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Estimating dead-space fraction for secondary analyses of acute respiratory distress syndrome clinical trials.
Pubmed ID: 25738857
Pubmed Central ID: PMC4400228
Journal: Critical care medicine
Publication Date: May 1, 2015
MeSH Terms: Humans, Male, Adult, Female, Aged, United States, Middle Aged, Randomized Controlled Trials as Topic, Reproducibility of Results, Research Design, Respiratory Function Tests, APACHE, Respiratory Dead Space, Respiratory Distress Syndrome
Grants: R37 HL051856, R01 HL051856, K24 HL093218, T32 HL007633, UM1 HL108724, HHSN268200536179C, HL-74005, K24-HL093218, N01-HR56179, R37-HL51856, T32-HL007633, UM1-HL108724, P50 HL074005, N01HR56179, L30 HL129438, R01 HL085188
Authors: Thompson BT, Hayden D, Matthay MA, Talmor D, Liu KD, Spragg RG, Beitler JR, Zhuo H, Malhotra A
Cite As: Beitler JR, Thompson BT, Matthay MA, Talmor D, Liu KD, Zhuo H, Hayden D, Spragg RG, Malhotra A. Estimating dead-space fraction for secondary analyses of acute respiratory distress syndrome clinical trials. Crit Care Med 2015 May;43(5):1026-35.
Studies:
- Acute Respiratory Distress Network (ARDSNet) Studies 01 and 03 Lower versus higher tidal volume, ketoconazole treatment and lisofylline treatment (ARMA/KARMA/LARMA)
- Acute Respiratory Distress Network (ARDSNet) Study 04 Assessment of Low tidal Volume and elevated End-expiratory volume to Obviate Lung Injury (ALVEOLI)
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.