UNSTRUCTURED Hematological medicine is a practical discipline that difficult to study. The cultivation for postgraduate majored in hematology is rather hard. Problem-based learning (PBL) is a student-centered innovating teaching method that students define their own learning objectives from clinically based problem. It has been widely accepted in student-centered medical education. Owing to the geographic and time dispersion of the students, traditional PBL has its own limitations. WeChat, the most popular platform among university students in China, was introduced in hematology teaching. In this study, we combine traditional PBL and WeChat together to explore a new WeChat Problem-Based learning mode for postgraduate majored in hematology. 100 questionnaires were distributed to evaluate how the students and tutors think about the WeChat-PBL teaching mode. The data showed that the WeChat-PBL teaching mode was popular and widely accepted. Our new PBL mode is time saving, convenience and easy to conduct. It emphasizes interoperable, interactive, effective and more participatory. We firmly believe that using this new WeChat-PBL teaching model will certainly help students be more excellent.

Multiple myeloma (MM) is a hematological malignancy of plasma cell origin. Cardiac amyloidosis (CA) is a common form of heart damage caused by MM and is associated with a poor prognosis. This study was a prospective cohort study and was aimed at evaluating the clinical predictive value of extracellular volume fraction (ECV) based on cardiovascular magnetic resonance (CMR) T1 mapping for cardiac amyloidosis and cardiac dysfunction in MM patients. Fifty-one newly diagnosed MM patients in Zhongnan Hospital of Wuhan University were enrolled in the study. A total of 19 patients (19/51; 37.25%) developed CA. The basal ECV of CA group was significantly higher than that of the non-CA group ( p < 0.01 ). Multivariate logistic regression analysis showed that basal ECV ( OR = 1.551 , 95% CI 1.084-2.219, p < 0.05 ) and LDH1 level ( OR = 1.150 , 95% CI 1.010-1.310, p < 0.05 ) were two independent risk factors for CA. Further study demonstrated that basal ECV in the heart failure group was significantly higher than that of the nonheart failure group ( p < 0.01 ). Notably, ROC curve showed that basal ECV had a good predictive value for CA and heart failure, with AUC of 0.911 and 0.893 (all p < 0.01 ), and the best cutoff values of 38.35 and 37.45, respectively. Taken together, basal ECV is a good predictor of CA and heart failure for MM patients.