Derivation and External Validation of a Simple Prediction Rule for the Development of Respiratory Failure in Hospitalized Patients With Influenza [post]

Blanca Ayuso, Antonio Lalueza, Estibaliz Arrieta, Eva Maria Romay, Álvaro Marchán-López, María Jose García-Pais, Dolores Folgueira, María José Gude, Cecilia Cueto, Antonio Serrano, Carlos Lumbreras
2022 unpublished
BACKGROUND: Influenza viruses cause seasonal epidemics worldwide with a significant morbimortality burden. Clinical spectrum of Influenza is wide, being respiratory failure (RF) one of its most severe complications. This study aims to elaborate a clinical prediction rule of RF in hospitalized Influenza patients.METHODS: a prospective cohort study was conducted during two consecutive Influenza seasons (December 2016 - March 2017 and December 2017 - April 2018) including hospitalized adults with
more » ... onfirmed A or B Influenza infection. A prediction rule was derived using logistic regression and recursive partitioning, followed by internal cross-validation. External validation was performed on a retrospective cohort in a different hospital between December 2018 - May 2019. RESULTS: Overall, 707 patients were included in the derivation cohort and 285 in the validation cohort. RF rate was 6.8% and 11.6%, respectively. Chronic obstructive pulmonary disease, immunosuppression, radiological abnormalities, respiratory rate, lymphopenia, lactate dehydrogenase and C-reactive protein at admission were associated with RF. A four category-grouped seven point-score was derived including radiological abnormalities, lymphopenia, respiratory rate and lactate dehydrogenase. Final model area under the curve was 0.796 (0.714-0.877) in the derivation cohort and 0.773 (0.687-0.859) in the validation cohort (p<0.001 in both cases). The predicted model showed an adequate fit with the observed results (Fisher's test p>0.43). CONCLUSION: we present a simple, discriminating, well-calibrated rule for an early prediction of the development of RF in hospitalized Influenza patients, with proper performance in an external validation cohort. This tool can be helpful in patient´s stratification during seasonal Influenza epidemics.
doi:10.21203/rs.3.rs-1247876/v1 fatcat:ohwlg2ii4bg5za5tebtbus4vca