Sweat conductivity diagnostic accuracy for cystic fibrosis: a systematic review and meta-analysis

Author:

Zhang LinjieORCID,Nomiyama Seiko,Bedran Renata Marcos,Alvim Cristina Gonçalves,Ribeiro José Dirceu,Camargos PauloORCID

Abstract

ObjectiveWe conducted a systematic review and meta‐analysis of diagnostic test accuracy studies to summarise the properties of sweat conductivity (SC) to rule in/out cystic fibrosis (CF).Data sourceWe searched PubMed, Embase, Web of Science, Google Scholar, SciELO and LILACS up to 13 March 2023.Study selectionWe selected prospective and retrospective diagnostic test accuracy studies which compared SC, measured through two well-established and commercially available devices, that is, Nanoduct or Sweat-Chek Analyser, to quantitative measurement of sweat chloride.Main outcome measuresPooled sensitivity, specificity, positive likelihood ratio (+LR) and negative likelihood ratio (−LR), and their corresponding 95% CIs.Data extraction and synthesisThe Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies guidelines were followed. Data were extracted by one reviewer and checked by another. The hierarchical summary receiver operating characteristics model was used to estimate diagnostic test accuracy.ResultsTen studies involving 8286 participants were included. The pooled estimates of sensitivity, specificity, +LR and −LR were 0.97 (95% CI 0.94 to 0.98), 0.99 (95% CI 0.98 to 0.99), 171 (95% CI 58 to 500) and 0.02 (95% CI 0.01 to 0.05), respectively. Sensitivity analyses did not reveal a substantial impact of study-level factors on the results, such as study quality, cut-off values for a positive test, study sample size and participant age group. The quality of evidence was considered moderate.ConclusionSC demonstrated excellent diagnostic performance. In addition, its accuracy parameters suggest its role as an alternative to the sweat test for CF diagnosis.PROSPERO registration numberCRD42022284504.

Funder

Brazilian Council

Publisher

BMJ

Subject

Pediatrics, Perinatology and Child Health

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