Jeremy R Beitler1, B Taylor Thompson, Michael A Matthay, Daniel Talmor, Kathleen D Liu, Hanjing Zhuo, Douglas Hayden, Roger G Spragg, Atul Malhotra. 1. 1Division of Pulmonary and Critical Care Medicine, University of California, San Diego, San Diego, CA. 2Pulmonary and Critical Care Unit, Massachusetts General Hospital, Boston, MA. 3Departments of Anesthesia and Medicine, University of California, San Francisco, San Francisco, CA. 4The Cardiovascular Research Institute, University of California, San Francisco, San Francisco, CA. 5Department of Anesthesia, Critical Care, and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, MA. 6Division of Nephrology, University of California, San Francisco, San Francisco, CA. 7Division of Critical Care Medicine, University of California, San Francisco, San Francisco, CA. 8Biostatistics Center, Massachusetts General Hospital, Boston, MA.
Abstract
OBJECTIVES: Pulmonary dead-space fraction is one of few lung-specific independent predictors of mortality from acute respiratory distress syndrome. However, it is not measured routinely in clinical trials and thus altogether ignored in secondary analyses that shape future research directions and clinical practice. This study sought to validate an estimate of dead-space fraction for use in secondary analyses of clinical trials. DESIGN: Analysis of patient-level data pooled from acute respiratory distress syndrome clinical trials. Four approaches to estimate dead-space fraction were evaluated: three required estimating metabolic rate; one estimated dead-space fraction directly. SETTING: U.S. academic teaching hospitals. PATIENTS: Data from 210 patients across three clinical trials were used to compare performance of estimating equations with measured dead-space fraction. A second cohort of 3,135 patients from six clinical trials without measured dead-space fraction was used to confirm whether estimates independently predicted mortality. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Dead-space fraction estimated using the unadjusted Harris-Benedict equation for energy expenditure was unbiased (mean ± SD Harris-Benedict, 0.59 ± 0.13; measured, 0.60 ± 0.12). This estimate predicted measured dead-space fraction to within ±0.10 in 70% of patients and ±0.20 in 95% of patients. Measured dead-space fraction independently predicted mortality (odds ratio, 1.36 per 0.05 increase in dead-space fraction; 95% CI, 1.10-1.68; p < 0.01). The Harris-Benedict estimate closely approximated this association with mortality in the same cohort (odds ratio, 1.55; 95% CI, 1.21-1.98; p < 0.01) and remained independently predictive of death in the larger Acute Respiratory Distress Syndrome Network cohort. Other estimates predicted measured dead-space fraction or its association with mortality less well. CONCLUSIONS: Dead-space fraction should be measured in future acute respiratory distress syndrome clinical trials to facilitate incorporation into secondary analyses. For analyses where dead-space fraction was not measured, the Harris-Benedict estimate can be used to estimate dead-space fraction and adjust for its association with mortality.
OBJECTIVES: Pulmonary dead-space fraction is one of few lung-specific independent predictors of mortality from acute respiratory distress syndrome. However, it is not measured routinely in clinical trials and thus altogether ignored in secondary analyses that shape future research directions and clinical practice. This study sought to validate an estimate of dead-space fraction for use in secondary analyses of clinical trials. DESIGN: Analysis of patient-level data pooled from acute respiratory distress syndrome clinical trials. Four approaches to estimate dead-space fraction were evaluated: three required estimating metabolic rate; one estimated dead-space fraction directly. SETTING: U.S. academic teaching hospitals. PATIENTS: Data from 210 patients across three clinical trials were used to compare performance of estimating equations with measured dead-space fraction. A second cohort of 3,135 patients from six clinical trials without measured dead-space fraction was used to confirm whether estimates independently predicted mortality. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Dead-space fraction estimated using the unadjusted Harris-Benedict equation for energy expenditure was unbiased (mean ± SD Harris-Benedict, 0.59 ± 0.13; measured, 0.60 ± 0.12). This estimate predicted measured dead-space fraction to within ±0.10 in 70% of patients and ±0.20 in 95% of patients. Measured dead-space fraction independently predicted mortality (odds ratio, 1.36 per 0.05 increase in dead-space fraction; 95% CI, 1.10-1.68; p < 0.01). The Harris-Benedict estimate closely approximated this association with mortality in the same cohort (odds ratio, 1.55; 95% CI, 1.21-1.98; p < 0.01) and remained independently predictive of death in the larger Acute Respiratory Distress Syndrome Network cohort. Other estimates predicted measured dead-space fraction or its association with mortality less well. CONCLUSIONS: Dead-space fraction should be measured in future acute respiratory distress syndrome clinical trials to facilitate incorporation into secondary analyses. For analyses where dead-space fraction was not measured, the Harris-Benedict estimate can be used to estimate dead-space fraction and adjust for its association with mortality.
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