1.Correlation between serum homocysteine, folic acid and sperm DNA fragmentation index
LE Yun ; ZHU Yurong ; ZHU Mengyi ; WANG Tengfei ; SHAO Shengsheng ; CHEN Xiaojun ; YANG Sheng
Journal of Preventive Medicine 2025;37(4):400-403
Objective:
To analyze the correlation between serum homocysteine (Hcy) and both folic acid (FA) and sperm DNA fragmentation index (DFI), so as to provide the evidence for male fertility assessment.
Methods:
Males who visited and measured the serum Hcy in the Reproductive Medicine Center of Huzhou Maternal and Child Health Care Hospital from September 2022 to September 2023 were selected as the study subjects. Sperm quality parameters and sperm DFI were analyzed by collecting sperm. Hcy and FA were measured by collecting venous blood. Participants were stratified into a high Hcy group (Hcy≥15.0 μmol/L) and a normal group (Hcy<15.0 μmol/L). The correlations between serum Hcy and FA and sperm DFI were evaluated using linear regression models.
Results:
A total of 173 participants were enrolled, including 39 in the high Hcy group and 134 in the normal group. The sperm concentration in the high Hcy group was significantly lower than that in the normal group [(91.77±61.11)×106/mL vs. (144.21±106.82)×106/mL, P<0.05]. No statistically significant differences were observed in semen volume, sperm motility, curvilinear velocity, straight-line velocity, average path velocity, or sperm morphology normal rate (all P>0.05). The FA level in the high Hcy group was lower than that in the normal group [(4.44±1.79) nmol/L vs. (7.64±3.68) nmol/L, P<0.05]. The sperm DFI in the high Hcy group was higher than that in the normal group [(19.21±8.85)% vs. (13.07±6.43)%, P<0.05]. Serum Hcy level showed a negative correlation with FA level (r=-0.369, P<0.05) and a positive correlation with sperm DFI (r=0.351, P<0.05).
Conclusion
Serum Hcy level is associated with sperm concentration, FA and sperm DFI, suggesting that serum Hcy may affect sperm quality.
2.Multidimensional CT radiomics for preoperative prediction of TFE3-rearranged renal cell carcinoma
Bin XIA ; Chengwei CHEN ; Na LI ; Yun BIAN ; Chengwei SHAO ; Jianping LU ; Qinqin KANG
Chinese Journal of Urology 2025;46(5):343-348
Objective:To develop a preoperative CT-based radiomics model integrating multidimensional features for the accurate prediction of TFE3-rearranged renal cell carcinoma(TFE3-rRCC).Methods:This study retrospectively enrolled 865 pathologically confirmed renal cell carcinoma(RCC)patients in The First Affiliated Hospital of Naval Medical University from June 2013 to June 2023,including 60 cases of TFE3-rRCC and 805 cases of non-TFE3 RCC(comprising clear cell RCC,papillary RCC,and chromophobe RCC). Among them,627 were male and 238 were female,with a mean age of(54.1 ± 12.7)years(range:14?82 years). The median maximum tumor diameter was 4.0(2.6,6.0)cm. Based on the chronological order of CT examinations,the patients were divided into training( n=478),validation( n=206),and test( n=181)sets in an approximate 6∶2∶2 ratio. Using precontrast and corticomedullary phase CT images,we extracted peritumoral imaging features,habitat features,3D radiomic features,and 2.5D deep learning radiomic features. A deep learning radiomics score(DLR-SCORE)prediction model was constructed using least absolute shrinkage and selection operator(LASSO)regression. The diagnostic performance of the model was evaluated by receiver operating characteristic(ROC)curve analysis,with the area under the curve(AUC)as the primary metric. Additionally,sensitivity,specificity,and accuracy were calculated based on the confusion matrix. Results:A total of 12 442 features were extracted from non-contrast and corticomedullary phase CT images,from which eight key features were selected to construct the DLR-SCORE model. The model demonstrated diagnostic accuracies for TFE3-rRCC of 98.5%(471/478)in the training set,81.6%(168/206)in the validation set,and 86.2%(156/181)in the test set. The AUC of ROC curve was 0.98(95% CI 0.96?1.00)in the training set,0.83(95% CI 0.71?0.94)in the validation set,and 0.88(95% CI 0.76?1.00)in the test set. In the test set,the DLR-SCORE model achieved a sensitivity of 88.9%(16/18)and a specificity of 85.9%(140/163)for detecting TFE3-rRCC. Conclusions:The DLR-SCORE model integrating multidimensional CT radiomics features demonstrated favorable predictive performance for TFE3-rRCC,offering a promising noninvasive tool to assist preoperative diagnosis.
3.Application of 3D-printed auxiliary guides in adolescent scoliosis surgery.
Dong HOU ; Jian-Tao WEN ; Chen ZHANG ; Jin HUANG ; Chang-Quan DAI ; Kai LI ; Han LENG ; Jing ZHANG ; Shao-Bo YANG ; Xiao-Juan CUI ; Juan WANG ; Xiao-Yun YUAN
China Journal of Orthopaedics and Traumatology 2025;38(11):1119-1125
OBJECTIVE:
To investigate the accuracy and safety of pedicle screw placement using 3D-printed auxiliary guides in scoliosis correction surgery for adolescents.
METHODS:
A retrospective analysis was conducted on the clinical data of 51 patients who underwent posterior scoliosis correction surgery from January 2020 to March 2023. Among them, there were 35 cases of adolescent idiopathic scoliosis and 16 cases of congenital scoliosis. The patients were divided into two groups based on the auxiliary tool used:the 3D-printed auxiliary guide screw placement group (3D printing group) and the free-hand screw placement group (free-hand group, without auxiliary tools). The 3D printing group included 32 patients (12 males and 20 females) with an average age of (12.59±2.60) years;the free-hand group included 19 patients (7 males and 12 females) with an average age of (14.58±3.53) years. The two groups were compared in terms of screw placement accuracy and safety, spinal correction rate, intraoperative blood loss, number of intraoperative fluoroscopies, operation time, hospital stay, and preoperative and last follow-up scores of the Scoliosis Research Society-22 (SRS-22) questionnaire.
RESULTS:
A total of 707 pedicle screws were placed in the two groups, with 441 screws in the 3D printing group and 266 screws in the free-hand group. All patients in both groups successfully completed the surgery. There was a statistically significant difference in operation time between the two groups (P<0.05). The screw placement accuracy rate of the 3D printing group was 95.46% (421/441), among which the Grade A placement rate was 89.34% (394/441);the screw placement accuracy rate of the free-hand group was 86.47% (230/266), with a Grade A placement rate of 73.31% (195/266). There were statistically significant differences in the accuracy of Grade A, B, and C screw placements between the two groups (P<0.05), while no statistically significant differences were observed in intraoperative blood loss, number of fluoroscopies, correction rate, or hospital stay (P>0.05). In the SRS-22 questionnaire scores, the scores of functional status and activity ability, self-image, mental status, and pain of patients in each group at the last follow-up were significantly improved compared with those before surgery (P<0.05), but there were no statistically significant differences in all scores between the two groups (P>0.05).
CONCLUSION
In scoliosis correction surgery, compared with traditional free-hand screw placement, the use of 3D-printed auxiliary guides for screw placement significantly improves the accuracy and safety of screw placement and shortens the operation time.
Humans
;
Male
;
Scoliosis/surgery*
;
Female
;
Adolescent
;
Printing, Three-Dimensional
;
Retrospective Studies
;
Pedicle Screws
;
Child
4.Postdischarge cancer and mortality in patients with coronary artery disease: a retrospective cohort study.
Yi-Hao WANG ; Shao-Ning ZHU ; Ya-Wei ZHAO ; Kai-Xin YAN ; Ming-Zhuang SUN ; Zhi-Jun SUN ; Yun-Dai CHEN ; Shun-Ying HU
Journal of Geriatric Cardiology 2025;22(6):578-586
BACKGROUND:
Our understanding of the correlation between postdischarge cancer and mortality in patients with coronary artery disease (CAD) remains incomplete. The aim of this study was to investigate the relationships between postdischarge cancers and all-cause mortality and cardiovascular mortality in CAD patients.
METHODS:
In this retrospective cohort study, 25% of CAD patients without prior cancer history who underwent coronary artery angiography between January 1, 2011 and December 31, 2015, were randomly enrolled using SPSS 26.0. Patients were monitored for the incidence of postdischarge cancer, which was defined as cancer diagnosed after the index hospitalization, survival status and cause of death. Cox regression analysis was used to explore the association between postdischarge cancer and all-cause mortality and cardiovascular mortality in CAD patients.
RESULTS:
A total of 4085 patients were included in the final analysis. During a median follow-up period of 8 years, 174 patients (4.3%) developed postdischarge cancer, and 343 patients (8.4%) died. A total of 173 patients died from cardiovascular diseases. Postdischarge cancer was associated with increased all-cause mortality risk (HR = 2.653, 95% CI: 1.727-4.076, P < 0.001) and cardiovascular mortality risk (HR = 2.756, 95% CI: 1.470-5.167, P = 0.002). Postdischarge lung cancer (HR = 5.497, 95% CI: 2.922-10.343, P < 0.001) and gastrointestinal cancer (HR = 1.984, 95% CI: 1.049-3.750, P = 0.035) were associated with all-cause mortality in CAD patients. Postdischarge lung cancer was significantly associated with cardiovascular death in CAD patients (HR = 4.979, 95% CI: 2.114-11.728, P < 0.001), and cardiovascular death was not significantly correlated with gastrointestinal cancer or other types of cancer.
CONCLUSIONS
Postdischarge cancer was associated with all-cause mortality and cardiovascular mortality in CAD patients. Compared with other cancers, postdischarge lung cancer had a more significant effect on all-cause mortality and cardiovascular mortality in CAD patients.
5.Efficacy and Safety of Yangxue Qingnao Pills Combined with Amlodipine in Treatment of Hypertensive Patients with Blood Deficiency and Gan-Yang Hyperactivity: A Multicenter, Randomized Controlled Trial.
Fan WANG ; Hai-Qing GAO ; Zhe LYU ; Xiao-Ming WANG ; Hui HAN ; Yong-Xia WANG ; Feng LU ; Bo DONG ; Jun PU ; Feng LIU ; Xiu-Guang ZU ; Hong-Bin LIU ; Li YANG ; Shao-Ying ZHANG ; Yong-Mei YAN ; Xiao-Li WANG ; Jin-Han CHEN ; Min LIU ; Yun-Mei YANG ; Xiao-Ying LI
Chinese journal of integrative medicine 2025;31(3):195-205
OBJECTIVE:
To evaluate the clinical efficacy and safety of Yangxue Qingnao Pills (YXQNP) combined with amlodipine in treating patients with grade 1 hypertension.
METHODS:
This is a multicenter, randomized, double-blind, and placebo-controlled study. Adult patients with grade 1 hypertension of blood deficiency and Gan (Liver)-yang hyperactivity syndrome were randomly divided into the treatment or the control groups at a 1:1 ratio. The treatment group received YXQNP and amlodipine besylate, while the control group received YXQNP's placebo and amlodipine besylate. The treatment duration lasted for 180 days. Outcomes assessed included changes in blood pressure, Chinese medicine (CM) syndrome scores, symptoms and target organ functions before and after treatment in both groups. Additionally, adverse events, such as nausea, vomiting, rash, itching, and diarrhea, were recorded in both groups.
RESULTS:
A total of 662 subjects were enrolled, of whom 608 (91.8%) completed the trial (306 in the treatment and 302 in the control groups). After 180 days of treatment, the standard deviations and coefficients of variation of systolic and diastolic blood pressure levels were lower in the treatment group compared with the control group. The improvement rates of dizziness, headache, insomnia, and waist soreness were significantly higher in the treatment group compared with the control group (P<0.05). After 30 days of treatment, the overall therapeutic effects on CM clinical syndromes were significantly increased in the treatment group as compared with the control group (P<0.05). After 180 days of treatment, brachial-ankle pulse wave velocity, ankle brachial index and albumin-to-creatinine ratio were improved in both groups, with no statistically significant differences (P>0.05). No serious treatment-related adverse events occurred during the study period.
CONCLUSIONS
Combination therapy of YXQNP with amlodipine significantly improved symptoms such as dizziness and headache, reduced blood pressure variability, and showed a trend toward lowering urinary microalbumin in hypertensive patients. These findings suggest that this regimen has good clinical efficacy and safety. (Registration No. ChiCTR1900022470).
Humans
;
Amlodipine/adverse effects*
;
Drugs, Chinese Herbal/adverse effects*
;
Male
;
Female
;
Hypertension/complications*
;
Middle Aged
;
Treatment Outcome
;
Drug Therapy, Combination
;
Adult
;
Blood Pressure/drug effects*
;
Double-Blind Method
;
Aged
;
Antihypertensive Agents/adverse effects*
6.Multi-scale radiomics combined with deep learning for pancreatic cancer prognosis prediction: model construction and validation
Yixuan SHEN ; Chengwei CHEN ; Wenbin LIU ; Xinyue ZHANG ; Yun BIAN ; Chengwei SHAO
Chinese Journal of Hepatobiliary Surgery 2025;31(9):678-684
Objective:A prognosis prediction model for pancreatic cancer was constructed based on multi-scale radiomics combined with deep learning, and the prediction effect of the model was evaluated.Methods:A retrospective analysis was conducted on the clinical data of 215 patients who underwent radical resection of pancreatic cancer at the First Affiliated Hospital of Naval Medical University from January 2017 to December 2017. Among them, 134 were male and 81 were female, with an age of (61.9±9.2) years. Patients were randomly divided into the training set ( n=151) and the test set ( n=64) in a ratio of 7: 3. Habitat features, peritumoral radiomics features, 3D radiomics features, and 2.5D deep learning features were extracted from preoperative CT images respectively. After feature screening, a survival prediction model was constructed using the CoxBoost machine learning algorithm that integrated the Boosting algorithm and the Cox proportional hazards model. The performance of the model was evaluated using the area under the time-dependent receiver operating characteristic curve and the consistency index. The clinical benefits of the model were evaluated using decision curve analysis. The survival curves were plotted using the Kaplan-Meier method, and the log-rank test was used for the comparison of survivals between groups. Results:The LASSO, random forest and extreme gradient boosting models were each used to screen out the top 10 most important features and take the union, ultimately obtaining 20 radiomics features for modeling. In the training set and test set, the consistency index of the CoxBoost model in predicting overall survival was 0.717 (95% CI: 0.669-0.765) and 0.688 (95% CI: 0.610-0.766), respectively, and the area under the curve for predicting overall survival at 1, 2, and 3 years after surgery was 0.830 (95% CI: 0.752-0.898), 0.753 (95% CI: 0.665-0.833), 0.828 (95% CI: 0.735-0.908) and 0.690 (95% CI: 0.549-0.824), 0.780 (95% CI: 0.649-0.887 and 0.793 (95% CI: 0.660-0.897), respectively. The area under the curve for predicting long-term survival after surgery (≥40 months) was above 0.8. Based on the optimal cutoff value of -0.19 for the predicted value of the CoxBoost model calculated by the R package " survminer", the patients were divided into high-risk (predicted value >-0.19) and low-risk (predicted value <-0.19) groups. In both the training set and the test set, the survival of patients in the low-risk group was better than that in the high-risk group (training set: χ2=39.01, P<0.001; test set: χ2=12.34, P<0.001). The median survival period of patients in the high-risk group was lower than that in the low-risk group (training set: 15.80 vs 34.07 months; test set: 16.87 vs 43.07; months). Decision curve analysis shows that patients obtain survival benefit when the threshold probability of the training set is greater than 0.25 and that of the test set is greater than 0.45. Conclusion:The CoxBoost model has a good predictive ability for the overall survival of pancreatic cancer patients after surgery and can effectively screen out patient subgroups that may significantly benefit from surgical treatment.
7.Multidimensional CT radiomics for preoperative prediction of TFE3-rearranged renal cell carcinoma
Bin XIA ; Chengwei CHEN ; Na LI ; Yun BIAN ; Chengwei SHAO ; Jianping LU ; Qinqin KANG
Chinese Journal of Urology 2025;46(5):343-348
Objective:To develop a preoperative CT-based radiomics model integrating multidimensional features for the accurate prediction of TFE3-rearranged renal cell carcinoma(TFE3-rRCC).Methods:This study retrospectively enrolled 865 pathologically confirmed renal cell carcinoma(RCC)patients in The First Affiliated Hospital of Naval Medical University from June 2013 to June 2023,including 60 cases of TFE3-rRCC and 805 cases of non-TFE3 RCC(comprising clear cell RCC,papillary RCC,and chromophobe RCC). Among them,627 were male and 238 were female,with a mean age of(54.1 ± 12.7)years(range:14?82 years). The median maximum tumor diameter was 4.0(2.6,6.0)cm. Based on the chronological order of CT examinations,the patients were divided into training( n=478),validation( n=206),and test( n=181)sets in an approximate 6∶2∶2 ratio. Using precontrast and corticomedullary phase CT images,we extracted peritumoral imaging features,habitat features,3D radiomic features,and 2.5D deep learning radiomic features. A deep learning radiomics score(DLR-SCORE)prediction model was constructed using least absolute shrinkage and selection operator(LASSO)regression. The diagnostic performance of the model was evaluated by receiver operating characteristic(ROC)curve analysis,with the area under the curve(AUC)as the primary metric. Additionally,sensitivity,specificity,and accuracy were calculated based on the confusion matrix. Results:A total of 12 442 features were extracted from non-contrast and corticomedullary phase CT images,from which eight key features were selected to construct the DLR-SCORE model. The model demonstrated diagnostic accuracies for TFE3-rRCC of 98.5%(471/478)in the training set,81.6%(168/206)in the validation set,and 86.2%(156/181)in the test set. The AUC of ROC curve was 0.98(95% CI 0.96?1.00)in the training set,0.83(95% CI 0.71?0.94)in the validation set,and 0.88(95% CI 0.76?1.00)in the test set. In the test set,the DLR-SCORE model achieved a sensitivity of 88.9%(16/18)and a specificity of 85.9%(140/163)for detecting TFE3-rRCC. Conclusions:The DLR-SCORE model integrating multidimensional CT radiomics features demonstrated favorable predictive performance for TFE3-rRCC,offering a promising noninvasive tool to assist preoperative diagnosis.
8.Multi-scale radiomics combined with deep learning for pancreatic cancer prognosis prediction: model construction and validation
Yixuan SHEN ; Chengwei CHEN ; Wenbin LIU ; Xinyue ZHANG ; Yun BIAN ; Chengwei SHAO
Chinese Journal of Hepatobiliary Surgery 2025;31(9):678-684
Objective:A prognosis prediction model for pancreatic cancer was constructed based on multi-scale radiomics combined with deep learning, and the prediction effect of the model was evaluated.Methods:A retrospective analysis was conducted on the clinical data of 215 patients who underwent radical resection of pancreatic cancer at the First Affiliated Hospital of Naval Medical University from January 2017 to December 2017. Among them, 134 were male and 81 were female, with an age of (61.9±9.2) years. Patients were randomly divided into the training set ( n=151) and the test set ( n=64) in a ratio of 7: 3. Habitat features, peritumoral radiomics features, 3D radiomics features, and 2.5D deep learning features were extracted from preoperative CT images respectively. After feature screening, a survival prediction model was constructed using the CoxBoost machine learning algorithm that integrated the Boosting algorithm and the Cox proportional hazards model. The performance of the model was evaluated using the area under the time-dependent receiver operating characteristic curve and the consistency index. The clinical benefits of the model were evaluated using decision curve analysis. The survival curves were plotted using the Kaplan-Meier method, and the log-rank test was used for the comparison of survivals between groups. Results:The LASSO, random forest and extreme gradient boosting models were each used to screen out the top 10 most important features and take the union, ultimately obtaining 20 radiomics features for modeling. In the training set and test set, the consistency index of the CoxBoost model in predicting overall survival was 0.717 (95% CI: 0.669-0.765) and 0.688 (95% CI: 0.610-0.766), respectively, and the area under the curve for predicting overall survival at 1, 2, and 3 years after surgery was 0.830 (95% CI: 0.752-0.898), 0.753 (95% CI: 0.665-0.833), 0.828 (95% CI: 0.735-0.908) and 0.690 (95% CI: 0.549-0.824), 0.780 (95% CI: 0.649-0.887 and 0.793 (95% CI: 0.660-0.897), respectively. The area under the curve for predicting long-term survival after surgery (≥40 months) was above 0.8. Based on the optimal cutoff value of -0.19 for the predicted value of the CoxBoost model calculated by the R package " survminer", the patients were divided into high-risk (predicted value >-0.19) and low-risk (predicted value <-0.19) groups. In both the training set and the test set, the survival of patients in the low-risk group was better than that in the high-risk group (training set: χ2=39.01, P<0.001; test set: χ2=12.34, P<0.001). The median survival period of patients in the high-risk group was lower than that in the low-risk group (training set: 15.80 vs 34.07 months; test set: 16.87 vs 43.07; months). Decision curve analysis shows that patients obtain survival benefit when the threshold probability of the training set is greater than 0.25 and that of the test set is greater than 0.45. Conclusion:The CoxBoost model has a good predictive ability for the overall survival of pancreatic cancer patients after surgery and can effectively screen out patient subgroups that may significantly benefit from surgical treatment.
9.Bioequivalence of amoxicillin clavulanate potassium tablet in healthy volunteers
Yi-Ting HU ; Yu-Fang XU ; Wan-Jun BAI ; Hao-Jing SONG ; Cai-Yun JIA ; Shao-Chun CHEN ; Zhan-Jun DONG
The Chinese Journal of Clinical Pharmacology 2024;40(3):419-424
Objective To evaluate the bioequivalence of test product and reference product in a single dose of amoxicillin clavulanate potassium tablet under fasting and fed conditions in healthy volunteers.Methods An open label,randomized,single dose,four-period,crossover bioequivalence study was designed.Fasting and postprandial tests were randomly divided into 2 administration sequence groups according to 1:1 ratio,amoxicillin clavulanate potassium tablet test product or reference product 375 mg,oral administration separately,liquid chromatography tanden mass spectrometry was applied to determine the concentration of amoxicillin and clavulanate potassium in plasma of healthy subjects after fasting or fed administration,while Phoenix WinNonlin 8.2 software were used for pharmacokinetics(PK)parameters calculation and bioequivalence analysis.Results Healthy subjects took the test product and the reference product under fasting condition,the main PK parameters of amoxicillin are as follows:Cmax were(5 075.57±1 483.37)and(5 119.86±1 466.73)ng·mL-1,AUC0_twere(1.32 × 104±2 163.76)and(1.30 × 104±1 925.11)ng·mL-1,AUC0-∞were(1.32 × 104±2 175.40)and(1.31 ×104±1 935.86)ng·mL-1;the main PK parameters of clavulanic acid are as follows:Cmax were(3 298.27±1 315.23)and(3 264.06±1 492.82)ng·mL-1,AUC0-twere(7 690.06±3 053.40)and(7 538.39±3 155.89)ng·mL-1,AUC0-∞were(7 834.81±3 082.61)and(7 671.67±3 189.31)ng·mL-1;the 90%confidence intervals of Cmax,AUC0-tand AUC0-∞ after logarithmic conversion of amoxicillin and clavulanate potassium of the two products were all within 80.00%-125.00%.Healthy subjects took the test and reference product under fed condition,the main PK parameters of amoxicillin are as follows:Cmax were(4 514.08±1 324.18)and(4 602.82±1 366.48)ng·mL-1,AUC0-twere(1.15 × 104±1 637.95)and(1.15 × 104±1 665.69)ng·mL-1,AUC0-∞ were(1.16 × 104±1 646.26)and(1.15 × 104±1 607.20)ng·mL-1;the main PK parameters of clavulanic acid are as follows:Cmax were(2 654.75±1 358.29)and(2 850.51±1 526.31)ng·mL-1,AUC0-twere(5 882.82±2 930.06)and(6 161.28±3 263.20)ng·mL-1,AUC0-∞ were(6 022.70±2 965.05)and(6 298.31±3 287.63)ng·mL-1;the 90%confidence intervals of Cmax,AUC0-t and AUC0-∞ after logarithmic conversion of amoxicillin and clavulanate potassium of the two products were all within 80.00%-125.00%.Conclusion The two formulations were bioequivalent to healthy adult volunteers under fasting and fed conditions.
10.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.


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