cVAN: A Novel Sleep Staging Method Via Cross-View Alignment Network.

Sleep staging is imperative for evaluating sleep quality and diagnosing sleep disorders. Extant sleep staging methods with fusing multiple data-views of physiological signals have achieved promising results. However, they remain neglectful of the relationship among different data-views at different feature scales with view position-alignment. To address this, we propose a novel cross-view alignment network, termed cVAN, utilising scale-aware attention for sleep stages classification. Specifically, cVAN principally incorporates two sub-networks of a residual- like network which learn spectral information from time-frequency images and a transformer- like network which learns corresponding temporal information. The prime advantage of cVAN is to adaptively align the learned feature scales among the different data-views of physiological signals with a scale-aware attention by reorganizing feature maps. Extensive experiments on three public sleep datasets demonstrate that cVAN can achieve a new state-of-the-art result, which is superior to existing counterparts. The source code for cVAN is accessible at the URL (https://github.com/Fibonaccirabbit/cVAN).

Chinese expert consensus on the diagnosis and treatment of coronary microvascular diseases (2023 Edition).

Since the four working groups of the Chinese Society of Cardiology issued first expert consensus on coronary microvascular diseases (CMVD) in 2017, international consensus documents on CMVD have increased rapidly. Although some of these documents made preliminary recommendations for the diagnosis and treatment of CMVD, they did not provide classification of recommendations and levels of evidence. In order to summarize recent progress in the field of CMVD, standardize the methods and procedures of diagnosis and treatment, and identify the scientific questions for future research, the four working groups of the Chinese Society of Cardiology updated the 2017 version of the Chinese expert consensus on CMVD and adopted a series of measures to ensure the quality of this document. The current consensus has raised a new classification of CMVD, summarized new epidemiological findings for different types of CMVD, analyzed key pathological and molecular mechanisms, evaluated classical and novel diagnostic technologies, recommended diagnostic pathways and criteria, and therapeutic strategies and medications, for patients with CMVD. In view of the current progress and knowledge gaps of CMVD, future directions were proposed. It is hoped that this expert consensus will further expedite the research progress of CMVD in both basic and clinical scenarios.

Cold Spells and the Onset of Acute Myocardial Infarction: A Nationwide Case-Crossover Study in 323 Chinese Cities.

BACKGROUND: Few studies have explored the relationships between cold spells and acute myocardial infarction (AMI) using the information of symptom onset. OBJECTIVES: We assessed the impact of cold spells on AMI onset and the potential effect modifiers. METHODS: We conducted a time-stratified case-crossover study among 456,051 eligible patients with AMI from 2,054 hospitals in 323 Chinese cities between January 2015 and June 2021 during cold seasons (November to March). Nine definitions of cold spells were used by combining three relative temperature thresholds (i.e., lower than the 7.5th, 5th, and 2.5th percentiles) and three durations of at least 2-4 consecutive d. Conditional logistic regressions with distributed lag models were applied to evaluate the cumulated effects of cold spells on AMI onset over lags 0-6 d, after adjusting for daily mean temperature. RESULTS: The associations generally appeared on lag 1 d, peaked on lag 3 d, and became nonsignificant approximately on lag 5 d. Cold spells defined by more stringent thresholds of temperature were associated with higher risks of AMI onset. For cold spell days defined by a daily mean temperature of ≤7.5th percentile and durations of ≥2d, ≥3d, and ≥4d, the percentage changes in AMI risk were 4.24% [95% confidence interval (CI): 2.31%, 6.20%], 3.48% (95% CI: 1.62%, 5.38%), and 2.82% (95% CI: 0.98%, 4.70%), respectively. Significant AMI risks associated with cold spells were observed among cases from regions without centralized heating, whereas null or much weaker risks were found among those from regions with centralized heating. Patients ≥65 years of age were more susceptible to cold spells. DISCUSSION: This national case-crossover study presents compelling evidence that cold spells could significantly increase the risk of AMI onset. https://doi.org/10.1289/EHP11841.

Predicting AKI in patients with AMI: Development and assessment of a new predictive nomogram.

Acute kidney injury (AKI) is a common complication of acute myocardial infarction (AMI) and is associated with both long- and short-term consequences. This study aimed to investigate relevant risk variables and create a nomogram that predicts the probability of AKI in patients with AMI, so that prophylaxis could be initiated as early as possible. Data were gathered from the medical information mart for the intensive care IV database. We included 1520 patients with AMI who were admitted to the coronary care unit or the cardiac vascular intensive care unit. The primary outcome was AKI during hospitalization. Independent risk factors for AKI were identified by applying least absolute shrinkage and selection operator regression models and multivariate logistic regression analyses. A multivariate logistic regression analysis was used to build a predictive model. The discrimination, calibration, and clinical usefulness of the prediction model were assessed using C-index, calibration plot, and decision curve analysis. Internal validation was assessed using bootstrapping validation. Of 1520 patients, 731 (48.09%) developed AKI during hospitalization. Hemoglobin, estimated glomerular filtration rate, sodium, bicarbonate, total bilirubin, age, heart failure, and diabetes were identified as predictive factors for the nomogram construction (P < .01). The model displayed good discrimination, with a C-index of 0.857 (95% CI:0.807-0.907), and good calibration. A high C-index value of 0.847 could still be reached during interval validation. Decision curve analysis showed that the AKI nomogram was clinically useful when the intervention was determined at an AKI possibility threshold of 10%. The nomogram constructed herein can successfully predict the risk of AKI in patients with AMI early and provide critical information that can facilitate prompt and efficient interventions.

Fully Automatic Classification of Cardiotocographic Signals with 1D-CNN and Bi-directional GRU.

Prenatal fetal monitoring, which can monitor the growth and health of the fetus, is vital for pregnant women before delivery. During pregnancy, it is essential to classify whether the fetus is abnormal, which helps physicians carry out early intervention to avoid fetal heart hypoxia and even death. Fetal heart rate and uterine contraction signals obtained by fetal heart monitoring equipment are essential to estimate fetal health status. In this paper, we pre-process the obtained data set and enhance them using Hermite interpolation on the abnormal classification in the samples. We use the 1D-CNN and GRU hybrid models to extract the abstract features of fetal heart rate and uterine contraction signals. Several evaluation metrics are used for evaluation, and the accuracy is 96 %, while the sensitivity is 95 %, and the specificity is 96 %. The experiments show the effectiveness of the proposed method, which can provide physicians and users with more stable, efficient, and convenient diagnosis and decision support.

Low ambient temperature might trigger the symptom onset of pulmonary embolism: A nationwide case-crossover study at hourly level in China.

BACKGROUND: Pulmonary embolism (PE) is an important cause of death and its seasonality has long been observed. Very few epidemiological studies have explored the potential role of ambient temperature in PE symptom onset, especially at the hourly level. METHODS: We conducted a time-stratified case-crossover study among 17,903 PE patients with hourly onset of symptom from 1590 hospitals across China between January 2015 and September 2020. Conditional logistic regression model combined with distributed lag non-linear models were used to explore the associations between hourly ambient temperature and PE symptom onset. The attributable fractions due to non-optimum temperature were calculated. RESULTS: The exposure-response relationship curve was inverse and almost linear. Lower temperature was significantly associated with higher risk of PE symptom onset when temperature was below 18 °C. This risk occurred immediately at the same hour, attenuated thereafter, and became nonsignificant at approximately 72 h after exposure. Compared with the referent temperature (P99, 34.1 °C), the odds ratio of PE symptom onset associated with extremely low temperature (P1, -16.1 °C) over lag 0-72 h was 1.63 (95%CI: 1.23, 2.16). Low temperature may account for 16.19 % of the symptom onset nationally with higher proportion in the south of China. The effects were stronger in older adults, males, and cold seasons. CONCLUSIONS: We provided the first-hand robust evidence that transient exposure (at the hourly level) to low temperature might trigger the symptom onset of PE and constitute a considerable burden for PE patients. Targeted protections and health education are needed for susceptible populations.

Deep learning-based automatic segmentation of images in cardiac radiography: A promising challenge.

BACKGROUND: Due to the advancement of medical imaging and computer technology, machine intelligence to analyze clinical image data increases the probability of disease prevention and successful treatment. When diagnosing and detecting heart disease, medical imaging can provide high-resolution scans of every organ or tissue in the heart. The diagnostic results obtained by the imaging method are less susceptible to human interference. They can process numerous patient information, assist doctors in early detection of heart disease, intervene and treat patients, and improve the understanding of heart disease symptoms and clinical diagnosis of great significance. In a computer-aided diagnosis system, accurate segmentation of cardiac scan images is the basis and premise of subsequent thoracic function analysis and 3D image reconstruction. EXISTING TECHNIQUES: This paper systematically reviews automatic methods and some difficulties for cardiac segmentation in radiographic images. Combined with recent advanced deep learning techniques, the feasibility of using deep learning network models for image segmentation is discussed, and the commonly used deep learning frameworks are compared. DEVELOPED INSIGHTS: There are many standard methods for medical image segmentation, such as traditional methods based on regions and edges and methods based on deep learning. Because of characteristics of non-uniform grayscale, individual differences, artifacts and noise of medical images, the above image segmentation methods have certain limitations. It is tough to obtain the needed results sensitivity and accuracy when performing heart segmentation. The deep learning model proposed has achieved good results in image segmentation. Accurate segmentation improves the accuracy of disease diagnosis and reduces subsequent irrelevant computations. SUMMARY: There are two requirements for accurate segmentation of radiological images. One is to use image segmentation to improve the development of computer-aided diagnosis. The other is to achieve complete segmentation of the heart. When there are lesions or deformities in the heart, there will be some abnormalities in the radiographic images, and the segmentation algorithm needs to segment the heart altogether. The quantity of processing inside a certain range will no longer be a restriction for real-time detection with the advancement of deep learning and the enhancement of hardware device performance.

Data Enhancement and Deep Learning for Bone Age Assessment using The Standards of Skeletal Maturity of Hand and Wrist for Chinese.

Conventional methods for artificial age determination of skeletal bones have several problems, such as strong subjectivity, large random errors, complex evaluation processes, and long evaluation cycles. In this study, an automated age determination of skeletal bones was performed based on Deep Learning. Two methods were used to evaluate bone age, one based on examining all bones in the palm and another based on the deep convolutional neural network (CNN) method. Both methods were evaluated using the same test dataset. Moreover, we can extend the dataset and increase the generalisation ability of the network by data expansion. Consequently, a more accurate bone age can be obtained. This method can reduce the average error of the final bone age evaluation and lower the upper limit of the absolute value of the error of the single bone age. The experiments show the effectiveness of the proposed method, which can provide doctors and users with more stable, efficient and convenient diagnosis support and decision support.

Comparação entre Dois Escores de Risco quanto à Predição de Obstrução Microvascular Coronariana durante a Intervenção Percutânea Primária / The Comparison between Two Risk Scores as for the Prediction of Coronary Microvascular Obstruction during Primary Percutaneous Intervention

Resumo Fundamento: Para pacientes com infarto do miocárdio com elevação do segmento ST (IAMCST) que sofrem de obstrução coronariana microvascular funcional e estrutural (OCM) subsequente, nenhuma abordagem terapêutica específica e definitiva de atenuação foi comprovada como válida em testes de larga escala atuais, o que destaca a necessidade de abordar seu reconhecimento precoce. Objetivos: Este estudo teve como objetivo comparar o desempenho de dois escores de risco clínico com uma medida objetiva de OCM durante intervenção coronária percutânea (ICP) em casos de IAMCST Métodos: A medição do índice de resistência microcirculatória (IRM) foi realizada e os parâmetros clínicos e angiográficos basais também foram registrados. Os pacientes foram divididos em entre os grupos OM (obstrução microvascular) e NOM (não-obstrução microvascular), de acordo com o valor de IRM pós-procedimento. O risco de OCM foi avaliado para todos os participantes pelos escores preditivos SAK e ATI, respectivamente. Cada sistema foi calculado somando-se as pontuações de todas as variáveis. As curvas de características do operador receptor (ROC) e a área sob a curva (AUC) de dois modelos de risco foram utilizadas para avaliar o desempenho discriminatório. Um ecocardiograma foi realizado sete dias após o procedimento para avaliar a fração de ejeção do ventrículo esquerdo (FEVE). Um valor P bicaudal de <0,05 foi considerado estatisticamente significativo. Resultados: Entre os 65 pacientes elegíveis com IAMCST, 48 foram alocados no grupo NOM e 17 no grupo OM, com uma incidência de OCM de 26,15%. Não houve diferença significativa na AUC entre os dois escores. A FEVE avaliada para o grupo NOM foi maior do que para o grupo OM. Conclusão: Os escores SAK e ATI tiveram bom desempenho para estimar o risco de OCM após ICP primário para pacientes com IAMCST.

Abstract Background: For patients with ST-segment elevation myocardial infarction (STEMI) that are suffering from subsequent coronary microvascular functional and structural obstruction (CMVO), no specific and definitive therapeutic approaches of attenuation have been proven valid in up-to-date large-scale tests, which highlights the urge to address its early recognition. Objectives: This study aimed to compare the performance of two clinical risk scores with an objective measurement of CMVO during percutaneous coronary intervention (PCI) with STEMI. Methods: The Index of Microcirculatory Resistance (IMR) measurement was conducted and the baseline clinical and angiographic parameters were also recorded. The patients were divided into MO (Microvascular obstruction) or NMO (Non-microvascular obstruction) groups according to the post-procedure IMR value. The CMVO risk was evaluated for all participants by SAK and ATI predictive scores, respectively. Each system was calculated by summing the scores of all variables. The receiver operator characteristic (ROC) curves and the area under the curve (AUC) of two risk models were used to evaluate the discriminatory performance. An echocardiography was performed seven days after the procedure to evaluate left ventricular ejection fraction (LVEF). A two-sided P-value of <0.05 was considered statistically significant. Results: Among the 65 eligible STEMI patients, 48 patients were allocated in the NMO group and 17 in the MO group, with a CMVO incidence of 26.15%. There was no significant difference in the AUC between both scores. The LVEF evaluated for the NMO group was higher than that of MO group. Conclusion: Both SAK and ATI scores performed well in estimating CMVO risk after primary PCI for STEMI patients.

The Comparison between Two Risk Scores as for the Prediction of Coronary Microvascular Obstruction during Primary Percutaneous Intervention. / Comparação entre Dois Escores de Risco quanto à Predição de Obstrução Microvascular Coronariana durante a Intervenção Percutânea Primária.

BACKGROUND: For patients with ST-segment elevation myocardial infarction (STEMI) that are suffering from subsequent coronary microvascular functional and structural obstruction (CMVO), no specific and definitive therapeutic approaches of attenuation have been proven valid in up-to-date large-scale tests, which highlights the urge to address its early recognition. OBJECTIVES: This study aimed to compare the performance of two clinical risk scores with an objective measurement of CMVO during percutaneous coronary intervention (PCI) with STEMI. METHODS: The Index of Microcirculatory Resistance (IMR) measurement was conducted and the baseline clinical and angiographic parameters were also recorded. The patients were divided into MO (Microvascular obstruction) or NMO (Non-microvascular obstruction) groups according to the post-procedure IMR value. The CMVO risk was evaluated for all participants by SAK and ATI predictive scores, respectively. Each system was calculated by summing the scores of all variables. The receiver operator characteristic (ROC) curves and the area under the curve (AUC) of two risk models were used to evaluate the discriminatory performance. An echocardiography was performed seven days after the procedure to evaluate left ventricular ejection fraction (LVEF). A two-sided P-value of <0.05 was considered statistically significant. RESULTS: Among the 65 eligible STEMI patients, 48 patients were allocated in the NMO group and 17 in the MO group, with a CMVO incidence of 26.15%. There was no significant difference in the AUC between both scores. The LVEF evaluated for the NMO group was higher than that of MO group. CONCLUSION: Both SAK and ATI scores performed well in estimating CMVO risk after primary PCI for STEMI patients.

FUNDAMENTO: Para pacientes com infarto do miocárdio com elevação do segmento ST (IAMCST) que sofrem de obstrução coronariana microvascular funcional e estrutural (OCM) subsequente, nenhuma abordagem terapêutica específica e definitiva de atenuação foi comprovada como válida em testes de larga escala atuais, o que destaca a necessidade de abordar seu reconhecimento precoce. OBJETIVOS: Este estudo teve como objetivo comparar o desempenho de dois escores de risco clínico com uma medida objetiva de OCM durante intervenção coronária percutânea (ICP) em casos de IAMCST. MÉTODOS: A medição do índice de resistência microcirculatória (IRM) foi realizada e os parâmetros clínicos e angiográficos basais também foram registrados. Os pacientes foram divididos em entre os grupos OM (obstrução microvascular) e NOM (não-obstrução microvascular), de acordo com o valor de IRM pós-procedimento. O risco de OCM foi avaliado para todos os participantes pelos escores preditivos SAK e ATI, respectivamente. Cada sistema foi calculado somando-se as pontuações de todas as variáveis. As curvas de características do operador receptor (ROC) e a área sob a curva (AUC) de dois modelos de risco foram utilizadas para avaliar o desempenho discriminatório. Um ecocardiograma foi realizado sete dias após o procedimento para avaliar a fração de ejeção do ventrículo esquerdo (FEVE). Um valor P bicaudal de <0,05 foi considerado estatisticamente significativo. RESULTADOS: Entre os 65 pacientes elegíveis com IAMCST, 48 foram alocados no grupo NOM e 17 no grupo OM, com uma incidência de OCM de 26,15%. Não houve diferença significativa na AUC entre os dois escores. A FEVE avaliada para o grupo NOM foi maior do que para o grupo OM. CONCLUSÃO: Os escores SAK e ATI tiveram bom desempenho para estimar o risco de OCM após ICP primário para pacientes com IAMCST.

FGF-23 correlates with endocrine and metabolism dysregulation, worse cardiac and renal function, inflammation level, stenosis degree, and independently predicts in-stent restenosis risk in coronary heart disease patients underwent drug-eluting-stent PCI.

BACKGROUND: The present study aimed to assess the correlation of fibroblast growth factor (FGF)-23 expression with clinical characteristics, then further explore its value in predicting 2-year in-stent restenosis (ISR) risk in coronary heart disease (CHD) patients underwent percutaneous coronary intervention (PCI) with drug-eluting stent (DES). METHODS: In this prospective, single-center, observational study, totally 214 CHD patients treated by PCI with DES were consecutively recruited, and peripheral blood samples were collected prior to PCI with DES for serum samples isolation. Following, FGF-23 level in the serum samples was detected via enzyme linked-immuno-sorbent Assay. The follow-up coronary angiography was performed at 1 year and 2 years after PCI or if suspected ISR symptoms occurred. RESULTS: FGF-23 was positively correlated with fasting blood-glucose, insulin resistance, serum creatinine, serum uric acid, LDL-C, high-sensitivity C-reactive protein, cardiac troponin I and N-terminal-proB-type natriuretic peptide, while was negatively associated with HDL-C and left ventricular ejection fraction (all P < 0.01). Furthermore, FGF-23 was positively correlated with hypercholesteremia, hyperuricemia and family history of CAD (all P < 0.05). However, it did not correlate with other chronic complications, biochemical indexes, lesion features or PCI parameters (all P > 0.05). Moreover, FGF-23 level was higher in 2-year ISR patients (n = 38) compared to 2-year non-ISR patients (n = 176) (P < 0.001), and receiver operating characteristic curve indicated that FGF-23 was of good value in predicting 2-year ISR risk (AUC 0.828, 95% CI 0.761-0.896). CONCLUSION: FGF-23 correlates with endocrine and metabolism dysregulation, worse cardiac and renal function, inflammation level, stenosis degree of target lesion, and serves as an independent risk factor for 2-year ISR risk in CHD patients underwent PCI with DES.

Three-year clinical outcome of unprotected left main coronary artery disease patients complicated with chronic kidney disease treated by coronary artery bypass graft versus percutaneous coronary intervention.

BACKGROUND: This study aimed to compare the incidence of major adverse cardiac and cerebrovascular events (MACCE) after coronary artery bypass graft (CABG) or after percutaneous coronary intervention (PCI) with drug-eluting stent (DES) in unprotected left main coronary artery disease (ULMCAD) patients complicated with chronic kidney disease (CKD). METHODS: Three hundred sixty-eight ULMCAD patients complicated with CKD who underwent first ever CABG (n = 207) or PCI with DES (n = 161) were recruited in this prospective cohort study. Patients were followed up to MACCE occurrence or 36 months after operations, and accumulating MACCE occurrence was calculated. RESULTS: Accumulating MACCE occurrence was decreased in CABG group compared with PCI group (P = 0.007). Subgroup analysis showed that CKD stage positively correlated with accumulating MACCE occurrence in total patients (P = 0.006) and in PCI-treated patients (P = 0.018), but not in CABG-treated patients (P = 0.217). Further univariate Cox's regression model displayed that CABG (versus (vs.) PCI) (P = 0.008) was associated with lower accumulating MACCE occurrence, while age (≥ 65 years) (P = 0.048), hyperlipidemia (P = 0.013), diabetes (P = 0.012), previous heart failure (P = 0.011), previous stroke (P = 0.030), LVEF < 50% (P = 0.048), higher CKD stage (P = 0.002), and more diseased vessels (P = 0.022) were associated with increased accumulating MACCE occurrence. Forward stepwise multivariate Cox's regression model disclosed that CABG (vs. PCI) (P = 0.002) independently predicted decreased accumulating MACCE occurrence, whereas hyperlipidemia (P = 0.033), diabetes (P = 0.002), higher CKD stage (P = 0.001), and more diseased vessels (P = 0.009) independently predicted elevated accumulating MACCE occurrence. CONCLUSION: CABG could be considered as the preferred treatment strategy compared with PCI with DES in ULMCAD patients complicated with CKD.

Comparison of long-term radial artery occlusion following trans-radial coronary intervention using 6-french versus 7-french sheaths.

BACKGROUND: The aim of this study was to explore the impact of 6-Fr and 7-Fr sheaths on the incidence of long-term radial artery occlusion (RAO) after trans-radial coronary intervention (TRI). METHODS: From September 2013 to January 2016, patients with ischemic heart disease including acute myocardial infarction and true bifurcation lesions were randomly assigned to 6-Fr group and 7-Fr group immediately after coronary angiography in a 1:1 ratio. The radial artery diameters were observed by ultrasound examination one day prior to TRI as well as at 30 days and 1 year after TRI. The primary endpoint was the incidence of RAO at 1-year after TRI. The secondary endpoints were the incidence of local vascular complications during hospitalization and changes of radial artery diameters within 1-year after TRI between the two groups. Additionally, multivariate logistic regression analysis was used to explore potential factors related to the incidence of long-term RAO after TRI. RESULTS: A total of 214 patients were enrolled and randomly assigned to 6-Fr group (n = 105) or 7-Fr group (n = 109). There was no significant difference in the incidence of RAO at 1-year after TRI (8.57% vs. 12.84%, p = 0.313). Moreover, no significant difference was observed in the incidence of local vascular complications during hospitalization (20% vs. 24.77%, p = 0.403). After 1-year follow-up, no significant difference was found in radial artery diameters (2.63 ± 0.31 mm vs. 2.64 ± 0.27 mm, p = 0.802). Multivariate logistic analysis revealed that repeated TRI was an independent risk factor of long-term RAO 1 year after TRI (OR = 10.316, 95% CI 2.928-36.351, p = 0.001). CONCLUSIONS: Compared to 6-Fr sheath, 7-Fr sheath did not increase short-term or long-term incidence of RAO after TRI.

Effects of sacubitril/valsartan on ventricular remodeling in patents with left ventricular systolic dysfunction following acute anterior wall myocardial infarction.

OBJECTIVE: The aim of this study was to investigate the effect of sacubitril/valsartan (Sal/Val) on left ventricular (LV) remodeling in patients with LV systolic dysfunction following acute anterior wall myocardial infarction (AAMI). METHODS: AAMI patients with LV systolic dysfunction were enrolled in this study. All patients underwent percutaneous coronary intervention. After hemodynamic stabilization, patients were randomly assigned either to group T (Sal/Val treatment) or group C (enalapril treatment). Changes in echocardiographic parameters and plasma biochemical markers were used to evaluate the effects of Sal/Val on LV remodeling and cardiac function. The incidence of major cardiac adverse events (MACEs) and adverse reactions during follow-ups was also recorded. RESULTS: In total, 137 eligible patients were prospectively included. Compared to group C, LV ejection fraction significantly improved (P < 0.05), while the LV end-systolic volume index and wall motion score index showed a tendency to decrease in group T. There was no difference in the LV end-diastolic volume index between groups. During follow-ups, the plasma N-terminal pro-B-type natriuretic peptide and soluble suppression of tumorigenesis-2 levels in both groups decreased (all P < 0.05), and the change was more prominent in group T. Additionally, drug-related adverse effects were similar between the two groups (P > 0.05); however, the incidence of MACEs was lower in group T than in group C (39.71% vs. 53.62%, P = 0.103), although the difference was insignificant. CONCLUSION: Sac/Val attenuated LV remodeling and dysfunction and was safe and effective in LV systolic dysfunction patients post AAMI.

Cardiac Chamber Segmentation Using Deep Learning on Magnetic Resonance Images from Patients Before and After Atrial Septal Occlusion Surgery.

We propose a robust technique for segmenting magnetic resonance images of post-atrial septal occlusion intervention in the cardiac chamber. The technique can be used to determine the surgical outcomes of atrial septal defects before and after implantation of a septal occluder, which intends to provide volume restoration of the right and left atria. A variant of the U-Net architecture is used to perform atrial segmentation via a deep convolutional neural network. The method was evaluated on a dataset containing 550 two-dimensional image slices, outperforming conventional active contouring regarding the Dice similarity coefficient, Jaccard index, and Hausdorff distance, and achieving segmentation in the presence of ghost artifacts that occlude the atrium outline. Moreover, the proposed technique is closer to manual segmentation than the snakes active contour model. After segmentation, we computed the volume ratio of right to left atria, obtaining a smaller ratio that indicates better restoration. Hence, the proposed technique allows to evaluate the surgical success of atrial septal occlusion and may support diagnosis regarding the accurate evaluation of atrial septal defects before and after occlusion procedures.

Long non-coding RNA LICPAR regulates atrial fibrosis via TGF-ß/Smad pathway in atrial fibrillation.

Long non-coding RNA predicting cardiac remodeling (lnc LIPCAR) was implicated in several human diseases, while its role in atrial fibrillation (AF) remained poorly understood. Our study aimed to discover the role of LICPAR played in AF. Samples of atrial muscle tissues from patients diagnosed with sinus rhythm (SR) and atrial fibrillation (AF) were collected, and human atrial fibroblasts were isolated and identified under immunofluorescence staining. After Angiotensin II (Ang II, as a activator of TGF-ß) stimulation with LICPAR overexpression or knockdown, the viability and proliferation of atrial fibroblasts were respectively determined using cell counting kit-8 (CCK-8) assay and clone formation assay. Relative expressions of LICPAR, fibrosis- and transforming growth factor-ß (TGF-ß)/Smad2/3-pathway related proteins were measured using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot as needed. LICPAR and TGF-ß1 were upregulated and were positively correlated in atrial muscle tissues from AF. Atrial fibroblasts were identified as Vimentin positive. Further analysis indicated that Ang II enhanced the levels of LIPCAR, Smad2/3 phosphorylation and α-smooth muscle actin (α-SMA). Also, upregulating LIPCAR further promoted the promotive effects of Ang II on levels of LIPCAR, Collagen I, Collagen II, α-SMA and Smad2/3 phosphorylation, cell viability and proliferation of atrial fibroblasts, whereas silencing LIPCAR resulted in opposite effects. LICPAR regulates atrial fibrosis via modulating TGF-ß/Smad pathway, which provided a potential therapeutic method for AF in clinical practice in the future.

Efficacy and safety of intracoronary prourokinase during percutaneous coronary intervention in treating ST-segment elevation myocardial infarction patients: a randomized, controlled study.

BACKGROUND: Prourokinase is a single-chain plasminogen activator presenting with fewer hemorrhagic complications and reduced reocclusion rate compared with the conventional fibrinolytic agents in patients with coronary artery disease. However, prourokinase intracoronary injection during PCI for treating patients with ST-segment elevation myocardial infarction (STEMI) is rarely investigated. Therefore, this study aimed to evaluate the efficacy and safety of intracoronary prourokinase during the percutaneous coronary intervention (PCI) in treating STEMI patients. METHODS: Fifty STEMI patients who underwent primary PCI were consecutively enrolled and randomly assigned to intracoronary prourokinase group (N = 25) or control group (N = 25). During the primary PCI procedure, patients in the intracoronary prourokinase group received 10 ml prourokinase injection, while patients in control group received 10 ml saline injection as control. The primary endpoints were coronary physiological indexes, the secondary endpoints were angiographic assessments, myocardial infarct size/reperfusion assessment, cardiac function evaluations, major adverse coronary events (MACEs) and hemorrhagic complications. All patients were followed up for 3 months. RESULTS: Post PCI, the index of microcirculatory resistance (IMR) was decreased in intracoronary prourokinase group than that in control group (34.56 ± 7.48 vs. 49.00 ± 8.98, P < 0.001), while no difference of coronary flow reserve (CFR) (2.01 ± 0.32 vs. 1.88 ± 0.23, P = 0.267) or fractional flow reserve (FFR) (0.89 ± 0.05 vs. 0.87 ± 0.04, P = 0.121) was found between the two groups. The thrombolysis in myocardial infarction myocardial perfusion grade (TMPG) (P = 0.024), peak values of creatine kinase (CK) (P = 0.028), CK isoenzyme-MB (CK-MB) (P = 0.016), cardiac troponin I (cTnI) (P = 0.032) and complete ST-segment resolution (STR) (P = 0.005) were better in intracoronary prourokinase group compared with control group. At 3-months post PCI, left ventricular ejection fraction (LVEF) and wall motion score index (WMSI) were higher, while left ventricular end-diastolic diameter (LVEDd) was lower in intracoronary prourokinase group compared with control group (all P < 0.05). There was no difference in hemorrhagic complication or total MACE between the two groups. CONCLUSION: Intracoronary prourokinase during PCI is more efficient and equally tolerant compared with PCI alone in treating STEMI patients. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR1800016207 . Prospectively registered.

General glycosylated hemoglobin goals potentially increase myocardial infarction severity in diabetes patients with comorbidities: Insights from a nationwide multicenter study.

AIMS/INTRODUCTION: We aimed to investigate the relationship between glycemic status and coronary artery disease (CAD) extent and severity in ST-elevation myocardial infarction (STEMI) patients, and further examine whether diabetes patients could benefit from glycosylated hemoglobin (HbA1c) below the recommended level. MATERIALS AND METHODS: Consecutive STEMI patients admitted in 2015-2017 across 244 hospitals were included in the China STEMI Care Project-2. We carried out a cross-sectional study comprising 8,370 participants with a record of HbA1c testing after admission. CAD extent and severity were assessed by admission heart rate, Killip classification and the number of stenosed vessels based on the coronary angiogram. RESULTS: Diabetes patients showed a greater risk for higher Killip class, admission tachycardia (admission heart rate ≥100 b.p.m.) and multivessel CAD (presence of left main and/or triple vessel disease). Likewise, HbA1c level was significantly associated with CAD extent and severity. While dividing diabetes patients according to general HbA1c targets (HbA1c ≤6.5, 6.5-7.0 and ≥7.0%), diabetes patients with HbA1c ≤6.5% showed a 1.30-fold higher risk for multivessel CAD (adjusted odds ratio 1.30, 95% confidence interval 1.05-1.62). In stratified analysis, the association was even stronger in patients with hypertension (adjusted odds ratio 1.41, 95% confidence interval 1.08-1.86) or hyperlipidemia (adjusted odds ratio 1.57, 95% confidence interval 1.17-2.12). CONCLUSIONS: HbA1c level is independently correlated with CAD extent and severity in STEMI patients. HbA1c below generally recommended levels might still increase the risk of CAD progression, especially for diabetes patients with hypertension or hyperlipidemia.

Occurrence and predictive factors of restenosis in coronary heart disease patients underwent sirolimus-eluting stent implantation.

BACKGROUND: This study aimed to investigate the occurrence and predictive factors of restenosis in coronary heart disease (CHD) patients underwent percutaneous coronary intervention (PCI) with sirolimus-eluting stent (SES). METHODS: Demographic data, clinical features, and laboratory tests of 398 CHD patients underwent PCI with SES were retrospectively reviewed. Coronary angiography was performed to evaluate coronary stenosis before PCI and in-stent restenosis at 1-year follow-up. RESULTS: There were 37 (9.3%) patients suffered restenosis, but 361 (90.7%) patients did not develop restenosis at 1-year follow-up. Demographic characteristic (age), cardiovascular risk factors (hypertension and hyperuricemia), biochemical indexes (fasting blood-glucose, total cholesterol, low density lipoprotein cholesterol (LDL-C) and high-sensitivity C-reactive protein (HsCRP)), cardiac function index (cardiac troponin I), lesion features (multivessel artery lesions, target lesion at left circumflex artery (LCX), two target lesions and length of target lesion), and operation procedure (length of stent) were correlated with higher restenosis risk. Moreover, age, hypertension, diabetes mellitus, LDL-C, HsCRP, and target lesion at LCX were independent predictive factors for raised restenosis risk. Based on these independent predictive factors, we established a restenosis risk prediction model, and receiver-operating characteristic curves displayed that this model exhibited an excellent predictive value for higher restenosis risk (areas under the curve 0.953 (95% CI 0.926-0.981)). CONCLUSION: Our findings provide a new insight into the prediction for restenosis in CHD patients underwent PCI with SES.

Prediction of fetal weight at varying gestational age in the absence of ultrasound examination using ensemble learning.

Obstetric ultrasound examination of physiological parameters has been mainly used to estimate the fetal weight during pregnancy and baby weight before labour to monitor fetal growth and reduce prenatal morbidity and mortality. However, the problem is that ultrasound estimation of fetal weight is subject to population's difference, strict operating requirements for sonographers, and poor access to ultrasound in low-resource areas. Inaccurate estimations may lead to negative perinatal outcomes. This study aims to predict fetal weight at varying gestational age in the absence of ultrasound examination within a certain accuracy. We consider that machine learning can provide an accurate estimation for obstetricians alongside traditional clinical practices, as well as an efficient and effective support tool for pregnant women for self-monitoring. We present a robust methodology using a data set comprising 4212 intrapartum recordings. The cubic spline function is used to fit the curves of several key characteristics that are extracted from ultrasound reports. A number of simple and powerful machine learning algorithms are trained, and their performance is evaluated with real test data. We also propose a novel evaluation performance index called the intersection-over-union (loU) for our study. The results are encouraging using an ensemble model consisting of Random Forest, XGBoost, and LightGBM algorithms. The experimental results show the loU between predicted range of fetal weight at any gestational age that is given by the ensemble model and ultrasound respectively. The machine learning based approach applied in our study is able to predict, with a high accuracy, fetal weight at varying gestational age in the absence of ultrasound examination.