First People's Hospital of Nanning

BackgroundEarly neurological improvement (ENI) within the first 24 h after acute ischemic stroke (AIS) has been proposed as a rapid dynamic predictor for treatment response. However, the prognostic value of ENI for 90-day functional recovery in real-world clinical practice remains uncertain, especially in heterogeneous stroke populations receiving mixed reperfusion treatments. We aimed to evaluate the association between 24-h neurological change and 90-day functional outcome in a contemporary single-center AIS cohort.MethodsWe conducted a prospective observational cohort study including 200 consecutive AIS patients between January 2023 and December 2024. Baseline demographic, vascular risk factor, clinical, laboratory, imaging, and treatment variables were collected at admission. ENI was defined as the change in NIHSS between baseline and 24 h (ΔNIHSS = NIHSS_baseline–NIHSS_24h). Two logistic regression models were developed: Model 1, using only baseline clinical and imaging variables, and Model 2, which incorporated ΔNIHSS as a dynamic predictor. Discrimination was evaluated using the area under the receiver operating characteristic curve (AUC), and calibration was assessed using bootstrap-corrected calibration plots. Nomograms were constructed for bedside application.ResultsAmong 200 patients, 118 (59.0%) achieved good functional outcome at 90 days (mRS 0–2). In Model 1, age, baseline NIHSS, and ASPECTS were independently associated with 90-day outcomes, whereas hypertension was negatively associated. Model 1 demonstrated strong discrimination (AUC 0.863). While discrimination reached a prognostic plateau (AUC 0.863 vs. 0.855), the incorporation of ΔNIHSS significantly optimized model calibration, reducing the mean absolute prediction error by 47% (0.051–0.027). This indicates that the dynamic model provides substantially more accurate probability estimates for individual patients. Greater early neurological improvement was independently associated with good outcome (adjusted OR per 5-point ΔNIHSS increase, 1.48; 95% CI 1.11–1.97). Corresponding ROC curves, calibration plots, and nomograms for both models are presented.ConclusionEarly neurological improvement within 24 h after AIS serves as a reliable and rapid dynamic predictor for 90-day functional recovery. While baseline clinical and imaging variables provide strong prognostic value, incorporating early neurological change enhances model calibration and clinical usefulness. This dynamic paradigm supports integrating short-term neurological change into prognostic assessment and individualized post-stroke care.

Coronary artery disease (CAD) remains a leading cause of mortality worldwide, with substantial unmet therapeutic needs. This study aimed to identify and prioritize genetically supported therapeutic targets for CAD using Mendelian randomization (MR). We implemented a two-sample MR framework to infer the causal effects of blood druggable cis-expression quantitative trait loci (cis-eQTLs) on CAD. To consolidate MR findings, we applied Steiger filtering, Bayesian colocalization, and multiple sensitivity analyses. Mediation and phenomewide MR analyses were employed to investigate potential mechanisms and on-target effects of prioritized druggable genes. We identified 66 causal druggable genes associated with CAD in European populations (false discovery rate < 0.001). Among these, ERP29 (odds ratio [OR] = 1.311; 95% confidence interval [CI]: 1.176-1.460), MCL1 (OR = 0.877; 95% CI: 0.840-0.915), TNXB (OR = 1.183; 95% CI: 1.102-1.269), DAGLB, FES, and TRPM4 colocalized with CAD (posterior probability for colocalization > 0.8). The associations for ERP29, MCL1, and TNXB were replicated in an East Asian cohort. Protein-protein interaction network analysis highlighted MAPK3 and TNF as prioritized druggable targets at the protein level. Mediation analysis indicated that body mass index, triglycerides, blood pressure, and atrial fibrillation partially mediate the association between MAPK3 and CAD. Phenome-wide MR analysis further suggested additional beneficial effects of targeting MAPK3 and TNF on diabetes mellitus, obesity, hypertension, unstable angina, myocardial infarction, angina pectoris, coronary atherosclerosis, ischemic heart disease, and disorders of lipoid metabolism. This druggable genome-wide MR study not only corroborated the targets of FDA-approved CAD medications (e.g., FGFR1, MAPK3, NEU1) but also uncovered several novel genes, such as ERP29, MCL1, TNXB, DAGLB, FES, and TRPM4, implicating mechanisms related to blood pressure, lipid metabolism, and additional beneficial effects on endocrine/cardiometabolic traits and circulatory system disorders. Further exploration is imperative to explore their feasibility and generalizability. We identified circulating ERP29, MCL1, TNXB, DAGLB, FES, TRPM4, MAPK3, and TNF as promising, genetically supported druggable targets for CAD treatment. Notably, MAPK3 and TNF demonstrated strong protein-level interactions and close associations with cardiometabolic disorders.

This study examined recent trends in the prevalence, incidence, mortality and disability-adjusted life years (DALYs) associated with acute glomerulonephritis, a global health challenge, using data from the Global Burden of Disease (GBD) 2021 database. We analysed age-standardised prevalence rate (ASPR), age-standardised incidence rate (ASIR), age-standardised mortality rate (ASMR), and age-standardised DALY rate at global, regional, and national levels from 1990 to 2021. The estimated annual percentage change (EAPC) in age-standardised rate (ASR) was calculated to assess the epidemiological trends. Bayesian age-period-cohort (BAPC) models were utilised to forecast future trends for 2021-2050. Age-period-cohort method was employed to analyse the temporal trends of AGN. Pearson correlation coefficient was used to assess the correlation between socio-demographic index (SDI) and ASR indicators across different GBD regions. Decomposition analysis was used to evaluate the drivers of changes in disease burden. The global prevalence, incidence, mortality, and DALYs of AGN showed an overall decline from 1990 to 2021. The greatest reductions in ASPR and ASIR occurred in high-middle SDI regions. The ASMR and the age-standardised DALY rate were increased only in high SDI regions. The prevalence and incidence of AGN peaked in the 10-14 years age group for both sexes. Males had a higher burden of AGN DALYs, particularly in the 65-69 group. Geographically, Brazil experienced the greatest increases in ASPR and ASIR. Mexico saw the highest rises in ASMR and age-standardised DALY rate. ASMR and age-standardised DALY rates were expected to decline for both sexes. Net drift results revealed an overall decline trend for AGN-related burden over time. The ASMR and age-standardised DALY rate across different GBD regions showed a negative correlation with SDI. Decomposition analysis indicated that the AGN burden in global and the low SDI regions was primarily driven by population growth. The development and implementation of evidence-based and effective public health policies are essential to mitigate the global disease burden of AGN and ensure equitable health outcomes.

BackgroundTraumatic splenic rupture is a life-threatening acute abdominal condition. While traditional total splenectomy effectively controls bleeding, it results in the loss of splenic function, increasing the risk of infectious complications and long-term health issues. Laparoscopic partial splenectomy, as a minimally invasive spleen-preserving approach, offers a new treatment option for such patients. However, its technical complexity limits its clinical adoption, requiring further experience accumulation and technical optimization.MethodsThis study retrospectively analyzed the clinical data of 13 patients with traumatic splenic rupture treated between 2018 and 2021 to evaluate the safety, efficacy, and applicability of laparoscopic partial splenectomy. All patients were diagnosed via contrast-enhanced abdominal CT imaging. During surgery, partial splenectomy was performed using splenic artery occlusion combined with anatomical dissection. Perioperative data and postoperative changes in blood parameters were recorded.ResultsThe median operative time was 120 min, with a median intraoperative blood loss of 1,500 mL. The residual spleen in all 13 patients maintained good blood supply. Blood tests showed a gradual resolution of postoperative inflammatory responses, with platelet levels returning to normal. Imaging follow-up confirmed improved blood supply to the residual spleen. The median postoperative hospital stay was 14 days, and all patients survived and preserved splenic tissue. One patient developed a minor splenic infarction that resolved, and no patient experienced re-bleeding, overwhelming infection, or other major complications.ConclusionsLaparoscopic partial splenectomy demonstrates favorable safety and efficacy in patients with traumatic splenic rupture. By optimizing intraoperative vascular control and careful management of the resection site, this procedure not only preserves partial splenic function but also reduces postoperative complications. It provides a reliable minimally invasive surgical option for the treatment of traumatic splenic rupture.

Endometriosis is a chronic inflammatory estrogen-dependent inflammatory disorder. Theobromine has been implicated in diverse health benefits, including anti-inflammatory and vasodilatory properties. However, the precise association between theobromine and endometriosis remains largely undetermined. To address this gap, this study sought to explore the causal relationship between theobromine exposure and the risk of endometriosis by leveraging Mendelian randomization (MR) and data from the National Health and Nutrition Examination Survey (NHANES). This study included 244 participants from the NHANES (1999–2004). Multivariable logistic regression (adjusted for age, body mass index, smoking, alcohol intake, and energy intake) assessed associations between dietary theobromine intake and endometriosis diagnosis age. Two-sample MR (16,588 cases/1,11,583 controls) used 12 theobromine-associated single-nucleotide polymorphisms (P < 5 × 10⁻⁸) as instruments, with inverse variance weighted analysis. MR assumptions were verified via F-statistics (>10), heterogeneity (Cochran’s Q P > .05), and pleiotropy (MR-Egger P > .05). In the observational study (NHANES), each 1 μg/d increment in dietary theobromine intake was associated with a 1.49-year delay in endometriosis diagnosis age (β = 1.49, 95% CI: 0.02–2.95, P = .048) after multivariable adjustment. In the MR analysis, the inverse variance weighted method showed a significant causal effect estimate of β = −0.1057 (95% CI: −0.2098 to −0.0016, P = .045) for the effect of theobromine on endometriosis risk. Sensitivity analyses confirmed robustness against pleiotropy and heterogeneity. This study suggests a potential causal relationship between dietary theobromine intake and a modestly reduced risk of endometriosis, providing preliminary insights into the potential protective effects of theobromine against the development of this condition. However, further investigations are necessary to validate these findings and to understand the underlying biological mechanisms.

Acute Respiratory Distress Syndrome (ARDS) remains a critical condition, characterized by severe respiratory failure and high mortality, despite significant advances in understanding its pathophysiology. Current treatments are largely supportive, with no definitive pharmacological solutions available. This review explores the potential of nanomedicine in ARDS management, focusing on nanocarrier-based delivery systems. Lipid nanoparticles (LNPs), particularly for RNA therapeutics, and nanostructured lipid carriers (NLCs) for conventional drug delivery, are highlighted for their enhanced targeting and stability profiles. The clinical success of LNPs in mRNA vaccine delivery demonstrates their efficacy in managing ARDS-related inflammation and tissue damage. Comparative analysis of various nanocarrier platforms reveals distinct advantages, with LNPs offering superior nucleic acid encapsulation efficiency, while NLCs provide enhanced drug-loading capacity and cost-effectiveness. Despite promising preclinical outcomes, clinical translation of nanomedicine in ARDS remains limited, constrained by challenges such as manufacturing scalability, regulatory hurdles, and potential immunogenicity. Moving forward, precision nanotherapies tailored to specific ARDS stages and triggers are essential for improving patient outcomes. This review underscores the need for further research to optimize nanocarrier properties and overcome current limitations, ultimately accelerating the clinical adoption of nanomedicine in ARDS treatment.

IntroductionThe combination of dapagliflozin and metformin is commonly used as an initial therapy for patients with type 2 diabetes mellitus (T2DM) with high glycated hemoglobin (HbA1c) levels. Although bioequivalence has been established for the fixed-dose combination (FDC) of dapagliflozin/metformin extended-release (XR) compared to the co-administration of dapagliflozin and metformin XR, it remains uncertain whether the efficacy of dapagliflozin/metformin FDC is comparable to that of co-administration. Additionally, it is still unclear whether fixed-dose combinations offer advantages in terms of patient adherence and satisfaction. This study aims to compare the dapagliflozin/metformin XR FDC with co-administration of dapagliflozin and metformin XR for efficacy in terms of glycemic control, patient satisfaction, quality of life and adherence in Chinese patients with newly diagnosed T2DM.Methods and analysisThis multicenter, randomized, non-inferiority, open-label clinical trial enrolled 632 patients with T2DM (HbA1c 7.5–10%) in 35 research centers in China. After enrollment, the patients will be randomly assigned to receive either FDC treatment (10 mg dapagliflozin and 1000 mg metformin XR) or co-administered 10 mg dapagliflozin and 1000 mg metformin XR tablets for 24 weeks. The primary endpoint was the change in HbA1c level from baseline after 24 weeks of treatment. Secondary endpoints included the proportion of patients achieving HbA1c below 7.0%, absolute changes in fasting plasma glucose and postprandial glucose from baseline to week 24, the difference in patient satisfaction measured with the diabetes treatment satisfaction questionnaire, medication usage measured with adherence to refills and medications scale for diabetes between the two groups at week 24, change from baseline in diabetes quality of life questionnaire score at week 12 and week 24, and safety. Continuous glucose monitoring will also be used to evaluate the benefits of FDC compared with co-administration on glycemic variability.DiscussionThis study, as the first of its kind, will provide comparative data on the efficacy of the dapagliflozin/metformin XR FDC and co-administration of dapagliflozin and metformin XR in terms of glycemic control, patient satisfaction, quality of life and adherence. These data will help clinicians make more informed decisions for patients with type 2 diabetes and may improve medication burden, treatment adherence, and satisfaction.

Combined nutrition and rehabilitation is a top research priority for ICU-acquired weakness, yet the optimal strategy and clinical benefits remain unclear. This study aimed to evaluate the independent and combined effects of resistance training (RT) and β-hydroxy-β-methylbutyrate (HMB) in critically ill adults. We conducted a multicenter, open-label, 2 × 2 factorial randomized controlled trial with blinded outcome assessment in 266 adult ICU patients. Participants were randomized to receive RT, HMB supplementation, combined interventions, or standard care. Treatments began in the ICU and continued until discharge. Primary outcomes at discharge included six-minute walk distance (6MWD) and the Short Physical Performance Battery (SPPB). Secondary outcomes included muscle strength and mass, patient-reported outcomes, and mortality at 1, 6, and 12 months. Analyses followed the intention-to-treat principle, using linear mixed-effects models to estimate the independent and interactive effects of RT and HMB. RT significantly improved physical function at discharge, with higher SPPB scores (mean difference:1.32 points; P = 0.003) and longer 6MWD (56.20 m; P < 0.001), compared with patients who did not receive RT. It was associated with lower 6-month (OR, 0.51; P = 0.011) and 12-month mortality (OR, 0.55; P = 0.014), and increased grip strength (3.19 kg; P = 0.008), appendicular skeletal muscle mass (0.997 kg; P = 0.005), and skeletal muscle index (0.428 kg/m²; P = 0.025). RT reduced fatigue and improved sleep quality and psychological symptoms (P < 0.05), but had no effect on cognition or overall quality of life. HMB modestly increased phase angle (0.367; P = 0.020) and reduced fatigue (–1.069 points, P = 0.005), but had no effect on other outcomes; hyperglycemia occurred in 3 of 134 patients receiving HMB. No interaction between RT and HMB was detected. This expanded trial provides novel evidence that RT not only improves physical function but also increases muscle mass, enhances patient-reported outcomes, and lowers 6- and 12-month mortality in critically ill patients. HMB supplementation offered only modest effects on phase angle and fatigue, with no synergistic benefit when combined with RT. ChiCTR2200057685 ( https://www.chictr.org.cn/ ) was registered on March 15th, 2022.

BackgroundSepsis-associated acute kidney injury (SA-AKI) is a frequent and life-threatening complication in patients in the intensive care unit (ICU), significantly increasing both mortality rates and the risk of chronic kidney dysfunction. However, existing prediction models have often focused on overall risk and lack severity-based stratification, which limits their clinical applicability.ObjectiveThis study aimed to identify critical time points in SA-AKI progression development and validate dynamic, stratified machine learning prediction models for moderate-to-severe (Kidney Disease: Improving Global Outcomes guideline stages 2-3) SA-AKI through multicenter, multiregional external validation, ultimately deploying them as publicly accessible, interpretable clinical decision support tools.MethodsThis study used three independent ICU databases: Medical Information Mart for Intensive Care-IV v3.0 (n=12,842; model development and internal validation), electronic ICU collaborative research database v2.0 (n=15,767; North American multicenter external validation), and the First Affiliated Hospital of Hainan Medical University ICU (n=210; Chinese single-center external validation). We identified 48 hours (acute phase) and 7 days (subacute phase) as critical time points. Based on clinical data from the first 24 hours of ICU admission, we used a two-stage feature selection process combining light gradient boosting machine (LightGBM) and Shapley additive explanation (SHAP) cross-validation analysis with clinical expert review, followed by modeling using 8 machine learning algorithms. The optimal model was selected based on the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. Internal validation used 5-fold cross-validation, while external validation and subgroup analyses assessed generalizability across different regions and populations. SHAP values and partial dependence plots were used to interpret the influence of key features on predictions.ResultsOur dual-timepoint LightGBM model demonstrated robust predictive performance. For the 48-hour prediction task, the model achieved an AUC of 0.839 (95% CI 0.824-0.854) in the internal test set, with AUCs of 0.770 (95% CI 0.762-0.779) and 0.793 (95% CI 0.726-0.856) in the external validation cohorts, respectively. For the 7-day prediction task, the corresponding AUCs across the three cohorts were 0.834 (95% CI 0.818-0.850), 0.720 (95% CI 0.711-0.729), and 0.773 (95% CI 0.687-0.851), respectively. Subgroup analyses confirmed robust model performance across different age, gender, and comorbidity subgroups. SHAP analysis identified urine output, mechanical ventilation, Sequential Organ Failure Assessment score, creatinine, Glasgow Coma Scale score, and nephrotoxic drug use as core predictive features. Decision curve analysis confirmed that LightGBM provided consistent clinical benefit across different threshold ranges. The optimal LightGBM model was deployed as a publicly accessible web-based prediction app with integrated SHAP interpretability.ConclusionsThis study developed and validated a dynamic, stratified prediction system that provides stage-specific risk assessment for moderate-to-severe SA-AKI. The system underwent rigorous multiregional, multicenter validation and was translated into an interpretable clinical decision support tool, providing a scientific foundation for precision management.