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Background: Hypertensive heart disease (HHD) is a significant public health concern in China. We intend to provide an updated estimate of the burden of HHD in China between 1990 and 2030., Methods: HHD prevalence, mortality, and disability-adjusted life years (DALYs) data were obtained from Global Burden of Disease (GBD) 2019 databases. Temporal trends of HHD from 1990 to 2019 were analyzed using Joinpoint regression models, and projections through 2030 were estimated by Bayesian age-period-cohort model., Results: In 2020, an estimated 334,695 newly prevalent cases and 13,196 deaths due to HHD occurred in China. From 1990 to 2019, age-standardized rate of prevalence (ASPR), mortality (ASMR) and DALYs (ASDR) showed a decreasing trend. The behavior-related risk, diet risk and excessive BMI were the most common reasons of death in HHD. According to our prediction, ASMRs and ASDRs will continue to decrease from 2020 to 2030. However, ASPRs will have a moderate rise., Conclusion: HHD continues to pose a significant threat to public health in China. To achieve the Healthy China 2030 objective, a tailored approach involving comprehensive strategies is essential. These strategies should include, but are not limited to, enhancing public awareness about hypertension through educational campaigns, improving access to healthcare services for early diagnosis and treatment, implementing policies to promote healthy lifestyles, such as regular physical activity and a balanced diet, and strengthening the surveillance and monitoring systems to track the prevalence and impact of HHD over time., Competing Interests: Declarations. Ethics approval and consent to participate: The informed consent was waived because no identifying data were used. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Background: Intertrochanteric fractures are one of the most common types of hip fractures, with delayed surgical treatment beyond 48 h associated with increased postoperative complications and mortality, especially in older adults. This study aimed to develop a predictive model for delayed preoperative waiting times in intertrochanteric fracture cases, based on previous research, to offer a valuable reference for clinical decision-making., Methods: A retrospective analysis was conducted on 1,116 patients with intertrochanteric fractures admitted to the Affiliated Hospital of Shandong University of Traditional Chinese Medicine for internal fixation surgery from January 2017 to January 2024. Patient demographic data and clinical examination results were collected. A logistic regression model was used to construct a predictive model, which was then visualized through a nomogram. The model's performance was subsequently validated., Results: The predictive model developed from 728 patients in the training cohort, identified key predictors, including age, sex, lower extremity deep vein thrombosis, injury location, and biochemical markers. The model demonstrated strong discriminative ability, with an area under the receiver operating characteristic curve of 0.749 (95% confidence interval: 0.621-0.801) for the training set, and 0.745 in the validation set. Calibration curves indicated that the predicted risk of surgical delay closely aligned with observed outcomes. Furthermore, decision curve analysis verified the model's clinical utility, demonstrating its effectiveness in guiding treatment decisions., Conclusion: The nomogram model developed in this study provides a reliable tool for predicting delayed surgical intervention in patients with intertrochanteric femur fractures. It offers clinicians a valuable reference to anticipate delays in surgical treatment and aids in the formulation of more timely and appropriate treatment strategies, potentially improving patient outcomes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2025 Gong, Jin, Xu, Zhang, Yuan, Xie and Zhang.)