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Abstract BackgroundUnderstanding the impact of asthma on public health is crucial for evidence-based prevention and treatment strategies. ObjectiveThis study aimed to identify the causes of asthma-related mortality in Pudong, Shanghai, China, offering insights for managing similar regions or countries in transition. MethodsMortality statistics were obtained from the Vital Statistics System of Pudong for 2005‐2021. Temporal patterns for the burden of asthma were examined. The crude mortality rate (CMR), age-standardized mortality rate by Segi’s world standard population (ASMRW), and years of life lost (YLL) for both all-cause and asthma-specific deaths were computed. Mortality rates associating with aging and other variables were categorized using the decomposition technique. The autoregressive integrated moving average model was used to forecast the asthma-related death mortality rate by 2035. ResultsA total of 1568 asthma-related deaths occurred during the follow-up period, with the CMR and ASMRW being 3.25/1055555PPP ConclusionsAsthma remains a significant public health challenge in transitioning countries, requiring increased attention and resource allocation.

Abstract Background Analyzing the glaucoma burden in "Belt and Road" (B&R) countries based on age, gender, and risk factors from 1990 to 2019 in order to provide evidence for future prevention strategies. Methods We applied global burden of disease(GBD) 2019 to compare glaucoma prevalence and Years lived with disabilities (YLDs) from 1990 to 2019 in the B&R countries. Trends of disease burden between 1990 and 2019 were evaluated using the average annual percent change and the 95% uncertainty interval (UI) were reported. Results From 1990 to 2019, most B&R countries showed a downward trend in age-standardized prevalence and YLDs (all P 85 years), Malaysia(75–84 years), Brunei Darussalam(45–49 years), Afghanistan(70–79 years). Finally, in all Central Asian countries, the age-standardized YLDs due to glaucoma caused by fasting hyperglycemia demonstrated have an increase between 1990 and 2019 (all P

Background: As scientific research advances, the landscape of detection indicators and methodologies evolves continuously. Our current study aimed to identify some novel perioperative indicators that can enhance the predictive accuracy of the Global Registry of Acute Coronary Events (GRACE) score for the in-hospital major adverse cardiovascular events (MACEs) in patients with acute myocardial infarction. Methods: A total of 647 adult patients with AMI admitted to the emergency department were consecutively enrolled in the retrospective research starting from June 2016 to September 2019. The endpoint was in-hospital MACE. Stepwise regression analysis and multivariate logistic regression were performed to select the indicators for the union model established by nomogram. Bootstrap with 1000 replicates was chosen as the internal validation of the union model. The area under the receiver operating curve (AUC) and calibration plot were used to evaluate the discrimination and calibration. Decision curve analysis (DCA) was performed to evaluate the clinical sufficiency of the nomogram. Akaike's information criterion (AIC) and Bayesian Information Criterion (BIC) were used to evaluate the goodness of fit. Results: Lipoprotein(a) combined with serum uric acid, fasting blood glucose, and hemoglobin could improve the GRACE risk score. The AUC of the union model was 0.86, which indicated a better discriminative ability than the GRACE risk score alone (AUC, 0.81; P

ObjectivesDue to the increase in life expectancy and the aging of the global population, the “Belt and Road” (“B&R”) countries are faced with varying degrees of lung cancer threat. The purpose of this study is to analyze the differences in the burden and trend of lung cancer disability in the “B&R” countries from 1990 to 2019 so as to provide an analytical strategic basis to build a healthy “B&R”.MethodsData were derived from the Global Burden of Disease 2019 (GBD 2019). Incidence, mortality, prevalence, the years lived with disability (YLDs), and disability-adjusted life years (DALYs) of lung cancer and those attributable to different risk factors were measured from 1990 to 2019. Trends of disease burden were estimated by using the average annual percent change (AAPC), and the 95% uncertainty interval (UI) was reported.ResultsChina, India, and the Russian Federation were the three countries with the highest burden of lung cancer in 2019. From 1990 to 2019, the AAPC of incidence, prevalence, mortality, and DALYs generally showed a downward trend in Central Asia (except Georgia) and Eastern Europe, while in China, South Asia (except Bangladesh), most countries in North Africa, and the Middle East, the trend was mainly upward. The AAPC of age-standardized incidence was 1.33% (1.15%–1.50%); the AAPC of prevalence, mortality, and DALYs from lung cancer in China increased by 24% (2.10%–2.38%), 0.94% (0.74%–1.14%), and 0.42% (0.25%–0.59%), respectively. A downward trend of the AAPC values of age-standardized YLD rate in men was shown in the vast majority of “B&R” countries, but for women, most countries had an upward trend. For adults aged 75 years or older, the age-standardized YLD rate showed an increasing trend in most of the “B&R” countries. Except for the DALY rate of lung cancer attributable to metabolic risks, a downward trend of the DALY rate attributable to all risk factors, behavioral risks, and environmental/occupational risks was shown in the vast majority of “B&R” countries.ConclusionThe burden of lung cancer in “B&R” countries varied significantly between regions, genders, and risk factors. Strengthening health cooperation among the “B&R” countries will help to jointly build a community with a shared future for mankind.

BackgroundCongenital birth defects (CBDs) are a major public health issue. This study aims to assess trends in the burden of CBDs between 1990 and 2019 across China based on the Global Burden of Disease Study 2019 (GBD 2019).MethodsIndicators of the burden of CBDs included incidence, mortality, and disability-adjusted life years (DALYs). Metrics included number, rate, and age-standardized rate with 95% uncertainty intervals (UIs). Data were stratified by region [China, global, high-, middle-, low-socio-demographic index (SDI)], age, sex, and type of CBD. Average annual percentage changes (AAPC) and trends were evaluated.ResultsIn China, between 1990 and 2019, the age-standardized incidence rate for CBDs showed an increasing trend, with an AAPC of 0.26% (0.11% to 0.41%), reaching 148.12 per 105 person-years (124.03 to 176.33) in 2019. Most CBDs were congenital heart anomalies, with an AAPC of 0.12% (−0.08% to 0.32%). The age-standardized mortality rate for CBDs showed a decreasing trend, with an AAPC of −4.57% (−4.97% to −4.17%), reaching 4.62 per 105 person-years (3.88 to 5.57) in 2019. Most mortality was associated with congenital heart anomalies, with an AAPC of −3.77% (−4.35% to −3.19%). The age-standardized DALYs rate for CBDs showed a decreasing trend, with an AAPC of −3.74% (−3.95% to −3.52%), reaching 480.95 per 105 person-years (407.69 to 570.04) in 2019.ConclusionsMorbidity associated with CBDs increased in China between 1990 and 2019, accelerated by the adoption of the two-child policy, and ranked high globally. These findings emphasize the need for prenatal screening and primary and secondary prevention strategies.

Background: Contrast induced nephropathy (CIN) is a common complication in patients receiving intravascular contrast media. In 2020, the American College of Radiology and the National Kidney Foundation issued a new contrast induced acute kidney injury (CI-AKI) criteria. Therefore, we aimed to explore the potential risk factors for CIN under the new criteria, and develop a predictive model for patients with coronary artery disease (CAD) with relatively normal renal function (NRF).Methods: Patients undergoing coronary angiography or percutaneous coronary intervention at Zhongshan Hospital, Fudan University between May 2019 and April 2020 were consecutively enrolled. Eligible candidates were selected for statistical analysis. Univariate and multivariate logistic regression analyses were used to identify the predictive factors. A stepwise method and a machine learning (ML) method were used to construct a model based on the Akaike information criterion. The performance of our model was evaluated using the area under the receiver operating characteristic curves (AUC) and calibration curves. The model was further simplified into a risk score.Results: A total of 2,009 patients with complete information were included in the final statistical analysis. The results showed that the incidence of CIN was 3.2 and 1.2% under the old and new criteria, respectively. Three independent predictors were identified: baseline uric acid level, creatine kinase-MB level, and log (N-terminal pro-brain natriuretic peptide) level. Our stepwise model had an AUC of 0.816, which was higher than that of the ML model (AUC = 0.668, P = 0.09). The model also achieved accurate predictions regarding calibration. A risk score was then developed, and patients were divided into two risk groups: low risk (total score < 10) and high risk (total score ≥ 10).Conclusions: In this study, we first identified important predictors of CIN in patients with CAD with NRF. We then developed the first CI-AKI model on the basis of the new criteria, which exhibited accurate predictive performance. The simplified risk score may be useful in clinical practice to identify high-risk patients.