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Diagnostic value of fractional exhaled nitric oxide in cough-variant asthma: an updated meta-analysis.
Journal of Asthma 2019 Februrary 2
OBJECTIVE: We aimed to evaluate the diagnostic value of fractional exhaled nitric oxide (FeNO) in cough-variant asthma (CVA) detection.
METHODS: Relevant studies on the FeNO test in patients with CVA were retrieved from electronic databases including PubMed, Medline, Springer, Elsevier Science Direct, the Cochrane Library, and Google Scholar, up to August 2018. Meta-analysis for sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) of the FeNO test were conducted after extracting related data from the included studies. Meta-DiSc 1.4 and Stata 12.0 software were applied to perform the meta-analysis.
RESULTS: In total, 12 studies involving 1968 participants were selected for the meta-analysis. The pooled results of the FeNO test for CVA diagnosis showed that the sensitivity was 0.74 (95% confidence interval [CI] = 0.70 to 0.77), specificity was 0.82 (95% CI = 0.80 to 0.84), PLR was 4.15 (95% CI = 3.04 to 5.65), NLR was 0.30 (95% CI = 0.22 to 0.41), and DOR was 15.33 (95% CI = 8.43 to 27.86). The area under the curve and Q* index were 0.87 and 0.80, respectively. Moreover, no significant publication bias was observed using Egger's linear regression test (P > 0.05).
CONCLUSION: The FeNO test might be an appropriate diagnostic tool for CVA detection.
METHODS: Relevant studies on the FeNO test in patients with CVA were retrieved from electronic databases including PubMed, Medline, Springer, Elsevier Science Direct, the Cochrane Library, and Google Scholar, up to August 2018. Meta-analysis for sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) of the FeNO test were conducted after extracting related data from the included studies. Meta-DiSc 1.4 and Stata 12.0 software were applied to perform the meta-analysis.
RESULTS: In total, 12 studies involving 1968 participants were selected for the meta-analysis. The pooled results of the FeNO test for CVA diagnosis showed that the sensitivity was 0.74 (95% confidence interval [CI] = 0.70 to 0.77), specificity was 0.82 (95% CI = 0.80 to 0.84), PLR was 4.15 (95% CI = 3.04 to 5.65), NLR was 0.30 (95% CI = 0.22 to 0.41), and DOR was 15.33 (95% CI = 8.43 to 27.86). The area under the curve and Q* index were 0.87 and 0.80, respectively. Moreover, no significant publication bias was observed using Egger's linear regression test (P > 0.05).
CONCLUSION: The FeNO test might be an appropriate diagnostic tool for CVA detection.
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