Rodríguez, Alejandro HAvilés-Jurado, Francesc XDíaz, EmiliSchuetz, PhilippTrefler, Sandra ISolé-Violán, JordiCordero, LourdesVidaur, LoretoEstella, ÁngelPozo Laderas, Juan CSocias, LorenzoVergara, Juan CZaragoza, RafaelBonastre, JuanGuerrero, José ESuberviola, BorjaCilloniz, CatiaRestrepo, Marcos IMartín-Loeches, IgnacioSEMICYUC/GETGAG Working Group2023-01-252023-01-252015-12-15http://hdl.handle.net/10668/9678To define which variables upon ICU admission could be related to the presence of coinfection using CHAID (Chi-squared Automatic Interaction Detection) analysis. A secondary analysis from a prospective, multicentre, observational study (2009-2014) in ICU patients with confirmed A(H1N1)pdm09 infection. We assessed the potential of biomarkers and clinical variables upon admission to the ICU for coinfection diagnosis using CHAID analysis. Performance of cut-off points obtained was determined on the basis of the binominal distributions of the true (+) and true (-) results. Of the 972 patients included, 196 (20.3%) had coinfection. Procalcitonin (PCT; ng/mL 2.4 vs. 0.5, p  PCT has a high negative predictive value (94%) and lower PCT levels seems to be a good tool for excluding coinfection, particularly for patients without shock.enAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/CHAID analysisCommunity-acquired pneumoniaInfluenza A(H1N1)pmdProcalcitoninPrognosisRespiratory coinfectionSeptic shockAdultBacterial InfectionsBiomarkersCalcitoninCalcitonin Gene-Related PeptideCoinfectionDecision TreesFemaleHumansInfluenza, HumanIntensive Care UnitsMaleMiddle AgedPredictive Value of TestsProspective StudiesProtein PrecursorsSensitivity and Specificityresearch article26702737open access10.1016/j.jinf.2015.11.0071532-2742http://diposit.ub.edu/dspace/bitstream/2445/144567/1/673758.pdf