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    In acute respiratory distress syndrome (ARDS), dead space fraction has been independently associated with mortality. We hypothesized that early measurement of the difference between arterial and end-tidal CO2 (arterial-ET difference), a surrogate for dead space fraction, would predict mortality in mechanically ventilated patients with ARDS. We performed two separate exploratory analyses. We first used publicly available databases from the ALTA, EDEN, and OMEGA ARDS Network trials (N = 124) as a derivation cohort to test our hypothesis. We then performed a separate retrospective analysis of patients with ARDS using University of Chicago patients (N = 302) as a validation cohort. The ARDS Network derivation cohort demonstrated arterial-ET difference, vasopressor requirement, age, and APACHE III to be associated with mortality by univariable analysis. By multivariable analysis, only the arterial-ET difference remained significant (P = 0.047). In a separate analysis, the modified Enghoff equation ((PaCO2-PETCO2)/PaCO2) was used in place of the arterial-ET difference and did not alter the results. The University of Chicago cohort found arterial-ET difference, age, ventilator mode, vasopressor requirement, and APACHE II to be associated with mortality in a univariate analysis. By multivariable analysis, the arterial-ET difference continued to be predictive of mortality (P = 0.031). In the validation cohort, substitution of the arterial-ET difference for the modified Enghoff equation showed similar results. Arterial to end-tidal CO2 (ETCO2) difference is an independent predictor of mortality in patients with ARDS. © 2021. The Author(s).

    Citation

    Paola Lecompte-Osorio, Steven D Pearson, Cole H Pieroni, Matthew R Stutz, Anne S Pohlman, Julie Lin, Jesse B Hall, Yu M Htwe, Patrick G Belvitch, Steven M Dudek, Krysta Wolfe, Bhakti K Patel, John P Kress. Bedside estimates of dead space using end-tidal CO2 are independently associated with mortality in ARDS. Critical care (London, England). 2021 Sep 15;25(1):333

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    PMID: 34526077

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