Modelo de probabilidad de ventilación mecánica prolongada. [artículo]
Por: Montejo González, Juan Carlos [Medicina Intensiva]
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Colaborador(es): Servicio de Medicina Intensiva.
Editor: Medicina Intensiva, 2012Descripción: 36(7):488-95.Recursos en línea: Solicitar documento Resumen: To design a probability model for prolonged mechanical ventilation (PMV) using variables obtained during the first 24 hours of the start of MV.
DESIGN: An observational, prospective, multicenter cohort study.
SCOPE: Thirteen Spanish medical-surgical intensive care units.
PATIENTS: Adult patients requiring mechanical ventilation for more than 24 hours.
INTERVENTIONS: None.
STUDY VARIABLES: APACHE 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.
RESULTS: Of 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).
CONCLUSIONS: The 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.
| Tipo de ítem | Ubicación actual | Signatura | Estado | Fecha de vencimiento |
|---|---|---|---|---|
Artículo
|
PC4733 (Navegar estantería) | Disponible |
Navegando Hospital Universitario 12 de Octubre Estantes Cerrar el navegador de estanterías
Formato Vancouver:
Añón JM, Gómez-Tello V, González-Higueras E, Oñoro JJ, Córcoles V, Quintana M, et al. Modelo de probabilidad de ventilación mecánica prolongada. Med Intensiva. 2012
Oct;36(7):488-95.
PMID: 22386270
Contiene 21 referencias
To design a probability model for prolonged mechanical ventilation (PMV) using variables obtained during the first 24 hours of the start of MV.
DESIGN: An observational, prospective, multicenter cohort study.
SCOPE: Thirteen Spanish medical-surgical intensive care units.
PATIENTS: Adult patients requiring mechanical ventilation for more than 24 hours.
INTERVENTIONS: None.
STUDY VARIABLES: APACHE 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.
RESULTS: Of 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).
CONCLUSIONS: The 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.
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