Background and objective: Postextubation problems such as laryngeal edema and reintubation are common complications after tracheal intubation. The cuff-leak test has been proposed as a method of identifying those patients at high risk in clinical practice, but its efficacy remains controversial. Methods: We searched electronic databases including PubMed, the Cochrane Controlled Trials Register, Web of Science, Ovid, and Embase. Studies were included if they were concerned with accuracy of the cuff-leak test and the effect of cuff-leak test screening on patient-important outcomes. Two reviewers independently assessed study quality with the QUADAS tool and extracted data. We compiled diagnostic two by two tables and pooled estimates of sensitivity and specificity, but refrained from pooling when there was considerable clinical or statistical heterogeneity. Results: Sixteen diagnostic tests with 3172 participants and six clinical trials with 2500 patients were identified. The median diagnostic odds ratios for predicting postextubation laryngeal edema and reintubation were 18.16 (range, 3.54 to 356.00) and 10.80 (2.74 to 1665.00), respectively. The accuracy of the cuff-leak test varied with different methods, duration of intubation, and study population. An indirect comparison found significant differences in post-extubation incidence of laryngeal edema (OR = 2.09, 95% CI, 1.28 to 2.89) but not reintubation (OR = 0.94, 95% CI, 0.32 to 1.57) if using cuff-leak test screening. Conclusions: Our results suggest the cuff-leak test accurately predicts which adult patients are at high risk of postextubation airway complications, but randomized controlled trials are needed to further assess this diagnostic strategy. © 2011 Blackwell Publishing Asia Pty Ltd and Chinese Cochrane Center, West China Hospital of Sichuan University.
CITATION STYLE
Zhou, T., Zhang, H. P., Chen, W. W., Xiong, Z. Y., Fan, T., Fu, J. J., … Wang, G. (2011, November). Cuff-leak test for predicting postextubation airway complications: A systematic review. Journal of Evidence-Based Medicine. https://doi.org/10.1111/j.1756-5391.2011.01160.x
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