Prolonged mechanical ventilation probability model

Abstract

ObjectiveTo design a probability model for prolonged mechanical ventilation (PMV) using variables obtained during the first 24h 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 24h. 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±16.2years. 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.