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Introduction: Severe acute respiratory viral infections are frequency accompanied by multiple organ dysfunction, including acute kidney injury (AKI). In December 2019, the coronavirus disease 2019 (COVID-19) outbreak began in Wuhan, Hubei Province, China, and rapidly spread worldwide. While diffuse alveolar damage and acute respiratory failure are the main features of COVID-19, other organs may be involved, and the incidence of AKI is not well described. We assessed the incidence and clinical characteristics of AKI in patients with laboratory-confirmed COVID-19 and its effects on clinical outcomes. Methods: We conducted a multicenter, retrospective, observational study of patients with COVID-19 admitted to two general hospitals in Wuhan from 5 January 2020 to 21 March 2020. Demographic data and information on organ dysfunction were collected daily. AKI was defined according to the KDIGO clinical practice guidelines. Early and late AKI were defined as AKI occurring within 72 h after admission or after 72 h, respectively. Results: Of the 116 patients, AKI developed in 21 (18.1%) patients. Among them, early and late AKI were found in 13 (11.2%) and 8 (6.9%) patients, respectively. Compared with patients without AKI, patients with AKI had more severe organ dysfunction, as indicated by a higher level of disease severity status, higher sequential organ failure assessment (SOFA) score on admission, an increased prevalence of shock, and a higher level of respiratory support. Patients with AKI had a higher SOFA score on admission (4.5 ± 2.1 vs. 2.8

Introduction: There has been a rapid increase in the number of influenza and invasive pulmonary aspergillosis (IPA) co-infection. Objectives: To explore the risk factors and predictors of a poor prognosis in influenza and IPA co-infection. Methods: We included patients with confirmed influenza during the 2017-2018 influenza season and cases of influenza and IPA co-infection in the literature. Results: A total of 64 patients with influenza infection were admitted to ICU. Of these patients, 18 were co-infected with IPA. Others were assigned to the control group (n = 46). A total of 45 patients from the literature were added to the IPA group (n = 63). A multivariate logistic regression suggested that influenza patients who were given steroids after ICU admission, who had a white blood count (WBC) of more than 10*10 9 /L on ICU admission and whose CT findings manifested as multiple nodules and cavities might have a higher risk of developing IPA. Compared to survivors, non-survivors had higher sequential organ failure assessment (SOFA) scores (16 ± 4 points vs 8 ± 4 points, P < 0.001), lower CD4 + T cell counts on ICU admission [315 (83-466) cells/μL vs 152 (50-220) cells/μL, P = 0.031] and more requirement extracorporeal membrane oxygenation (ECMO) support [13 (50%) vs 7 (18.9%), P = 0.015]. Conclusions: Influenza patients who are given steroids after ICU admission, who have WBCs of greater than 10*10 9 /L on ICU admission, and whose CT imaging shows multiple nodules and cavities might have a high risk of IPA. Higher SOFA scores, CD4 + T cell counts lower than 200 cells/μL on ICU admission and more ECMO requirement might be predictors of a poor prognosis. K E Y W O R D Sclinical presentations, influenza, invasive pulmonary aspergillosis (IPA), prognosis, risk factor | 203 HUANG et Al.

BackgroundLeptospirosis is a water-borne and widespread spirochetal zoonosis caused by pathogenic bacteria called leptospires. Human leptospirosis is an important zoonotic infectious disease with frequent outbreaks in recent years in China. Leptospirosis’s emergence has been linked to many environmental and ecological drivers of disease transmission. In this paper, we identified the environmental and socioeconomic factors associated with leptospirosis in China, and predict potential risk area of leptospirosis using predictive models.MethodsLeptospirosis incidence data were derived from the database of China’s web-based infectious disease reporting system, a national surveillance network maintained by Chinese Center for Disease Control and Prevention. We built statistical relationship between occurrence of leptospirosis and nine environmental and socioeconomic risk factors using logistic regression model and Maxent model.ResultsBoth logistic regression model and Maxent model have high performance in predicting the occurrence of leptospirosis, with AUC value of 0.95 and 0.96, respectively. Annual mean temperature (Bio1) and annual total precipitation (Bio12) are two most important variables governing the geographic distribution of leptospirosis in China. The geographic distributions of areas at risk of leptospirosis predicted from both models show high agreement. The risk areas are located mainly in seven provinces of China: Sichuan Province, Chongqing Municipality, Hunan Province, Jiangxi Province, Guangdong Province, Guangxi Province, and Hainan Province, where surveillance and control programs are urgently needed. Logistic regression model and Maxent model predicted that 403 and 464 counties are at very high risk of leptospirosis, respectively.ConclusionsOur results highlight the importance of socioeconomic and environmental variables and predictive models in identifying risk areas for leptospirosis in China. The values of Geographic Information System and predictive models were demonstrated for investigating the geographic distribution, estimating socioeconomic and environmental risk factors, and enhancing our understanding of leptospirosis in China.

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BackgroundPneumocystis jiroveci pneumonia (PJP) in non-HIV patients is still a challenge for intensivists. The aim of our study was to evaluate mortality predictors of PJP patients requiring Intensive care unit (ICU) admission.MethodsRetrospectively review medical records of patients with diagnosis of PJP admitted to four ICUs of two academic medical centers from October 2012 to October 2015.ResultsEighty-two patients were enrolled in the study. Overall hospital mortality was 75.6 %. Compared with survivors, the non-survivors had older age (55 ± 16 vs. 45 ± 17, p = 0.014), higher APACHE II score (20 ± 5 vs. 17 ± 5, p = 0.01), lower white blood cell count (7.68 ± 3.44 vs. 10.48 ± 4.62, p = 0.005), less fever (80.6%vs. 100 %, p = 0.033), more hypotension (58.1 % vs. 20 %, p = 0.003), more pneumomediastinum (29 % vs. 5 %, p = 0.027). Logistic regression analysis demonstrated that age [odds ratio (OR)1.051; 95 % CI 1.007-1.097; p = 0.022], white blood cell count [OR 0.802; 95 % CI 0.670-0.960; p = 0.016], and pneumomediastinum [OR 16.514; 95 % CI 1.330-205.027; p = 0.029] were independently associated with hospital mortality.ConclusionsMortality rate for non-HIV PJP patients requiring ICU admission was still high. Poor prognostic factors included age, white blood cell count and pneumomediastinum.Electronic supplementary materialThe online version of this article (doi:10.1186/s12879-016-1855-x) contains supplementary material, which is available to authorized users.