Background: The credible materials about the burden of asthma in China when compared to other countries in the group of twenty (G20) remain unavailable. Objectives and design: Following the popular analysis strategy used in the Global Burden of Disease Study, the age-, sex-, country-specific prevalence, and disability-adjusted life years (DALYs) of asthma in China were analyzed. Meanwhile, the comparison in trends between China and other countries in the G20 was also evaluated. Results: In 2019, asthma was the 8th leading cause of the DALYs’ burden of 369 diseases in China. From 1990 to 2019, the age-standardized prevalence and DALY rates of asthma in China decreased by 14% and 51%, respectively; further, the decline rate of DALYs was much higher than the global average (−51%: −43%). It is worth noting that the overall population age-standardized DALYs rate of asthma in China was the lowest in the G20 during 2019 (102.81, 95%UI: (72.30,147.42)/100,000). Moreover, the age-standardized asthma prevalence rate peaks in both childhood (178.14, 95%UI: (90.50, 329.01)/100,000) and the elderly (541.80, 95%UI: (397.79, 679.92)/100,000). Moreover, throughout the study, subjects in the 5 to 9 years old interval were a constant focus of our attention. Conclusions: The disease burden of asthma has varied greatly by gender and age over the past 30 years. In contrast to the increasing burden in most other G20 countries, the age-standardized prevalence rate of asthma shows a significant decreasing trend in China, however, the age-standardized DALYs rate shows a fluctuating change, and has even shown a rebound trend in recent years.

Purpose: The development of biomarkers and models can screen inpatients with a low probability of cure in the early stages of admission to help doctors adjust the management of community-acquired pneumonia (CAP) patients.Methods: We conducted a 30-day cohort study of newly admitted adult CAP patients over 20 years of age. Prognosis models to predict the short-term prognosis were developed using random survival forest (RSF) method.Results: A total of 247 adult CAP patients were studied and 208 (84.21%) of them reached clinical stability within 30 days. The soluble form of suppression of tumorigenicity-2 (sST2) was an independent predictor of clinical stability and the addition of sST2 to the prognosis model could improve the performance of the prognosis model. The C-index of the RSF model to predict clinical stability was 0.8342 (95%CI, 0.8086-0.8598), which is higher than 0.7181 (95%CI, 0.6933-0.7429) of CURB 65 score, 0.8025 (95%CI, 0.7776-8274) of PSI score and 0.8214(95% CI, 0.8080-0.8348) of cox regression. In addition, the RSF model was associated with adverse clinical events during hospitalization, ICU admissions and short-term mortality.Conclusion: The RSF model by incorporating sST2 was more accurate than traditional methods in assessing the short-term prognosis of CAP patients.

(1) Background: Biomarker and model development can help physicians adjust the management of patients with community-acquired pneumonia (CAP) by screening for inpatients with a low probability of cure early in their admission; (2) Methods: We conducted a 30-day cohort study of newly admitted adult CAP patients over 20 years of age. Prognosis models to predict the short-term prognosis were developed using random survival forest (RSF) method; (3) Results: A total of 247 adult CAP patients were studied and 208 (84.21%) of them reached clinical stability within 30 days. The soluble form of suppression of tumorigenicity-2 (sST2) was an independent predictor of clinical stability and the addition of sST2 to the prognosis model could improve the performance of the prognosis model. The C-index of the RSF model for predicting clinical stability was 0.8342 (95% CI, 0.8086–0.8598), which is higher than 0.7181 (95% CI, 0.6933–0.7429) of CURB 65 score, 0.8025 (95% CI, 0.7776–8274) of PSI score, and 0.8214 (95% CI, 0.8080–0.8348) of cox regression. In addition, the RSF model was associated with adverse clinical events during hospitalization, ICU admissions, and short-term mortality; (4) Conclusions: The RSF model by incorporating sST2 was more accurate than traditional methods in assessing the short-term prognosis of CAP patients.