Objective To analyze the clinical features and treatment of severe H1N1 influenza.Methods The clinical data of 34 patients with severe H1N1 influenza admitted to intensive care unit from October to December 2009 were reviewed. Results The patients aged 3 months to 60 years with an average of ( 13. 9 ±4. 5) years, of which 24 patients were younger than 7 years old. Fever( 30 cases) , cough( 32 cases) , progressive shortness of breath( 19 cases) were the main symptoms. White blood cell count was normal in 21 cases, increased in 6 cases, and decreased in 7 cases. Lymphocyte count was normal in 16 cases, increased in 12 cases, and decreased in6 cases. Chest X-ray films showed bilateral or unilateral patchy pulmonary fuzzy shadows in28 cases. Chest CT showed diffuse interstitial lesion in1 case, pleural effusion in 2 cases, and bronchiectasis in 1 case. The hepatic and myocardial enzymogramparameters were all abnormal.30 cases were treated by oseltamivir and ribavirin, 4 cases by methyllprednisolone, and 6 cases by gamma globulin. 8 cases underwent routine intubation and mechanical ventilation, and 5 cases received non-invasive mechanical ventilation. All 34 patients were cured. Conclusions Lung, heart, and liver are the major target organs in severe H1N1 influenza. Mechanical ventilatory support is an important treatment for severe H1N1influenza.
Objective To explore the clinical characteristics of patients with severe pandemic H1N1 Influenza in Sichuan and risk factors related to patients’ prognosis. Methods We observed 135 severe patients who came to hospitals for pandemic H1N1 Influenza from 12 cities in Sichuan, China,between September 12, 2009 to December 14, 2009, and described their baseline characteristics, treatment,and outcomes. A stepwise multiple Logistic-regression analysis was used to evaluate the independentpredictors of death. Results Of the 135 patients we studied, 86 patients were male. The average age was ( 28. 2 ±19. 3) years old, while patients between 19 to 45 years of age accounted for 47. 4% . 96 patients ( 71. 1% ) presented with fever. 51 patients( 37. 8% ) had comorbid conditions. The most frequent organdysfunction was seen in lung ( 71. 1% ) , liver( 27. 4% ) and cardia( 24. 4%) ; 130 patients( 96. 3% ) had received oseltamivir, 26 patients ( 19. 3% ) required mechanical ventilation. 12 of the 135 patients died.Compared with the survivors, patients who died were more likely to have a higher age, lower average bloodpressure when admitted, more organ dysfunction, and more likely to have cardia or nervous system dysfunction. The nonsurvivors also seemed to have less opportunity to be exposed to neuraminidase inhibitors, and have more demand for mechanical ventilation. The P value were all under 0. 05. The multipleLogistic-regression analysis showed the independent predictors of death were the average blood pressure when admitted and the demand for mechanical ventilation . The P value were both under 0. 05. The OR value was 0. 86(95% CI 0. 002-0. 936) and 13. 86( 95% CI 1. 146-16. 583) , respectively. Conclusions For these severe patients with pandemic H1N1 Influenza we study, the male patients are more than female. Most patients are between 19 to 45 years of age. The most frequent organ dysfunction is seen in lung, liver and cardia. The mortality of these patients is 8. 9% . Compared with the survivors, patients who died were morelikely to have a higher age, lower average blood pressure when admitted, more organ dysfunction, and more likely to have cardia ornervous systemdysfunction. The nonsurvivors also seemed to have less opportunity to be exposed to neuraminidase inhibitors, and more demand for mechanical ventilation. The multiple Logisticregression analysis showed the independent predictors of death are the average blood pressure and the demand for mechanical ventilation. The OR value is 0. 86 ( 95% CI 0. 002-0. 936) and 13. 86 ( 95% CI1. 146-16. 583) respectively.
ObjectiveTo analyze the clinical and epidemiological characteristics of hospitalized avian influenza A (H7N9) virus infections in Hunan province from 2013 to 2017, and provide evidences for control, diagnosis and treatment of this disease.MethodsNinety-one hospitalized patients were confirmed with H7N9 infection in Hunan. Excluding 2 patients less than 18 years old and 10 with missing data, 79 patients with H7N9 infection were analyzed.ResultsMost confirmed cases were affected in the second and fifth epidemic wave and number of patients in the fifth wave was more than the sum in prior 4 waves. Epidemiological characteristics, clinical symptoms and case fatality did not change significantly. Administration of antiviral drugs was more active in the fifth wave [from illness onset to antiviral drug: (6.3±2.4)d vs. (7.6±2.4)d, P=0.047]. Multiple logistic regression analysis showed that shock (OR=4.683, 95%CI 1.136–19.301, P=0.033) was the independent risk factor of H7N9 infections. There were no significant differences in case fatality among group oseltamivir, group oseltamivir+peramivir, and group peramivir.ConclusionsPatients with avian influenza A (H7N9) increased in the fifth wave but clinical characteristics changed little. Antiviral treatment should be more active. Shock is an independent risk factor of H7N9 infections. Oseltamivir-peramivir biotherapy can not reduce case fatality compared with oseltamivir or peramivir monotherapy.
Objective To investigate the clinical characteristics and treatment of severe H1N1 influenza during pregnancy and postpartum.Methods Clinical data of 7 pregnant women and 2 postpartum women with severe H1N1 influenza admitted from October to December 2009 were reviewed. Results Three pregnant women underwent caesarean section during hospitalization. The main symptoms included fever ( in9 cases, and fever lasted more than 3 days in 7 cases) , cough and sputum ( in 9 cases) , and dyspnea ( in 7 cases) . Asthenia and muscular soreness were not serious, and there were no accompanying symptoms of digestive tract. Moist rales were heard in 5 cases. White blood cell count decreased in 3 cases, neutrophils increased in 6 cases, and lymphocytes reduced in 7 cases. Hepatic enzymes were abnormal in 4 cases, and myocardial enzymes were abnormal in5 cases. 8 patients had hypoxemia, with PaO2 less than 40 mmHg in5 cases. Chest X-ray films and CT showed double pneumonia in 9 patients. 9 patients were given oseltamivir antiviral treatment. 8 cases were given antibiotic therapy. 5 patients with bilateral severe pneumonia and respiratory failure were given corticosteriod therapy. 5 severe patients were treated with non-invasive ventilation. One case switched to invasive ventilation and eventually died. Conclusions Pregnant and postpartum women with influenzaH1N1 are likely to develop into severe condition which is commonly rapidlyprogressive and even life-threatening. The main causes of death are pneumonia and acute respiratory distress syndrome.
Objective To investigate the free influenza vaccination of health care workers in major departments and explore the possible influencing factors of influenza vaccination of staff. Methods In November 2021, a questionnaire survey was conducted among health care workers who received free influenza vaccination in 19 major departments of West China Hospital of Sichuan University, and the un-vaccinated workers’ information was obtained from the registration system of staff information. Multiple logistic regression model was used to analyze the possible influencing factors of free influenza vaccination. Results The coverage rate of centralized free influenza vaccination of staff in major departments was 32.7% (1101/3369). Multiple logistic regression analysis showed that workers who were female [odds ratio (OR)=1.853, 95% confidence interval (CI) (1.481, 2.318), P<0.001], with an educational background of high school or below [OR=4.304, 95%CI (2.484, 7.455), P<0.001], engaged in nursing work [OR=2.341, 95%CI (1.701, 3.221), P<0.001], and with 11 or more years of working experience [OR=2.410, 95%CI (1.657, 3.505), P<0.001] were more likely to inject influenza vaccine, and workers who had a bachelor’s degree were less likely to inject influenza vaccine. Conclusions The rate of free influenza vaccination among medical staff is low. In order to mobilize the enthusiasm of influenza vaccination among medical staff, it is necessary to analyze the characteristics of the population and take targeted measures to improve the level of vaccination among medical staff.
摘要:目的: 探讨传染病医院工作人员对甲型H1N1流感医院感染控制知识的认知程度。 方法 :选择救治甲型H1N1流感期间传染病医院不同岗位工作人员进行无记名自填式调查问卷。 结果 :全院对甲型H1N1流感医院感染控制认知总体情况良好,认知的薄弱环节是对防护措施,尤其是一级防护和三级防护的认知;不同工作岗位的工作人员对甲型H1N1流感医院感染控制认知程度不同,与甲型H1N1流感有接触的工作人员认知度高于其他工作人员,中高级职称、高年龄段(35岁以上)的医务人员认知度高于初级职称及低年龄段(35岁以下)的医务人员。 结论 :针对薄弱环节,进一步加强全员医院感染控制知识、技能的培训考核。Abstract: Objective: To explore the knowledge about the Influenza A (H1N1) of Chengdu Hospital for Infectious Diseases ‘s staff. Methods : Different medical staff of the infectious Disease Hospital during the influenza A (H1N1) treatment in Chinese mainland was selected to fill in anonymous questionnaire. Results : The awareness of the hospital is well about the hospital infection control to Influenza A (H1N1). Preventive measure is weak, especially about the primary barriers and the third barriers. The different position awareness is different. The staff who is in touch with Influenza A (H1N1) is more awareness than the others, the senior and intermediate title is more awareness than the Junior Title, the high ages group(over 35 ages) is more awareness than the low ages group (under 35 ages). Conclusion : For the weak link, further strengthens the entire hospital infection control knowledge, skills training and examination.
Objective To investigate the clinical characteristics of patients with sever H1N1 influenza in Xinjiang region, and analyze risk factors related to patients’prognosis. Methods 63 patients with severe H1N1 influenza from September 2009 to December 2009, who came from five general hospitals and contagious disease hospitals were retrospectively studied. Data of baseline characteristics, treatment, and outcomes were collected. Results Among the 63 cases of severe H1N1 influenza patients, 46 patients survived, in which 30 cases were complicated with pneumonia( 63. 8% ) , 10 cases with MODS ( 43. 48% ) ;26 were male,20 were female; the median age was ( 28. 48 ±19. 59) years old.17 patients died, in which 11 were male, 6 were female; the median age was ( 39. 47 ±21. 23) years old. There were no significantdifferences in white blood cells, neutrophils, granulocytes, lymphocytes, Hb, platelets, CK-MB, HB, DH, UN,APTT, INR, K+ , Na+ , Cl - , PaO2 , SaO2 between the survival patients and the died patients ( P gt; 0. 05) .However there were significant differences in AST, ALT, CK, LDH, AL, CR, and pH ( P lt; 0. 05) .Conclusions Most of the patients with sever H1N1 influenza are young. The typical clinical manifestations are fever, cough, and expectoration. The patients usually are complicated with pneumonia. The patients complicated with MODS have a higher risk of death. Early administration of effective antiviral agents, low dose corticosteroids, and reasonable mechanical ventilation may improve the prognosis.
H7N9, a novel avian influenza A virus that causes human infections emerged in February, 2013 in Anhui and Shanghai, China. The epidemic quickly spread to Zhejiang, Jiangsu and other neighbor provinces. As of May 30th, 2013, WHO had reported 132 cases, 37 (28%) of which died. Aiming at such serious outbreak of epidemic, we retrospectively analyzed its etiology, epidemiology, clinical characteristics, treatment, prevention and control based on data and evidence. Experience and evidence of the risk surveillance and management of such a novel anthropozoonosis lacks in China, or even lacks around the world. Quick and accurate identification of the rules and of the variation and transmission of avian influenza virus becomes a key to prevention, control and treatment. According to current best available evidence around the world, Chinese medicine and biomedicine should be put in to parallel use. Only realizing evidence-based decision making can we effectively prevent and control the epidemic, treat patients, and reduce the loss.
Objective To study the effect of nontypeable Hemophilus influenzae(NTHi) strain ATCC49247 on proinflammatory cytokines expression of human A549 lung epithelial cell line. Methods Confluent A549 cells were co-incubated with NTHi, NTHi+Erythromycin(10 mg/L), NTHi+Gentamicin(100 mg/L), and NTHi+Dexamethasone(100 μmol/L),and nuclear factor kappa B(NF-κB) inhibitor primed cells were co-incubated with NTHi for 24 h. Then levels of interleukin-8（IL-8） and tumor necrosis factor-α(TNF-α) in the supernatant was assayed by enzyme-linked immunosorbent assay(ELISA) and the expression of intercellular adhesion molecule-1(ICAM-1) in cells was detected by immunohistochemistry staining. Results A549 cells were transformed and died after co-intubated with NTHi for 24 h. NTHi induced A549 cells to release significantly greater amounts of IL-8, which was inhibited by NF-κB inhibitor pyrrolidine dithiocarbamate（PDTC）. Incubating of A549 cells with NTHi significantly induced release of IL-8 and the expression of ICAM-1, which was blocked by erythromycin and dexamethasone and not by gentamicin. TNF-α was not detected in all circumstances. Conclusions NTHi can increase significantly the release and expression of proinflammatory cytokines through NF-κB pathway. Antibacterial drug erythromycin also has anti-inflammatory effect.
Objective To establish and verify the early prediction model of critical illness patients with influenza. Methods Critical illness patients with influenza who diagnosed with influenza in the emergency departments from West China Hospital of Sichuan University, Shangjin Hospital of West China Hospital of Sichuan University, and Panzhihua Central Hospital between January 1, 2017 and June 30, 2020 were selected. According to K-fold cross validation method, 70% of patients were randomly assigned to the model group, and 30% of patients were assigned to the model verification group. The patients in the model group and the model verification group were divided into the critical illness group and the non-critical illness group, respectively. Based on the modified National Early Warning Score (MEWS) and the Simplified British Thoracic Society Score (confusion, uremia, respiratory, BP, age 65 years, CRB-65 score), a critical illness influenza early prediction model was constructed and its accuracy was evaluated. Results A total of 612 patients were included. Among them, there were 427 cases in the model group and 185 cases in the model verification group. In the model group, there were 304 cases of non-critical illness and 123 cases of critical illness. In the model verification group, there were 152 cases of non-critical illness and 33 cases of critical illness. The results of binary logistic regression analysis showed that age, hypertension, the number of days between the onset of symptoms and presentation at the emergency department, consciousness state, white blood cell count, and lymphocyte count, oxygen saturation of blood were the independent risk factors for critical illness influenza. Based on these 7 risk factors, an early prediction model for critical illness influenza was established. The correct percentages of the model for non-critical illness and critical illness patients were 95.4% and 77.2%, respectively, with an overall correct prediction percentage of 90.2%. The results of the receiver operator characteristic curve showed that the sensitivity and specificity of the early prediction model for critical illness influenza in predicting critical illness patients were 0.909, 0.921, and the area under the curve and its 95% confidence interval were 0.931 (0.860, 0.999). The sensitivity, specificity, and area under the curve (0.935, 0.865, 0.942) of the early prediction model for critical illness influenza were higher than those of MEWS (0.642, 0.595, 0.536) and CRB-65 (0.628, 0.862, 0.703). Conclusions The conclusion is that age, hypertension, the number of days between the onset of symptoms and presentation at the emergency department, consciousness, oxygen saturation, white blood cell count, and absolute lymphocyte count are independent risk factors for predicting severe influenza cases. The early prediction model for critical illness patients with influenza has high accuracy in predicting severe influenza cases, and its predictive value and accuracy are superior to those of the MEWS score and CRB-65 score.