Diagnosis-related groups (DRG) based hospital payment systems are gradually becoming the main mechanism for reimbursement of acute inpatient care. We reviewed the existing literature to ascertain the global use of DRG-based hospital payment systems, compared the similarities and differences of original DRG versions in ten countries, and used ischemic stroke as an example to ascertain the design and implementation strategies for various DRG systems. The current challenges with and direction for the development of DRG-based hospital payment systems are also analyzed. We found that the DRG systems vary greatly in countries in terms of their purpose, grouping, coding, and payment mechanisms although based on the same classification concept and that they have tended to develop differently in countries with different income classifications. In high-income countries, DRG-based hospital payment systems have gradually begun to weaken as a mainstream payment method, while in middle-income countries DRG-based hospital payment systems have attracted increasing attention and increased use. The example of ischemic stroke provides suggestions for mutual promotion of DRG-based hospital payment systems and disease management. How to determine the level of DRG payment incentives and improve system flexibility, balance payment goals and disease management goals, and integrate development with other payment methods are areas for future research on DRG-based hospital payment systems.

Tuberculosis (TB) is one of the top ten causes of death worldwide, taking the lives of over a million people annually. In addition to being a serious health issue, TB is also closely linked to eradicating poverty according to the Sustainable Development Goals (SDGs) of the United Nations (UN). All UN members have committed to ending the TB epidemic by 2030. China has one of the highest TB loads worldwide, ranking third in the world on many TB burden indices. The national strategy for TB control is aimed at creating a collaborative network and integrating TB treatment into the medical system. According to the WHO's global TB report, China is expected to have 748,000 new cases of TB in 2022 and an incidence of 52 cases per 100,000 people. Ending TB remains a huge challenge and requires comprehensive control strategies in China. In this work, we have discussed the challenges of TB prevention and control in China and proposed specific measures to end TB.

Hepatocellular carcinoma (HCC), a challenging malignancy, often necessitates surgical intervention, notably liver resection. However, the high recurrence rate, reaching 70% within 5 years post-resection, significantly impacts patient outcomes. Neoadjuvant therapies aim to preoperatively address this challenge, reducing lesion size, improving surgical resection rates, deactivating potential micro-metastases, and ultimately lowering postoperative recurrence rates. This review concentrates on advances in research on and clinical use of neoadjuvant therapies for HCC, with particular attention to the use of immune checkpoint inhibitors (ICIs) targeting programmed cell death-1 (PD-1), programmed cell death ligand-1 (PD-L1), and cytotoxic T-lymphocyte-associated protein-4 (CTLA-4). Ongoing clinical studies exploring immunotherapy combined with a tyrosine kinase inhibitor (TKI), interventional therapy, radiotherapy, and other modalities offer promising insights into overcoming resistance to monotherapies. In summary, neoadjuvant therapies hold significant promise in terms of improving the prognosis for patients with HCC and enhancing long-term survival, particularly through innovative combination strategies.

Therapies for patients with unresectable hepatocellular carcinoma (uHCC) are currently popular. Current first-line standard-of-care treatments for uHCC are systematic therapies. However, treatments that combine locoregional therapy with systemic therapy are widely accepted in China and have demonstrated high rates of tumor response and conversion to resection with manageable toxicity. A literature review was performed by searching published literature in PubMed and Web of Science up to December 2023 for relevant articles on the use of triple therapy (transarterial chemoembolization combined with lenvatinib and anti–PD-1 antibodies) in uHCC. This review concentrates on the efficacy and safety of triple therapy with Chinese characteristics in patients with uHCC and describes the outcome of conversion surgery, degree of pathological necrosis, and effect prediction. This article will contribute to a comprehensive understanding of the role of triple therapy with Chinese characteristics in patients with uHCC.

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. Due to the complexity of the disorder and the presence of the blood-brain barrier (BBB), its drug discovery and development are facing enormous challenges, especially after several failures of monoclonal antibody (mAb) trials. Nevertheless, the Food and Drug Administration's approval of the mAb aducanumab has ushered in a new day. As we better understand the disease's pathogenesis and identify novel intracerebral therapeutic targets, antibody-based therapies have advanced over the past few years. The mAb drugs targeting β-amyloid or hyperphosphorylated tau protein are the focus of the current research. Massive neuronal loss and glial cell-mediated inflammation are also the vital pathological hallmarks of AD, signaling a new direction for research on mAb drugs. We have elucidated the mechanisms by which AD-specific mAbs cross the BBB to bind to targets. In order to investigate therapeutic approaches to treat AD, this review focuses on the promising mAbs targeting intracerebral dysfunction and related strategies to cross the BBB.

The early detection of mild cognitive impairment (MCI) is crucial to preventing the progression of dementia. However, it necessitates that patients voluntarily undergo cognitive function tests, which may be too late if symptoms are only recognized once they become apparent. Recent advances in deep learning have improved model performance, leading to applied research in various predictive problems. Studies attempting to estimate dementia and the risk of MCI based on readily available data are being conducted, with the hope of facilitating the early detection of MCI. The data used for these predictions vary widely, including facial imagery, voice recordings, blood tests, and inertial information during walking. Deep learning models that make predictions based on these data sources have been proposed. This article summarizes recent research efforts to predict the risk of dementia using easily accessible data. As research progresses and more accurate predictions become feasible, simple tests could be incorporated into daily life to monitor one's personal health status and to facilitate an early intervention.

Relatively little is known about education placements for children with autism spectrum disorder (ASD) in China. While disparities in ASD diagnoses and services for the population broadly are often documented, the presence and determinants of differences in the educational placement of ASD children are less studied and understood. By identifying who is likely to be in segregated settings, we can discern how to best support them and facilitate a possible transition to a less restrictive setting. This study describes four placements (regular schools, special schools, institutions, homes) and their influencing factors retrospectively in a large sample (n = 2,190) of Chinese primary school-aged children (6-12 years old). We divided ASD into severe and mild to moderate categories for analysis. Children with ASD were more likely to study in a regular school (48.60%), while 13.88% were in a special school. Children with severe ASD were placed in less regular settings than children with mild to moderate ASD. However, families with higher socioeconomic status (SES) were more likely to place their children in regular schools than lower SES families if their children experienced mild to moderate symptoms. Children with severe ASD were more likely to be placed in expensive institutions for families with higher SES than those with lower SES. SES disparities in educational placement existed and had two manifestations. It is important to characterize educational placements of students with ASD to determine the extent to which they are placed in general education settings, which are often the preferred placement.

The adequacy of screw anchorage is a critical factor in achieving successful spinal fusion. This study aimed to use machine learning algorithms to identify critical variables and predict pedicle screw loosening after degenerative lumbar fusion surgery. A total of 552 patients who underwent primary transpedicular lumbar fixation for lumbar degenerative disease were included. The LASSO method identified key features associated with pedicle screw loosening. Patient clinical characteristics, intraoperative variables, and radiographic parameters were collected and used to construct eight machine learning models, including a training set (80% of participants) and a test set (20% of participants). The XGBoost model exhibited the best performance, with an AUC of 0.884 (95% CI: 0.825–0.944) in the test set, along with the lowest Brier score. Ten crucial variables, including age, disease diagnosis: degenerative scoliosis, number of fused levels, fixation to S1, HU value, preoperative PT, preoperative PI-LL, postoperative LL, postoperative PT, and postoperative PI-LL were selected. In the prospective cohort, the XGBoost model demonstrated substantial performance with an accuracy of 83.32%. This study identified crucial variables associated with pedicle screw loosening after degenerative lumbar fusion surgery and successfully developed a machine learning model to predict pedicle screw loosening. The findings of this study may provide valuable information for clinical decision-making.

This study aimed to investigate the causal role of diabetes mellitus (DM), glycemic traits, and sodium-glucose cotransporter 2 (SGLT2) inhibition in pulmonary arterial hypertension (PAH). Utilizing a two-sample two-step Mendelian randomization (MR) approach, we determined the causal influence of DM and glycemic traits (including insulin resistance, glycated hemoglobin, and fasting insulin and glucose) on the risk of PAH. Moreover, we examined the causal effects of SGLT2 inhibition on the risk of PAH. Genetic proxies for SGLT2 inhibition were identified as variants in the SLC5A2 gene that were associated with both levels of gene expression and hemoglobin A1c. Results showed that genetically inferred DM demonstrated a causal correlation with an increased risk of PAH, exhibiting an odds ratio (OR) of 1.432, with a 95% confidence interval (CI) of 1.040-1.973, and a p-value of 0.028. The multivariate MR analysis revealed comparable outcomes after potential confounders (OR = 1.469, 95%CI = 1.021-2.115, p = 0.038). Moreover, genetically predicted SGLT2 inhibition was causally linked to a reduced risk of PAH (OR = 1.681*10^-7, 95%CI = 7.059*10^-12-0.004, p = 0.002). Therefore, our study identified the suggestively causal effect of DM on the risk of PAH, and SGLT2 inhibition may be a potential therapeutic target in patients with PAH.

Lactylation of α-myosin heavy chain (α-MHC) has recently been reported to preserve sarcomeric structure and function and attenuate the development of heart failure. Specifically, lactylation enhanced the interaction of α-MHC with the sarcomeric protein Titin, thereby maintaining normal sarcomeric structure and myocardial contractile function. Furthermore, the administration of lactate or inhibition of lactate efflux potentially treats heart failure by restoring lactylation of α-MHC and the interaction of α-MHC with Titin. This finding highlights the significant role of α-MHC lactylation in myocardial diseases and presents a new therapeutic target for the treatment of heart failure.