍 , Ruan 阮 Manqi 曼奇 , Ye 叶 Jingbo 竞波
Published: October 2024

In this study, we employed the heavy quark expansion model with the kinetic scheme to evaluate

, the strong coupling constant at the charm quark mass

, using data on inclusive semileptonic decays of charmed mesons. Using the experimental values of the semileptonic decay widths of the

and the

, the value of

was determined to be

, where the first uncertainty is experimental and the second is systematic. This value of

is in good agreement with the value of

which calculated by running

at the

boson mass

with the renormalization group evolution equation. In addition, the values of

obtained individually from each of the

,

, and

mesons were consistent, as they were of the same origin.
Design and analysis of pump casing and impeller using reverse engineering technique
Authors: Patil Sushil S , Gawade Sanjaykumar S , Patil Sharad D
Published: October 2024

Advances in three-dimensional (3D) laser measurement technology have resulted in progress in the field of Reverse Engineering. This study introduces a Reverse Engineering technique utilized to restore the initial design of a Pump Casing and its Impeller. This study provides a detailed understanding of the creation of the casing and its impeller 3D model by using the scanned model and its detailed steps, and a 3D deviation report is plotted in order to get a complete deviation idea between the scan data and the design extracted. The Casing and Impeller both have a range of upper and lower is +/− 0.75 mm for the deviation measurement. The Casing is that all points are within its limit, and it’s 100% for most points within its limit and the impeller is 90.9% for most points is in its limit.
Spectroscopy-guided discovery of three-dimensional structures of disordered materials with diffusion models
Authors: Kwon Hyuna , Hsu Tim , Sun Wenyu , Jeong Wonseok , Aydin Fikret , Chapman James , Chen Xiao , Lordi Vincenzo , Carbone Matthew R , Lu Deyu , Zhou Fei , Anh Pham Tuan
Published: October 2024

Spectroscopy techniques such as x-ray absorption near edge structure (XANES) provide valuable insights into the atomic structures of materials, yet the inverse prediction of precise structures from spectroscopic data remains a formidable challenge. In this study, we introduce a framework that combines generative artificial intelligence models with XANES spectroscopy to predict three-dimensional atomic structures of disordered systems, using amorphous carbon (a-C) as a model system. In this work, we introduce a new framework based on the diffusion model, a recent generative machine learning method, to predict 3D structures of disordered materials from a target property. For demonstration, we apply the model to identify the atomic structures of a-C as a representative material system from the target XANES spectra. We show that conditional generation guided by XANES spectra reproduces key features of the target structures. Furthermore, we show that our model can steer the generative process to tailor atomic arrangements for a specific XANES spectrum. Finally, our generative model exhibits a remarkable scale-agnostic property, thereby enabling generation of realistic, large-scale structures through learning from a small-scale dataset (i.e. with small unit cells). Our work represents a significant stride in bridging the gap between materials characterization and atomic structure determination; in addition, it can be leveraged for materials discovery in exploring various material properties as targeted.
Federated learning with tensor networks: a quantum AI framework for healthcare
Authors: Singh Bhatia Amandeep , Bernal Neira David E
Published: October 2024

The healthcare industry frequently handles sensitive and proprietary data, and due to strict privacy regulations, it is often reluctant to share it directly. In today’s context, Federated Learning (FL) stands out as a crucial remedy, facilitating the rapid advancement of distributed machine learning while effectively managing critical concerns regarding data privacy and governance. The fusion of federated learning and quantum computing represents a groundbreaking interdisciplinary approach with immense potential to revolutionize various industries, from healthcare to finance. In this work, we propose a federated learning framework based on quantum tensor networks (QTNs) that takes advantage of the principles of many-body quantum physics. Currently, there are no known classical tensor networks (TNs) implemented in federated settings. Furthermore, we investigated the effectiveness and feasibility of the proposed framework by conducting a differential privacy analysis to ensure the security of sensitive data across healthcare institutions. Experiments on popular medical image datasets show that the federated quantum tensor network (FedQTNs) model achieved a mean receiver-operator characteristic area under the curve of 91%–98%, outperforming several state-of-the-art federated learning methods. Moreover, QTN models require fewer parameters in FL settings compared to traditional classical models, which often suffer from over-parameterization. This reduction in parameters not only improves the efficiency of the communication process but also significantly decreases data consumption during training. As a result, QTN models facilitate a more effective and resource-efficient approach to training in decentralized environments with limited communication bandwidth. The FedQTN models demonstrate a smaller performance drop even when using strong differential privacy settings, maintaining higher accuracy compared to classical models under similar privacy constraints. Experimental results demonstrate that the quantum federated global model, consisting of highly entangled TN structures, showed better generalization and robustness and achieved higher testing accuracy, surpassing the performance of locally trained clients under unbalanced data distributions among healthcare institutions.
Quasiparticle spectroscopy in technologically relevant niobium using London penetration depth measurements: experiment and theory
Authors: Ghimire Sunil , Joshi Kamal R , Datta Amlan , Goerdt Aidan , Tanatar Makariy A , Schlagel Deborah , Kramer Matthew J , Marshall Jayss , Kopas Cameron J , Mutus Joshua Y , Romanenko Alexander , Grassellino Anna , Prozorov Ruslan
Published: October 2024

The London penetration depth,

λ
(
T
)

, was measured in various forms of niobium, including foils, thin films, single crystals, and samples from superconducting radio-frequency (SRF) cavities. We observed a significant difference in

λ
(
T
)

at low temperatures,

T
<

T

c

/

3

, due to low-energy quasiparticles. In particular, an unusual downturn of

λ
(
T
)

on cooling in the SRF cavity samples required to take into account deep in-gap bound states. Theoretical modeling using the generalized Dynes density of states shows that such in-gap states lead to a downturn or a peak in

λ
(
T
)

upon cooling. Combined, experimental and theoretical findings provide a method for detecting two-level systems or states related to magnetic impurities in the bulk of niobium. This result is particularly relevant for the quantum informatics sciences technologies used in qubits and circuit quantum electrodynamics architecture based on SRF cavities.
Impact of gradient microstructure on strain hardening via activation of multiple deformation mechanisms in CoCrNi medium entropy alloy
Authors: Meng Jiaqi , Zhao Yonghao , Liu Yi , Li Zongyao , Gao Bo , Xu Mengning , Xia Weiheng , Chen Xuefei , Zhou Hao , Zhu Yuntian
Published: October 2024

Face centered cubic (FCC) structural medium/high entropy alloys (MEAs), characterized by excellent strength and ductility, have attracted significant attention by the research community. The incorporation of gradient structures (GSs) further can enhance their mechanical properties. In the present research, we employ the rotation acceleration shot peening technique to introduce a GS within the CoCrNi FCC MEA to investigate underlying mechanisms governing the physical deformation processes during the generation of GSs through processing, which the primary goal is mitigating the intrinsic trade-off between strength and ductility. Through the microstructures analysis along the depth direction, both pre and post uniaxial tensile plastic deformation, we unveiled that the low stacking fault (SF) energy characteristic of the CoCrNi MEA triggered the emergence of diverse defects in the core region. The presence of nanoscale deformation twins, SFs, Lomer–Cottrell dislocation locks and phase transformation from FCC to hexagonal close-packed at twin boundaries synergistically enhanced the strain hardening capacity of the material.
An analysis of observed and predicted extreme heat and precipitation trends across four pulse producing regions in North America: North Dakota, Montana, Saskatchewan, and Northeastern United States
Authors: Weiss Sophia , Coughlan de Perez Erin
Published: October 2024

The consumption of plant-based proteins in lieu of animal proteins is the most important dietary shift that would be needed to keep the world under 2 °C of warming, and this shift would require a dramatic increase in the percentage of cropland devoted to nuts and pulses (Peters et al 2016 Elementa
4 000116). As the demand for plant-based proteins, like pulse crops, continues to grow, it is critical to understand the impact of climate change on crop production. In this paper, we study two climate-related stressors for pulse production in North America: extreme heat and excess moisture during harvest. Pulses must be dried on the plant before harvest, requiring a 7 day dry spell before harvest or the use of Roundup (glyphosate) to kill the plants quickly. However, little is known about the changes in frequency of hot extremes or dry spells during harvest in pulse-growing regions. We analyze climate trends using the Unprecedented Simulated Extreme Ensemble method with historical data, and we compare results to the average future change in the ssp370 scenario, which is a medium-high climate change scenario of 40 models of the the Coupled Model Intercomparison Project (CMIP6) in four pulse growing regions across North America: Montana, North Dakota, Saskatchewan, and the Northeast USA. We find that temperature extremes have increased in all regions, with extreme events 3–4 times more likely today than in 1981, increasing the risk of crop loss. August and September rainfall during the harvest months has been decreasing in the Midwestern regions and it is projected to continue to decrease in the future; however, the likelihood of a wet August in the Northeast has nearly doubled. Even with this drying trend, farmers cannot assume that they will have a 7 day consecutive dry spell that would enable natural drying of pulses without synthetic drying agents like glyphosate. Future expansion of pulse production should incorporate adaptation measures to manage extreme heat and the potential for rain events during harvest.
Georgia’s potentials for sustainable intensification, increasing food security and rural incomes
Authors: Gollnow Florian , Cortner Owen , Chen Shijuan , Olofsson Pontus , Garrett Rachael
Published: October 2024

Increasing global demand for agricultural commodities spurs conversions of natural ecosystems. Sustainable intensification in areas of high yield gaps has been proposed as a pathway to achieve food security, support rural livelihoods, and improve resource efficiency while also reducing the impact of commodity production by narrowing yield gaps on existing agricultural lands. Following the dissolution of the Union of Soviet Socialist Republics (USSR), Georgia experienced one of the highest losses of agricultural productivity among all former USSR countries and is now highly dependent on food imports. Closing yield gaps in Georgia through sustainable intensification has the potential to increase food self-sufficiency, support rural livelihoods, and strengthen food security and sovereignty. We estimated Georgia’s potential for sustainable intensification in current agricultural areas to achieve self-sufficiency for wheat, maize, and barley. We found that crop yields can be doubled to tripled under high-input production systems, using high-yielding varieties, optimized inputs, fertilizers, and pest control. Yet, self-sufficiency in wheat can only be reached if at least 80% of the attainable yields are achieved and if land is strategically allocated between crops. To achieve such increases, farmers need access to and training for using different crop varieties, fertilizers, and pest and disease control practices and products. Intensification with very high levels of inputs can increase the ecological and human risks of agriculture and raise equity concerns. Yet, intensifying very low input agricultural production systems is often found to be more sustainable, with high yield increases compared to limited impacts on the environment. The high employment rate in the agricultural sector in Georgia provides opportunities for intensification to help reduce poverty and improve livelihoods by increasing incomes and food security.
Committing Violence
Authors: Rembis Michael
Published: October 2024

During the formative years of the asylum system in the United States (1830–1890), asylum commitment was a process of negotiation among mad people, families, friends, neighbors, strangers, and physicians, which often became protracted and always involved varying forms of affect and violence. Centering mad stories and mad writers in a wider account of the role of affect and violence in the history of asylum commitment reveals the multiple historical actors and many layers of interaction that shaped the creation of the asylum system and contributed to the development of a culture of surveillance that depended upon fear and sympathy, and policing and care.
Efficient protocol for isolating human fibroblast from primary skin cell cultures: application to keloid, hypertrophic scar, and normal skin biopsies
Authors: Ningsih Sri Suciati , Jusman Sri Widia A , Syaidah Rahimi , Nauli Raisa , Fadilah Fadilah
Published: October 2024

This protocol introduces a streamlined and efficient method for isolating human fibroblast from skin primary cell culture with a specific focus on its application to keloid, hypertrophic scar, and normal skin biopsies. Additionally, the absence of suitable animal models for keloid and hypertrophic scar has led preclinical research to rely on in vitro studies using primary cell cultures. This approach addresses the challenges of existing protocols in terms of time, cost, equipment, and technical expertise required. The method involves derivation, culture, and characterization analysis including cell proliferation, migration, and fibroblastic marker (Vimentin, CD90, CD73, and CD105) expression. Our study yielded high amounts of fibroblast from tested skin explants while maintaining their in vivo-like characteristics and behaviour. Immunostaining assay confirmed that the cultivated fibroblast was positively expressed Vimentin. Flowcytometry results showed high expression of CD90 and CD73 while relatively showing lower expression of CD105. Fibroblast derived from keloid tissue showed the highest rate of proliferation and migration ability compared to the other samples. These findings suggest an efficient and reproducible technique to cultivate high qualified fibroblast from human skin in normal or pathological condition, particularly for keloid and hypertrophic scar. The application of this protocol provides a foundation for further studies to investigate the progression and potential intervention of aberrant fibrotic dermatological disorder, in vitro.
Dermatopathology
Authors: Zhou Peiyu , Chen Wei , Zhang Xueyu , Liu Hongjie , Wang Lin
Published: October 2024

We report a 71-year-old woman who presented with a large ulcer on her right facial cheek. We provide the results of a pathological examination and immunohistochemistry. We also discuss clinical and pathological characteristics, differential diagnoses, treatment methods and prognoses.
Acquired comedonal plaques in a middle-aged woman
Authors: Chung Jenny G , Wilsher Mark J , Calonje Eduardo , Magdalinou Nadia , Mummery Catherine , Hussain Khawar , Roberts Nerys
Published: October 2024

A 54-year-old woman presented to outpatient dermatology (Department of Dermatology, Chelsea and Westminster Hospital NHS Foundation Trust, London, UK) with a discrete acneiform rash over the right forearm, lower back and chin. These plaques had slowly grown over 4 years and were mildly itchy.
Toward Sino-American Ideological Clash? The Lasswellian World Revolution Approach
Authors: Jo Sam-Sang
Published: October 2024

The power competition between the USA and China engrosses the profound fascination of scholars, beckoning them to delve into its intricacies, nuances, causes, and implications for world politics. Regardless of their perspectives on whether normative dimensions are seen as factors solely fueling strategic competition, operating autonomously, or existing within a mutually constitutive relationship with institutions and material capabilities, conventional wisdom such as realism, critical theory, and holistic approach affirms the centrality of material elements in power competition. This article adopts a constructivist lens to analyze complex patterns of international relations and power competition, acknowledging the inherent normative dimensions of power, as much more pervasive, as inherent and independent attributes of any complex, persistent pattern of international relations and, particularly, power competition. In particular, this article introduces an underexplored insight from Lasswell’s “world revolution” concept, termed the “Lasswellian world revolution.” According to this approach, no ideologies remain ascendant indefinitely, they change over time, and the ideology of a rising power often challenges that of an established power. The article contends that this framework provides a fresh lens to understand the intricate interactions between American liberal democracy and socialism with Chinese characteristics, shedding light on the dynamics of power transition and the evolving international landscape. In conclusion, the article posits that we are witnessing the “interregnum.” Unfolding in the interstice between the waning yet dominant American liberal democracy and the nascent yet fragile socialism with Chinese characteristics, this phase marks a period of rivalry and uncertainty between the USA and China.
Echocardiographic assessment of the right heart pulmonary circulation unit in mitral regurgitation due to mitral valve prolapse
Authors: Maheut R , Trousselle L , Eggenspieler F , Pace N , Filippetti L , Fraix A , Popovic B , Vanhuyse F , Huttin O , Selton-Suty C
Published: October 2024

Background

Right ventricular evaluation is essential in the context of chronic mitral regurgitation (MR). Chronic MR is associated with a progressive cardiac remodeling with enlargement and dysfunction of all cardiac chambers, and the development of functional tricuspid regurgitation (TR). Besides, right ventricle (RV) dysfunction and functional TR have been shown to influence patient prognosis.

Purpose

The aim of this study was to evaluate simple and combined echocardiographic parameters analysing the right heart – pulmonary circulation unit, according to the severity of MR.

Methods

In this monocentric retrospective study, echocardiographic studies of patients followed for a mitral valve prolapse (with or without MR) were reviewed. Usual parameters analysing RV morphology, load and function were obtained. Combined parameters of RV – pulmonary artery (RV-PA) coupling were calculated: TAPSE/PASP and RVFWS/PASP. Comparison between MR grades were performed with ANOVA or Kruskal Wallis tests as appropriate. Two-by-two post-hoc comparisons of continuous variables across the 5 groups were made using the Bonferroni correction.

Results

158 patients with mitral valve prolapse (MVP) were included: 37 without MR, 28 with mild MR, 23 with mild-to-moderate MR, 21 with moderate-to-severe MR and 49 with severe MR. Clinical and echocardiographic results are presented in Table 1. Patients with a higher-grade MR tended to be older and were more likely to be men. They were also significantly more symptomatic. Most echocardiographic parameters were significantly different between grades of MR. RV remodeling, studied with morphologic parameters, started with the first grade of MR and had a linear progression between levels of MR severity (Figure 1A). Load parameters were stable until grade 2 and then showed progressive increase of RV afterload. RV free wall strain slightly increased with MR grade 1, and then decreased with each grade of MR (Figure 1B). RV fractional area change, Tissue Doppler MPI and RV free wall strain rate tended to stagnate between grade 0 and 2, and then they progressively decreased. Combined parameters of RV-PA coupling including load and function, increased with the first grade of MR, and then gradually decreased (Figure 1C).

Conclusion

In this study, multiparametric assessment of the cardiopulmonary unit in patients with MVP showed that RV morphologic remodeling starts with the first grades of MR, before any significant increase of pulmonary pressure. This remodeling seemed to initially enhance RV function (evaluated with parameters of RV – pulmonary artery coupling) in the first grade of MR and was then followed by a progressive decrease of RV function with the increasing severity of MR.
Prognostic prediction of cardiovascular adverse events in patients after percutaneous coronary intervention using machine learning
Authors: Okada K , Kusu K K , Kikuchi S K , Etou H E , Iguchi A I , Onimura Y O , Tsutsumi K T , Hanajima Y H , Kirigaya H K , Nakahashi H N , Matsushita K M , Gohbara M G , Sugano T S , Seki Y S , Hibi K H
Published: October 2024

Introduction

While prevention of major cardiovascular adverse events (MACE) is important in the management of patients after percutaneous coronary intervention (PCI), risk stratification of MACE remains a significant challenge with increasingly diverse and complex patient backgrounds. In response to that, this retrospective observational study aimed to explore whether machine learning (ML) methods can predict future MACE after PCI using a variety of features extracted from electronic medical records (EMRs).

Methods

In 3,016 patients with coronary artery disease who performed PCI, 3 machine learning (ML) algorithms (gentle boost, random forest, and neural network) and statistical model were retrospectively applied to predict the occurrence of MACE within two years after PCI (564 patients, 18.7%). MACE was defined as composite endpoint of cardiac death, myocardial infarction (MI), any revascularization, and congestive heart failure (CHF). Basic patient information (e.g., age, sex, coronary risk factors) and laboratory test results were used for the analysis. Feature importance was calculated to identify key factors for MACE. Hold-out method with an 8:2 split between training and test was used to calculate sensitivity, specificity, positive predictive value, negative predictive value, and F-value for each model.

Results

As shown in Figure 1, ML models showed excellent diagnostic accuracies in the prediction of MACE after PCI, demonstrating higher F-values compared with statistical model (logistic regression analysis). Similar results were seen in the subgroup analyses for estimating cardiac death, MI, revascularization, or CHF. Although the weighting of feature importance for MACE recurrence varied among ML models, infarct size (peak CK levels), increased inflammatory status, and traditional coronary risk factors were identified as important features for predicting MACE within two years after PCI (Figure 2).

Conclusions

It is suggested that ML using EMRs is promising for inferring future MACE within two years after PCI. Further studies are warranted to address whether ML-based risk stratification could lead to improved clinical decision-making after PCI.
The association between elevated systemic inflammation response index and long-term mortality in patients with triple-vessel coronary disease
Authors: Li Q X , Yuan J Q
Published: October 2024

Background

Inflammation is a critical factor in the development of coronary artery disease. The systemic inflammatory response index (SIRI) is a novel biomarker of inflammation. Studies have shown that SIRI is associated with the severity of coronary artery disease. However, there is currently a lack of research on the relationship between SIRI and adverse outcomes in patients with multivessel coronary artery disease. Our study aimed to investigate the correlation between SIRI and long-term mortality risk in patients with triple-vessel coronary disease (TVD) and explore the interaction between SIRI and treatment strategies.

Methods

After excluding patients with missing data or loss to follow-up, a total of 8559 patients with TVD were included in our study. Based on their SIRI levels during hospitalization, patients were evenly divided into three groups (SIRI-L, SIRI-M, and SIRI-H). All patients received appropriate treatment, including medical therapy alone (MT), percutaneous coronary intervention (PCI), or coronary artery bypass grafting (CABG). The primary endpoint was all-cause death. SIRI was calculated by the formula: neutrophil counts × monocyte counts / lymphocyte counts.

Results

During a median follow-up of 6.58 years, a total of 1264 all-cause deaths (14.8%) were recorded. Elevated SIRI was significantly associated with increased mortality rates (11.1%, 14.6%, and 18.6% in the SIRI-L, SIRI-M, and SIRI-H groups, respectively). The risk of all-cause mortality was significantly higher in the SIRI-M and SIRI-H groups compared to the SIRI-L group (adjusted HR: 1.203, 95% CI: 1.037-1.395, p=0.015; adjusted HR: 1.400, 95% CI: 1.212-1.617, p<0.001; respectively). In elderly patients, the relationship between elevated SIRI and the risk of all-cause mortality was more pronounced, while it attenuated in younger patients. Additionally, it is noteworthy that there was an interaction between SIRI and treatment strategy (p=0.037). In patients of the SIRI-L group, there was no significant difference between PCI and CABG treatment. However, in patients of the SIRI-M and SIRI-H groups, CABG shows a significant survival advantage over PCI.

Conclusion

Evaluating SIRI may help identify high-risk groups among patients with triple-vessel coronary disease and guide the selection of treatment strategies.Kaplan-Meier curves
Galectin-3 and cancer mortality in patients with suspected or known coronary artery disease: the ANOX study
Authors: Wada H , Suzuki M , Matsuda M , Ajiro Y , Shinozaki T , Sakagami S , Yonezawa K , Shimizu M , Funada J , Takenaka T , Nakayama T , Iguchi M , Abe M , Akao M , Hasegawa K
Published: October 2024

Background

Galectin-3 is a multifunctional carbohydrate-binding lectin that is involved in inflammation, tissue remodeling, and fibrosis. High circulating levels of galectin-3 are associated with all-cause mortality, cardiovascular (CV) mortality, and/or major adverse CV events in patients with CV diseases such as heart failure and coronary artery disease (CAD). However, the associations of galectin-3 with non-CV mortality and cancer mortality in patients with suspected or known CAD are unknown.

Methods

Serum galectin-3 levels were measured in 2,418 patients with suspected or known CAD undergoing elective coronary angiography. The outcomes were all-cause death, CV death, non-CV death, cancer death, and other non-CV death. Patients were followed up over a 6-year period.

Results

During the follow-up, 536 (22.2%) deaths occurred, including 166 (6.9%) CV deaths, 326 (13.5%) non-CV deaths, 128 (5.3%) cancer deaths, 198 (8.2%) other non-CV deaths, and 44 (1.8%) undetermined deaths. After adjustment for potential clinical confounders (i.e., age, sex, body mass index, hypertension, dyslipidemia, diabetes, current smoker, estimated glomerular filtration rate, the Gensini score, previous myocardial infarction, previous stroke, previous heart failure hospitalization, atrial fibrillation, valvular heart disease, malignancies, anemia, antihypertensive drug use, statin use, and aspirin use) and established CV biomarkers (i.e., N-terminal pro-brain natriuretic peptide, high-sensitivity cardiac troponin I, and high-sensitivity C-reactive protein), galectin-3 levels were significantly associated with all-cause death (hazard ratio [HR] for 1-SD increase, 1.22; 95% confidence interval [CI], 1.13–1.31), CV death (HR, 1.16; 95% CI, 1.02–1.33), non-CV death (HR, 1.27; 95% CI, 1.15–1.40), cancer death (HR, 1.31; 95% CI, 1.07–1.61), and other non-CV death (HR, 1.30; 95% CI, 1.15–1.46). The addition of galectin-3 levels to the model with potential clinical confounders and established CV biomarkers significantly improved the prediction of all-cause death (P<0.001 for continuous net reclassification improvement [NRI], P<0.001 for integrated discrimination improvement [IDI]) and cancer death (P=0.001 for NRI, P=0.005 for IDI), but not that of CV death (P=0.601 for NRI, P= 0.708 for IDI), non-CV death (P=0.060 for NRI, P=0159 for IDI), or other non-CV death (P=0.266 for NRI, P=0.699 for IDI).

Conclusions

The galectin-3 level independently predicted all-cause mortality and cancer mortality in patients with suspected or known CAD.
The incidence of cardiovascular conditions in patients admitted to hospital with and without COVID-19 in the South-East of Scotland
Authors: Bularga A , Gruber F , Lyell I , Kimenai D , Anand A , Pollock K , Sandler S , Mills N
Published: October 2024

Background

Multiple studies have reported an increased risk of acute myocardial infarction, cardiac arrhythmia, heart failure, myocarditis, and venous thromboembolism in patients admitted to hospital with COVID-19 infection. Whether the incidence of these cardiovascular conditions differ in patients hospitalised with COVID-19 compared to those who have COVID-19 excluded is not clear.

Methods

In a prospective, multi-centre, cohort study in secondary and tertiary care hospitals in Scotland, consecutive adults with symptoms of suspected COVID-19 were identified by the attending clinician using an electronic form integrated into the care pathway. Using linked electronic health record data, we evaluated the incidence of acute myocardial infarction, atrial fibrillation, heart failure hospitalisation, myocarditis, and venous thromboembolism during the index admission and the first 90 days following the index admission. In multivariable regression models the frequency of cardiovascular conditions at 90 days were compared in patients with confirmed COVID-19 infection defined by RT-PCR test with those in whom COVID-19 was excluded.

Results

Between April 2020 and May 2022, 53,644 (median age 68 [interquartile range, IQR 49-90] years, 54% women) consecutive patients were hospitalised and underwent RT-PCR for suspected COVID-19 infection. In total, 4,365 (8%) had COVID-19 confirmed and 49,279 (92%) had COVID-19 excluded. At 90 daythe myocardial infarction was less common (2% versus 5%) and venous thromboembolism was more common (6% versus 4%) in patients with COVID-19 compared to those without, but the proportion with atrial fibrillation (15% versus 14%), heart failure hospitalisation (10% versus 9%), and myocarditis (<0.1% versus <0.1%) were similar. Overall, the proportion with a cardiovascular condition at 90 days did not differ in patients with or without COVID-19 (Figure). Age (over 65 years, adjusted hazard ratio [aHR] 2.75, 95% confidence interval [CI] 2,61 to 2.89), male sex (aHR 1.35, 1.30 to 1.40), and risk factors (diabetes [aHR 1.13, 1.08 to 1.19], hyperlipidaemia [aHR 1.09, 1.01 to 1.18], hypertension [aHR 1.45, 1.39 to 1.52]) were independent predictors of cardiovascular complications, whilst COVID-19 status was not associated with increased risk (aHR 0.94, 0.88 to 1.01).

Conclusion

Cardiovascular conditions are common in patients hospitalised with suspected COVID-19, however the incidence at 90 days does not differ in those with or without COVID-19 and COVID-19 infection does not confer an increase in risk.
Single spot albumin to creatinine ratio as an independent predictor of 12 years follow-up mortality in acute coronary syndromes without ST-segment elevation
Authors: Higa C , Castro Ortega J S , Montoya R , Gambarte M J , Korolov Y , Donato M S , Ciambrone M G , Novo F A
Published: October 2024

Background

To the best of our knowledge there is no evidence of the association between microalbuminuria, measured as single spot urine albumin to creatinine ratio (ACR), with very long-term mortality in patients with non-ST segment Elevation Acute Coronary Syndromes.

Aim

To evaluate the association between admission ACR and very long-term all-cause mortality in an unselected cohort of non-ST-segment elevation acute coronary syndromes patients.

Methods

A prospective cohort study was conducted, including patients with non-ST-segment elevation acute coronary syndromes admitted in the Intensive Care Unit. The ACR was determined in spontaneous urine samples during the first 24 hours after admission and analyzed by immunoturbidimetry. The primary endpoint was all-cause mortality during the follow-up. Actuarial survival curves were compared by log rank test and a logistical Cox regression analysis was performed to identify variables independently associated with mortality in the follow-up. Statistics were calculated using the IBM Statistics program SPSS version 26.

Results

600 patients were analyzed. The overall average ACR value was 7 mg/gr (95% CI 4-26). 76% had normoalbuminuria (ACR 0-30 mg/gr), 22% had microalbuminuria (ACR 30-300 mg/gr), and 1.5% had macroalbuminuria (ACR > 300 mg/gr). The median and interquartile range of follow-up was 12 years (95% IC 11-14). The average ACR among those who met the primary endpoint was 59.15 mg/gr (95% CI 52-66) and among the survivors, 27.66 mg/gr (95 % CI 63-77), p > 0,003. ACR terciles were defined by 33th and 66th percentiles: tercile 1: patients with ACR of 0 to 4 mg/gr, tercile 2: ACR from 4 to 17 mg/g and tercile 3 values greater than 17mg/gr. Strong associations were observed between ACR with age, hypertension, stroke and history of COPD, previous use of angiotensin II converter/blocking enzyme inhibitors, systolic blood pressure at admission, ST segment deviation, left ventricle ejection fraction and elevation of serum Troponin T and CPK MB. All cause-mortality during the follow-up was 14% (CI 95% 11-17). Elevation of ACR was significantly associated with long term mortality risk: log rank test chi square: 133.936, p = 0.0001. By multivariate Cox regression analysis adjusted by age, gender, diabetes, hypertension, serum creatinine, troponin T elevation, ST segment deviation, previous AMI, prior use of aspirin, statins and percutaneous coronary intervention after hospitalization, the ACR was independently associated with a 12-year follow-up mortality: OR 13 (95% IC 5-35; p < 0.0001).

Conclusion

Single spot urine ACR at admission is a strong predictor of 12-year follow-up mortality in an unselected cohort of patients with non-ST-segment elevation acute coronary syndromes.Baselines characteristics of cohortsMultivariable COX regression analysis
Electrocardiogram-based artificial intelligence to identify prevalent coronary artery disease
Authors: Kany S , Friedman S F , Al-Alusi M , Khurshid S , Raemoe J T , Pipilas D , Pirruccello J P , Reeder C , Phillippakis A A , Ho J E , Maddah M , Ellinor P T , Fahed A C
Published: October 2024

Background

Coronary artery disease (CAD) often goes undetected for years before it manifests and results in substantial morbidity and mortality. Some patients have neither typical risk factors nor symptomatic angina despite progressive disease.

Purpose

Develop a deep-learning model to detect prevalent CAD and identify people at risk for adverse events using electrocardiograms (ECG) in a primary care setting.

Methods

We developed a convolutional neural network using 12-lead ECG waveforms to discriminate the presence of CAD defined using diagnostic codes ("ECG2CAD"). ECG2CAD was trained on 764,670 ECGs from 137,199 individuals at the Massachusetts General Hospital (MGH). Model performance for discrimination of prevalent CAD was measured using AUROC and AUPRC, and compared against a model comprising age and sex, as well as the Pooled Cohort Equations (PCE), in three test sets independent of model training: MGH, Brigham and Women’s Hospital (BWH) and UK Biobank. ECG2CAD was assessed across subgroups of age, sex and self-reported ethnicity and for incident CAD-related events in the BWH primary care subset.

Results

ECG2CAD was evaluated in MGH (N=18,706 [N=6,051 cases], age 57±16 years), BWH (N=88,270 [N=27,898 cases], age 57±16 years), and UK Biobank (N=42,147 [N=1,509 cases], age 65±8 years). ECG2CAD consistently discriminated prevalent CAD (MGH: AUROC 0.782, AUPRC 0.639; BWH: AUROC 0.747, AUPRC 0.588; UK Biobank: AUROC 0.760, AUPRC 0.155) and incrementally improved upon both a model based on age and sex (p<0.01) and the PCE (p<0.01) in MGH and BWH.

In the BWH primary care subset (N=51,808), model performance was consistent in subgroups defined by age, sex and self-reported ethnicity/race. The incorporation of ECG2CAD in addition to age and sex consistently improved discrimination (AUROC delta of 0.011-0.086) in all subgroups.

In the BWH primary care subset with over 10 years of follow-up, we observed that either the presence of ECG2CAD-predicted CAD (HR 2.18, 95% CI 2.00-2.38, P<0.001) and ICD-based known CAD (HR 2.13, 95% CI 1.86-2.45, P<0.001) were associated with increased risk for incident myocardial infarction. The presence of both definitions was associated with an almost five-fold increase in risk (HR 4.97, 95% CI 4.51-5.48, P<0.001).

The risk of incident adverse events was highest among people in the top quintile of ECG-based predicted risk (high risk) compared with people from quintile 4-2 (intermediate risk) or the lowest quintile (low risk), even when excluding those with known prevalent CAD at baseline.

Conclusions

Artificial intelligence-enabled analysis of the 12-lead ECG may facilitate efficient identification of individuals with possible undiagnosed CAD and inform downstream testing and preventive measures.
Diagnostic performance of coronary computed tomography angiography for coronary in-stent re-stenosis
Authors: Kim D , Cho S W , Kim B G , Kim G S , Byun Y S , Hwang J , Kim G , Doh J H
Published: October 2024

Background

Through the development of CT equipment and proper preparation before CT scanning, the accuracy of Coronary computed tomography angiography (CCTA) diagnosis of ischemic heart disease (IHD) is improving, and the role of CCTA in treatment decision is gradually expanding. The latest guidelines recommend CCTA as Class IIa to evaluate stent patency and native vessels in patients with chronic coronary disease. However, diagnostic performance of CCTA to evaluate stent patency in patients who underwent coronary stent was not clarified, respectively the role of CCTA in the evaluation of IHD in native coronary artery was established..

Purpose

In the present study, we evaluate the agreement between CCTA and CAG in assessing stent patency in patients with de novo ischemic chest pain who underwent percutaneous coronary intervention (PCI) and evaluated which factors contribute to the differences.

Methods

From January 1, 2010 to December 31, 2020, we analyzed 845 patients who underwent new CCTA and CAG sequentially for the evaluation of chest pain previously underwent PCI. In CAG and CCTA, ISR is equally defined as a stenosis greater than 50% of the vessel diameter of within the stented segment or its edge (5-mm segments adjacent to the stent). The degree of In-stent restenosis was analyzed by an independently by quantitative coronary angiography (QCA).

Results

A total of 208 stents were analyzed, the pooled sensitivity and specificity for CCTA on the diagnosis of ISR were 0.78 (0.65-0.89) and 0.93 (0.88-0.96), respectively. LR+ and LR- were 11.19 (6.22-20.15) and 0.23 (0.14-0.39). As a result of analyzing the ISR diagnostic agreement of CCTA by dividing into ACS and CCD group, the agreement of CCTA for ISR diagnosis was relatively low in the ACS group (Sensitivity 0.69 (0.48-0.86) vs. 0.88 (0.69-0.97), specificity 0.92 (0.84-0.97) vs. 0.94 (0.86-0.98), LR+ 9 (4-20.24) vs. 13.9 (5.88-32.88), LR- 0.33 (0.19-0.6) vs. 0.13 (0.04-0.37)) (Table 1). As a result of analyzing related factors in cases of discrepancy in ISR diagnosis, the degree of stenosis in both ACS and CCD groups was mostly intermediate stenosis, which often required additional clinical evaluation (Figure 1).

Conclusion

When new ischemic chest pain occurred in a patient who previously underwent PCI, the diagnostic accuracy of ISR by CCTA differed depending on the patient’s IHD category. In the CCD group, the diagnostic usefulness of CCTA was comparable both native vessels and ISR, but not in the ACS group. As majority of ISR diagnostic discrepancies were in intermediate lesions, even in the ACS group, CCTA may be considered as a diagnostic tool.
The impact of lipid rich plaque on coronary-microvascular-dysfunction evaluated by near-infrared spectroscopy IVUS and angiography-derived index of microcirculatory resistance after percutaneous-coron
Authors: Yamada N , Ueno M , Onishi K , Sugimoto K , Kakehi K , Fujita K , Nakazawa G
Published: October 2024

Background

Coronary microvascular dysfunction (CMD) after percutaneous coronary intervention (PCI) has been reported to be associated not only with periprocedural myocardial infarction, but also with poor prognosis. While index of microcirculatory resistance using pressure wire (invasive IMR) has been conventionally used to evaluate CMD, angio-derived IMR (angio-IMR) has recently emerged as a noninvasive method and has shown good correlation with invasive IMR. Previous investigations have already shown that the maximum value of LCBI for any of the 4-mm segments (maxLCBI4mm) by near-infrared spectroscopy IVUS (NIRS-IVUS) represents the degree of lipid rich plaque (LRP) and can predict microvascular obstruction after PCI. However, few studies have examined the relationship between maxLCBI4mm values assessed by NIRS-IVUS and the degree of CMD from physiological assessment, or the optimal maxLCBI4mm cut-off values to predict CMD after PCI.

Purpose

The purpose of this study was to define the relationship between LRP identified by NIRS-IVUS and CMD assessed by angio-IMR in coronary artery disease (CAD) patients and to determinate the optimal diagnostic cut-off values of maxLCBI4mm.

Methods

We retrospectively evaluated 101 consecutive patients who underwent PCI using NIRS-IVUS for CAD, excluding STEMI, at our hospital from November 2021 to January 2024. MaxLCBI4mm and angio-IMR were measured in culprit vessel before and after PCI. CMD was defined as angio-IMR≥25. ROC curve analysis was performed to determine the optimal cut-off values of maxLCBI4mm for angio-IMR≥25. Plaques with maxLCBI4mm values above the cut-off were defined as the LRP group.

Results

Of 101 patients, CMD after PCI occurred in 37 patients (37%). MaxLCBI4mm values were significantly higher in the CMD group compared to the non-CMD group (659±198 vs. 403±226, P<0.001). Figure 1 shows the results of ROC analysis for predicting the incidence of CMD after PCI. ROC analysis determined maxLCBI4mm≥579 (LRP group) as an optimal cut-off value associated with incidence of CMD (AUC=0.80, P<0.01, sensitivity=0.78, specificity=0.75). LRP group had significantly higher angio-IMR values and incidence of CMD than non-LRP group (24.7±7.8 vs. 19.1±7.2, P<0.01, 64% vs. 14%, P<0.01). Furthermore, Δangio-IMR (post PCI-Pre PCI) of the LRP group was significantly higher than that of the non-LRP group (Figure 2). On multivariable analysis, maxLCBI4mm≥579 emerged as the independent predictor of the incidence of CMD after PCI (OR=10.6, 95% CI=2.29-48.8, P<0.01).

Conclusions

The results of this study indicate that NIRS-IVUS-guided PCI is a useful predictor of the incidence of CMD after PCI.Figure 1Figure 2
The relationship between atherogenic index of plasma and plaque vulnerabilities: an optical coherence tomography study
Authors: Wu S J , Gao Y N , Wang Z J , Liu W , Ma Q , Gao C , Wang R T , Liu Y Y , Shi D M , Zhou Y J
Published: October 2024

Background

Atherogenic index of plasma (AIP) has been recommended as a marker of plasma atherogenicity. The impact of AIP on plaque characteristics is not fully understood.

Purpose

The study investigates the relationship between AIP and coronary plaque features in patients with acute coronary syndrome (ACS).

Methods

From January 2015 to June 2017 pre-intervention optical coherence tomography (OCT) was performed in 522 ACS patients. AIP was defined as the base 10 logarithm of the ratio of the concentrations of triglyceride to high-density lipoprotein cholesterol. Patients were divided into four groups according to AIP quartiles.

Results

A total of 332 patients were included for the analysis. The incidence of thin-cap fibroatheroma (TCFA) (group I [lowest] 9.09% vs group II 16.5% vs group III 44.7% vs group IV [highest] 52.9%), macrophage accumulation (group I 18.2% vs group II 22.4% vs group III 31.8% vs group IV 47.1%), plaque rupture (group I 10.4% vs group II 14.1% vs group III 17.6% vs group IV 34.1%) and plaque erosion (group I 2.6% vs group II 2.4% vs group III 14.1% vs group IV 12.9%) were significantly different among AIP quartiles. Multivariate logistic regression revealed the risk of TCFA (odds ratio 11.938, 95% confidence interval 4.723-30.174, p<0.001) and plaque rupture (OR 4.976, 95% CI 1.993-12.424, p<0.001) increased in group IV compared to group I. Receiver operating characteristics curve showed the predictive value of AIP for TCFA and plaque rupture were 0.720 and 0.669 respectively.

Conclusions

AIP is an independent predictor for vulnerable plaques beyond traditional factors. It can be integrated in clinical practice for risk stratification of ACS patients.Multivariate logistic analysisROC curves