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AIM: The aim of this study is to construct a quality evaluation system for fever clinic nursing management. BACKGROUND: Fever clinic is the first line of defence against the epidemic during COVID-19 in China. METHODS: Our study combines the Delphi method and the analytic hierarchy process. Delphi method was used to carry out two rounds of consultation for 18 experts, to select and revise indicators at all levels. Analytic hierarchy process was used to calculate the weight of indicators at all levels. RESULTS: A quality evaluation system of nursing management for fever clinics is built using Delphi method. It includes five first-level indexes, 14 second-level indexes and 82 third-level indexes. A two-round expert consultation is used to build the indicators. The recovery rates of expert questionnaires in the two rounds were, respectively, 100% and 94%, and expert authority coefficients were 0.925. The Kendall coefficients in the two rounds were, respectively, 0.205 and 0.162 (P < .001). The weight analysis shows that health management of nursing staff (0.2803) and disinfection isolation and treatment of medical waste (0.2803) are most important, followed by nursing post management and personnel training (0.1889), configuration and management of equipment (0.1427) and patient consultation management and nursing (0.1078). CONCLUSION: The quality evaluation system of nursing management in the constructed fever clinic is used to put forward a specific, objective and quantifiable evaluation criteria of nursing quality for fever clinic management, which can better meet the needs of epidemic prevention and control, and has a certain application and promotion value. IMPLICATIONS FOR NURSING MANAGEMENT: The establishment and improvement of a quality system for fever clinic care management will help to respond to outbreaks such as COVID-19.

Objectives. To compare the epidemic prevention ability of COVID-19 of each province in China and to evaluate the existing prevention and control capacity of each province. Methods. We established a quasi-Poisson linear mixed-effects model using the case data in cities outside Wuhan in Hubei Province, China. We adapted this model to estimate the number of potential cases in Wuhan and obtained epidemiological parameters. We estimated the initial number of cases in each province by using passenger flowrate data and constructed the extended susceptible–exposed–infectious–recovered model to predict the future disease transmission trends. Results. The estimated potential cases in Wuhan were about 3 times the reported cases. The basic reproductive number was 3.30 during the initial outbreak. Provinces with more estimated imported cases than reported cases were those in the surrounding provinces of Hubei, including Henan and Shaanxi. The regions where the number of reported cases was closer to the predicted value were most the developed areas, including Beijing and Shanghai. Conclusions. The number of confirmed cases in Wuhan was underestimated in the initial period of the outbreak. Provincial surveillance and emergency response capabilities vary across the country.

Introduction Previous research has debated whether red blood cell (RBC) transfusion is associated with decreased or increased mortality in patients admitted to the intensive care unit (ICU). We conducted a systematic review and meta-analysis to assess the relationship of RBC transfusion with in-hospital mortality in ICU patients. Methods We carried out a literature search on Medline (1950 through May 2013), Web of Science (1986 through May 2013) and Embase (1980 through May 2013). We included all prospective and retrospective studies on the association between RBC transfusion and in-hospital mortality in ICU patients. The relative risk for the overall pooled effects was estimated by random effects model. Sensitivity analyses were conducted to assess potential bias. Results The meta-analysis included 28,797 participants from 18 studies. The pooled relative risk for transfused versus nontransfused ICU patients was 1.431 (95% CI, 1.105 to 1.854). In sensitivity analyses, the pooled relative risk was 1.211 (95% CI, 0.975 to 1.505) if excluding studies without adjustment for confounders, 1.178 (95% CI, 0.937 to 1.481) if excluding studies with relative high risk of bias, and 0.901 (95% CI, 0.622 to 1.305) if excluding studies without reporting hazard ratio (HR) or relative risk (RR) as an effect size measure. Subgroup analyses revealed increased risks in studies enrolling patients from all ICU admissions (RR 1.513, 95%CI 1.123 to 2.039), studies without reporting information on leukoreduction (RR 1.851, 95%CI 1.229 to 2.786), studies reporting unadjusted effect estimates (RR 3.933, 95%CI 2.107 to 7.343), and studies using odds ratio as an effect measure (RR 1.465, 95%CI 1.049 to 2.045). Meta-regression analyses showed that RBC transfusion could decrease risk of mortality in older patients (slope coefficient −0.0417, 95%CI −0.0680 to −0.0154). Conclusions There is lack of strong evidence to support the notion that ICU patients who receive RBC transfusion have an increased risk of in-hospital death. In studies adjusted for confounders, we found that RBC transfusion does not increase the risk of in-hospital mortality in ICU patients. Type of patient, information on leukoreduction, statistical method, mean age of patient enrolled and publication year of the article may account for the disagreement between previous studies. Electronic supplementary material The online version of this article (doi:10.1186/s13054-014-0515-z) contains supplementary material, which is available to authorized users.