Impact of perioperative RSV or influenza infection on length of stay and risk of unplanned ICU admission in children: a case-control study

<p>Abstract</p> <p>Background</p> <p>Children with viral respiratory infections who undergo general anesthesia are at increased risk of respiratory complications. We investigated the impact of RSV and influenza infection on perioperative outcomes in children undergoing general anesthesia.</p> <p>Methods</p> <p>We performed a retrospective case-control study. All patients under the age of 18 years who underwent general anesthesia at our institution with confirmed RSV or influenza infection diagnosed within 24 hours following induction between October 2002 and September 2008 were identified. Controls were randomly selected and were matched by surgical procedure, age, and time of year in a ratio of three controls per case. The primary outcome was postoperative length of stay (LOS).</p> <p>Results</p> <p>Twenty-four patients with laboratory-confirmed RSV or influenza who underwent general anesthesia prior to diagnosis of viral infection were identified and matched to 72 controls. Thirteen cases had RSV and 11 had influenza. The median postoperative LOS was three days (intra-quartile range 1 to 8 days) for cases and two days (intra-quartile range 1 to 5 days) for controls. Patients with influenza had a longer postoperative LOS (p < 0.001) and patients with RSV or influenza were at increased risk of unplanned admission to the PICU (p = 0.04) than matched controls.</p> <p>Conclusions</p> <p>Our results suggest that children with evidence of influenza infection undergoing general anesthesia, even in the absence of symptoms previously thought to be associated with a high risk of complications, may have a longer postoperative hospital LOS when compared to matched controls. RSV and influenza infection was associated with an increased risk of unplanned PICU admission.</p

Time-series model to predict impact of H1N1 influenza on a children\u27s hospital

The spring of 2009 witnessed the emergence of a novel influenza A(H1N1) virus resulting in the first influenza pandemic since 1968. In autumn of 2010, the 2009 novel H1N1 influenza strain re-emerged. We performed a retrospective time-series analysis of all patients with laboratory-confirmed H1N1 influenza who presented to our institution during 2009. Cases of influenza were assembled into 3-day aggregates and forecasting models of H1N1 influenza incidence were created. Forecasting estimates of H1N1 incidence for the 2010–2011 season were compared to actual values for our institution to assess model performance. Ninety-five percent confidence intervals calculated around our model\u27s forecasts were accurate to ±3·6 cases per 3-day period for our institution. Our results suggest that time-series models may be useful tools in forecasting the incidence of H1N1 influenza, helping institutions to optimize distribution of resources based on the changing burden of illness

How to approach and treat viral infections in ICU patients

Patients with severe viral infections are often hospitalized in intensive care units (ICUs) and recent studies underline the frequency of viral detection in ICU patients. Viral infections in the ICU often involve the respiratory or the central nervous system and can cause significant morbidity and mortality especially in immunocompromised patients. The mainstay of therapy of viral infections is supportive care and antiviral therapy when available. Increased understanding of the molecular mechanisms of viral infection has provided great potential for the discovery of new antiviral agents that target viral proteins or host proteins that regulate immunity and are involved in the viral life cycle. These novel treatments need to be further validated in animal and human randomized controlled studies