-
Multicenter Study
[Prolonged mechanical ventilation probability model].
- J M Añón, V Gómez-Tello, E González-Higueras, J J Oñoro, V Córcoles, M Quintana, J López-Martínez, L Marina, G Choperena, A M García-Fernández, C Martín-Delgado, F Gordo, R Díaz-Alersi, J C Montejo, A García de Lorenzo, M Pérez-Arriaga, and R Madero.
- Servicio de Medicina Intensiva, Hospital Virgen de la Luz, Cuenca, España. jmaelizalde@gmail.com
- Med Intensiva. 2012 Oct 1;36(7):488-95.
ObjectiveTo design a probability model for prolonged mechanical ventilation (PMV) using variables obtained during the first 24 hours of the start of MV.DesignAn observational, prospective, multicenter cohort study.ScopeThirteen Spanish medical-surgical intensive care units.PatientsAdult patients requiring mechanical ventilation for more than 24 hours.InterventionsNone.Study VariablesAPACHE II, SOFA, demographic data, clinical data, reason for mechanical ventilation, comorbidity, and functional condition. A multivariate risk model was constructed. The model contemplated a dependent variable with three possible conditions: 1. Early mortality; 2. Early extubation; and 3. PMV.ResultsOf the 1661 included patients, 67.9% (n=1127) were men. Age: 62.1±16.2 years. APACHE II: 20.3±7.5. Total SOFA: 8.4±3.5. The APACHE II and SOFA scores were higher in patients ventilated for 7 or more days (p=0.04 and p=0.0001, respectively). Noninvasive ventilation failure was related to PMV (p=0.005). A multivariate model for the three above exposed outcomes was generated. The overall accuracy of the model in the training and validation sample was 0.763 (95%IC: 0.729-0.804) and 0.751 (95%IC: 0.672-0.816), respectively. The likelihood ratios (LRs) for early extubation, involving a cutoff point of 0.65, in the training sample were LR (+): 2.37 (95%CI: 1.77-3.19) and LR (-): 0.47 (95%CI: 0.41-0.55). The LRs for the early mortality model, for a cutoff point of 0.73, in the training sample, were LR (+): 2.64 (95%CI: 2.01-3.4) and LR (-): 0.39 (95%CI: 0.30-0.51).ConclusionsThe proposed model could be a helpful tool in decision making. However, because of its moderate accuracy, it should be considered as a first approach, and the results should be corroborated by further studies involving larger samples and the use of standardized criteria.Copyright © 2011 Elsevier España, S.L. y SEMICYUC. All rights reserved.
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