Multicenter Study

To develop and externally validate a machine learning model for predicting the 1-year risk of relapse in patients with stable ABPA, and to further evaluate its value in risk stratification and clinical decision-making.

The objective of this study is to collect data in Flanders on the incidence of suicide attempts and suicidal ideation across various healthcare settings. The study also aims to assess the proportion of individuals who receive adequate aftercare following a suicide attempt and to systematically document the methods and means used in suicidal behavior.

Previous studies have reported the efficacy of Bacillus Calmette-Guérin (BCG) combined with other drugs for the treatment of bladder cancer. However, research on the combination of tislelizumab and BCG for bladder cancer treatment has largely been retrospective. Currently, ongoing clinical trials have not discussed the effectiveness of PD-1/PD-L1 inhibitors combined with BCG instillation in reducing postoperative recurrence in intermediate-risk NMIBC. Therefore, this study aims to explore the clinical efficacy and safety of tislelizumab combined with BCG in the treatment of intermediate and high-risk NMIBC. For this purpose, investigators have established strict screening criteria to include eligible patients in the study and have recruited suitable patients from multiple medical centers.Investigators have also developed a meticulous implementation process and follow-up considerations, hoping to better verify the clinical efficacy and safety of the combined use of these two drugs.

The incidence of Heart failure with preserved ejection fraction (HFpEF) in Heart failure patients increases rapidly. However, the current clinical awareness is insufficient, and the cardiac structural and functional injury are not well understood. It is difficult to recognize the subclinical changes of the cardiac in the early stage with conventional imaging techniques, and it is common to ignore the existence of the clinical alterations. This study aimed to investigate the cardiac features, early diagnosis and risk factors of HFpEF patients, based on the multi-modality (Magnetic resonance imaging- nuclear medicine imaging- echocardiography) imaging and multicenter study, combined with large data and artificial intelligence. This study will provide deep insights into the HFpEF in multicenter population.