Lung protective mechanical ventilation and two year survival in patients with acute lung injury: prospective cohort study

Dale M Needham, Elizabeth Colantuoni, Pedro A Mendez-Tellez, Victor D Dinglas, Jonathan E Sevransky, Cheryl R Dennison Himmelfarb, Sanjay V Desai, Carl Shanholtz, Roy G Brower, Peter J Pronovost, Dale M Needham, Elizabeth Colantuoni, Pedro A Mendez-Tellez, Victor D Dinglas, Jonathan E Sevransky, Cheryl R Dennison Himmelfarb, Sanjay V Desai, Carl Shanholtz, Roy G Brower, Peter J Pronovost

Abstract

Objective: To evaluate the association of volume limited and pressure limited (lung protective) mechanical ventilation with two year survival in patients with acute lung injury.

Design: Prospective cohort study.

Setting: 13 intensive care units at four hospitals in Baltimore, Maryland, USA.

Participants: 485 consecutive mechanically ventilated patients with acute lung injury.

Main outcome measure: Two year survival after onset of acute lung injury.

Results: 485 patients contributed data for 6240 eligible ventilator settings, as measured twice daily (median of eight eligible ventilator settings per patient; 41% of which adhered to lung protective ventilation). Of these patients, 311 (64%) died within two years. After adjusting for the total duration of ventilation and other relevant covariates, each additional ventilator setting adherent to lung protective ventilation was associated with a 3% decrease in the risk of mortality over two years (hazard ratio 0.97, 95% confidence interval 0.95 to 0.99, P=0.002). Compared with no adherence, the estimated absolute risk reduction in two year mortality for a prototypical patient with 50% adherence to lung protective ventilation was 4.0% (0.8% to 7.2%, P=0.012) and with 100% adherence was 7.8% (1.6% to 14.0%, P=0.011).

Conclusions: Lung protective mechanical ventilation was associated with a substantial long term survival benefit for patients with acute lung injury. Greater use of lung protective ventilation in routine clinical practice could reduce long term mortality in patients with acute lung injury.

Trial registration: Clinicaltrials.gov NCT00300248.

Conflict of interest statement

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; and no other relationships or activities that could appear to have influenced the submitted work.

Figures

https://www.ncbi.nlm.nih.gov/pmc/articles/instance/4789897/bin/need000144.f1_default.jpg
Fig 1 Flow of patients through study
https://www.ncbi.nlm.nih.gov/pmc/articles/instance/4789897/bin/need000144.f2_default.jpg
Fig 2 Unadjusted Kaplan-Meier survival curve, with 95% confidence limits, for 485 patients with acute lung injury in primary analysis
https://www.ncbi.nlm.nih.gov/pmc/articles/instance/4789897/bin/need000144.f3_default.jpg
Fig 3 Predicted absolute risk reduction in mortality by adherence to lung protective ventilation. Estimates based on Cox proportional hazards regression model with time varying covariates used to predict survival estimates for a prototypical patient with eight eligible mechanical ventilator settings with 0% versus 50% or 0% versus 100% adherence to lung protective ventilation. The prototypical patient was presumed to survive for at least four days of eligible ventilation and had median values for all continuous covariates and mode values for binary covariates. Confidence intervals were generated using 500 bootstrap samples
https://www.ncbi.nlm.nih.gov/pmc/articles/instance/4789897/bin/need000144.f4_default.jpg
Fig 4 Predicted change in hazard of mortality for increasing mean tidal volume, based on multivariable Cox model, across 485 patients with acute lung injury. A more flexible non-linear Cox model for mean tidal volume (cubic spline with three degrees of freedom) did not yield significant improvement in model fit compared with linear model (P=0.182 for non-linear terms in cubic spline model)

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Source: PubMed

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