Objective:To analyze the clinical epidemiological characteristics and the prognostic risk factors of patients with hemorrhagic fever with renal syndrome (HFRS).Methods:A total of 2 245 HFRS patients who were admitted to the Second Affiliated Hospital of Air Force Medical University from September 2008 to December 2021 were enrolled. Clinical epidemiological data (including gender, age, onset season, onset region, case fatality rate, et al) of HFRS patients were analyzed. The clinical epidemiological characteristics of patients with HFRS in the 2008 to 2012, 2013 to 2017, and 2018 to 2021 groups were compared. Statistical comparisons were performed using chi-square test. The Bonferroni adjusted P-value method was used for pairwise comparisons between groups, and logistic regression analysis was used to screen and evaluate the risk factors associated with the prognosis of HFRS patients. Results:The age of 2 245 HFRS patients was (42.3±15.9) years old. Most of them were male (79.24%(1 779/2 245)), and the main incidence area was Xi′an City (69.53%(1 561/2 245)). There were 132 deaths with an overall case fatality rate of 5.88%. There were 1 088 patients (48.46%) from 2008 to 2012, 647 patients (28.82%) from 2013 to 2017, and 510 patients (22.72%) from 2018 to 2021, with a mortality rate of 7.17%(78/1 088), 5.10%(33/647) and 4.12%(21/510), respectively. From 2008 to 2021, both the number of HFRS cases and the case fatality rate had shown a fluctuating downward trend. There were significant differences in case fatality rate, age distribution, onset season, and onset region among patients in the different year groups ( χ2=6.84, 49.22, 83.47 and 19.29, respectively, all P<0.05). The results of pairwise comparisons showed that the proportion of patients aged >60 years in the 2018 to 2021 group (23.33%(119/510)) was higher than those in the 2008 to 2012 group (12.13%(132/1 088)) and the 2013 to 2017 group (12.36%(80/647)), and the differences were statistically significant (both P<0.05). The proportions of patients at large peak (October to December) were 62.35%(318/510) in the 2018 to 2021 group and 56.26%(364/647) in the 2013 to 2017 group, which were both lower than that in the 2008 to 2012 group (75.18%(818/1 088)), and the differences were both statistically significant (both P<0.05). The case fatality rate of patients aged >60 years was 9.67%(32/331), which was higher than those of patients aged <30 years (2.86%(16/559)) and patients aged 30 to 60 years (6.20%(84/1 355)), with statistically significant differences (both P<0.05). Univariate analysis showed that age 30 to 60 years, age >60 years, smoking, complicated with hypertension, hypotensive shock and hypoxemia were significantly correlated with the prognosis of HFRS patients (odds ratio ( OR)=2.243, 3.632, 1.484, 3.532, 79.422 and 143.955, respectively, all P<0.05). The results of multivariate logistic regression analysis indicated that complicated with hypertension ( OR=2.467, P=0.004), hypotensive shock ( OR=11.658, P=0.001), and hypoxemia ( OR=67.767, P<0.001) were the independent risk factors affecting the prognosis of HFRS patients. Conclusions:The prevalence of HFRS has shown new changing characteristics from 2008 to 2021. The numbers of HFRS patients and the case fatality rates show a downward trend, and the proportion of HFRS patients aged >60 years increases. Complicated with hypertension, hypotensive shock and development with hypoxemia are the independent risk factors for the prognosis of HFRS.

Objective:To investigate the dynamic changes of routine laboratory parameters during the course of hemorrhagic fever with renal syndrome (HFRS) and estimate the predictive value for the severity of the disease.Methods:A retrospective cohort study was conducted, which enrolled 394 HFRS patients admitted to the Second Affiliated Hospital of Air Force Medical University (374 cases) and the Second Affiliated Hospital of Xi′an Jiaotong University (20 cases) from January 2019 to January 2022. The patients were divided into mild (mild and moderate) and severe (severe and critical) groups.The basic information, personal history, past history, treatment, complications and other clinical data of patients were collected and the results of the laboratory examinations in the morning at day 1, 2, 3, 4, 5, 7, 10, 15, 20 and 25 of hospitalization and before discharge were recorded. The dynamic changes of the patients′ routine laboratory indicators and the dynamic predictive values of each indicator for severe condition were analyzed. Mann-Whitney U test and chi-square test were used for comparison, and receiver operator characteristic (ROC) curve was used for predictive value evaluation. Results:The age of 212 patients in the mild group was 38(27, 61) years, and that of 182 patients in the severe group was 49(32, 64) years, the difference was statistically significant ( Z=-2.24, P=0.025). The incidences of acute pancreatitis, acute respiratory distress syndrome, multiple organ dysfunction syndrome, the utilization rates of blood purification and mechanical ventilation in the severe group were 6.0%(11/182), 12.6%(23/182), 19.8%(36/182), 89.6%(163/182) and 22.5%(41/182), respectively, and those in the mild group were 0(0/212), 0(0/212), 0(0/212), 15.6%(33/212) and 0.5%(1/212) respectively, and the differences were all statistically significant ( χ2=13.18, 28.45, 46.15, 214.48 and 50.02, respectively, all P<0.05). The levels of white blood cell count, lymphocyte count, monocyte count and neutrophil count were all increased rapidly after onset and peaked at days 4 to 6 of illness, with the counts of 14.2(9.7, 20.7)×10 9/L, 4.2(2.3, 6.2)×10 9/L, 1.5 (0.8, 3.3)×10 9/L and 8.3(4.3, 11.4)×10 9/L, respectively. Aspartate aminotransferase peaked (102(66, 178) U/L) within three days after onset and then decreased rapidly, returned to normal level by day 12. Blood urea nitrogen and creatinine both increased steadily after onset, peaked at day 9 to 10, with the levels of 13.2(7.7, 19.1) mmol/L and 255.4(122.9, 400.9) μmol/L, respectively. Prothrombin time, activated partial thromboplastin time, fibrinogen degradation products and D-dimer levels at day 3 after onset were 12.7(12.0, 13.2) s, 38.7(33.5, 51.9) s, 12.6(6.9, 32.0) mg/L and 4.9(2.2, 13.7) mg/L, respectively.Platelet count at day 4, neutrophil count at day 5, creatinine at day 11 and blood urea nitrogen at day 14 after onset had decent predictive values for estimating severity, of which the area under curve (AUC) values were 0.801(95% confidence interval (95% CI) 0.727 to 0.875), 0.824(95% CI 0.770 to 0.878), 0.862(95% CI 0.805 to 0.919) and 0.810(95% CI 0.722 to 0.897), respectively. Conclusions:Routine blood count, liver function and coagulation are important reference indicators for early warning of severe disease of HFRS, while with the progress of the disease, renal function indicators are effective in differentiating the severity of the disease. The platelet count at day 4, neutrophil count at day 5, creatinine at day 11 and blood urea nitrogen at day 14 after onset have predictive values for severe HFRS.

Objective:To analyze the clinical characteristics and risk factors for severe disease of hemorrhagic fever with renal syndrome (HFRS) in underage patients, and to construct the severe disease risk model.Methods:A total of 170 HFRS patients (<18 years old) from the Second Affiliated Hospital of Air Force Medical University (153 cases) and the Second Affiliated Hospital of Xi′an Jiaotong University (17 cases) from January 2009 to December 2021 were included. According to the severity of the disease, the patients were divided into mild and severe groups. Baseline demographic data, symptoms, signs, laboratory examination on admission and prognosis were analyzed between the two groups. Statistical comparisons were performed using the Mann-Whitney U test and chi-square test.Binary logistic regression was used to analyze the independent risk factors of patients with severe disease, and the severe disease risk model was built.The receiver operator characteristic curve was used to analyze the value of the risk model in predicting severity of disease. Results:Among the 170 underage patients, 132 (77.6%) were males, aged (14.9±3.1) years, including 124 cases in mild group and 46 cases in severe group. One hundred and sixty-nine cases (99.4%) had fever, 119 cases (70.0%) had headache, 106 cases (62.4%) had lumbago, 158 cases (92.9%) had skin and mucous congestion, and 101 cases (59.4%) had nausea and vomiting. Renal percussive pain was found in 139(81.8%) patients. The incidence of nausea and vomiting and bleeding of skin and mucosa in the severe group were 71.7%(33/46) and 67.4%(31/46), respectively, which were both higher than those in the mild group (54.8%(68/124) and 44.4%(55/124), respectively), and the differences were statistically significant ( χ2=3.97 and 7.12, respectively, both P<0.05). There were significant differences in platelet count, activated partial thromboplastin time (APTT), serum creatinine (SCr), aspartate aminotransferase, alanine aminotransferase, leukocyte count, total bilirubin and albumin levels between the two groups ( Z=-4.14, -4.04, -4.87, -3.90, -4.07, -2.60, -2.78 and t=2.50, respectively, all P<0.05). Binary logistic regression analysis showed that chemosis (odds ratio ( OR)=8.035, 95% confidence interval (95% CI) 2.946 to 21.916), SCr ( OR=1.010, 95% CI 1.006 to 1.015) and APTT ( OR=1.049, 95% CI 1.003 to 1.098) were the independent risk factors for severe HFRS in the underage patients. The risk model was constructed as: Logit(P)=-10.323+ 2.084×chemosis (no=0, grade Ⅰ=1, grade Ⅱ=2, grade Ⅲ=3)+ 0.010×SCr (μmol/L)+ 0.048×APTT (s). The area under the curve to predict severity of disease in underage HFRS patients was 0.868, with an optimal cut-off value of -4.39, with a sensitivity of 73.90% and a specificity of 91.10%. According to the internal verification of the data of the study based on the severe disease risk model, 34 out of 46 patients with severe disease were severe (sensitivity, 73.91%), 113 out of 124 patients with mild disease were mild (specificity, 91.13%). Conclusions:The clinical manifestations of the underage HFRS patients are not typical.The main manifestations are fever, headache and lumbago, nausea and vomiting, and the incidences of skin and mucous congestion and renal percussive pain are high.Chemosis, SCr and APTT are independent risk factors for severe disease in underage patients with HFRS. The severe disease risk model could effectively predict the severity of disease.

Objective:To analyze the medication and compatibility law of TCM compound patents in the treatment of diabetic nephropathy (DN) based on data mining method; To provide basis for research and development of new drug in clinic.Methods:TCM compound patents for DN treatment were retrieved from national patent platform. Excel 2019 was used to conduct statistical analysis on drug frequency, property and taste and meridian. SPSS Modeler 18.0 and SPSS Statistic 26.0 were used for drug association rules and clustering analysis. The complex network of co-occurrence of core drugs was constructed with Cytoscape 3.9.0, and the potential of the correlation between new prescriptions and drugs was demonstrated.Results:A total of 261 TCM compound patents were included, including 438 kinds of Chinese materia medica. High-frequency drugs included Astragali Radix, Rehmanniae Radix, Salviae Miltiorrhizae Radix et Rhizoma, Lycii Fructus, etc. Drug categories were mainly deficiency tonic drugs. The properties and tastes were mainly cold and sweet, and the meridians were mainly liver and kidney meridians. The commonly used medicinal pair was Ganoderma-Rehmannine Radix. The commonly used triple medicinal combination was Notoginseng Radix et Rhizoma-Angelicae Sinensis Radix-Ganoderma. There were 7 groups of clustering medicines, including Notoginseng Radix et Rhizoma, Ganoderma, Angelicae Sinensis Radix, Euryales Semen, Rehmanniae Radix and Lycii Fructus. There were 5 groups of potential medicines, including Campsis Flos-Caulis Tinosporae Sinensis-Kalopanacis Radix-Fimbristylis Rigiduta Nees-Padicularisdis Dissectae Radix -Korshinsk Peashrub-Alismatis Fructus-Cynanchi Wallichii Radix. The core new prescriptions for treating DN were obtained through topological attribute analysis and screening.Conclusions:The national TCM compounds patents treatment for DN is based on the pathogenesis of this disease, which is characterized by deficiency in nature and excess in superficiality. It often uses methods such as tonifying qi and spleen, nourishing yin and tonifying kidney, promoting blood circulation and resolving blood stasis to improve clinical efficacy, providing ideas for the development of new drugs.

ObjectiveTo investigate the clinical features of patients with acute-on-chronic liver failure （ACLF） and bacterial infection and early warning indicators associated with multidrug-resistant infections. MethodsA retrospective analysis was performed for 130 patients with ACLF and bacterial infection who attended The Second Affiliated Hospital of Air Force Medical University from January 1， 2010 to December 31， 2021， and according to the drug susceptibility results， the patients were divided into multidrug-resistant （MDR） bacterial infection group with 80 patients and non-MDR bacterial infection group with 50 patients. General information and laboratory examination results were compared between the two groups to screen for the early warning indicators associated with MDR bacterial infection. The Student’s t-test was used for comparison of normally distributed continuous data with homogeneity of variance between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data or continuous data with heterogeneity of variance between two groups； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. The binary logistic regression analysis and the receiver operating characteristic （ROC） curve were used to assess the predictive value of early warning indicators. ResultsAmong the 130 patients with ACLF and bacterial infection， sputum （27.7%） was the most common specimen for detection， followed by blood （24.6%）， urine （18.5%）， and ascites （17.7%）. Bacterial infections were dominated by Gram-negative bacteria （58.5%）. Of all bacteria， Escherichia coli （18.5%）， Klebsiella pneumoniae （14.6%）， and Enterococcus faecium （13.8%） were the most common pathogens. Gram-positive bacteria had a high resistance rate to the antibacterial drugs such as erythromycin （72.2%）， penicillin （57.4%）， ampicillin （55.6%）， and ciprofloxacin （53.7%）， while Gram-negative bacteria had a high resistance rate to the antibacterial drugs such as ampicillin （73.3%）， cefazolin （50.0%）， and cefepime （47.4%）. The patients with ACLF and bacterial infection had a relatively high rate of MDR bacterial infection （61.5%）. Comparison of clinical data between the two groups showed that compared with the patients with non-MDR bacterial infection， the patients with MDR bacterial infection had significantly higher levels of alanine aminotransferase （Z=2.089， P=0.037）， aspartate aminotransferase （Z=2.063， P=0.039）， white blood cell count （Z=2.207， P=0.027）， and monocyte count （Z=4.413， P<0.001）. The binary logistic regression analysis showed that monocyte count was an independent risk factor for MDR bacterial infection （odds ratio=7.120， 95% confidence interval ［CI］： 2.478‍ ‍—‍ ‍20.456，P<0.001） and had an area under the ROC curve of 0.686 （95%CI： 0.597‍ ‍—‍ ‍0.776） in predicting ACLF with MDR bacterial infection（P<0.001）， with the optimal cut-off value of 0.50×10⁹/L， a sensitivity of 0.725， and a specificity of 0.400. ConclusionACLF combined with bacterial infections is mainly caused by Gram-negative bacteria， with the common pathogens of Escherichia coli and Klebsiella pneumoniae and a relatively high MDR rate in clinical practice. An increase in monocyte count can be used as an early warning indicator to distinguish MDR bacterial infection from non-MDR bacterial infection.