Prediction of death and prolonged mechanical ventilation in acute lung injury

Ognjen Gajic, Bekele Afessa, B. Taylor Thompson, Fernando Frutos-Vivar, Michael Malinchoc, Gordon D. Rubenfeld, André Esteban, Antonio R Anzueto, Rolf D. Hubmayr

Research output: Contribution to journalArticle

46 Citations (Scopus)

Abstract

Introduction: Prediction of death and prolonged mechanical ventilation is important in terms of projecting resource utilization and in establishing protocols for clinical studies of acute lung injury (ALI). We aimed to identify risk factors for a combined end-point of death and/ or prolonged ventilator dependence and developed an ALI-specific prediction model. Methods: In this retrospective analysis of three multicenter clinical studies, we identified predictors of death or ventilator dependence from variables prospectively recorded during the first three days of mechanical ventilation. After the prediction model was derived in an international cohort of patients with ALI, it was validated in two independent samples of patients enrolled in a clinical trial involving 17 academic centers and a North American population-based cohort. Results: A combined end-point of death and/or ventilator dependence at 14 days or later occurred in 68% of patients in the international cohort, 60% of patients in the clinical trial, and 59% of patients in the population-based cohort. In the derivation cohort, a model based on age, oxygenation index on day 3, and cardiovascular failure on day 3 predicted death and/or ventilator dependence. The prediction model performed better in the clinical trial validation cohort (area under the receiver operating curve 0.81, 95% confidence interval 0.77 to 0.84) than in the population-based validation cohort (0.71, 95% confidence interval 0.65 to 0.76). Conclusion: A model based on age and cardiopulmonary function three days after the intubation is able to predict, moderately well, a combined end-point of death and/or prolonged mechanical ventilation in patients with ALI.

Original languageEnglish (US)
Article numberR53
JournalCritical Care
Volume11
DOIs
StatePublished - May 10 2007

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Acute Lung Injury
Artificial Respiration
Mechanical Ventilators
Clinical Trials
Confidence Intervals
Population
Intubation
Multicenter Studies

ASJC Scopus subject areas

  • Critical Care and Intensive Care Medicine
  • Medicine(all)

Cite this

Gajic, O., Afessa, B., Thompson, B. T., Frutos-Vivar, F., Malinchoc, M., Rubenfeld, G. D., ... Hubmayr, R. D. (2007). Prediction of death and prolonged mechanical ventilation in acute lung injury. Critical Care, 11, [R53]. https://doi.org/10.1186/cc5909

Prediction of death and prolonged mechanical ventilation in acute lung injury. / Gajic, Ognjen; Afessa, Bekele; Thompson, B. Taylor; Frutos-Vivar, Fernando; Malinchoc, Michael; Rubenfeld, Gordon D.; Esteban, André; Anzueto, Antonio R; Hubmayr, Rolf D.

In: Critical Care, Vol. 11, R53, 10.05.2007.

Research output: Contribution to journalArticle

Gajic, O, Afessa, B, Thompson, BT, Frutos-Vivar, F, Malinchoc, M, Rubenfeld, GD, Esteban, A, Anzueto, AR & Hubmayr, RD 2007, 'Prediction of death and prolonged mechanical ventilation in acute lung injury', Critical Care, vol. 11, R53. https://doi.org/10.1186/cc5909
Gajic O, Afessa B, Thompson BT, Frutos-Vivar F, Malinchoc M, Rubenfeld GD et al. Prediction of death and prolonged mechanical ventilation in acute lung injury. Critical Care. 2007 May 10;11. R53. https://doi.org/10.1186/cc5909
Gajic, Ognjen ; Afessa, Bekele ; Thompson, B. Taylor ; Frutos-Vivar, Fernando ; Malinchoc, Michael ; Rubenfeld, Gordon D. ; Esteban, André ; Anzueto, Antonio R ; Hubmayr, Rolf D. / Prediction of death and prolonged mechanical ventilation in acute lung injury. In: Critical Care. 2007 ; Vol. 11.
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AU - Malinchoc, Michael

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AU - Esteban, André

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AB - Introduction: Prediction of death and prolonged mechanical ventilation is important in terms of projecting resource utilization and in establishing protocols for clinical studies of acute lung injury (ALI). We aimed to identify risk factors for a combined end-point of death and/ or prolonged ventilator dependence and developed an ALI-specific prediction model. Methods: In this retrospective analysis of three multicenter clinical studies, we identified predictors of death or ventilator dependence from variables prospectively recorded during the first three days of mechanical ventilation. After the prediction model was derived in an international cohort of patients with ALI, it was validated in two independent samples of patients enrolled in a clinical trial involving 17 academic centers and a North American population-based cohort. Results: A combined end-point of death and/or ventilator dependence at 14 days or later occurred in 68% of patients in the international cohort, 60% of patients in the clinical trial, and 59% of patients in the population-based cohort. In the derivation cohort, a model based on age, oxygenation index on day 3, and cardiovascular failure on day 3 predicted death and/or ventilator dependence. The prediction model performed better in the clinical trial validation cohort (area under the receiver operating curve 0.81, 95% confidence interval 0.77 to 0.84) than in the population-based validation cohort (0.71, 95% confidence interval 0.65 to 0.76). Conclusion: A model based on age and cardiopulmonary function three days after the intubation is able to predict, moderately well, a combined end-point of death and/or prolonged mechanical ventilation in patients with ALI.

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