1.Establishment and verification of LIPS score combined with APACHE Ⅱ score and oxygenation index to predict the occurrence model of ARDS
Feng ZHAO ; Ziyuan SHEN ; Cui YANG ; Zhukai CONG ; Hua ZHANG ; Xi ZHU
Chinese Critical Care Medicine 2022;34(10):1048-1054
Objective:To construct and verify the occurrence model of acute respiratory distress syndrome (ARDS) using lung injury prediction score (LIPS) combined with acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) score and oxygenation index (PaO 2/FiO 2). Methods:Using a prospective cohort study method, 244 patients with complete medical records who were admitted to the intensive care unit (ICU) of Peking University Third Hospital from December 2020 to July 2022 were selected as research objects according to the inclusion and exclusion criteria. They were divided into training set (173 cases) and validation set (71 cases). Patients' gender, age, body mass index (BMI), various causes (shock, sepsis, craniocerebral injury, pulmonary contusion, multiple trauma, aspiration, pneumonia, acute abdomen, hypoproteinemia, acidosis, major surgery, etc.), underlying diseases (diabetes, malignant tumor, cerebrovascular disease, liver disease, kidney disease) and laboratory test indicators were collected. According to the above data, the LIPS score, APACHE Ⅱ score, sequential organ failure assessment (SOFA) and PaO 2/FiO 2, etc within 24 hours after admission to the ICU were calculated. Univariate analysis was used to screen the influencing factors for the occurrence of ARDS, and the factors with P < 0.2 were included in the multivariate Logistic regression analysis to screen out the independent predictive factors for the occurrence of ARDS. According to the results of multivariate Logistic regression analysis, the risk score of patients with ARDS was obtained to construct the risk prediction model of ARDS, the receiver operator characteristic curve (ROC curve) was drawn, and the area under the ROC curve (AUC) was calculated. The established ARDS prediction model was externally validated, and ROC curves were drawn to evaluate the predictive accuracy of the prediction model for the occurrence of ARDS in critically ill patients, and the AUC of the validation set was calculated to analyze the predictive performance of each risk factor on the occurrence of ARDS. Results:A total of 173 patients were enrolled in the training set, including 121 patients without ARDS and 52 patients with ARDS; 77 cases of acute abdomen, 64 cases of sepsis, 60 cases of shock, 51 cases of acidosis, 40 cases of hypoproteinemia, 37 cases of diabetes, 34 cases of craniocerebral injury, 34 cases of abnormal liver function, 28 cases of multiple trauma, 23 cases of malignant tumor, 23 cases of spinal orthopedic surgery, 17 cases of obesity, 12 cases of pneumonia, 11 cases of pulmonary contusion, and 7 cases of chronic kidney disease, chemotherapy in 6 cases, and aspiration in 2 cases. The rates of shock, sepsis, acute abdomen, acidosis, abnormal liver function, lung contusion, pneumonia and aspiration, gender, age, LIPS score, APACHE Ⅱ score, and SOFA score in the ARDS group were significantly higher than those in the non-ARDS group (all P < 0.05), moreover, PaO 2/FiO 2 ratio was significantly lower than that of non-ARDS group ( P < 0.01). Multivariate Logistic regression analysis showed that LIPS score, APACHE Ⅱ score, and PaO 2/FiO 2 ratio were independent risk factors for ARDS in ICU patients with high risk factors for ARDS, and the odds ratio ( OR) was 1.768 [95% confidence interval (95% CI) was 1.380-2.266], 1.242 (95% CI was 1.089-1.417), 0.985 (95% CI was 0.978-0.991), all P < 0.05. ROC curve analysis showed that the AUC of the ARDS prediction model training set was 0.920, the sensitivity was 86.5%, and the specificity was 86.8%; the AUC of the verification set was 0.896, the sensitivity was 96.8%, and the specificity was 76.6%. Conclusion:LIPS score, APACHE Ⅱ score and PaO 2/FiO 2 are independent risk factors for the occurrence of ARDS in ICU patients with high risk factors for ARDS. The ARDS risk prediction model established based on these three indicators has a good predictive ability for the occurrence of ARDS in critically ill patients, wihich needs to be verified by multicenter cohort studies.
2.Correlation of prognostic nutritional index and clinical characteristics with prognosis in patients with diffuse large B-cell lymphoma
Shuo ZHANG ; Ziyuan SHEN ; Yingliang JIN ; Kailin XU ; Wei SANG
Journal of Leukemia & Lymphoma 2021;30(10):588-592
Objective:To investigate the effect of prognostic nutrition index (PNI) and clinical characteristics on the prognosis of patients with diffuse large B-cell lymphoma (DLBCL).Methods:The clinical data of 236 patients with DLBCL treated in the Affiliated Hospital of Xuzhou Medical University from November 2014 to December 2018 were retrospectively analyzed. X-Tile software and restricted cubic spline (RCS) were used to determine the best cut-off values of PNI, age and hemoglobin; Cox proportional hazard regression model was used for univariate and multivariate analyses; Kaplan-Meier method was used to analyze the overall survival (OS) of patients, and log-rank test was also performed.Results:One-hundred and fifteen of the 236 patients (48.7%) died, with a median OS time of 32 months. The 3-year OS rate was 46%, and the 5-year OS rate was 36%. The best cut-off value of PNI was 49. There was a significant non-linear relationship between PNI and the risk of poor prognosis of DLBCL ( χ2=34.64, P < 0.01); the analysis of the dose-response relationship showed that with the change of PNI, the correlation strength of the risk of poor prognosis declined non-linearly. The best cut-off value of age was 63 years old, and the correlation strength between age and the risk of poor prognosis of DLBCL showed a non-linear upward trend ( χ2=14.86, P=0.022). The best cut-off values of hemoglobin calculated by X-Tile software were 93 g/L and 129 g/L. Multivariate analysis showed that PNI, central nervous system involvement, liver involvement, age, hemoglobin, international prognostic index (IPI) score, and bulky disease were independent influencing factors of OS in DLBCL patients (all P < 0.05). In patients with germinal center B-cell-like (GCB) subtype, bcl-2-positive and bcl-6-positive, there were statistical differences in the 3-year OS rate of patients with PNI < 49 and PNI ≥ 49 (all P < 0.05). Conclusion:PNI has a certain value in the prognosis assessment of DLBCL patients, and PNI ≥ 49 indicates that the patient has a good prognosis.
3.Analysis of the distribution of infectious bacteria and the status of drug resistance in hospitalized patients of hematology department
Ziyuan SHEN ; Haiquan KANG ; Yingliang JIN ; Wei SANG
Journal of Leukemia & Lymphoma 2022;31(1):42-45
Objective:To investigate the bacterial distribution of secondary infection and the status of drug resistance in hospitalized patients of hematology department.Methods:The clinical data of 1 125 inpatients in the Hematology Department of the Affiliated Hospital of Xuzhou Medical University from January 2015 to December 2019 were retrospectively analyzed, and the distribution of infectious pathogens and the status of drug resistance of these inpatients were analyzed.Results:A total of 9 335 microbial samples from 1 125 inpatients were submitted for examination, among which 1 349 were positive samples. Among 1 349 positive samples, the gram-negative bacteria-positive samples accounted for 66.4% (895/1 349) and the gram-positive bacteria-positive samples accounted for 33.7% (454/1 349); the blood samples accounted for 44.7%(603/1 349), the sputum samples accounted for 33.9% (457/1 349), and the urine samples accounted for 9.4%(127/1 349). The isolated bacteria whose proportion ranked as the top 3 were Escherichia coli (31.0%), Staphylococcus aureus (21.0%) and Klebsiella pneumoniae (18.0%). The drug resistance rate of Escherichia coli to ceftriaxone was as high as 77.2%, and that of Staphylococcus aureus and coagulase-negative Staphylococcus to benzoxicillin was 58.2% and 66.7%, but both had no resistance to vancomycin.Conclusions:There are a wide variety of infectious pathogens in hospitalized patients of hematology department, and the Escherichia coli and Klebsiella pneumonia are predominant. More attention should be paid to antibiotic prescribing training for clinicians to optimize and standardize the use of antibiotics.
4.Predictive value of controlling nutritional status score in the prognosis of patients with advanced diffuse large B-cell lymphoma
Huirong SHAN ; Xicheng CHEN ; Hao ZHANG ; Yuqing MIAO ; Fei WANG ; Yuye SHI ; Ling WANG ; Jingjing YE ; Ziyuan SHEN ; Wei SANG ; Hongfeng GE
Journal of Leukemia & Lymphoma 2024;33(2):104-109
Objective:To investigate the predictive value of controlling nutritional status (CONUT) score in the prognosis of patients with advanced diffuse large B-cell lymphoma (DLBCL).Methods:A retrospective case series study was performed. The clinical data of 654 patients newly diagnosed with advanced DLBCL diagnosed in 7 medical centers in Huaihai Lymphoma Working Group from October 2009 to January 2022 were retrospectively collected. All the patients received rituximab-based immune chemotherapy regimens. The patients were randomly assigned to the training set (458 cases) and the validation set (196 cases) in a 7:3 ratio. The clinicopathological data of patients were collected, and the CONUT score was calculated based on albumin, lymphocyte count, and total cholesterol. The optimal critical value of CONUT scote was determined by using MaxStat method. Kaplan-Meier method was used to draw survival curves; Cox proportional hazards model was used to make univariate analysis and multivariate analysis on the factors influencing overall survival (OS). The efficacy of CONUT score in combination with the International prognostic index (IPI) and an enhanced IPI (NCCN-IPI) in predicting OS was evaluated by using receiver operating characteristic (ROC) curves.Results:The median follow-up time of 654 patients was 38.1 months (95% CI: 35.3 months- 40.9 months), and the 5-year OS rate was 49.2%. According to the MaxStat method, the optimal critical value for CONUT score was determined to be 6 points. All the patients were classified into the normal nutritional status group (CONUT score ≤ 6 points, 489 cases) and the poor nutritional status group (CONUT score > 6 points, 165 cases). The results of the multivariate analysis showed that CONUT score > 6 points, male, lactate dehydrogenase >240 U/L, high white blood cell count, low hemoglobin level and age > 60 years were independent risk factors for OS of patients with advanced DLBCL (all P < 0.05). Patients in the poor nutritional status group (CONUT score > 6 points) had worse OS compared with that in the normal nutritional status group in the overall cohort of advanced DLBCL. Subgroup analysis revealed that among patients with Eastern Cooperative Oncology Group-performance status (ECOG PS) score < 2 points, IPI low-intermediate risk, IPI intermediate-high risk, NCCN-IPI low-intermediate risk, and NCCN-IPI intermediate-high risk, the patients in the poor nutritional status group (CONUT score > 6 points) had worse OS compared with that in the normal nutritional status group (CONUT score ≤ 6 points) (all P < 0.05). Conclusions:CONUT score has a certain value in the assessment of the prognosis of patients with advanced DLBCL, and its predictive efficacy is further improved when combined with IPI and NCCN-IPI.
5.Clinical prognosis of lymphoma-associated hemophagocytic syndrome in adults: a multicenter study
Ziyuan SHEN ; Chenlu HE ; Ying WANG ; Qinhua LIU ; Hao ZHANG ; Yuqing MIAO ; Weiying GU ; Chunling WANG ; Ling WANG ; Jingjing YE ; Yingliang JIN ; Wei SANG ; Taigang ZHU
Journal of Leukemia & Lymphoma 2021;30(9):542-546
Objective:To explore the prognostic influencing factors of adult lymphoma-associated hemophagocytic syndrome (LAHS) based on multicenter data.Methods:The clinical data of 86 LAHS patients diagnosed in 9 medical centers of Huaihai Lymphoma Working Group from January 2015 to August 2020 were retrospectively analyzed. The optimal cut-off value of continuous variables was obtained based on MaxStat algorithm. Cox proportional hazard regression model was used for univariate and multivariate analyses. Kaplan-Meier method was used for survival analysis, and log-rank test was performed.Results:Among the 86 adult LAHS patients, 50 (58.1%) were males and 36 (41.9%) were females, the median age of the patients was 57 years old (19-76 years old), and the median overall survival (OS) time was 1.67 months (95% CI 0.09- 3.24 months). The most common pathologic type was diffuse large B-cell lymphoma (58 cases, 67.44%). Based on MaxStat algorithm, the optimal cut-off values of age, albumin, serum creatinine, lactate dehydrogenase, fibrinogen and platelet count were 64 years old, 30.1 g/L, 67 μmol/L, 1 045 U/L, 4.58 g/L and 72×10 9/L, respectively. Multivariate analysis showed that patient's age, lactate dehydrogenase, albumin and fibrinogen levels were independent influencing factors for OS (all P < 0.05). Conclusions:LAHS is dangerous and progresses quickly. Patients with age ≥ 64 years old, lactate dehydrogenase ≥ 1 045 U/L, fibrinogen ≥ 4.58 g/L and albumin < 30.1 g/L have poor survival.
6.Value of lymphocyte subsets in assessing the prognosis of adult hemophagocytic syndrome
Ziyuan SHEN ; Chenlu HE ; Ying WANG ; Qian SUN ; Qinhua LIU ; Ruixiang XIA ; Hao ZHANG ; Yuqing MIAO ; Hao XU ; Weiying GU ; Chunling WANG ; Yuye SHI ; Jingjing YE ; Chunyan JI ; Taigang ZHU ; Dongmei YAN ; Wei SANG ; Kailin XU ; Shuiping HUANG ; Xiangmin WANG
Chinese Journal of Laboratory Medicine 2022;45(9):914-920
Objective:To explore the prognostic value of lymphocyte subsets in adult hemophagocytic syndrome (HPS).Methods:A total of 172 adult HPS patients diagnosed in 8 medical centers from January 2013 to August 2020 were selected for the study, of whom 87 were male (50.6%, 87/172), and 85 were female (49.4%, 85/172), with 68 survivors and 104 deaths. The clinical data were summarized, and variables such as lymphocyte subsets, immunoglobulin characteristics and fibrinogen were retrospectively analyzed, and the correlation between the mentioned variables and patient prognosis was analyzed. The optimal cut-off values of continuous variables were calculated by MaxStat, and the prognostic factors of HPS patients were screened based on the Cox proportional hazard regression model.Results:The median age of HPS patients was 56 (42, 66) years old, and the 5-year cumulative survival rate was 37.4% (37.4/100). The median age, platelet and albumin were 48 (27, 63) years, 84×10 9/L and 32.3 g/L in the survival group, and 59 years, 45.5×10 9/L, and 27.3 g/L in the death group, respectively. The differences between the two groups was statistically significant ( Z=?3.368, P=0.001; Z=?3.156, P=0.002; Z=?3.431, P=0.001). Patients with differentiated cluster 8+(CD8+)<11.1%, CD3+<64.9%, CD4+>51%, and CD4/CD8 ratio>2.18 had poor prognosis (χ 2=7.498, P=0.023; χ 2=4.169, P=0.041; χ 2=4.316, P=0.038; χ 2=9.372, P=0.002). Multivariable analysis showed that CD4/CD8 ratio, age, fibrinogen and hemoglobin were independent prognostic factors in HPS patients ( HR=2.435, P=0.027; HR=5.790, P<0.001; HR=0.432, P=0.018; HR=0.427, P=0.018). Conclusion:Peripheral blood lymphocyte subsets can be used to evaluate the prognosis of patients with HPS; CD4/CD8 ratio, age, fibrinogen, and hemoglobin are independent prognostic factors in HPS patients.
7.Characterization of chromatin accessibility in psoriasis.
Zheng ZHANG ; Lu LIU ; Yanyun SHEN ; Ziyuan MENG ; Min CHEN ; Zhong LU ; Xuejun ZHANG
Frontiers of Medicine 2022;16(3):483-495
The pathological hallmarks of psoriasis involve alterations in T cell genes associated with transcriptional levels, which are determined by chromatin accessibility. However, to what extent these alterations in T cell transcriptional levels recapitulate the epigenetic features of psoriasis remains unknown. Here, we systematically profiled chromatin accessibility on Th1, Th2, Th1-17, Th17, and Treg cells and found that chromatin remodeling contributes significantly to the pathogenesis of the disease. The chromatin remodeling tendency of different subtypes of Th cells were relatively consistent. Next, we profiled chromatin accessibility and transcriptional dynamics on memory Th/Treg cells. In the memory Th cells, 803 increased and 545 decreased chromatin-accessible regions were identified. In the memory Treg cells, 713 increased and 1206 decreased chromatin-accessible regions were identified. A total of 54 and 53 genes were differentially expressed in the peaks associated with the memory Th and Treg cells. FOSL1, SPI1, ATF3, NFKB1, RUNX, ETV4, ERG, FLI1, and ETC1 were identified as regulators in the development of psoriasis. The transcriptional regulatory network showed that NFKB1 and RELA were highly connected and central to the network. NFKB1 regulated the genes of CCL3, CXCL2, and IL1RN. Our results provided candidate transcription factors and a foundational framework of the regulomes of the disease.
Chromatin/genetics*
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Chromatin Assembly and Disassembly
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Gene Regulatory Networks
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Humans
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Psoriasis/genetics*
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T-Lymphocytes, Regulatory
8.Research progress of D-psicose: function and its biosynthesis.
Xuemei SHEN ; Jing WANG ; Yuan ZHANG ; Xiaoyan WANG ; Ziyuan DING ; Yi LI ; Bo CHEN ; Yi TONG
Chinese Journal of Biotechnology 2018;34(9):1419-1431
As the morbidity of metabolic syndrome like obesity and diabetes increases rapidly worldwide, the issue of nutrition (functional food) and health has drawn more attention. D-psicose, a rare natural ketohexose, has become a hot topic in functional food and health-care field because of its hypoglycemic and hypolipidemic function with good sweetness. This article mainly discusses the functional properties and biosynthesis research progress of D-psicose, together with the crystal structure of ketose-3-epimerase, to provide theoretical guidance for D-psicose-producing strain screening as well as improving the thermostability and catalytic efficiency of ketose-3-epimerase for industrial application.
9.Quality of urodynamics: a national cross-sectional study in China.
Xiao ZENG ; Ziyuan XIA ; Liao PENG ; Jiapei WU ; Jiayi LI ; Jianhui YANG ; Juan CHEN ; Changqin JIANG ; Dewen ZHONG ; Yang SHEN ; Jumin NIU ; Xiao XIAO ; Li WEN ; Hong SHEN ; Deyi LUO
Chinese Medical Journal 2023;136(2):236-238