Objective To evaluate the effect of donor gender on short-term survival rate of lung transplant recipients. Methods A retrospective analysis was conducted on the data of 1 066 lung transplant recipients. The log-rank test was used to evaluate the differences in short-term fatality among different donor gender groups and donor-recipient gender combination groups. Multivariate Cox regression, propensity score (PS) regression, and propensity score matching (PSM) were employed to control for confounding factors and further assess the differences in fatality. Subgroup analyses were also performed based on donor gender. Results Multivariate Cox regression analysis showed no statistically significant differences in fatality at 30 days, 1 year, 2 years and 3 years postoperatively between male and female donor groups (all P>0.05). After PS regression and PSM, univariate Cox regression analysis indicated that recipients from female donors had a higher fatality at 2 years postoperatively compared to those from male donors, with hazard ratios (95% confidence intervals) of 1.29 (1.01-1.65) and 1.36 (1.03-1.80) respectively. Multivariate Cox regression analysis also revealed no statistically significant differences in fatality at various follow-up time points among different donor-recipient gender combination groups (all P>0.05). Subgroup analyses based on donor sex showed no statistically significant differences in fatality among recipients of different gender within either male or female donor groups (all P>0.05). Conclusions Female donors may reduce the short-term postoperative survival rate of lung transplant recipients, but this negative impact is not sustainable in the long term. At present, there is no evidence to support the inclusion of sex as a factor in lung allocation rules.

BACKGROUND: Mild cognitive impairment (MCI) is common in atrial fibrillation (AF) patients and may develop earlier in those with multiple cardiovascular comorbidities, potentially impairing self-management and treatment adherence. This study aimed to characterize the prevalence and profile of MCI in AF patients, examine its associations with cardiovascular comorbidities, and assess how these comorbidities influence specific cognitive domains. METHODS: This cross-sectional study analyzed data from AF patients who underwent cognitive assessment between 2017 and 2021. Cognitive status was categorized as MCI or non-MCI based on the Montreal Cognitive Assessment. Associations between comorbidities and MCI were assessed by logistic regression, and cognitive domains were compared using the Mann-Whitney U test. RESULTS: Of 4136 AF patients (mean age: 64.7 ± 9.4 years, 64.7% male), 33.5% of patients had MCI. Among the AF patients, 31.2% of patients had coronary artery disease, 20.1% of patients had heart failure, and 18.1% of patients had hypertension. 88.7% of patients had left atrial enlargement, and 11.0% of patients had reduced left ventricular ejection fraction. Independent factors associated with higher MCI prevalence included older age (OR = 1.04, 95% CI: 1.03-1.05, P < 0.001), lower education level (OR = 1.51, 95% CI: 1.31-1.73, P < 0.001), hypertension (OR = 1.28, 95% CI: 1.07-1.52, P = 0.001), heart failure (OR = 1.24, 95% CI: 1.04-1.48, P = 0.020), and lower left ventricular ejection fraction (OR = 1.43, 95% CI: 1.04-1.98, P = 0.028). A higher CHA₂DS₂-VASc score (OR = 1.27, 95% CI: 1.22-1.33, P < 0.001; ≥ 2 points vs. < 2 points), and greater atherosclerotic cardiovascular disease burden (OR = 1.45, 95% CI: 1.02-2.08, P = 0.040; 2 types vs. 0 type) were linked to increased MCI risk. These above factors influenced various cognitive domains. CONCLUSIONS MCI is common in AF and closely associated with cardiovascular multimorbidity. Patients with multiple comorbidities are at higher risk, highlighting the importance of routine cognitive assessment to support self-management and integrated care.

Lung transplantation is an important means to treat end-stage lung disease and improve the survival rate and quality of life of patients. However, many postoperative complications seriously affect the prognosis of recipients. Accurate identification of key prognostic factors and construction of individualized and accurate prediction models are of great significance for postoperative prognosis evaluation, treatment strategy formulation and clinical decision-making. In recent years, the clinical prediction model of lung transplantation has gradually changed from traditional statistical methods to machine learning-driven. Compared with traditional models such as Cox regression and Logistic regression, machine learning models such as random forest, support vector machine and artificial neural network have certain advantages in postoperative survival rate prediction, early warning of complications and pulmonary function evaluation. However, their application is also affected by insufficient sample size and poor interpretability of models. Under the condition of small samples, the traditional model still has important value in prediction accuracy. The appropriate prediction model should be selected according to the clinical status of lung transplantation in China, considering the factors such as sample size, variable complexity and model interpretability. In the future, a multi-center, large-sample lung transplantation database should be constructed to further optimize and tap the potential of machine learning algorithms to improve the robustness and clinical applicability of the model.

Objective:To explore the effects of 4C management mode on rehabilitation and quality of life in patients with acute heart failure(AHF)in cardiovascular intensive care unit(CCU).Methods:This randomized controlled study enrolled 110 patients with AHF admitted in CCU of Guangdong Provincial Hospital of Traditional Chinese Medicine between February 2021 and February 2023.Patients were randomly divided into intervention group(n=55)and control group(n=55).Patients in the control group received routine intervention,while those in the inter-vention group received additional 4C management mode,both groups were intervened for 3 months.The indexes of cardiac function,self-efficacy,exercise tolerance,blood oxygen saturation(SpO2),mental state and quality of life were compared between the two groups.Results:Compared to those in the control group after intervention,patients in the intervention group had significantly lower interventricular septal thickness(IVST)[(9.20±0.10)mm vs.(10.30±0.17)mm,P＜0.001],left ventricular end-systolic volume index(LVESVI)[(35.21±0.74)ml/m2 vs.(39.70±1.09)ml/m2,P＜0.001],left ventricular end-diastolic volume index(LVED VI)[(45.35±0.71)ml/m2 vs.(56.76±1.48)ml/m2,P＜0.001],scores of self-rating anxiety scale(SAS)[(32.10±1.57)points vs.(45.36±1.94)points,P＜0.001],self-rating depression scale(SDS)[(35.03±1.52)points vs.(47.70±2.12)points,P＜0.001]and Minnesota living with heart failure questionnaire(MLHFQ)[(51.27±2.85)points vs.(56.46±3.53)points,P＜0.001],and significantly higher score of general self-efficacy scale(GSES)[(28.71±3.84)points vs.(20.34±1.56)points,P＜0.001],6 min walking distance(6MWD)[(428.53±5.50)m vs.(362.14±6.18)m,P＜0.001]and SpO2[(99.11±0.87)％vs.(94.23±0.73)％,P＜0.001].Conclusion:4C management mode may improve the cardiac function,self-efficacy,mental state and quality of life in patients with acute heart failure in CCU.

Objective:To explore the effects of 4C management mode on rehabilitation and quality of life in patients with acute heart failure(AHF)in cardiovascular intensive care unit(CCU).Methods:This randomized controlled study enrolled 110 patients with AHF admitted in CCU of Guangdong Provincial Hospital of Traditional Chinese Medicine between February 2021 and February 2023.Patients were randomly divided into intervention group(n=55)and control group(n=55).Patients in the control group received routine intervention,while those in the inter-vention group received additional 4C management mode,both groups were intervened for 3 months.The indexes of cardiac function,self-efficacy,exercise tolerance,blood oxygen saturation(SpO2),mental state and quality of life were compared between the two groups.Results:Compared to those in the control group after intervention,patients in the intervention group had significantly lower interventricular septal thickness(IVST)[(9.20±0.10)mm vs.(10.30±0.17)mm,P＜0.001],left ventricular end-systolic volume index(LVESVI)[(35.21±0.74)ml/m2 vs.(39.70±1.09)ml/m2,P＜0.001],left ventricular end-diastolic volume index(LVED VI)[(45.35±0.71)ml/m2 vs.(56.76±1.48)ml/m2,P＜0.001],scores of self-rating anxiety scale(SAS)[(32.10±1.57)points vs.(45.36±1.94)points,P＜0.001],self-rating depression scale(SDS)[(35.03±1.52)points vs.(47.70±2.12)points,P＜0.001]and Minnesota living with heart failure questionnaire(MLHFQ)[(51.27±2.85)points vs.(56.46±3.53)points,P＜0.001],and significantly higher score of general self-efficacy scale(GSES)[(28.71±3.84)points vs.(20.34±1.56)points,P＜0.001],6 min walking distance(6MWD)[(428.53±5.50)m vs.(362.14±6.18)m,P＜0.001]and SpO2[(99.11±0.87)％vs.(94.23±0.73)％,P＜0.001].Conclusion:4C management mode may improve the cardiac function,self-efficacy,mental state and quality of life in patients with acute heart failure in CCU.

Lung transplantation is an important means to treat end-stage lung disease and improve the survival rate and quality of life of patients. However, many postoperative complications seriously affect the prognosis of recipients. Accurate identification of key prognostic factors and construction of individualized and accurate prediction models are of great significance for postoperative prognosis evaluation, treatment strategy formulation and clinical decision-making. In recent years, the clinical prediction model of lung transplantation has gradually changed from traditional statistical methods to machine learning-driven. Compared with traditional models such as Cox regression and Logistic regression, machine learning models such as random forest, support vector machine and artificial neural network have certain advantages in postoperative survival rate prediction, early warning of complications and pulmonary function evaluation. However, their application is also affected by insufficient sample size and poor interpretability of models. Under the condition of small samples, the traditional model still has important value in prediction accuracy. The appropriate prediction model should be selected according to the clinical status of lung transplantation in China, considering the factors such as sample size, variable complexity and model interpretability. In the future, a multi-center, large-sample lung transplantation database should be constructed to further optimize and tap the potential of machine learning algorithms to improve the robustness and clinical applicability of the model.

Organ transplantation has become an effective treatment for multiple end-stage diseases. However, the recipients of organ transplantation need to take immunosuppressive drugs for a long time after operation, which leads to low immune function and relatively high incidence of bacterial, viral and fungal infections. Traditional microbial detection methods, such as pathogen culture, immunological detection and polymerase chain reaction, have been widely applied in infection detection, whereas these methods may cause problems, such as long detection time and presumed pathogens. Metagenomic next-generation sequencing has been widely adopted in infection prevention and control in organ transplantation in recent years due to high detection rate and comprehensive detection of pathogen spectrum. In this article, the application of metagenomic next-generation sequencing in the prevention and control of infection in solid organ transplantation was reviewed, aiming to provide reference for the diagnosis and treatment of transplantation-related infection.

Ovarian cancer, notable for its severe prognosis among gynecologic cancers, has seen substantial progress in treatment approaches recently. Enhanced protocols in chemotherapy and the introduction of poly (ADP-ribose) polymerase (PARP) inhibitors for maintenance therapy have markedly improved outcomes for patients with specific genetic profiles, such as those positive for BRCA mutations or exhibiting homologous recombination deficiency (HRD). Additionally, the method of intraperitoneal chemotherapy administration has emerged as a valuable alternative to traditional transvenous routes, showing promise for wider clinical adoption. The field of surgery has also evolved, with increasing exploration into the benefits and feasibility of laparoscopic methods over more invasive traditional surgeries, aiming for complete tumor removal but with reduced patient impact. The hereditary nature of ovarian cancer underscores the importance of genetic testing, which has become integral in tailoring treatment strategies, particularly in determining suitability for PARP inhibitors.The formation of the East Asian Gynecologic Oncology Trial Group (EAGOT) aims to optimize treatment across Japan, Korea, China, and Taiwan. The ovarian cancer committee of EAGOT shared the current policies, focusing on 5 topics: 1) strategies for maintenance therapy after initial surgery and chemotherapy, 2) drug regimens for platinum-sensitive and platinum-resistant recurrence, 3) intraperitoneal chemotherapy, 4) laparoscopic surgery as an alternative to laparotomy, and 5) current status of genetic testing (BRCA, HRD, and panel tests) for ovarian cancer and its prospects. EAGOT’s multi-national trials aim to harmonize these evolving treatment strategies, ensuring that the latest and most effective protocols are accessible across the region, thereby significantly impacting patient outcomes in East Asia.

Ovarian cancer, notable for its severe prognosis among gynecologic cancers, has seen substantial progress in treatment approaches recently. Enhanced protocols in chemotherapy and the introduction of poly (ADP-ribose) polymerase (PARP) inhibitors for maintenance therapy have markedly improved outcomes for patients with specific genetic profiles, such as those positive for BRCA mutations or exhibiting homologous recombination deficiency (HRD). Additionally, the method of intraperitoneal chemotherapy administration has emerged as a valuable alternative to traditional transvenous routes, showing promise for wider clinical adoption. The field of surgery has also evolved, with increasing exploration into the benefits and feasibility of laparoscopic methods over more invasive traditional surgeries, aiming for complete tumor removal but with reduced patient impact. The hereditary nature of ovarian cancer underscores the importance of genetic testing, which has become integral in tailoring treatment strategies, particularly in determining suitability for PARP inhibitors.The formation of the East Asian Gynecologic Oncology Trial Group (EAGOT) aims to optimize treatment across Japan, Korea, China, and Taiwan. The ovarian cancer committee of EAGOT shared the current policies, focusing on 5 topics: 1) strategies for maintenance therapy after initial surgery and chemotherapy, 2) drug regimens for platinum-sensitive and platinum-resistant recurrence, 3) intraperitoneal chemotherapy, 4) laparoscopic surgery as an alternative to laparotomy, and 5) current status of genetic testing (BRCA, HRD, and panel tests) for ovarian cancer and its prospects. EAGOT’s multi-national trials aim to harmonize these evolving treatment strategies, ensuring that the latest and most effective protocols are accessible across the region, thereby significantly impacting patient outcomes in East Asia.

Objective To investigate the renal protective effect and mechanism of sodium acetate(Ace)on hyperuricemic nephropathy(HN)in mice.Methods Uric acid nephropathy mice model was prepared by intraperitoneal injection of potassium oxonate combined with adenine gavage.Mice were divided into blank control group(0.9％NaCl+0.5％carboxymethyl cellulose sodium),Ace group(200 mmol·L-1 Ace+0.5％carboxymethyl cellulose sodium),model group(0.9％NaCl+350 mg·kg-1 potassium oxonate+70 mg·kg-1 adenine),and experimental group(based on model group with additional 200 mmol·L-1 Ace).Serum and urine uric acid(UA)and serum creatinine(SCr)levels were observed in each group.Real-time fluorescence quantitative reverse transcription-polymerase chain reaction(qRT-PCR)was used to detect the expression levels of kidney injury molecule-1(Kim-1)and anti-aging gene Klotho,renal fibrosis markers Collagen Ⅰ and Fibronectin,intestinal inflammation-related factors interleukin-1 β(IL-1 β),and mRNA expression levels of tight junction proteins Zo-1.Results The serum UA levels of blank control group,Ace group,model group,and experimental group mice were(259.52±24.40),(227.71±35.91),(604.06±73.55),and(496.24±30.16)μmol·L-1,respectively;SCr levels were(16.85±0.40),(16.18±0.94),(22.38±1.56),and(19.78±1.43)μmol·L-1;Kim-1 mRNA relative expression levels were 1.04±0.25,1.17±0.28,13.00±2.87,and 4.24±3.92;Klotho mRNA relative expression levels were 1.04±0.15,1.02±0.18,0.43±0.12,and 0.69±0.12;Collagen Ⅰ mRNA relative expression levels were 1.05±0.15,1.02±0.18,3.19±1.09,and 1.61±0.55;Fibronectin mRNA relative expression levels were 1.07±0.18,1.02±0.25,7.86±2.40,and 3.34±2.10;intestinal IL-1β mRNA relative expression levels were 1.00±0.01,1.01±0.03,2.55±0.63,and 1.21±0.28;intestinal Zo-1 mRNA relative expression levels were 1.00±0.07,1.07±0.09,0.54±0.20,and 0.92±0.17.The above indicators in blank control group compared with model group,and experimental group compared with model group,all showed statistically significant differences(P＜0.05,P＜0.01,P＜0.001).Conclusion Sodium acetate can effectively reduce UA levels in HN mice,significantly improve renal injury and fibrosis,and its mechanism may be related to the improvement of intestinal inflammatory response and up-regulation of intestinal Zo-1/Occuludin pathway to reduce intestinal mucosal permeability.