Diagnostic accuracy of point-of-care lung ultrasound for COVID-19: a systematic review and meta-analysis
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Point-of-care (POC) lung ultrasound (LUS) is widely used in the emergency setting and there is an established evidence base across a range of respiratory diseases, including previous viral epidemics. The necessity for rapid testing combined with the limitations of other diagnostic tests has led to the proposal of various potential roles for LUS during the COVID-19 pandemic. This systematic review and meta-analysis focused specifically on the diagnostic accuracy of LUS in adult patients presenting with suspected COVID-19 infection.
Methods
Traditional and grey-literature searches were performed on 1 June 2021. Two authors independently carried out the searches, selected studies and completed the Quality Assessment Tool for Diagnostic Test Accuracy Studies (QUADAS-2). Meta-analysis was carried out using established open-source packages in R . We report overall sensitivity, specificity, positive and negative predictive values, and the hierarchical summary receiver operating characteristic curve for LUS. Heterogeneity was determined using the I 2 statistic.
Results
Twenty studies were included, published between October 2020 and April 2021, providing data from a total of 4314 patients. The prevalence and admission rates were generally high across all studies. Overall, LUS was found to be 87.2% sensitive (95% CI 83.6 to 90.2) and 69.5% specific (95% CI 62.2 to 72.5) and demonstrated overall positive and negative likelihood ratios of 3.0 (95% CI 2.3 to 4.1) and 0.16 (95% CI 0.12 to 0.22), respectively. Separate analyses for each reference standard revealed similar sensitivities and specificities for LUS. Heterogeneity was found to be high across the studies. Overall, the quality of studies was low with a high risk of selection bias due to convenience sampling. There were also applicability concerns because all studies were undertaken during a period of high prevalence.
Conclusion
During a period of high prevalence, LUS had a sensitivity of 87% for the diagnosis of COVID-19 infection. However, more research is required to confirm these results in more generalisable populations, including those less likely to be admitted to hospital.
PROSPERO registration number
CRD42021250464
Article activity feed
-
-
SciScore for 10.1101/2021.10.09.21264799: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding Data collection and synthesis: Two independent reviewers (AM, MT) extracted the following data (displayed in Table 1): Study design, exclusion criteria, number of patients, admission rate (used as a measure of disease severity), prevalence of COVID-19, sensitivity, specificity, number of true positive and negative results, number of false positive and negative results, scanning technique and diagnostic threshold (or scoring) for LUS, reference test and blinding. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Search strategy: Traditional sources of literature were … SciScore for 10.1101/2021.10.09.21264799: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding Data collection and synthesis: Two independent reviewers (AM, MT) extracted the following data (displayed in Table 1): Study design, exclusion criteria, number of patients, admission rate (used as a measure of disease severity), prevalence of COVID-19, sensitivity, specificity, number of true positive and negative results, number of false positive and negative results, scanning technique and diagnostic threshold (or scoring) for LUS, reference test and blinding. Power Analysis not detected. Table 2: Resources
Software and Algorithms Sentences Resources Search strategy: Traditional sources of literature were searched, including Ovid MEDLINE, Embase, SCOPUS, Cochrane Library and Google Scholar. Embasesuggested: (EMBASE, RRID:SCR_001650)Cochrane Librarysuggested: (Cochrane Library, RRID:SCR_013000)Google Scholarsuggested: (Google Scholar, RRID:SCR_008878)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Study limitations: The overall quality of studies was low, with internal validity affected by convenience sampling and the external validity by patient selection concerns. Furthermore, several studies reported data from small samples and provided no prior sample size estimates. There was significant variation in the LUS protocols used as well as the diagnostic threshold for a positive scan. Furthermore, there was some variability regarding the prior experience and training of the operators. POCUS is an operator-dependent technique where a single provider is responsible for both image acquisition and interpretation. Therefore, both the specific training received and prior experience of the scanning physicians is likely to influence diagnostic accuracy. Future research: Future research should focus on wider populations, including mildly and asymptomatic patients, during periods of lower disease prevalence to define the role and setting in which LUS is most useful. As previously described, future work is required to define the optimal diagnostic threshold for LUS. Finally, further work is required to understand the training and experience required to gain proficiency in LUS. Recommendations / Conclusions: LUS was found to be highly sensitive in a population of both high prevalence and mostly admitted patients and may improve detection of COVID-19 pneumonia in this group compared to CXR. In hypoxic patients requiring admission, a normal LUS should prompt consideration of an alter...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
-
