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Characteristics and outcomes of a cohort hospitalized for pandemic and seasonal influenza in Germany based on nationwide inpatient data

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Figshare2017-07-15 更新2026-04-29 收录
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https://figshare.com/articles/dataset/Characteristics_and_outcomes_of_a_cohort_hospitalized_for_pandemic_and_seasonal_influenza_in_Germany_based_on_nationwide_inpatient_data/5210383
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RationaleFrom June of 2009 to August of 2010 the influenza subtype H1N1pdm09 caused a worldwide pandemic. The impact on populations and health care systems around the globe evolved differently. Substantial data come from the German national surveillance network in an outpatient and private practice setting, while information on hospitalized patients in Germany is rather limited.MethodsData from the Federal Statistics Office comprising health insurance claims of the entire nationwide inpatient sample from 2005 to 2012 were used to identify patients who were hospitalized for laboratory-confirmed influenza and to analyse demographical aspects, comorbidities, hospitalization duration, outcomes and ventilator use during the pandemic and seasonal waves of influenza.Measurements and main resultsA number of 34,493 admissions for laboratory-confirmed influenza occurred during waves between 2005 and 2012. During the pandemic seasonal waves, the number of hospitalizations vastly surpassed the level that was seen in any of the seasonal waves. A major demographic shift was seen with respect to patient age, as younger patients ( 60 years old). Time to ventilation was shorter in non-fatal cases (328 vs. 349 hours) and longer in fatal cases (419 vs. 358 hours). Logistic regression was used to show the impact of comorbidities and co-diagnoses on mortality and the need for ventilation, as well as differences between pandemic and seasonal influenza.ConclusionsInpatient data suggest differences in patient populations during pandemic and seasonal influenza. Younger patients were more frequently hospitalized. Differences with respect to the presence of certain comorbidities and co-diagnoses, length of stay, time to ventilation and ventilation time could be identified.
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2017-07-15
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