Diagnostic Test Accuracy of Lung Ultrasound for Acute Chest Syndrome in Sickle Cell Disease: A Systematic Review and Meta-analysis

Abstract

Acute chest syndrome (ACS) is a leading cause of death in patients with sickle cell disease. Lung ultrasound (LUS) is emerging as a point-of-care method to diagnose ACS, allowing for more rapid diagnosis in the ED setting and sparing patients from ionizing radiation exposure. What is the diagnostic accuracy of LUS for ACS diagnosis, using the current reference standard of chest radiography? Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed for this systematic review and meta-analysis. Embase, MEDLINE, Web of Science, and Google Scholar were used to compile all relevant studies. Two reviewers screened the studies for inclusion in this review. Cases of discrepancy were resolved by a third reviewer. Meta-analyses were conducted using both metadta and midas STATA software packages to retrieve summary receiver operating characteristic curves, sensitivities, and specificities. Three reviewers scored the studies with QUADAS-2 for risk of bias assessment. From a total of 713 unique studies retrieved, six studies were included in the final quantitative synthesis. Of these, five studies were in pediatric EDs. Two studies were conference abstracts and not published manuscripts. Data were available for 625 possible ACS cases (97%of cases in patients aged≤ 21 years) and 95 confirmed ACS diagnoses (pretest probability of 15.2%). The summary sensitivity was 0.92 (95%CI, 0.68-0.98) and the summary specificity was 0.89 (95%CI, 0.69-0.97) with an area under the curve of the summary receiver operating characteristic curve of 0.96 (95%CI, 0.94-0.97). LUS has excellent sensitivity and very good specificity for ACS diagnosis and may serve as an initial point-of-care test to facilitate rapid treatment of ACS and spare pediatric patients from ionizing radiation; however, further research is warranted to improve the generalizability to the adult sickle cell disease population.