1.Diagnostic value of a combined clinical-radiomics model based on MRI for the assessment of renal fibrosis in chronic kidney disease
Chaogang WEI ; Ying ZENG ; Qing MA ; Zhicheng JIN ; Yilin XU ; Ye ZHU ; Xiaojing LI ; Junkang SHEN ; Zhen JIANG
Chinese Journal of Radiology 2025;59(10):1163-1169
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.
2.Diagnostic value of a combined clinical-radiomics model based on MRI for the assessment of renal fibrosis in chronic kidney disease
Chaogang WEI ; Ying ZENG ; Qing MA ; Zhicheng JIN ; Yilin XU ; Ye ZHU ; Xiaojing LI ; Junkang SHEN ; Zhen JIANG
Chinese Journal of Radiology 2025;59(10):1163-1169
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.
3.Systemic lupus erythematosus related thrombotic microangiopathy: A retrospective study based on Chinese SLE Treatment and Research Group (CSTAR) registry.
Yupei ZHANG ; Nan JIANG ; Zhen CHEN ; Xinwang DUAN ; Xiaofei SHI ; Hongbin LI ; Zhenyu JIANG ; Yuhua WANG ; Yanhong WANG ; Jiuliang ZHAO ; Qian WANG ; Xinping TIAN ; Mengtao LI ; Xiaofeng ZENG
Chinese Medical Journal 2025;138(5):613-615
4.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
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.
5.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
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.
6.Isolation,identification,and biological characteristics of Staphylococcus aureus infection in yaks
Hong-Cai MA ; Hao-Feng QIN ; Jiang-Yong ZENG ; Duo-Ji JINMEI ; Dong-Jing WANG ; Zhen-Jie YUAN
Chinese Journal of Zoonoses 2024;40(7):662-669
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.
7.Fipronil and its metabolites in indoor dust in Shenzhen in 2020 -2021: analysis of residual levels and temporal variations
Ying JIANG ; Xiandong ZENG ; Jie LIU ; Shiyi FANG ; Zhouning FANG ; Jianhui YUAN
Journal of Public Health and Preventive Medicine 2023;34(2):27-31
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.
8.To compare the efficacy and incidence of severe hematological adverse events of flumatinib and imatinib in patients newly diagnosed with chronic phase chronic myeloid leukemia.
Xiao Shuai ZHANG ; Bing Cheng LIU ; Xin DU ; Yan Li ZHANG ; Na XU ; Xiao Li LIU ; Wei Ming LI ; Hai LIN ; Rong LIANG ; Chun Yan CHEN ; Jian HUANG ; Yun Fan YANG ; Huan Ling ZHU ; Ling PAN ; Xiao Dong WANG ; Gui Hui LI ; Zhuo Gang LIU ; Yan Qing ZHANG ; Zhen Fang LIU ; Jian Da HU ; Chun Shui LIU ; Fei LI ; Wei YANG ; Li MENG ; Yan Qiu HAN ; Li E LIN ; Zhen Yu ZHAO ; Chuan Qing TU ; Cai Feng ZHENG ; Yan Liang BAI ; Ze Ping ZHOU ; Su Ning CHEN ; Hui Ying QIU ; Li Jie YANG ; Xiu Li SUN ; Hui SUN ; Li ZHOU ; Ze Lin LIU ; Dan Yu WANG ; Jian Xin GUO ; Li Ping PANG ; Qing Shu ZENG ; Xiao Hui SUO ; Wei Hua ZHANG ; Yuan Jun ZHENG ; Qian JIANG
Chinese Journal of Hematology 2023;44(9):728-736
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
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Humans
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Adolescent
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Imatinib Mesylate/adverse effects*
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Incidence
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Antineoplastic Agents/adverse effects*
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Retrospective Studies
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Pyrimidines/adverse effects*
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Leukemia, Myelogenous, Chronic, BCR-ABL Positive/drug therapy*
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Treatment Outcome
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Benzamides/adverse effects*
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Leukemia, Myeloid, Chronic-Phase/drug therapy*
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Aminopyridines/therapeutic use*
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Protein Kinase Inhibitors/therapeutic use*
9.Status of fungal sepsis among preterm infants in 25 neonatal intensive care units of tertiary hospitals in China.
Xin Cheng CAO ; Si Yuan JIANG ; Shu Juan LI ; Jun Yan HAN ; Qi ZHOU ; Meng Meng LI ; Rui Miao BAI ; Shi Wen XIA ; Zu Ming YANG ; Jian Fang GE ; Bao Quan ZHANG ; Chuan Zhong YANG ; Jing YUAN ; Dan Dan PAN ; Jing Yun SHI ; Xue Feng HU ; Zhen Lang LIN ; Yang WANG ; Li Chun ZENG ; Yan Ping ZHU ; Qiu Fang WEI ; Yan GUO ; Ling CHEN ; Cui Qing LIU ; Shan Yu JIANG ; Xiao Ying LI ; Hui Qing SUN ; Yu Jie QI ; Ming Yan HEI ; Yun CAO
Chinese Journal of Pediatrics 2023;61(1):29-35
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
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Infant, Newborn
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Humans
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Birth Weight
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Intensive Care Units, Neonatal
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Retrospective Studies
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Tertiary Care Centers
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Infant, Extremely Low Birth Weight
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Gestational Age
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Infant, Extremely Premature
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Sepsis/epidemiology*
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Retinopathy of Prematurity/epidemiology*
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Bronchopulmonary Dysplasia/epidemiology*
10.Clinical characteristics and diagnosis and treatment strategies of patients with severe traumatic aortic injury.
Ying Zhen BU ; Xuan Ze LIU ; Tie Nan ZHOU ; Xu Dong LIU ; Hong Xu JIN ; Xiao Jiang LIU ; Xiao Zeng WANG
Chinese Journal of Cardiology 2022;50(8):767-773
Objective: To investigate the clinical characteristics and diagnosis and treatment strategies of patients with severe traumatic aortic injury (TAI). Methods: A total of 25 patients with TAI, who hospitalized in our hospital between August 2005 to March 2021 and underwent thoracic aortic endovascular repair (TEVAR), were included in this retrospective study. According to the time from admission to TEVAR, the patients were divided into emergency TEVAR group (14 cases, TEVAR within 24 h of admission) and elective TEVAR group (11 cases, patients underwent surgery or fracture reduction and fixation first for serious injuries and then underwent TEVAR more than 24 h after admission). The general clinical data of patients, injury severity score (ISS), time from admission to intervention, total hospital stay, the proportion of closed chest drainage and the proportion of abdominal organ repair were obtained and compared. Clinical follow-up and 1-year postoperative aortic computed tomography angiography (CTA) were performed on the patients. Death, the occurrence of aortic adverse events and injury recovery were followed up and recorded. Results: The mean age of these 25 TAI patients was (41.4±14.4) years, 20 patients were males (80.0%). 21 patients (84.0%) had persistent chest and back pain, 17 (68.0%) had pleural effusion and 5 (20.0%) had mediastinal hematoma. The injury severity score (ISS) was significantly higher in the elective TEVAR group than in the emergency TEVAR group (24.9±14.4 vs. 35.5±9.3, P=0.044). The time from admission to intervention ((1.0±0.0) d vs. (3.4±0.9) d, P<0.001], the time from admission to TEVAR ((1.0±0.0) d vs. (11.5±13.8) d, P=0.030) and total hospital stay ((6.1±2.3) d vs. (26.8±7.7) d, P<0.001) were significantly longer in elective TEVAR group than in emergency TEVAR group. The proportion of thoracic closed drainage was significantly lower in the elective TEVAR group than in the emergency TEVAR group (9 (64.3%) vs. 2 (18.2%), P=0.042). The proportion of abdominal organ repair was significantly higher than in the emergency TEVAR group (0 vs. 4 (36.4%), P=0.026). All of 25 patients were discharged alive and followed up for (84.0±30.5) months. All patients survived and completed 1-year postoperation CTA. There were no aortic adverse events occurred, and no complications after surgery, and the fractures and organ injuries healed well. Conclusions: The clinical characteristics of severe TAI are acute multi-injuries combined with persistent chest and/or back pain, pleural effusion, and mediastinal hematoma. Timely diagnosis and treatment are important factors for the outcome. The treatment strategy for multi-injuries should give priority to dealing with life-threatening injuries. TEVAR is the primary treatment strategy for severe TAI and is related to satisfactory outcomes.
Adult
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Aorta, Thoracic/surgery*
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Aortic Diseases
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Blood Vessel Prosthesis Implantation/adverse effects*
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Endovascular Procedures/methods*
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Female
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Hematoma/surgery*
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Humans
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Male
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Middle Aged
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Pleural Effusion/surgery*
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Retrospective Studies
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Risk Factors
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Treatment Outcome


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