Global Variability in Reported Mortality for Critical Illness during the 2009-10 Influenza A(H1N1) Pandemic: A Systematic Review and Meta-Regression to Guide Reporting of Outcomes during Disease Outbreaks.

• Main Authors: Abhijit Duggal, Ruxandra Pinto, Gordon Rubenfeld, Robert A Fowler
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2016-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC4865181?pdf=render

PURPOSE:To determine how patient, healthcare system and study-specific factors influence reported mortality associated with critical illness during the 2009-2010 Influenza A (H1N1) pandemic. METHODS:Systematic review with meta-regression of studies reporting on mortality associated with critical illness during the 2009-2010 Influenza A (H1N1) pandemic. DATA SOURCES:Medline, Embase, LiLACs and African Index Medicus to June 2009-March 2016. RESULTS:226 studies from 50 countries met our inclusion criteria. Mortality associated with H1N1-related critical illness was 31% (95% CI 28-34). Reported mortality was highest in South Asia (61% [95% CI 50-71]) and Sub-Saharan Africa (53% [95% CI 29-75]), in comparison to Western Europe (25% [95% CI 22-30]), North America (25% [95% CI 22-27]) and Australia (15% [95% CI 13-18]) (P<0.0001). High income economies had significantly lower reported mortality compared to upper middle income economies and lower middle income economies respectively (P<0.0001). Mortality for the first wave was non-significantly higher than wave two (P = 0.66). There was substantial variability in reported mortality among the specific subgroups of patients: unselected critically ill adults (27% [95% CI 24-30]), acute respiratory distress syndrome (37% [95% CI 32-44]), acute kidney injury (44% [95% CI 26-64]), and critically ill pregnant patients (10% [95% CI 5-19]). CONCLUSION:Reported mortality for outbreaks and pandemics may vary substantially depending upon selected patient characteristics, the number of patients described, and the region and economic status of the outbreak location. Outcomes from a relatively small number of patients from specific regions may lead to biased estimates of outcomes on a global scale.