ObjectiveTo analyze the trend of incidence, mortality rate and survival rate of breast cancer among women with registered residence in Xiaoshan District of Hangzhou City in Zhejiang Province from 2014 to 2023, and to provide a basis for improving breast cancer prevention and control strategies. MethodsData on the incidence and mortality of breast cancer among women with registered residence in Xiaoshan District from 2014 to 2023 were collected through Zhejiang Chronic Disease Monitoring and Management System. The crude incidence and mortality rate, as well as the age-standardized incidence and mortality rate using both the 2000 Chinese standard population (abbreviated as “Chinese ASR”) and Segi’s 1960 world standard population (“world ASR”) were calculated. Joinpoint model was employed to analyze the trends in incidence and mortality rate, while R software (version 4.1.1) was used to analyze the 5-year relative survival rate to assess the survival status of breast cancer patients. ResultsFrom 2014 to 2023, the crude incidence rate, the Chinese age-standardized incidence rate (ASIRC) and the world age-standardized incidence rate (ASIRW) of breast cancer among women with registered residence in Xiaoshan District were from 70.00/100 000 to 128.35/100 000, from 52.92/100 000 to 94.29/100 000, and from 40.82/100 000 to 72.07/100 000, respectively, with the corresponding average annual percentage changes (AAPC) of 5.80%, 4.63% and 4.71%, respectively, showing a significant increasing trend over the decade (all P<0.05). The incidence rate of breast cancer among people aged 30‒<40 years old or 50‒<75 years old exhibited a significant increase trend from 2014 to 2023 (all P<0.05). The crude mortality rate of breast cancer in female was from 7.75/100 000 to 12.34/100 000, the ASMRC of breast cancer in female was from 4.62/100 000 to 7.53/100 000, and the ASMRW of breast cancer in female was from 3.58/100 000 to 5.71/100 000, and the AAPC had no statistically significance. However, the mortality rate of breast cancer was increased with age (P<0.001). The 5-year age-standardized relative survival rate of breast cancer in female in Xiaoshan District was significantly higher in the 2016‒2018 period (94.46%) compared to the 2013‒2015 period (91.02%) (P<0.05). ConclusionFrom 2014 to 2023, the annual incidence of breast cancer among women with registered residence in Xiaoshan District of Hangzhou City in Zhejiang Province showed an increasing trend, while the change in mortality rate was not statistically significant. The 5-year survival rate of breast cancer in female was at a high level, indicating notable achievements in comprehensive prevention and control efforts. It is essential to continue to strengthen public awareness campaigns for breast cancer prevention and control, control breast cancer risk factors, actively carry out early diagnosis and treatment of breast cancer among target groups, and improve the quality of life for breast cancer patients.

Objective To explore the factors influencing blood drug concentrations of first-line anti-tuberculosis drugs in fixed-dose combinations by analyzing therapeutic drug monitoring data from tuberculosis patients receiving these regimens.Methods This retrospective study enrolled 224 patients who received treatment at Guangzhou Chest Hospital between January 2020 and December 2024.All participants underwent standardized therapy during the intensive phase,with therapeutic drug monitoring of first-line anti-tuberculosis drugs(ANTDs),including isoniazid(INH)and rifampicin(RFP).Data collection was completed in January 2025,at which time clinical records and measured INH and RFP plasma concentrations were updated.Data analysis was conducted from January to February 2025.Eight baseline variables—gender,age,hypoproteinemia(serum albumin<35 g/L),glomerular filtration rate(GFR),and others—were collected.Univariate chi-square tests and multivariate logistic regression analyses were performed to identify independent risk factors associated with subtherapeutic INH and RFP plasma concentrations.Results Among the study participants,71.43%(160/224)exhibited blood drug concentrations below the reference range for INH,compared to 41.07%(92/224)for RFP.The mean blood concentrations(mg/L,±SD)were 2.532±1.371 for INH and 9.428±4.317 for RFP,respectively.One-way analysis indicated significant associations between male gender,positive etiological test results,and subtherapeutic RFP concentrations(P<0.05),suggesting statistically significant differences.Multivariate regression analysis further revealed that male gender(OR=1.992,95%CI:1.094～3.628)and positive etiological tests(OR=1.929,95%CI:1.058～3.517)were independent risk factors for low RFP levels.Conclusions This study demonstrates that therapeutic drug monitoring(TDM)frequently identifies subtherapeutic RFP concentrations in tuberculosis patients undergoing treatment.Multivariate analysis reveals that male sex and positive pathogen test results are independent risk factors associated with low RFP plasma levels.Consequently,clinicians should exercise heightened vigilance in patients exhibiting these characteristics,promptly implementing TDM to guide individualized dose adjustments.Such an approach is crucial for optimizing treatment efficacy and minimizing the risk of drug resistance development.

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.

Sacroiliac complex injuries are commonly seen in high-energy pelvic fractures. The injuries make a big difference in treatment patterns due to the diverse injury types, posing considerable challenges in formulating optimal treatment strategies, and hence are persistent clinical difficulties in orthopedic trauma. The clinical management of sacroiliac complex injuries presents several key challenges such as a non-negligible rate of missed diagnoses in associated vascular and visceral injuries, absence of standardized protocols for surgical approaches and reduction-fixation strategies across different injury patterns, and ongoing controversies regarding surgical indications and optimal timing for patients combined with concomitant lumbosacral plexus injuries. Currently, no systematic clinical guidelines are available for the diagnosis and treatment of sacroiliac complex injuries both domestically and internationally. To this end, the Pelvic and Acetabular Surgery Group, Orthopedic Branch, China International Exchange and Promotive Association for Medical and Health Care and Orthopedic Physician Branch, Chinese Medical Doctor Association organized a panel of domestic experts in the field to develop the Clinical guideline for the diagnosis and treatment of sacroiliac complex injuries ( version 2025), based on evidence-based medicine and adhering to the principles of scientific rigor, clinical applicability, and innovation. These guidelines provided 11 recommendations covering diagnosis, therapeutic principles and techniques, management protocols for lumbosacral plexus injuries, outcome evaluation, and postoperative rehabilitation pathways, etc., aiming to standardize the clinical management of sacroiliac complex injuries.

ObjectiveTo analyze the incidence rate and mortality of acute myocardial infarction (AMI) and their changing trends among the registered residents in Xiaoshan District, Hangzhou City from 2017 to 2023, so as to provide references for formulating policies related to AMI prevention. MethodsThe morbidity and mortality data of AMI among the registered residents in Xiaoshan District from 2017 to 2023 were collected through the Hangzhou Chronic Disease and Death Cause Monitoring System. Software such as Excel 2019, SPSS 25.0 and Joinpoint 4.9.1.0 were used to calculate the incidence rate, mortality, and average annual percentage change (AAPC) of AMI. ResultsFrom 2017 to 2023, the average annual crude incidence rate, age-standardized incidence rate using China standard population (ASIRC), and the age-standardized incidence rate using World standard population (ASIRW) of AMI in Xiaoshan District were 48.25/100 000, 29.14/100 000, and 21.64/100 000, respectively, and, from which the AAPCs were 5.495%, 6.010%, and 6.533%, respectively, all showing an upward trend. The average annual crude mortality rate, the age-standardized mortality rate using China standard population (ASMRC), and the age-standardized mortality rate using World standard population (ASMRW) were 11.76/100 000, 6.52/100 000, and 4.71/100 000, respectively, from which the AAPCs were -9.669%, -10.433% and -9.615%, respectively, all showing a downward trend. The average annual crude incidence rate of AMI was higher in males (65.87/100 000) than that in females (31.31/100 000). Moreover, the average annual crude mortality rate of AMI was higher in males (14.08/100 000) than that in females (9.52/100 000), and the difference was statistically significant (all P<0.001) .After age grouping, the crude incidence rate of AMI among the residents aged 35-, 45-, 55-, and 65- years in Xiaoshan District from 2017 to 2023 showed an upward trend over time, with AAPCs of 16.993%, 17.149%, 8.523%, and 5.002%, respectively. While the crude mortality rate in residents aged 35-, 75-, and 85-102 years showed an decreasing trend over time, with AAPCs of -23.977%, -15.467%, and -17.415%, respectively, but there was no statistically significant difference in the trends in incidence rate and mortality of other age groups (all P>0.05). ConclusionThe situation of AMI prevention and control among the registered residents in Xiaoshan District is not optimistic, and targeted measures should be strengthened for the male residents aged ≥35 years old.

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.

Sacroiliac complex injuries are commonly seen in high-energy pelvic fractures. The injuries make a big difference in treatment patterns due to the diverse injury types, posing considerable challenges in formulating optimal treatment strategies, and hence are persistent clinical difficulties in orthopedic trauma. The clinical management of sacroiliac complex injuries presents several key challenges such as a non-negligible rate of missed diagnoses in associated vascular and visceral injuries, absence of standardized protocols for surgical approaches and reduction-fixation strategies across different injury patterns, and ongoing controversies regarding surgical indications and optimal timing for patients combined with concomitant lumbosacral plexus injuries. Currently, no systematic clinical guidelines are available for the diagnosis and treatment of sacroiliac complex injuries both domestically and internationally. To this end, the Pelvic and Acetabular Surgery Group, Orthopedic Branch, China International Exchange and Promotive Association for Medical and Health Care and Orthopedic Physician Branch, Chinese Medical Doctor Association organized a panel of domestic experts in the field to develop the Clinical guideline for the diagnosis and treatment of sacroiliac complex injuries ( version 2025), based on evidence-based medicine and adhering to the principles of scientific rigor, clinical applicability, and innovation. These guidelines provided 11 recommendations covering diagnosis, therapeutic principles and techniques, management protocols for lumbosacral plexus injuries, outcome evaluation, and postoperative rehabilitation pathways, etc., aiming to standardize the clinical management of sacroiliac complex injuries.

Objective To explore the factors influencing blood drug concentrations of first-line anti-tuberculosis drugs in fixed-dose combinations by analyzing therapeutic drug monitoring data from tuberculosis patients receiving these regimens.Methods This retrospective study enrolled 224 patients who received treatment at Guangzhou Chest Hospital between January 2020 and December 2024.All participants underwent standardized therapy during the intensive phase,with therapeutic drug monitoring of first-line anti-tuberculosis drugs(ANTDs),including isoniazid(INH)and rifampicin(RFP).Data collection was completed in January 2025,at which time clinical records and measured INH and RFP plasma concentrations were updated.Data analysis was conducted from January to February 2025.Eight baseline variables—gender,age,hypoproteinemia(serum albumin<35 g/L),glomerular filtration rate(GFR),and others—were collected.Univariate chi-square tests and multivariate logistic regression analyses were performed to identify independent risk factors associated with subtherapeutic INH and RFP plasma concentrations.Results Among the study participants,71.43%(160/224)exhibited blood drug concentrations below the reference range for INH,compared to 41.07%(92/224)for RFP.The mean blood concentrations(mg/L,±SD)were 2.532±1.371 for INH and 9.428±4.317 for RFP,respectively.One-way analysis indicated significant associations between male gender,positive etiological test results,and subtherapeutic RFP concentrations(P<0.05),suggesting statistically significant differences.Multivariate regression analysis further revealed that male gender(OR=1.992,95%CI:1.094～3.628)and positive etiological tests(OR=1.929,95%CI:1.058～3.517)were independent risk factors for low RFP levels.Conclusions This study demonstrates that therapeutic drug monitoring(TDM)frequently identifies subtherapeutic RFP concentrations in tuberculosis patients undergoing treatment.Multivariate analysis reveals that male sex and positive pathogen test results are independent risk factors associated with low RFP plasma levels.Consequently,clinicians should exercise heightened vigilance in patients exhibiting these characteristics,promptly implementing TDM to guide individualized dose adjustments.Such an approach is crucial for optimizing treatment efficacy and minimizing the risk of drug resistance development.

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.