OBJECTIVE:Comprehensive data and analyses on cardiovascular research could clarify recent research trends for the academic community and facilitate policy development. We examined publications and reference data to identify research topics, trends and interdisciplinarity for cardiovascular disease (CVD). METHODS:We extracted and clustered text fragments from the titles and abstracts of 2 512 445 publications using artificial intelligence techniques, including natural language processing (NLP) for semantic analysis. Cardiovascular experts identified topics and document clusters based on the output of those semiautomatic methods. We also applied machine learning algorithms to predict the trends over the next 5 years in each field. We examined the crossover between the two cluster groups using citation relationships in the documents. RESULTS:Research in clinical studies showed the most notable increase; that was followed by research in population and basic studies. The research hotspots were minimally invasive treatments for valve disease, circulatory haemodynamics, and prevention and control of hypertension. The fastest-growing topics were health monitoring, evidence-based medicine and immunotherapy. We found extensive crossover relationships among document clusters for the periods of 2017-2018 and 2020-2021. CONCLUSIONS:This study provides valuable insights into the research hotspots for cardiovascular research, including an increasing emphasis on early disease detection and prevention, exploration of minimally invasive treatments and assessment of risk factors. The research landscape demonstrates signs of interdisciplinarity and integration as reflected in citation relationships. These findings suggest practical implications for optimising resource allocation in healthcare systems, guiding clinical guideline updates and informing policy-making to prioritise high-impact research areas aligned with evolving CVD challenges. Given the evolving global burden of CVD, continuous research and innovation are imperative, with interdisciplinary collaboration assuming a pivotal role in advancing scientific knowledge.

Background:Percutaneous balloon mitral valvuloplasty (PBMV) is the preferred treatment for selected patients with rheumatic mitral stenosis (MS). Although prior research has established the feasibility and safety of echocardiography-guided PBMV, this study aimed to compare the mid- to long-term clinical outcomes and safety profiles between echocardiography-guided and conventional fluoroscopy-guided approaches. Methods:Consecutive patients who underwent successful PBMV from January 2016 to December 2022 were enrolled. Participants were stratified into two groups based on procedural guidance method: echocardiography-guided and conventional fluoroscopy-guided. The primary outcome of this study was the success of PBMV, and the secondary outcome was a composite of all-cause mortality, reoperation for mitral valve surgery, or repeat PBMV after discharge. Statistical analyses included the Kaplan-Meier survival analysis with log-rank tests and propensity score matching to adjust for confounding factors. Results:A total of 429 patients underwent PBMV, with 71 (16.6%) in the echo-guided group and 358 (83.4%) in the conventional fluoroscopy-guided group. A success rate of 98.6% was demonstrated in the echocardiography-guided group, and 98.9% in the fluoroscopy-guided group after propensity score match (p = 0.84). During follow-up, nine (14.3%) patients in the echo-guided group required surgical intervention, and 13 (10.4%) in the fluoroscopy-guided group; one (1.6%) patient in the echocardiography-guided group and six (4.8%) in the fluoroscopy-guided group died. No significant differences were observed in freedom from re-intervention (p = 0.33) and survival (p = 0.23). Conclusions:For selected patients with rheumatic MS, echocardiography-guided PBMV demonstrated an equivalent mid- to long-term efficacy and safety profile compared to fluoroscopy-guided approaches.

Background and objectives:Comprehensive data analyses in heart failure research can provide academics with information and help policymakers formulate relevant policies. We collected data from reports published between 1945 and 2021 to identify research topics, trends, and cross-domains in the heart failure disease literature. Methods:Text fragments were extracted and clustered from the titles and abstracts in 270617 publications using artificial intelligence techniques. Two algorithms were used to corroborate the results and ensure that they were reliable. Experts named themes and document clusters based on the results of these semiautomated methods. Using consistent methods, we identified and flagged 107 heart failure topics and 16 large document clusters (divided into two groups by time). The annual vocabularies of research hotspots were calculated to draw attention to niche research fields. Results:Clinical research is an expanding field, followed by basic research and population research. The most frequently raised issues were intensive care treatment for heart failure, applications of artificial intelligence technologies, cardiac assist devices, stem cells, genetics, and regional distribution and use of heart failure-related health care. Risk scoring and classification, care for patients, readmission, health economics of treatment and care, and cell regeneration and signaling pathways were among the fastest-growing themes. Drugs, signaling pathways, and biomarkers were all crucial issues for clinical and basic research in the entire population. Studies on intelligent medicine and telemedicine, interventional therapy for valvular disease, and novel coronavirus have emerged recently. Conclusion:Clinical and population research is increasingly focusing on the customization of intelligent treatments, improving the quality of patients' life, and developing novel treatments. Basic research is increasingly focusing on regenerative medicine, translational medicine, and signaling pathways. Additionally, each research field exhibits mutual fusion characteristics. Medical demands, new technologies, and social support are all potential drivers for these changes.

Objective:Echocardiography (ECG) is the most common method used to diagnose heart failure (HF). However, its accuracy relies on the experience of the operator. Additionally, the video format of the data makes it challenging for patients to bring them to referrals and reexaminations. Therefore, this study used a deep learning approach to assist physicians in assessing cardiac function to promote the standardization of echocardiographic findings and compatibility of dynamic and static ultrasound data. Methods:A deep spatio-temporal convolutional model r2plus1d-Pan (trained on dynamic data and applied to static data) was improved and trained using the idea of "regression training combined with classification application," which can be generalized to dynamic ECG and static cardiac ultrasound views to identify HF with a reduced ejection fraction (EF < 40%). Additionally, three independent datasets containing 8976 cardiac ultrasound views and 10085 cardiac ultrasound videos were established. Subsequently, a multinational, multi-center dataset of EF was labeled. Furthermore, model training and independent validation were performed. Finally, 15 registered ultrasonographers and cardiologists with different working years in three regional hospitals specialized in cardiovascular disease were recruited to compare the results. Results:The proposed deep spatio-temporal convolutional model achieved an area under the receiveroperating characteristic curve (AUC) value of 0.95 (95% confidence interval [CI]: 0.947 to 0.953) on the training set of dynamic ultrasound data and an AUC of 1 (95% CI, 1 to 1) on the independent validation set. Subsequently, the model was applied to the static cardiac ultrasound view (validation set) with simultaneous input of 1, 2, 4, and 8 images of the same heart, with classification accuracies of 85%, 81%, 93%, and 92%, respectively. On the static data, the classification accuracy of the artificial intelligence (AI) model was comparable with the best performance of ultrasonographers and cardiologists with more than 3 working years (P = 0.344), but significantly better than the median level (P = 0.0000008). Conclusion:A new deep spatio-temporal convolution model was constructed to identify patients with HF with reduced EF accurately (< 40%) using dynamic and static cardiac ultrasound images. The model outperformed the diagnostic performance of most senior specialists. This may be the first HF-related AI diagnostic model compatible with multi-dimensional cardiac ultrasound data, and may thereby contribute to the improvement of HF diagnosis. Additionally, the model enables patients to carry "on-the-go" static ultrasound reports for referral and reexamination, thus saving healthcare resources.

Background: Non-rheumatic heart valve disease (NRVD) is a common cardiovascular disease, whereas calcific aortic valve disease (CAVD) is a type of disease with the fastest-growing mortality and disability adjusted life years (DALYs). This study presents an overview of the trends noted in the DALY, CAVD mortality, and the modifiable risk factors in the last 30 years, across 204 countries and territories, and their relationship with the period, age, and birth cohort. Methods: Data were obtained from the Global Burden of Disease (GBD) 2019 database. An age-period cohort (APC) model was used to assess general annual percentage changes in DALYs and mortality over the past 30 years in 204 countries and territories. Results: In 2019, the age-standardized mortality rate for the entire population in areas with a high sociodemographic index (SDI) was more than 4 times higher than that in low-SDI areas. From 1990 to 2019, the net drift in mortality for the whole population was from -2.1% [95% confidence interval (CI): -2.39% to -1.82%] per year in high-SDI regions to 0.05% (95% CI: -0.13% to 0.23%) per year in low-to medium SDI regions. The trend of DALYs was similar to that of mortality. The age-wise distribution of deaths exhibited a shift toward older populations in high-SDI regions globally, except for Qatar, Saudi Arabia, and the United Arab Emirates. Over time, in most medium, medium-low, and low SDI regions, there was no significant improvement in the period and birth cohort or even an unfavorable or worsening risk. The main variable risk factors of CAVD death and DALYs lost were high sodium diet, high systolic blood pressure, and lead exposure. Those risk factors only showed a significant downward trend in middle-and high-SDI regions. Conclusion: Health disparities between regions for CAVD are widening and could lead to a heavy disease burden in the future. Health authorities and policymakers in low SDI areas, in particular, need to consider improving resource allocation, increasing access to medical resources, and controlling variable risk factors to stem the growth of the disease burden.

The treatment of myocardial infarction (MI) remains a substantial challenge due to excessive inflammation, massive cell death, and restricted regenerative potential, leading to maladaptive healing process and eventually heart failure. Current strategies of regulating inflammation or improving cardiac tissue regeneration have limited success. Herein, a hybrid hydrogel coassembled by acellular cardiac extracellular matrix (ECM) and immunomodulatory glycopeptide is developed for endogenous tissue regeneration after MI. The hydrogel constructs a niche recapitulating the architecture of native ECM for attracting host cell homing, controlling macrophage differentiation via glycopeptide unit, and promoting endotheliocyte proliferation by enhancing the macrophage-endotheliocyte crosstalk, which coordinate the innate healing mechanism for cardiac tissue regeneration. In a rodent MI model, the hybrid hydrogel successfully orchestrates a proreparative response indicated by enhanced M2 macrophage polarization, increased angiogenesis, and improved cardiomyocyte survival, which alleviates infarct size, improves wall thicknesses, and enhances cardiac contractility. Furthermore, the safety and effectiveness of the hydrogel are demonstrated in a porcine MI model, wherein proteomics verifies the regulation of immune response, proangiogenesis, and accelerated healing process. Collectively, the injectable composite hydrogel serving as an immunomodulatory niche for promoting cell homing and proliferation, inflammation modulation, tissue remodeling, and function restoration provides an effective strategy for endogenous cardiac repair.

目的:评价单纯经胸超声心动图(TTE)引导经皮介入治疗复杂房间隔缺损的临床疗效.方法:选取中国医学科学院阜外医院 2019 年 1 月至 2019 年 12 月在单纯TTE引导下接受经皮介入封堵复杂房间隔缺损的 47 例患者(男性 9 例、女性 38 例)的临床资料.所有患者术前均经超声心动图明确诊断,术中在TTE引导下经股静脉完成治疗.收集患者术前、术后 6 个月和 12 个月的超声心动图和心电图数据.结果:所有患者均使用1个封堵器完成介入封堵,平均手术时间为(55.2±21.0)min,平均住院时间为(5.0±1.7)d,封堵器的平均直径为(22.0±6.6)mm.出院前1例(2.1%)患者房水平分流7 mm(使用8 mm带孔封堵器),中量、少量、微量残余分流患者分别有 4 例(8.5%)、2 例(4.3%)、1 例(2.1%).术后新发不完全性右束支阻滞 1 例(2.1%),经药物治疗后好转.与术前相比,术后6个月和12个月时患者的右心房内径、右心室舒张末期内径均明显减小(P均＜0.05).术后 1 年时,出院前的 3 例少量和微量残余分流均消失,4 例中量残余分流变为少量残余分流,1 例患者房水平分流由出院前的 7 mm减少为 5 mm;1 年完全封堵率为 89.4%(42/47).结论:单纯TTE引导经皮介入封堵复杂房间隔缺损的效果良好,该方法不仅避免了放射线损伤,而且保持了传统经皮介入治疗安全、微创的优点.

Background: Transcatheter edge-to-edge repair (TEER) of the mitral valve has emerged as an alternative treatment for mitral regurgita-tion (MR). However, the high radiation exposure during the process has been associated with multiple adverse effects for medical staff. In this study, we assessed the feasibility and safety of TEER performed solely under the echocardiographic (echo) guidance. Methods: Between April 2021 to August 2021, we retrospectively collected characteristics of 23 patients with MR who underwent TEER under echocardiographic guidance exclusively. Follow-up evaluations were performed at 1-, 3-months and 1-year post procedure. Results: All 23 patients (mean age, 66.1 +/- 12.1 years; 65.2% males) successfully underwent echo-guided TEER, with 22 patients under trans -esophageal echo (TEE) guidance and 1 patient under transthoracic echo (TTE) guidance for severe esophageal stenosis. Of the patients, 60.9% received 1 implant and 39.1% received 2 implants. The median total procedural time was 130 (interquartile range, IQR: 90-150) min and the device procedure time was 73 (IQR: 58-100) min. The median length of stay was 6 (IQR: 5-9) days. At 3-months follow-up, 63.6% of patients had an MR <1+ and 90.9% had an MR <2+ (p < 0.001 vs. baseline). Improvement in functional status was observed, with 40.9% of patients classified as New York Heart Association (NYHA) functional class I and 45.5% as NYHA functional class II (p < 0.001 compared to baseline) at 3-months. At 1-year follow-up, 90.4% maintained MR reduction with MR <2+ (p < 0.001 vs. base-line). Single leaflet device attachment (SLDA) occurred in one patient (4.3%) 1-week post procedure. Conclusions: This retrospective, single-center, and pilot study demonstrates the feasibility, safety, and low complication rates of TEER guided solely by echocardiogra-phy. Our findings support the systematic use of echocardiography as the sole guidance modality for TEER, highlighting its potential as an alternative to fluoroscopy-guided procedures. Further multicenter and comparative studies are warranted to confirm these results and provide a more comprehensive evaluation of this approach.

Background: The increase in the use of ultrasound-guided interventional therapy for cardiovascular diseases has increased the importance of intraoperative real-time cardiac ultrasound image interpretation. We thus aimed to develop a deep learning-based model to accurately identify, localize, and track the critical cardiac structures and lesions (9 kinds in total) and to validate the algorithm's performance using independent data sets.Methods: This diagnostic study developed a deep learning-based model using data collected from Fuwai Hospital between January 2018 and June 2019. The model was validated with independent French and American data sets. In total, 17,114 cardiac structures and lesions were used to develop the algorithm. The model findings were compared with those of 15 specialized physicians in multiple centers. For external validation, 516,805 tags and 27,938 tags were used from 2 different data sets.Results: Regarding structure identification, the area under the receiver operating characteristic curve (AUC) of each structure in the training data set, optimal performance in the test data set, and median AUC of each structure identification were 1 (95% CI: 1-1), 1 (95% CI: 1-1), and 1 (95% CI: 1-1), respectively. Regarding structure localization, the optimal average accuracy was 0.83. As for structure identification, the accuracy of the model significantly outperformed the median performance of the experts (P<0.01). The optimal identification accuracies of the model in 2 independent external data sets were 89.5% and 90%, respectively (P=0.626).Conclusions: The model outperformed most human experts and was comparable to the optimal performance of all human experts in cardiac structure identification and localization, and could be used in the external data sets.

Studies relating to the right ventricle (RV) are inadequate, and specific diagnostic algorithms still need to be improved. This essay is designed to make exploration and verification on an algorithm of deep learning based on imaging and clinical data to detect RV abnormalities. The Automated Cardiac Diagnosis Challenge dataset includes 20 subjects with RV abnormalities (an RV cavity volume which is higher than 110 mL/m2 or RV ejection fraction which is lower than 40

目的:探究甲磺酸倍他司丁辅助治疗前庭性偏头痛的效果及对脑血流速度、血清神经递质水平及眩晕症状的影响.方法:选取我科2020年9月—2022年9月收治的87例前庭性偏头痛患者作为研究对象,采用随机数字表法分为对照组(43例)和观察组(44例).对照组给予口服盐酸氟桂利嗪胶囊治疗,观察组在对照组基础上联合甲磺酸倍他司丁治疗,比较两组临床疗效、眩晕情况、血清神经递质水平[降钙素基因相关肽(CGRP)、内皮素-1(ET-1)及P物质(SP)]、脑血流速度[基底动脉(BA)、大脑中动脉(MCA)、大脑后动脉(PCA)、大脑前动脉(ACA)]及不良反应.结果:观察组CGRP、SP、ET-1 水平低于对照组(P<0.05);观察组MCA、ACA、PCA及BA指数低于对照组(P<0.05);观察组眩晕累计发作时间、眩晕累计发作次数及眩晕发作强度均低于对照组(P<0.05);观察组治疗总有效率为 90.91%,高于对照组的 72.09%(P<0.05);观察组不良反应发生率与对照组比较,差异无统计学意义(P>0.05).结论:加用甲磺酸倍他司丁辅助治疗VM患者的疗效确切,可明显降低患者血清神经递质水平,改善脑血流循环,调节脑血流速度,改善眩晕症状,且不良反应少.

Background: As the global burden of hypertension continues to increase, early diagnosis and treatment play an increasingly important role in improving the prognosis of patients. In this study, we developed and evaluated a method for predicting abnormally high blood pressure (HBP) from infrared (upper body) remote thermograms using a deep learning (DL) model.Methods: The data used in this cross-sectional study were drawn from a coronavirus disease 2019 (COVID-19) pilot cohort study comprising data from 252 volunteers recruited from 22 July to 4 September 2020. Original video files were cropped at 5 frame intervals to 3,800 frames per slice. Blood pressure (BP) information was measured using a Welch Allyn 71WT monitor prior to infrared imaging, and an abnormal increase in BP was defined as a systolic blood pressure (SBP) >_140 mmHg and/or diastolic blood pressure (DBP) >_90 mmHg. The PanycNet DL model was developed using a deep neural network to predict abnormal BP based on infrared thermograms.Results: A total of 252 participants were included, of which 62.70% were male and 37.30% were female. The rate of abnormally high HBP was 29.20% of the total number. In the validation group (upper body), precision, recall, and area under the receiver operating characteristic curve (AUC) values were 0.930, 0.930, and 0.983 [95% confidence interval (CI): 0.904-1.000], respectively, and the head showed the strongest predictive ability with an AUC of 0.868 (95% CI: 0.603-0.994).Conclusions: This is the first technique that can perform screening for hypertension without contact using existing equipment and data. It is anticipated that this technique will be suitable for mass screening of the population for abnormal BP in public places and home BP monitoring.

目的 比较经颈静脉与经股静脉两种途径在门诊行房间隔缺损(ASD)封堵术的临床治疗效果及特点.方法 回顾性分析中国医学科学院阜外医院门诊2021年3—12月收治的行单纯超声引导经皮ASD封堵术的56例患者的临床资料.根据血管途径不同,将患者分入经股静脉途径组(n=31)与经颈静脉途径组(n=25).比较两组患者的手术成功率、封堵器大小、手术操作时间、在院时间、住院费用等指标,观察围术期和随访期间的并发症发生情况.结果 两组患者在经胸超声引导下完成手术,手术成功率均为100％,术中未出现外周血管损伤、心包积液、封堵器脱落等严重并发症.经股静脉途径组和经颈静脉途径组封堵器大小和手术操作时间比较,差异均无统计学意义(P>0.05).经颈静脉途径组在院时间短于经股静脉途径组,住院费用少于经股静脉途径组,差异均有统计学意义(P<0.05).经股静脉途径组中的1例患者因术后5 h下床后伤口渗血而于术后第1天出院,其余患者均于手术当天出院.两组患者均接受6(3,6)个月随访,随访期间无残余分流、外周血管损伤、心脏穿孔、封堵器脱落等严重并发症.结论 门诊开展单纯超声引导经颈静脉或经股静脉途径ASD封堵术安全有效,建议在技术成熟的心脏中心首选经颈静脉途径.

目的:分析鼓室内小剂量注射庆大霉素对梅尼埃病患者的疗效、听阈值及平衡功能的影响.方法:102例单侧梅尼埃患者,随机分为两组,对照组给予甲磺酸倍他司汀片治疗;观察组在对照组的基础上,鼓室内再注射小剂量庆大霉素治疗.治疗4周后,比较两组的治疗效果及相关指标.结果:观察组总有效率98.4％,高于对照组77.1％,差异有统计学意义(P<0.05).治疗后,观察组平衡功能评分高于对照组,听阈值高于对照组(P<0.05).结论:鼓室内注入小剂量庆大霉素治疗梅尼埃患者,可提高治疗的总有效率和平衡功能,但患者听力有些损失.