The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

Objective To develop an innovative recognition algorithm that aids physicians in the identification of pulmonary nodules. Methods Patients with pulmonary nodules who underwent thoracoscopic surgery at the Department of Thoracic Surgery, Affiliated Drum Tower Hospital of Nanjing University Medical School in December 2023, were enrolled in the study. Chest surface exploration data were collected at a rate of 60 frames per second and a resolution of 1 920×1 080. Frame images were saved at regular intervals for subsequent block processing. An algorithm database for lung nodule recognition was developed using the collected data. Results A total of 16 patients were enrolled, including 9 males and 7 females, with an average age of (54.9±14.9) years. In the optimized multi-topology convolutional network model, the test results demonstrated an accuracy rate of 94.39% for recognition tasks. Furthermore, the integration of micro-variation amplification technology into the convolutional network model enhanced the accuracy of lung nodule identification to 96.90%. A comprehensive evaluation of the performance of these two models yielded an overall recognition accuracy of 95.59%. Based on these findings, we conclude that the proposed network model is well-suited for the task of lung nodule recognition, with the convolutional network incorporating micro-variation amplification technology exhibiting superior accuracy. Conclusion Compared to traditional methods, our proposed technique significantly enhances the accuracy of lung nodule identification and localization, aiding surgeons in locating lung nodules during thoracoscopic surgery.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

Objective To observe the effect of Huoxin pill （concentrated pill） combined with Baduanjin on the prognosis of patients with acute myocardial infarction complicated by percutaneous coronary intervention （PCI）. Methods 120 patients with acute myocardial infarction complicated with heart failure who received emergency interventional treatment in our hospital from January 2022 to January 2023 were randomly divided into western medicine treatment group and Traditional Chinese Medicine （TCM）comprehensive treatment group. Western medicine treatment: standard western medicine treatment + five prescriptions for cardiac rehabilitation; based on western medicine treatment, Huoxin pill （concentrated pill） combined with Baduanjin therapy was added to the TCM comprehensive treatment group, and the follow-up was 6 months. The observed indexes were exertion angina pectoris scale, Chinese Medicine Syndrome Scale, Chinese medicine syndrome treatment effect evaluation, 6-minute walking test （6MWT）, left ventricular ejection fraction （LVEF）, and brain natriuretic peptide precursor （pro-BNP）. Results Sixty patients were enrolled in the two groups respectively. During the treatment, 2 cases fell off in the western medicine treatment group and 8 cases fell off in the TCM comprehensive treatment group, and a total of 110 cases were enrolled in the group. Compared with the western treatment group, TCM combined therapy significantly improved angina pectoris scale score, TCM Syndrome Scale score, pro-BNP, LVEF and 6MWT （P<0.001）. There were no significant differences in blood routine, liver and kidney function, potassium, blood glucose, blood lipids and cardiac Troponin I （cTnI） between the two groups （P>0.05）. No adverse cardiovascular events occurred during the entire treatment period in both groups. Conclusion Huoxin pill （concentrated pill） combined with Baduanjin was more effective than western therapy in improving LVEF, 6MWT distance, exercise tolerance and cardiac function in patients with acute myocardial infarction complicated with heart failure.

The International Severe Asthma Registry (ISAR) was established in 2017 to advance the understanding of severe asthma and its management, thereby improving patient care worldwide. As the first global registry for adults with severe asthma, ISAR enabled individual registries to standardize and pool their data, creating a comprehensive, harmonized dataset with sufficient statistical power to address key research questions and knowledge gaps. Today, ISAR is the largest repository of real-world data on severe asthma, curating data on nearly 35,000 patients from 28 countries worldwide, and has become a leading contributor to severe asthma research. Research using ISAR data has provided valuable insights on the characteristics of severe asthma, its burdens and risk factors, real-world treatment effectiveness, and barriers to specialist care, which are collectively informing improved asthma management. Besides changing clinical thinking via research, ISAR aims to advance real-world practice through initiatives that improve registry data quality and severe asthma care. In 2024, ISAR refined essential research variables to enhance data quality and launched a web-based data acquisition and reporting system (QISAR), which integrates data collection with clinical consultations and enables longitudinal data tracking at patient, center, and population levels. Quality improvement priorities include collecting standardized data during consultations and tracking and optimizing patient journeys via QISAR and integrating primary/secondary care pathways to expedite specialist severe asthma management and facilitate clinical trial recruitment. ISAR envisions a future in which timely specialist referral and initiation of biologic therapy can obviate long-term systemic corticosteroid use and enable more patients to achieve remission.

Background::While type 2 diabetes mellitus (T2DM) is considered a putative causal risk factor for coronary artery disease (CAD), the intrinsic link underlying T2DM and CAD is not fully understood. We aimed to highlight the importance of integrated care targeting both diseases by investigating the phenotypic and genetic relationships between T2DM and CAD.Methods::We evaluated phenotypic associations using data from the United Kingdom Biobank ( N = 472,050). We investigated genetic relationships by leveraging genomic data conducted in European ancestry for T2DM, with and without adjustment for body mass index (BMI) (T2DM: Ncase/ Ncontrol = 74,124/824,006; T2DM adjusted for BMI [T2DM adjBMI]: Ncase/ Ncontrol = 50,409/523,897) and for CAD ( Ncase/ Ncontrol = 181,522/984,168). We performed additional analyses using genomic data conducted in multiancestry individuals for T2DM ( Ncase/ Ncontrol = 180,834/1,159,055). Results::Observational analysis suggested a bidirectional relationship between T2DM and CAD (T2DM→CAD: hazard ratio [HR] = 2.12, 95% confidence interval [CI]: 2.01–2.24; CAD→T2DM: HR = 1.72, 95% CI: 1.63–1.81). A positive overall genetic correlation between T2DM and CAD was observed ( rg = 0.39, P = 1.43 × 10 -75), which was largely independent of BMI (T2DM adjBMI–CAD: rg = 0.31, P = 1.20 × 10 –36). This was corroborated by six local signals, among which 9p21.3 showed the strongest genetic correlation. Cross-trait meta-analysis replicated 101 previously reported loci and discovered six novel pleiotropic loci. Mendelian randomization analysis supported a bidirectional causal relationship (T2DM→CAD: odds ratio [OR] = 1.13, 95% CI: 1.11-1.16; CAD→T2DM: OR = 1.12, 95% CI: 1.07-1.18), which was confirmed in multiancestry individuals (T2DM→CAD: OR = 1.13, 95% CI: 1.10-1.16; CAD→T2DM: OR = 1.08, 95% CI: 1.04-1.13). This bidirectional relationship was significantly mediated by systolic blood pressure and intake of 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors, with mediation proportions of 54.1% (95% CI: 24.9-83.4%) and 90.4% (95% CI: 29.3-151.5%), respectively. Conclusion::Our observational and genetic analyses demonstrated an intrinsic bidirectional relationship between T2DM and CAD and clarified the biological mechanisms underlying this relationship.

Background::Whether the dynamic weight change is an independent risk factor for mortality remains controversial. This study aimed to examine the association between weight change and risk of all-cause and cause-specific mortality based on the Linxian Nutrition Intervention Trial (NIT) cohort.Methods::Body weight of 21,028 healthy residents of Linxian, Henan province, aged 40-69 years was measured two times from 1986 to 1991. Outcome events were prospectively collected up to 2016. Weight maintenance group (weight change <2 kg) or stable normal weight group was treated as the reference. Cox proportional hazard model was performed to calculate hazard ratios (HRs) and 95% confidence intervals (95% CIs) to estimate the risk of mortality.Results::A total of 21,028 subjects were included in the final analysis. Compared with the weight maintenance group, subjects with weight loss ≥2 kg had an increased risk of death from all-cause (HR All-cause = 1.14, 95% CI: 1.09-1.19, P <0.001), cancer (HR Cancer = 1.12, 95% CI: 1.03-1.21, P = 0.009), and heart disease (HR Heart diseases = 1.21, 95% CI: 1.11-1.31, P <0.001), whereas subjects with weight gain ≥5 kg had 11% (HR Cancer = 0.89, 95% CI: 0.79-0.99, P = 0.033) lower risk of cancer mortality and 23% higher risk of stroke mortality (HR Stroke = 1.23,95% CI: 1.12-1.34, P <0.001). For the change of weight status, both going from overweight to normal weight and becoming underweight within 5 years could increase the risk of total death (HR Overweight to normal = 1.18, 95% CI: 1.09-1.27; HR Becoming underweight = 1.35, 95% CI: 1.25-1.46) and cancer death (HR Overweight to normal = 1.20, 95% CI: 1.04-1.39; HR Becoming underweight = 1.44, 95% CI: 1.24-1.67), while stable overweight could increase the risk of total death (HR Stable overweight = 1.11, 95% CI: 1.05-1.17) and death from stroke (HR Stable overweight = 1.44, 95% CI: 1.33-1.56). Interaction effects were observed between age and weight change on cancer mortality, as well as between baseline BMI and weight change on all-cause, heart disease, and stroke mortality (all Pinteraction <0.01). Conclusions::Weight loss was associated with an increased risk of all-cause, cancer, and heart disease mortality, whereas excessive weight gain and stable overweight were associated with a higher risk of stroke mortality. Efforts of weight management should be taken to improve health status.Trial registration::https://classic.clinicaltrials.gov/, NCT00342654.

Objective: The purpose of this study is to describe utilization, demographics, complications, and revisions for patients with degenerative spondylolisthesis (DS) with stenosis undergoing decompression or decompression with fusion in the United States. Methods: A national insurance database was used to identify patients who underwent either decompression and fusion or decompression alone for management of DS from 2010–2022. Utilization trends, demographics, and complications for each procedure were compared. Results: A total of 162,878 patients were identified, of which 78,043 patients underwent combined single-level lumbar decompression and fusion and 84,835 underwent single-level lumbar decompression alone. Between 2010–2021, lumbar decompression and fusion became the predominant surgical intervention for DS in 2016 and continued to account for more than half of all procedures during the remainder of the study period. Factors such as age, sex, comorbidities, geographic region, and physician specialty training were associated with procedure choice. Decompression with fusion was associated with a lower risk of revision surgery up to 5 years postoperatively and an overall lower incidence of 30-day complications. Conclusion Decompression with fusion has become the most common treatment for lumbar DS over the past decade despite a lack of compelling evidence supporting its use compared to decompression alone. A variety of patient and surgeon-specific factors is associated with procedure choice. After accounting for cofounders, we identified treatment-specific complications that may be valuable when counseling patients.