Objective:To explore the diagnostic value of a clinical-radiomics model based on the T 1 mapping and apparent diffusion coefficient (ADC)-based radiomics, and the clinical indicator for renal fibrosis (RF) caused by chronic kidney disease (CKD). Methods:This cross-sectional study prospectively and consecutively enrolled 122 patients with CKD at the Second Affiliated Hospital of Soochow University from September 2021 to December 2023 who were randomly allocated to a training set ( n=85) or a validation set ( n=37) in an approximate 7∶3 ratio using simple random sampling. Patients underwent T 1 mapping and diffusion-weighted imaging scans. Renal biopsy was performed within 3 days after the MRI scans. Patients were categorized into three groups based on the degree of RF: no RF ( n=25), mild RF ( n=55), and moderate to severe RF ( n=42). To differentiate the presence of RF (no RF vs. any RF) and the severity of RF (mild RF vs. moderate to severe RF), univariate and multivariate logistic regression were used to optimize the independent clinical predictor, which constituted the clinical model. Radiomics features were extracted from regions of interest delineated within the renal parenchyma of the right kidney on T 1 mapping and ADC maps. Features were selected using least absolute shrinkage and selection operator regression to build the radiomics model. A clinical-radiomics model was subsequently constructed by integrating the independent clinical predictors with the selected radiomics features. Model diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). Calibration curve was plotted to assess model calibration, and decision curve analysis was performed to evaluate clinical net benefit. Results:Univariate logistic regression analysis revealed that estimated glomerular filtration rate (eGFR), serum creatinine, and blood urea nitrogen exhibited statistically significant differences ( P0.05) in distinguishing both the presence and severity of RF. Multivariate analysis identified eGFR as an independent clinical predictor for both the presence of RF ( OR=0.939, 95% CI 0.898-0.982, P=0.006) and RF severity ( OR=0.956, 95% CI 0.917-0.997, P=0.037). From the MRI images, 7 radiomics features were selected to build the radiomics model for distinguishing the presence of RF, and 8 features were selected for the model assessing RF severity. These radiomics models were then combined with eGFR to construct the clinical-radiomics models. The clinical-radiomics models demonstrated the highest diagnostic performance, with an AUC of 0.935 (95% CI 0.859-0.977) for RF presence and 0.967 (95% CI 0.891-0.995) for RF severity in the training set, and 0.914 (95% CI 0.774-0.981) and 0.908 (95% CI 0.748-0.981) in the validation set. Calibration curves and decision curve analysis confirmed that the clinical-radiomics models exhibited excellent calibration and provided the highest clinical net benefit for assessing RF in CKD patients. Conclusion:The clinical-radiomics model integrating T 1 mapping and ADC-based radiomics and eGFR can effectively improve the diagnostic performance for RF in CKD patients.

Objective:To explore the diagnostic value of a clinical-radiomics model based on the T 1 mapping and apparent diffusion coefficient (ADC)-based radiomics, and the clinical indicator for renal fibrosis (RF) caused by chronic kidney disease (CKD). Methods:This cross-sectional study prospectively and consecutively enrolled 122 patients with CKD at the Second Affiliated Hospital of Soochow University from September 2021 to December 2023 who were randomly allocated to a training set ( n=85) or a validation set ( n=37) in an approximate 7∶3 ratio using simple random sampling. Patients underwent T 1 mapping and diffusion-weighted imaging scans. Renal biopsy was performed within 3 days after the MRI scans. Patients were categorized into three groups based on the degree of RF: no RF ( n=25), mild RF ( n=55), and moderate to severe RF ( n=42). To differentiate the presence of RF (no RF vs. any RF) and the severity of RF (mild RF vs. moderate to severe RF), univariate and multivariate logistic regression were used to optimize the independent clinical predictor, which constituted the clinical model. Radiomics features were extracted from regions of interest delineated within the renal parenchyma of the right kidney on T 1 mapping and ADC maps. Features were selected using least absolute shrinkage and selection operator regression to build the radiomics model. A clinical-radiomics model was subsequently constructed by integrating the independent clinical predictors with the selected radiomics features. Model diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). Calibration curve was plotted to assess model calibration, and decision curve analysis was performed to evaluate clinical net benefit. Results:Univariate logistic regression analysis revealed that estimated glomerular filtration rate (eGFR), serum creatinine, and blood urea nitrogen exhibited statistically significant differences ( P0.05) in distinguishing both the presence and severity of RF. Multivariate analysis identified eGFR as an independent clinical predictor for both the presence of RF ( OR=0.939, 95% CI 0.898-0.982, P=0.006) and RF severity ( OR=0.956, 95% CI 0.917-0.997, P=0.037). From the MRI images, 7 radiomics features were selected to build the radiomics model for distinguishing the presence of RF, and 8 features were selected for the model assessing RF severity. These radiomics models were then combined with eGFR to construct the clinical-radiomics models. The clinical-radiomics models demonstrated the highest diagnostic performance, with an AUC of 0.935 (95% CI 0.859-0.977) for RF presence and 0.967 (95% CI 0.891-0.995) for RF severity in the training set, and 0.914 (95% CI 0.774-0.981) and 0.908 (95% CI 0.748-0.981) in the validation set. Calibration curves and decision curve analysis confirmed that the clinical-radiomics models exhibited excellent calibration and provided the highest clinical net benefit for assessing RF in CKD patients. Conclusion:The clinical-radiomics model integrating T 1 mapping and ADC-based radiomics and eGFR can effectively improve the diagnostic performance for RF in CKD patients.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

To understand the pathogenicity,virulence genes,drug resistance genes,and drug resistance of Staphylococcus aureus isolated from yaks in some areas of Lhasa and Nagqu City,55 yak nasal swab samples were analyzed for S.aureus in this study.The cocci were isolated and identified,and the carriage of virulence genes and drug resistance genes,as well as the pathogenicity and drug sensitivity of the isolated S.aureus strains,were detected with PCR,artificially infected mice,and the K-B drug susceptibility disk method.Seven strains of S.aureus were isolated from the 55 yak nasal swab samples,with an iso-lation rate of 12.73％.The isolated strains were all pathogenic to mice,with a fatality rate exceeding 60％.These seven strains of S.aureus carried three drug resistance genes(tetM,tet,and mecA)and six virulence genes(seb,sec,clfA,hla,hlb,and nuc).The detection rate of the three drug resistance genes was 100％,whereas the detection rate of the six virulence genes in the isolates ranged from 83.33％to 100％.The resistance rates of the isolated strains to penicillin,ampicillin,and cotrimox-azole reached 85.71％-100％,whereas the resistance rates to tetracycline and ceftazidime were both 28.57％.Thus,yaks in Lhasa and Nagqu cities were found to be infected by S.aureus strains carrying various drug-resistance genes and virulence genes.These strains were highly pathogenic and showed sensi-tivity to most antibacterial drugs.These findings may serve as a reference for treating S.aureus infection in yaks in the cities of Lhasa and Nagqu.

Objective: To analyze the prevalence and the risk factors of fungal sepsis in 25 neonatal intensive care units (NICU) among preterm infants in China, and to provide a basis for preventive strategies of fungal sepsis. Methods: This was a second-analysis of the data from the "reduction of infection in neonatal intensive care units using the evidence-based practice for improving quality" study. The current status of fungal sepsis of the 24 731 preterm infants with the gestational age of <34⁺⁰ weeks, who were admitted to 25 participating NICU within 7 days of birth between May 2015 and April 2018 were retrospectively analyzed. These preterm infants were divided into the fungal sepsis group and the without fungal sepsis group according to whether they developed fungal sepsis to analyze the incidences and the microbiology of fungal sepsis. Chi-square test was used to compare the incidences of fungal sepsis in preterm infants with different gestational ages and birth weights and in different NICU. Multivariate Logistic regression analysis was used to study the outcomes of preterm infants with fungal sepsis, which were further compared with those of preterm infants without fungal sepsis. The 144 preterm infants in the fungal sepsis group were matched with 288 preterm infants in the non-fungal sepsis group by propensity score-matched method. Univariate and multivariate Logistic regression analysis were used to analyze the risk factors of fungal sepsis. Results: In all, 166 (0.7%) of the 24 731 preterm infants developed fungal sepsis, with the gestational age of (29.7±2.0) weeks and the birth weight of (1 300±293) g. The incidence of fungal sepsis increased with decreasing gestational age and birth weight (both P<0.001). The preterm infants with gestational age of <32 weeks accounted for 87.3% (145/166). The incidence of fungal sepsis was 1.0% (117/11 438) in very preterm infants and 2.0% (28/1 401) in extremely preterm infants, and was 1.3% (103/8 060) in very low birth weight infants and 1.7% (21/1 211) in extremely low birth weight infants, respectively. There was no fungal sepsis in 3 NICU, and the incidences in the other 22 NICU ranged from 0.7% (10/1 397) to 2.9% (21/724), with significant statistical difference (P<0.001). The pathogens were mainly Candida (150/166, 90.4%), including 59 cases of Candida albicans and 91 cases of non-Candida albicans, of which Candida parapsilosis was the most common (41 cases). Fungal sepsis was independently associated with increased risk of moderate to severe bronchopulmonary dysplasia (BPD) (adjusted OR 1.52, 95%CI 1.04-2.22, P=0.030) and severe retinopathy of prematurity (ROP) (adjusted OR 2.55, 95%CI 1.12-5.80, P=0.025). Previous broad spectrum antibiotics exposure (adjusted OR=2.50, 95%CI 1.50-4.17, P<0.001), prolonged use of central line (adjusted OR=1.05, 95%CI 1.03-1.08, P<0.001) and previous total parenteral nutrition (TPN) duration (adjusted OR=1.04, 95%CI 1.02-1.06, P<0.001) were all independently associated with increasing risk of fungal sepsis. Conclusions: Candida albicans and Candida parapsilosis are the main pathogens of fungal sepsis among preterm infants in Chinese NICU. Preterm infants with fungal sepsis are at increased risk of moderate to severe BPD and severe ROP. Previous broad spectrum antibiotics exposure, prolonged use of central line and prolonged duration of TPN will increase the risk of fungal sepsis. Ongoing initiatives are needed to reduce fungal sepsis based on these risk factors.
Infant ; Infant, Newborn ; Humans ; Birth Weight ; Intensive Care Units, Neonatal ; Retrospective Studies ; Tertiary Care Centers ; Infant, Extremely Low Birth Weight ; Gestational Age ; Infant, Extremely Premature ; Sepsis/epidemiology* ; Retinopathy of Prematurity/epidemiology* ; Bronchopulmonary Dysplasia/epidemiology*

Objective To explore the residual level of FPMs in indoor dust samples in Shenzhen from 2020 and 2021, and to analyze its temporal distribution characteristics. Methods In the present study, indoor dust samples (n=193) from residential buildings in Shenzhen. were collected to analyze the temporal variation characteristics of FPMs. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was applied to determine the concentrations of FP and its four major metabolites (fipronil-sulfone, fipronil-sulfide, fipronil-desulfinyl, and fipronil-amide; abbreviated as FP-SFO, FP-SFI, FP-DES, and FP-AM) in the samples. The sum of the concentrations of FP and its four metabolites was represented as additive mass concentration (ΣFPMs). Additionaly, Wilcoxon test was performed to determine the temporal distribution differences of FPMs’ concentrations. Results From 2020 to 2021, the concentration of ΣFPMs for the in door dust samples in Shenzhen ranged from 0.51 to 4 415 ng/g (median: 18.8ng/g). FP, FP-SFO AND FP-SFI were the major target analytes in the sample with detection rates of 90.60%，86.20% and 75.40%, respectively. The detection rates of other metabolites were low (≤ 44.3%). Analysis of the temporal variation trend of FPMs’ concentrations showed that there was no significant difference in the levels of ΣFPMs between warm season（spring and summer）and cold season（autumn and winter）in the indoor dust samples from 2020 to 2021(2.38 vs 2.84ng/g , P > 0.05). However , the concentrations of FP-SFI and ΣFPMs in the indoor dust samples collected from 2021 showed an significantly increasing trend compared with 2020（1.02 vs 1.89 , 17.80vs. 20.10 ng/g , P < 0.05). Conclusion From 2020 to 2021 , the detection level of FPMs in indoor dust in Shenzhen is relatively high and shows an upward trend , with no obvious seasonal difference. However, whether the residual level of FPMs in indoor dust poses a risk to human health needs further study.

Objective: To analyze and compare therapy responses, outcomes, and incidence of severe hematologic adverse events of flumatinib and imatinib in patients newly diagnosed with chronic phase chronic myeloid leukemia (CML) . Methods: Data of patients with chronic phase CML diagnosed between January 2006 and November 2022 from 76 centers, aged ≥18 years, and received initial flumatinib or imatinib therapy within 6 months after diagnosis in China were retrospectively interrogated. Propensity score matching (PSM) analysis was performed to reduce the bias of the initial TKI selection, and the therapy responses and outcomes of patients receiving initial flumatinib or imatinib therapy were compared. Results: A total of 4 833 adult patients with CML receiving initial imatinib (n=4 380) or flumatinib (n=453) therapy were included in the study. In the imatinib cohort, the median follow-up time was 54 [interquartile range (IQR), 31-85] months, and the 7-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.2%, 88.4%, 78.3%, and 63.0%, respectively. The 7-year FFS, PFS, and OS rates were 71.8%, 93.0%, and 96.9%, respectively. With the median follow-up of 18 (IQR, 13-25) months in the flumatinib cohort, the 2-year cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) were 95.4%, 86.5%, 58.4%, and 46.6%, respectively. The 2-year FFS, PFS, and OS rates were 80.1%, 95.0%, and 99.5%, respectively. The PSM analysis indicated that patients receiving initial flumatinib therapy had significantly higher cumulative incidences of CCyR, MMR, MR(4), and MR(4.5) and higher probabilities of FFS than those receiving the initial imatinib therapy (all P<0.001), whereas the PFS (P=0.230) and OS (P=0.268) were comparable between the two cohorts. The incidence of severe hematologic adverse events (grade≥Ⅲ) was comparable in the two cohorts. Conclusion: Patients receiving initial flumatinib therapy had higher cumulative incidences of therapy responses and higher probability of FFS than those receiving initial imatinib therapy, whereas the incidence of severe hematologic adverse events was comparable between the two cohorts.
Adult ; Humans ; Adolescent ; Imatinib Mesylate/adverse effects* ; Incidence ; Antineoplastic Agents/adverse effects* ; Retrospective Studies ; Pyrimidines/adverse effects* ; Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy* ; Treatment Outcome ; Benzamides/adverse effects* ; Leukemia, Myeloid, Chronic-Phase/drug therapy* ; Aminopyridines/therapeutic use* ; Protein Kinase Inhibitors/therapeutic use*

Objective: To analyze the feasibility and safety of bridge therapy with active fixed electrodes connected to external permanent pacemakers (AFLEP) for patients with infective endocarditis after lead removal and before permanent pacemaker implantation. Methods: A total of 44 pacemaker-dependent patients, who underwent lead removal due to infective endocarditis in our center from January 2015 to January 2020, were included. According to AFLEP or temporary pacemaker option during the transition period, patients were divided into AFLEP group or temporary pacemaker group. Information including age, sex, comorbidities, indications and types of cardial implantable electionic device (CIED) implantation, lead age, duration of temporary pacemaker or AFLEP use, and perioperative complications were collected through Haitai Medical Record System. The incidence of pacemaker perception, abnormal pacing function, lead perforation, lead dislocation, lead vegetation, cardiac tamponade, pulmonary embolism, death and newly infection of implanted pacemaker were compared between the two groups. Pneumothorax, hematoma and the incidence of deep vein thrombosis were also analyzed. Results: Among the 44 patients, 24 were in the AFLEP group and 20 in the temporary pacemaker group. Age was younger in the AFLEP group than in the temporary pacemaker group (57.5(45.5, 66.0) years vs. 67.0(57.3, 71.8) years, P=0.023). Male, prevalence of hypertension, diabetes mellitus, chronic renal dysfunction and old myocardial infarction were similar between the two groups (all P>0.05). Lead duration was 11.0(8.0,13.0) years in the AFLEP group and 8.5(7.0,13.0) years in the temporary pacemaker group(P=0.292). Lead vegetation diameter was (8.2±2.4)mm in the AFLEP group and (9.1±3.0)mm in the temporary pacemaker group. Lead removal was successful in all patients. The follow-up time in the AFLEP group was 23.0(20.5, 25.5) months, and the temporary pacemaker group was 17.0(14.5, 18.5) months. In the temporary pacemaker group, there were 2 cases (10.0%) of lead dislocation, 2 cases (10.0%) of sensory dysfunction, 2 cases (10.0%) of pacing dysfunction, and 2 cases (10.0%) of death. In the AFLEP group, there were 2 cases of abnormal pacing function, which improved after adjusting the output voltage of the pacemaker, there was no lead dislocation, abnormal perception and death. Femoral vein access was used in 8 patients (40.0%) in the temporary pacemaker group, and 4 patients developed lower extremity deep venous thrombosis. There was no deep venous thrombosis in the AFLEP group. The transition treatment time was significantly longer in the AFLEP group than in the temporary pacemaker group (19.5(16.0, 25.8) days vs. 14.0(12.0, 16.8) days, P=0.001). During the follow-up period, there were no reinfections with newly implanted pacemakers in the AFLEP group, and reinfection occurred in 2 patients (10.0%) in the temporary pacemaker group. Conclusions: Bridge therapy with AFLEP for patients with infective endocarditis after lead removal and before permanent pacemaker implantation is feasible and safe. Compared with temporary pacemaker, AFLEP is safer in the implantation process and more stable with lower lead dislocation rate, less sensory and pacing dysfunction.
Humans ; Male ; Bridge Therapy ; Feasibility Studies ; Pacemaker, Artificial ; Endocarditis, Bacterial/etiology* ; Electrodes ; Device Removal