RT Journal Article
T1 Derivation and external validation of a simple prediction rule for the development of respiratory failure in hospitalized patients with influenza.
A1 Ayuso, Blanca
A1 Lalueza, Antonio
A1 Arrieta, Estibaliz
A1 Romay, Eva María
A1 Marchán-López, Álvaro
A1 García-País, María José
A1 Folgueira, Dolores
A1 Gude, María José
A1 Cueto, Cecilia
A1 Serrano, Antonio
A1 Lumbreras, Carlos
K1 Clinical prediction rules
K1 Human
K1 Influenza
K1 Mechanical ventilation
K1 Pneumonia
K1 Respiratory failure
K1 Viral
AB 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. A prospective cohort study was conducted during two consecutive Influenza seasons (December 2016-March 2017 and December 2017-April 2018) including hospitalized adults with confirmed 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 and May 2019. 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  0.43). 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.
YR 2022
FD 2022-11-24
LK http://hdl.handle.net/10668/20318
UL http://hdl.handle.net/10668/20318
LA en
DS RISalud
RD Apr 17, 2025