To investigate the risk factors for the development of pulmonary infections after thoracoscopic surgery for pulmonary nodules.

Total of 1 526 patients admitted to the Department of Thoracic Surgery of the First Affiliated Hospital of Guangzhou Medical University with confirmed diagnosis of thoracoscopic surgery for pulmonary nodules treatment from June 2020 to June 2021 were collected. According to whether pulmonary infection occurred after surgery, the patients were divided into pulmonary infection group and control group. The clinical baseline data and surgical data of patients in both groups were collected. The clinical and surgical influencing factors of patients with lung nodules after thoracoscopy were analyzed by single factor analysis, and the risk factors of pulmonary infection after thoracoscopy were analyzed by Logistic regression.

Among the 1 526 patients, 700 patients (45.87%) occurred pulmonary infection (pulmonary infection group), while 826 patients (54.13%) did not develop pulmonary infection (control group). The proportion of male patients (61.86%), smoking history (66.43%), nodule size > 2 cm (66.57%), diabetes history (57.29%), resection area (56.43%), smoking index [ (538.01 ± 18.26) annual expenditure] and intraoperative blood loss [(121.53 ± 12.16) ml] of patients in pulmonary infection group were all significantly higher than those in control group (all P < 0.05). The operative time [(202.15 ± 77.83) min] in the pulmonary infection group were significantly longer than that of control group (all P < 0.05). Logistic regression analysis results showed that male (OR = 5.226, 95%CI: 2.600-10.501, P < 0.001), history of smoking (OR = 2.484, 95%CI: 1.137-5.427, P = 0.022), smoking index (OR = 3.304, 95%CI: 1.614-6.767, P = 0.001), history of diabetes (OR = 3.569, 95%CI: 1.684-7.564, P < 0.001), nodule size > 2 cm (OR = 6.157, 95%CI: 2.855-13.276, P < 0.001), intraoperative blood loss (OR = 7.572, 95%CI: 3.166-18.112, P < 0.001), operative time (OR = 10.180, 95%CI: 4.251-24.374, P < 0.001) and pulmonary segmental resection (OR = 9.485, 95%CI: 1.398-64.363, P = 0.021) were all risk factors for pulmonary infection in patients with thoracoscopic surgery for pulmonary nodules.

The factors of pulmonary infection in patients with pulmonary nodules after thoracoscopic surgery include male, smoking, nodule size, intraoperative blood loss, diabetes, operation time and pulmonary segmental resection, which should be prevented and controlled clinically to reduce the risk of infection in patients.

To investigate the value of platelet count (PLT) and red blood cell distribution width (RDW) in predicting the prognosis of acute hepatitis E-induced liver failure.

Total of 128 patients with acute hepatitis E-induced liver failure who were hospitalized in Nantong Third People’s Hospital, Affiliated Nantong Hospital 3 of Nantong University from January 2018 to December 2022 were selected. General data such as gender and age, liver and kidney function, blood routine, coagulation index, inflammation index and alpha-fetoprotein (AFP) of patients within one week after admission were collected, and the model of end-stage liver disease (MELD) score and model of end-stage liver disease combined serum sodium (MELD-Na) score were calculated. According to the survival status at 12 weeks after treatment, the enrolled patients were divided into survival group (104 cases) and death group (24 cases). The levels of total bilirubin (TBil), peripheral white blood cell count (WBC), red blood cell distribution width (RDW), MELD-Na score, serum glutamyltransferase (GGT), total cholesterol (TC), apolipoprotein A (ApoA), fibrinogen (FIB) and antithrombin-Ⅲ (AT-Ⅲ), platelet count (PLT), blood sodium (Na) and other indicators were compared between the two groups. Stata 14.0 software was used for statistical analysis. Logistic regression analysis was used to screen the risk factors affecting the prognosis of patients. The prognostic efficacy of these risk factors in hepatitis E-induced liver failure were evaluated by receiver operating characteristic curve (ROC).

Among the 128 patients with acute hepatitis E-induced liver failure, 116 cases were males (90.62%) and 12 cases were females (9.38%), with an average age of (60.25 ± 9.96) years old. Among the 128 patients, 52 cases were complicated with infection, 12 cases were complicated with hepatic encephalopathy, and 55 cases were treated with artificial liver. In the death group, age (t =-0.35, P = 0.36), sex (χ² = 0.04, P = 0.85), incidence of infection (χ² = 1.97, P = 0.16), incidence of hepatic encephalopathy (χ² = 1.85, P = 0.17) and treatment rate of artificial liver (χ² = 3.16, P = 0.08). The difference was statistically significant compared with survival group. Serum TBil (t =-3.18, P < 0.001), WBC (t =-2.41, P = 0.01), RDW (Z =-2.40, P = 0.02) and MELD-Na score (t =-2.18, P = 0.02) of patients in death group were significantly higher than those of survival group, with significant differences. GGT (Z = 2.40, P = 0.02), TC (t = 2.03, P = 0.02), ApoA (Z = 3.27, P < 0.001), FIB (Z = 2.30, P = 0.02), AT-Ⅲ (t = 3.25, P < 0.001), PLT (t = 3.42, P < 0.001), Na (Z = 2.58, P = 0.01) levels were significantly lower than those of survival group, the differences were statistically significant. Multiple Logistic regression analysis indicated RDW (OR = 1.45, 95%CI: 1.04-2.12, P = 0.03) and PLT count (OR = 0.97, 95%CI: 0.95-0.99, P = 0.04) were all independent prognostic factors of patients with acute hepatitis E-induced liver failure at 12 weeks. Logistic regression analysis results obtained regression equation LogitP = 26.01-0.03 × PLT + 0.37 × RDW, according to a model including PLT and RDW which can be obtained and named PRM. Receiver operating characteristic (ROC) curves of PLT, RDW and PRW were plotted respectively, and the area under the curve (AUC) were calculated. The optimal Cut-off value of PLT for predicting 12-week prognosis of patients with acute hepatitis E-induced liver failure was 157.5, the sensitivity and specificity were 49% and 93%, respectively, and the AUC was 0.7303. The optimal Cut-off value of RDW for predicting prognosis was 16.75, the sensitivity and specificity were 53% and 92%, respectively, and the AUC was 0.6990. The optimal Cut-off value of PRM was 28.33, the sensitivity and specificity were 67% and 92%, respectively, and the AUC was 0.8369. The predictive value of PRM was significantly better than that of PLT (Z = 2.29, P = 0.02).

Blood RDW and blood PLT count are independent factors of 12-week prognosis in patients with acute hepatitis E-induced liver failure. PRM model consisting of PLT and RDW could be used as a simple and accurate prognostic indicator to evaluate the prognosis of acute hepatitis E-induced liver failure.

To investigate the incidence and main risk factors of plastic bronchitis (PB) caused by refractory Mycoplasma pneumoniae pneumonia (RMPP) in children, and to construct a quantitative risk nomograph model for guiding early clinical high-risk stratification.

The clinical data of 350 children diagnosed as RMPP admitted to Jianhu Clinical Medical College, Yangzhou University from February 2020 to February 2023 were analyzed, retrospectively, and were divided into modeling set (280 cases) and validation set (70 cases) by 4︰1, randomly. The model set was divided into PB group (120 cases) and no PB group (160 cases) according to bronchofiberscopy and histopathological findings. The clinical manifestations, blood biochemistry and chest CT signs of patients in different groups were compared, the most different indicators were screened by LASSO regression, the main risk factors were screened by multivariate Logistic regression, and the prediction model was drawn by histogram. The area under the curve (AUC) of plastic bronchitis was predicted by receiver operating curve (ROC) calculation model. The goodness of fit of the model was evaluated by Hosmer-Lemeshow test. The consistency and benefit of the model were evaluated by calibration curve and decision curve.

The modeling set diagnosed 120 cases of PB (42.9%, 120/280) and the verification set diagnosed 25 cases of PB (35.7%, 25/70). The positive rates of PB and other general clinical data were comparable between the two groups (all P > 0.05). Single-factor comparison showed that peak body temperature (t = 3.659, P = 0.001), fever duration (t = 5.021, P < 0.001), hypoxemia (χ² = 4.060, P = 0.044), glucocorticoid (χ² = 7.154, P = 0.007), intravenous gamma globulin (χ² = 16.169, P < 0.001), atelectasis (χ² = 13.810, P < 0.001), pleural effusion (χ² = 11.118, P < 0.001), neutrophil percentage (N%) (Z =1.659, P < 0.001), C-reactive protein (CRP) (Z =15.659, P < 0.001), procalcitonin (PCT) (Z = 9.654, P < 0.001), interleukin 6 (IL-6) (Z = 23.324, P < 0.001), alanine aminotransferase (ALT) (Z = 3.425, P < 0.001), lactate dehydrogenase (LDH) (Z = 123.325, P < 0.001) and D-dimer (Z = 5.246, P < 0.001) were significantly higher than those without PB, while platelet count (PLT) was significantly decreased (Z = 1.995, P < 0.001). Total of 6 non-collinear indexes were selected by LASSO regression, namely peak body temperature, atelectasis, pleural effusion, N%, IL-6 and LDH. Multivariate Logistic regression showed that peak body temperature (OR = 2.756, 95%CI: 2.03-3.567, P < 0.001), atelectasis (OR = 3.526, 95%CI: 2.869-4.123, P < 0.001), pleural effusion (OR = 2.032, 95%CI: 1.456-2.758, P < 0.001), N% (OR = 1.856, 95%CI: 1.235-2.632, P < 0.001), IL-6 (OR = 1.525, 95%CI: 1.124-2.201, P < 0.001), and LDH (OR = 1.302, 95%CI: 1.052-1.968, P < 0.001) were all the risk factors to PB caused by RMPP. The nomogram model was established by R software, with a total score of 500 points. The AUC of the model for predicting PB in model set and validation set were 0.902 (95%CI: 0.856-0.945, P < 0.001) and 0.866 (95%CI: 0.823-0.914, P < 0.001), respectively. Both the calibration curve and the decision curve showed that the model had good degree of coincidence and clinical net benefit ratio.

Children with RMPP have a high incidence of PB, peak body temperature, atelectasis, pleural effusion, N%, IL-6 and LDH are all main risk factors; a nomograph model was developed that has good potential for guiding clinical evaluation of high-risk PB and is worth promoting.

To explore the clinical diagnosis experience of pleural effusion caused by paragonimus infection, so as to avoid misdiagnosis or delayed diagnosis.

The clinical data and treatment of 6 patients with exudative pleural effusion caused by paragonimus infection in the Department of Respiratory and Critical Care Medicine of Taihe Hospital of Shiyan City from May 2018 to December 2022 were analyzed, retrospectively. Data included the demographic characteristics, clinical symptoms, exposure history, laboratory results, pleural fluid cytology, pleural biopsy histopathology, intradermal test for paragonimus-specific antigen, outcome of antiparasitic treatment and follow-up results of 6 patients were collected, respectively.

Three male and three female patients were enrolled, with a mean age of (46.5 ± 5.1) years old. The absolute count and percentage of eosinophils in peripheral blood elevated to varying degrees (12.6%-54.0%). Cytological examination of pleural fluid of four patients showed a small to large number of eosinophils. Four patients underwent thoracoscopic pleural biopsy, of which 3 patients showed extensive eosinophilic infiltration in the interstitium, 1 patient showed parasite eggs and 1 patient showed nonspecific inflammation. There were 4 cases among the 6 patients had a history of intaking fresh water crabs or stream water. Meanwhile, 6 patients were positive in intradermal test of paragonimus-specific antigen (IDTPA) and serum enzyme-linked immunosorbent assay (ELISA) for paragonimus antibody. Paragonimus infection in extrapulmonary organs was excluded and pleural effusion caused by paragonimus was confirmed. All the 6 patients received oral praziquantel treatment (25 mg/kg, 3 times a day, continuous 3 days as a course of treatment, intermittent 7 days and then the second course). Chest computed tomography (CT) showed reduced or disappeared pleural effusion after treatment.

In the diagnosis of unexplained pleural effusion, paragonimus infection should be highly suspected in patients with elevated eosinophils in peripheral blood, pleural fluid, or pleural tissue, and with a history of raw freshwater crab or stream water intaking, especially in patients from areas which paragonimus infection is endemic.

To investigate the significance of genotype identification and drug resistance analysis of children’s respiratory drug-resistant Haemophilus influenzae (HI) for antibiotic treatment.

Total of 92 children with respiratory HI infection admitted to the Fifth People’s Hospital of Hainan Province from March 2018 to March 2022 were selected. Serotype, biotype, genotyping (TEM-1 and ROB-1), antibiotic sensitivity and β-lactamase expression were collected. The influence factors of positive HI β-lactamase in children’s respiratory tract were analyzed by Logistic regression analysis; A line map model of children’s respiratory tract with HI β-lactamase positive was constructed. The model was evaluated by receiver operating characteristic (ROC) curve, calibration curve and clinical decision curve, respectively.

The 92 strains of HI were classified into 8 biotypes, which were Ⅰ, Ⅱ, Ⅲ, Ⅳ, Ⅴ, Ⅵ, Ⅶ and Ⅷ. Among these, types Ⅱ [35.87% (33/92)] and Ⅲ [28.26% (26/92)] were the most prevalent. The serological typing revealed that HIa accounted for the highest proportion [28.26% (26/92)]. The detection rates of TEM-1 and ROB-1 genes were 57.61% (53/92) and 21.74% (20/92), respectively. Sensitivity testing on the 8 biotypes of HI showed that types Ⅴ, Ⅵ, Ⅶ and Ⅷ exhibited no antibiotic resistance. Type Ⅳ HI demonstrated a relatively high resistance rate to ampicillin [57.14% (4/7)], while type Ⅱ HI exhibited a higher resistance rate to cefuroxime [39.39% (13/33)]. Among the 92 strains, 37 (40.22%) were β-lactamase positive and 55 (59.78%) were negative. β-lactamase positive strains showed significantly higher resistance rates to cefpodoxime and ampicillin [33 (89.19%) and 37 (100.00%), respectively] compared to β-lactamase negative strains [4 (6.35%) and 7 (11.11%), respectively], with statistically significant differences (χ² = 68.628, 74.747, both P < 0.001). Multifactor Logistics regression analysis revealed that using antibiotics continuously for ≥ 5 days (OR = 163.464, 95%CI: 8.420-3 173.439, P < 0.001), having ≥ 2 courses of continuous medication (OR = 19.890, 95%CI: 2.300-171.977, P = 0.007), combining ≥ 2 types of drugs (OR = 32.468, 95%CI: 2.792-377.616, P = 0.005) and frequently changing medication ≥ 2 times (OR = 30.769, 95%CI: 3.358-281.921, P = 0.002) were independent risk factors for β-lactamase-positive HI in children’s respiratory tracts. Constructing a column chart model based on these risk factors exhibited high discrimination, accuracy and effectiveness in predicting β-lactamase-positive HI in children’s respiratory tracts without altering the structure.

Clinically, the separation and identification of respiratory HI and the monitoring of drug resistance should be strengthened; the resistance mechanism of HI should be analyzed correctly, the antimicrobial drugs should be rationally used.

To investigate the effect of drug-resistant mutations in the reverse transcriptase region (RT) of hepatitis B virus (HBV) on serum hepatitis B surface antigen (HBsAg) level.

HBV DNA RT region was sequenced from 402 patients with chronic hepatitis B (CHB) who received nucleos(t)ide analogues drug treatment in Infectious Diseases Department of the 910th Joint Logistic Support Unit of the People’s Liberation Army of China from January 2016 to December 2021 by direct sequencing. According to the resistance mutation in RT region, the patients were divided into HBV RT wild group (181 cases) and HBV RT resistant mutation group (221 cases, including 33 cases with A181 mutation, 15 cases with V191 mutation, 82 cases with L180 + M204V mutation and 91 cases with M204I mutation). The influence factors of serum HBsAg level and the impact of HBV RT region resistance mutations on serum HBsAg level were analyzed by non parametric rank sum test (Mann Whitney U). The correlation between serum HBsAg level and HBV DNA in HBV RT resistant mutation group was explored by Spearman correlation analysis.

The levels of serum HBsAg, ALT, AST and HBV genotype B infected patients in HBV RT wild group were significantly higher than those in HBV RT resistant mutation group (Z = -3.426, P = 0.001; Z =-2.347, P = 0.019; Z =-2.532, P = 0.011; Z =-10.387, P = 0.001). Among patients with HBV RT resistant mutation, serum HBsAg level in A181 mutation group, V191 mutation group, L180 + M204V mutation group, and M204I mutation group were significantly lower than those in HBV RT wild group (Z = 2.475, P = 0.013; Z = 2.148, P = 0.032; Z = 2.115, P = 0.034; Z = 2.449, P = 0.014). There was no significant difference in HBV DNA level among the mutation groups (all P > 0.05). Serum HBsAg level were significantly positively correlated with HBV DNA load in A181 mutation group, L180M + M204V mutation group and M204I mutation group (r = 0.486, P = 0.004; r = 0.578, P < 0.001; r = 0.369, P < 0.001).

HBV RT region drug resistance mutation in site of A181, V191, L180 and M204V had negative effect on serum HBsAg level of patients with CHB.

To investigate the risk factors of the occurrence of bloodstream infection, and to analyze the difference of clinical characteristics between multi-bacterial bloodstream infection and single negative bacteria, to provide evidence for the prevention and treatment of bloodstream infection in cardiac surgery.

Medical records of patients with bloodstream infection in Department of Cardiac surgery, Beijing Anzhen Hospital, Capital Medical University from January 2018 to October 2021 were selected to summarize the detection and distribution of pathogens. Non-infection patients were selected with 1︰1 according to the age and gender of patients in infection group during the same period. The clinical data of the bloodstream infection group (including the multi-bacterial infection and single infection of Gram-negative bacteria and Gram-positive bacteria) and the non-infection group were analyzed, respectively. The measurement data were analyzed by t test or non-parametric test, and the counting data was analyzed by χ² test. The indicators that may affect bloodstream infection were analyzed by multivariate Logistic regression, the risk factors of bloodstream infection and mixed bloodstream infection were analyzed.

During the same period, a total of 55 908 cardiac surgery patients were admitted, and 181 cases with bloodstream infection, with an infection rate of 0.3% (181/55 908). The results showed that CPB time (Z = 5.031, P = 0.001) and operation time (Z = 3.830, P = 0.001), usage of ECMO (χ² = 11.569, P = 0.001), IABP (χ² = 30.685, P = 0.001) and CRRT (χ² = 24.761, P = 0.001), exposure to carbapenems (χ² = 11.661, P = 0.001), quinolones (χ² = 4.096, P = 0.043), vancomycin (χ² = 4.096, P = 0.043) and combined antibiotics (χ² = 13.286, P = 0.001) before infection were statistically different between infection group and non-infection group. Multivariate Logistic regression analysis showed that CPB time (OR = 5.031, 95%CI: 1.843-6.798, P < 0.001) and operation time (OR = 1.228, 95%CI: 1.056-1.427, P = 0.008), usage of ECMO (OR = 4.180, 95%CI: 1.863-9.377, P = 0.001), IABP (OR = 4.017, 95%CI: 1.572-10.267, P = 0.004), CRRT (OR = 8.586, 95%CI: 2.494-29.560, P = 0.001), exposure to carbapenems (OR = 15.742, 95%CI: 5.699-43.478, P < 0.001), quinolones (OR = 2.272, 95%CI: 1.057-4.886, P = 0.030) and vancomycin (OR = 4.297, 95%CI: 1.199-15.400, P = 0.025) and combined use of antibiotics (OR = 4.520, 95%CI: 2.154-9.484, P = 0.001) before infection were all risk factors of postoperative bloodstream infection, with statistically significant differences. The total hospital duration of patients in infection group was significantly longer than that of non-infection group, with significant difference (Z = 8.033, P = 0.001). There were 52 deaths (28.7%) in infection group and 17 deaths (9.3%) in non-infecteion group, the mortality rate of the two groups was significantly different (χ² = 21.935, P = 0.001). Among bloodstream infection group, 37 patients (20.4%) were infected with single Gram-negative bacilli, 28 patients (15.5%) were infected with single Gram-positive cocci, 116 patients (64.1%) were infected with Gram-negative bacilli and Gram-positive cocci. Total of 234 Gram-negative bacillus strains were detected, Acinetobacter baumannii (64 strains, 27.3%) and Klebsiella pneumoniae (56 strains, 23.9%) were the most common pathogens. Total of 145 strains of Gram-positive cocci were detected, among which Staphylococcus epidermidis (69 strains, 47.6%) was the most common. The results showed that CPB time (t =-4.010, P = 0.001) and operation time (t =-8.532, P = 0.001), exposure to 3 kinds of invasive endovascular devices (χ² = 11.723, P = 0.001) and more than 3 kinds of invasive endovascular devices (χ² = 4.618, P = 0.032), exposure to carbapenems (χ² = 11.661, P = 0.001), vancomycin (χ² = 4.096, P = 0.043), linezolid (χ² = 15.174, P = 0.001), polycolistin (χ² = 6.353, P = 0.012) and combined antibiotics (χ² = 13.286, P = 0.001) before infection were significantly different between multi-bacterial bloodstream infection and single negative bacteria group. Multivariate Logistic regression analysis showed that CPB time (OR = 4.851, 95%CI: 1.190-1.313, P = 0.015) and operation time (OR = 14.764, 95%CI: 1.363-17.264, P = 0.014), exposure to 3 (OR = 1.257, 95%CI: 1.046-1.510, P = 0.015) or more than 3 (OR = 1.006, 95%CI: 1.001-1.012, P = 0.032) invasive endovascular devices, usage of carbapenems (OR = 4.765, 95%CI: 1.770-12.828, P = 0.002), vancomycin (OR = 7.750, 95%CI: 1.277-4.203, P = 0.026), linezolid (OR = 3.925, 95%CI: 1.665-9.254, P = 0.002), polycolistin (OR = 1.987, 95%CI: 1.985-3.451, P = 0.020) and combined use of antibiotics (OR = 1.466, 95%CI: 1.012-1.976, P = 0.012) before infection were the risk factors of postoperative multi-bacterial bloodstream infection, and the differences were statistically significant. The length of hospital duration was significantly prolonged after multi-bacterial bloodstream infection, with significant difference (Z =-1.576, P = 0.001).

Bloodstream infection and mixed bloodstream infection of patients with cardiac surgery are mostly associated with invasive intravascular device implantation and antibiotic exposure, and can lead to prolonged hospitalization and increased mortality, which seriously affect the prognosis of patients. Therefore, it is necessary to pay attention to the surgical operation and the rational use of antibiotics to reduce the occurrence of blood flow infection in cardiac surgery.

To investigate the characteristics of distribution and drug resistance of bacterial infection in neonates from 2020 to 2022 in Xi’an Children’s Hospital.

The specimens were collected from hospitalized neonates from January 2020 to December 2022 in Xi’an Children’s Hospital, and the distribution, composition and drug resistance of the specimens were analyzed, which were compared with the national children surveillance data by Pearson Chi-square test.

Total of 496 strains of bacteria were isolated from 9 346 specimens; including 251 (50.60%) strains of Gram-negative bacteria and 231 (46.57%) strains of Gram-positive bacteria; 14 (2.83%) strains of fungi. The top-five bacteria were Escherichia coli (Eco) (90 strains, 18.15%), Coagulase negative Staphylococci (CNS) (71 strains, 14.31%), Klebsiella peneumoniae (Kpn) (69 strains, 13.91%), Staphylococcus aureus (Sau) (57 strains, 11.49%) and Enterococcus faecium (Efa) (41 strains, 8.27%). Total of 184 strains of multi-drug resistant bacteria were detected from 496 pathogenic bacteria (37.09%); 105 (57.07%) strains of Gram-negative bacteria and 79 (42.93%) strains of Gram-positive bacteria were detected among multiple drug resistant bacteria. The detection rates of Kpn, CNS, Sau, Eco, AB and Pa were 58 strains (84.06%), 56 strains (78.87%), 23 strains (40.35%), 36 strains (40.00%), 4 strains (36.36%) and 7 strains (33.33%). The strains were highly resistant to many kinds of antibiotics, some drug resistance rates were significantly different from the national surveillance levels. The resistance rate of CNS (97.2%) to penicillin were significantly higher than those of Sau (94.7%). The resistance rate of Sau and CNS against clindamycin were 68.4% and 59.2%, which were significantly higher than those of the national surveillance levels (36.7% and 42.3%) (χ² = 24.431, P < 0.001; χ² = 8.119, P = 0.004). The resistance rates of Eco to cephalosporins were different as the follows: 75.5% to cefazolin, 67.8% to cefuroxime, 65.5% to cefatriaxone, which were significantly higher than those of the national surveillance levels (58.8%, 47.5% and 46.6%) (χ² = 10.329, P = 0.001; χ² = 14.674, P < 0.001; χ² = 12.841, P < 0.001). The resistance rates of Kpn to cephalosporins were as the follows: 76.81% to cefatriaxone, 68.1% to Cefazolin, 62.8% to ceftazidime, 62.3% to cefuroxime, which were significantly higher than those of the national surveillance levels (44.1%, 53.2%, 30.6% and 49.0%), with significant differences (χ² = 29.240, P < 0.001; χ² = 6.056, P = 0.014, χ² = 34.583, P < 0.001; χ² = 4.789, P = 0.029). The resistance rates to meropenem and imipenem were 39.1% and 40.6%, respectively, significantly higher than 14.8% and 11.7% of the national monitoring data, with significant differences (χ² = 30.816, P < 0.001; χ² = 52.243, P < 0.001).

The majority of hospitalized neonatal pathogens from 2020 to 2022 in our hospital were CNS, Eco and Kpn. The drug resistance rates of Sau and CNS to clindamycin; Eco to cefazolin, cefuroxime, and ceftriaxone, and Kpn to cephalosporins and carbapenems were significantly higher than the national surveillance data. Antibiotics should be used rationally according to the distribution of main pathogenic bacteria locally and the results of drug sensitivity.

To investigate the risk factors of liver damage in patients with hepatitis B virus (HBV) infection complicated with pulmonary tuberculosis, and to construct a nomogram prediction model.

Total of 192 patients with HBV infection combined with tuberculosis were selected from Songjiang District Central Hospital of Shanghai from January 2018 to December 2021 were collected. According to whether had liver injury or not, patients were grouped into control group (104 cases) and liver injury group (88 cases). Logistic regression analysis was used to screen the risk factors of liver damage in patients with hepatitis B virus infection complicated with pulmonary tuberculosis; The nomogram model for predicting liver damage in patients with HBV infection and pulmonary tuberculosis was constructed by R software, and the receiver operator characteristic curves (ROC) curve and calibration curve were used to verify the nomogram model.

The comparison between patients of the two group in terms of education level (χ² = 5.224, P = 0.022), albumin (χ² = 15.147, P < 0.001), preventive antiviral therapy (χ² = 10.831, P = 0.001), use of hepatoprotective drugs (χ² = 6.159, P = 0.013), treatment type (χ² = 13.135, P < 0.001) and history of liver disease (χ² = 5.493, P = 0.019) were all significantly different. Logistic regression analysis showed that albumin < 35 g/L (OR = 4.062, 95%CI: 1.993-8.280, P < 0.001), no preventive antiviral therapy (OR = 2.586, 95%CI: 1.295-5.165, P = 0.007), no hepatoprotective drugs (OR = 2.327, 95%CI: 1.190-4.551, P = 0.014), treatment type of "retreatment" (OR = 2.701, 95%CI: 1.299-5.615, P = 0.008) and history of liver disease (OR = 3.024, 95%CI: 1.149-7.955, P = 0.025) were all independent risk factors for liver injury in patients with HBV infection complicated with pulmonary tuberculosis. The area under the ROC curve of nomogram model predicts HBV infection with tuberculosis was 0.766 (95%CI: 0.701-0.832). The slope of the constructed nomogram prediction model calibration curve is close to 1, and the H-L goodness-of-fit test showed good fitting degree (χ² = 6.272, P = 0.617).

The nomogram prediction model constructed based on five risk factors including albumin < 35 g/L, no preventive antiviral treatment, no use of hepatoprotective drugs, treatment type of "retreatment", and history of liver disease can effectively predict liver damage in patients with HBV infection complicated with pulmonary tuberculosis.