Literature DB >> 32726240

Point-of-care Lung Ultrasound Is More Sensitive than Chest Radiograph for Evaluation of COVID-19.

Joseph R Pare1,2, Ingrid Camelo3, Kelly C Mayo1,2, Megan M Leo1,2, Julianne N Dugas2, Kerrie P Nelson4, William E Baker1,2, Faizah Shareef1, Patricia M Mitchell2, Elissa M Schechter-Perkins1,2.   

Abstract

INTRODUCTION: Current recommendations for diagnostic imaging for moderately to severely ill patients with suspected coronavirus disease 2019 (COVID-19) include chest radiograph (CXR). Our primary objective was to determine whether lung ultrasound (LUS) B-lines, when excluding patients with alternative etiologies for B-lines, are more sensitive for the associated diagnosis of COVID-19 than CXR.
METHODS: This was a retrospective cohort study of all patients who presented to a single, academic emergency department in the United States between March 20 and April 6, 2020, and received LUS, CXR, and viral testing for COVID-19 as part of their diagnostic evaluation. The primary objective was to estimate the test characteristics of both LUS B-lines and CXR for the associated diagnosis of COVID-19. Our secondary objective was to evaluate the proportion of patients with COVID-19 that have secondary LUS findings of pleural abnormalities and subpleural consolidations.
RESULTS: We identified 43 patients who underwent both LUS and CXR and were tested for COVID-19. Of these, 27/43 (63%) tested positive. LUS was more sensitive (88.9%, 95% confidence interval (CI), 71.1-97.0) for the associated diagnosis of COVID-19 than CXR (51.9%, 95% CI, 34.0-69.3; p = 0.013). LUS and CXR specificity were 56.3% (95% CI, 33.2-76.9) and 75.0% (95% CI, 50.0-90.3), respectively (p = 0.453). Secondary LUS findings of patients with COVID-19 demonstrated 21/27 (77.8%) had pleural abnormalities and 10/27 (37%) had subpleural consolidations.
CONCLUSION: Among patients who underwent LUS and CXR, LUS was found to have a higher sensitivity than CXR for the evaluation of COVID-19. This data could have important implications as an aid in the diagnostic evaluation of COVID-19, particularly where viral testing is not available or restricted. If generalizable, future directions would include defining how to incorporate LUS into clinical management and its role in screening lower-risk populations.

Entities:  

Mesh:

Year:  2020        PMID: 32726240      PMCID: PMC7390587          DOI: 10.5811/westjem.2020.5.47743

Source DB:  PubMed          Journal:  West J Emerg Med        ISSN: 1936-900X


INTRODUCTION

Novel coronavirus, SARS-CoV-2, is responsible for causing the coronavirus disease 2019 (COVID-19). With an estimated case fatality rate of 1%, COVID-19 has resulted in over 305,000 deaths worldwide to date.1 COVID-19’s mortality is primarily due to lung injury resulting in acute respiratory distress syndrome (ARDS).2 The definition of ARDS has changed over time; however, using the 2012 Berlin definition it would include acute bilateral lung injury in the absence of fluid overload, causing hypoxemia and respiratory failure.3 Physicians evaluating patients may wish to order radiographic imaging to screen for findings of COVID-19, evaluate severity of pulmonary involvement, or assess for alternative etiologies of illness. Radiographic results may alter the treating physician’s concern for COVID-19 thereby guiding patient counseling, or supporting clinical choices such as hospitalization, the need for closer follow-up, or anticipating complications of the disease. The American College of Radiology (ACR) recommended the use of portable chest radiograph (CXR) when medically necessary for patients with suspected or known COVID-19, which does not include screening purposes.4 However, it is estimated that portable CXR is only 69% sensitive for findings of COVID-19.5 When compared to CXR, lung ultrasound (LUS) may offer improved diagnostic accuracy in the evaluation of patients with suspected COVID-19 pneumonia. LUS has a high sensitivity and often out-performs CXR in the diagnosis of other pulmonary infections.6 LUS findings for COVID-19 have been reported in the literature and include B-lines, pleural abnormalities, and subpleural consolidations.7–9 Evaluation of B-lines is already within the scope of practice for emergency physicians (EP), and instruction in interpreting LUS is part of current residency education standards.10

Importance

LUS is a safe, readily available tool that can be employed by EPs to provide real-time clinical assessment for COVID-19. Lab testing utility is hampered by delays in results, accuracy, and availability. CXR may miss pulmonary disease, and the ACR has cautioned against routine screening with chest computed tomography (CT), citing concerns of poor specificity of ground-glass opacities for COVID-19 as well as infection control procedures necessary to decontaminate the CT scanner.4 Regarding infection control procedures, we expect that portable (or hand-held) ultrasounds would be easier to decontaminate than portable CXR machines or CT suites.

Goals of This Investigation

Our primary aim was to determine whether detection of B-lines on LUS, among patients without alternative etiologies for their presence, is more sensitive for the diagnosis of COVID-19 than CXR. Our secondary aim was to evaluate the proportion of patients with COVID-19 that have secondary LUS findings of pleural abnormalities and subpleural consolidations.

METHODS

Study Design and Setting

This was a retrospective, observational, cohort study of patients undergoing COVID-19 testing (based on real-time reverse transcriptase-polymerase chain reaction [RT-PCR] of nasopharyngeal sampling performed on an assay developed by the Center for Regenerative Medicine at Boston University, operating under an Emergency Use Authorization], who also had both diagnostic LUS and CXR for the evaluation of COVID-19 in the emergency department (ED). This study had institutional review board approval and was conducted based on Standards for Reporting of Diagnostic Accuracy Studies (STARD) guidelines and best practices for retrospective reviews.11 What do we already know about this issue? Lung ultrasound (LUS) has been shown to outperform chest radiograph (CXR) in its ability to detect abnormalities with non-coronavirus disease 2019 (COVID-19) pulmonary infections. What was the research question? To determine if B-lines detected by LUS are more sensitive for the associated diagnosis of COVID-19 than an abnormal CXR. What was the major finding of the study? B-lines detected by LUS were more sensitive for the associated diagnosis of COVID-19 than an abnormal CXR. How does this improve population health? In locations where viral testing is not available or has significant delays, LUS may provide important information for the evaluation of suspected COVID-19. This investigation was performed at a large urban academic ED in the United States with >140,000 visits per year. The ED is associated with an emergency medicine residency and clinical ultrasound fellowship, and has six dedicated portable ultrasound machines (Philips SPARQ, Wayne, PA; and MINDRAY TE7, Arnold, MD). All ultrasound studies are transferred wirelessly and stored in QPATH (Telexy, Blaine, WA). There was no formal education for LUS specific to COVID-19; however, all physicians have had structured training in LUS. All physicians were provided literature from a small study of 20 patients with COVID-19 that had 12 lung zones evaluated with ultrasound, which found 75% of patients had abnormal LUS findings at the posterior lung bases.9 When performing point-of-care ultrasound in the clinical setting, all EPs at our institution are required to archive at least one image that is representative of their findings.

Selection of Participants

All ultrasound studies completed in the ED between March 20, 2020–April 6, 2020, were reviewed for LUS imaging. We reviewed the electronic health record (EHR), EPIC (Verona, WI) to determine whether COVID-19 testing was performed. Subjects were included for evaluation if they had a COVID-19 test performed during the index hospitalization or within two weeks of the LUS examination. At the hospital during this time period, COVID-19 testing was performed only on people with symptoms concerning for disease, and no routine screening practices were in place. However, performance of viral testing was at physician discretion, and those without viral testing were excluded from analysis. We also excluded subjects if they did not have a CXR. Lastly, based on EHR review from patient history or physician documentation, patients were excluded if they had reasons for alternative causes of B-lines (congestive heart failure, renal disease leading to volume overload, or underlying lung disease), as it would not be possible to determine the etiology of the abnormal ultrasound results.

Test Methods

All lung ultrasounds were reviewed by two expert EPs, both with clinical ultrasound fellowship training (JRP and KCM), who were blinded to COVID-19 results. When disagreements occurred, a third ultrasound fellowship-trained, blinded independent expert reviewer adjudicated (MML). LUS were scored as positive or negative after review of all images. Subjects were considered to have a positive LUS if any B-lines were detected. The reviewers further graded positive ultrasounds as having 1–2 B-lines or ≥3 B-lines.12 If B-lines coalesced, the score was graded as ≥3 B-lines if the area of B-lines took up ≥30% of the intercostal space. Although ground-glass opacities can manifest as thinner B-lines <3mm apart, we allowed for percentage grading to account for coalescing in addition to “light beam” artifact, which is a broader, band-shaped artifact described in COVID-19.13 Because COVID-19 is reported to cause focal and diffuse lung disease, we chose the image with the most B-lines detected at one intercostal space to score each patient. The images were subsequently evaluated for subpleural consolidations and pleural abnormalities (Figure 1 and Online Supplemental Videos A–E). We defined subpleural consolidations as an area of hypoechoic focus at the pleural line. These areas may be associated with increased B-lines originating from this area of hypoechoic focus. For pleural abnormalities we defined this as a) loss of pleural line echogenicity; b) irregular contour of the pleural line; or c) areas that appeared >3 millimeters in thickness by visual estimation.14 Secondary LUS findings were determined by a consensus of all reviewers. Finalized CXR reports were recorded. We classified CXRs as positive if the report included infection in the differential, as defined by words such as opacity, consolidation, or airspace disease. CXRs were classified as negative if no abnormality was noted, an abnormality was noted but attributed to a non-infectious etiology, or was inconclusive for infectious process.
Figure 1

Lung ultrasounds. (A) Normal lung ultrasound. A-lines are horizontal lines that can be seen in the absence of pathology. (B) Abnormal lung ultrasound. The pleura is noted at the top of the lung. This is an example of coalescing B-lines shown as what appear to be headlights coming down from the pleura. (C) Abnormal lung ultrasound. Demonstrated is pleural thickening, >3 millimeters by visual estimate was considered abnormal. (D) Abnormal lung ultrasound. Demonstrated is an irregular pleural line seen in viral infections. (E) Abnormal lung ultrasound. Shown is a subpleural consolidation that appears black between the pleura above the pleural line.

After LUS scoring and data collection, clinical data including demographics, co-morbidities, vital signs, and laboratory values, was collected from the EHR by two investigators (JRP and FS) using a standardized abstraction technique and entered into REDCap.

Outcome Measures

The primary outcome measure was the sensitivity of LUS compared to CXR for the detection of COVID-19, using the RT-PCR laboratory test as the reference standard. Secondary outcome measures were the proportion of additional secondary LUS findings (pleural abnormalities or subpleural consolidation) detected.

Analysis

A sample size of 43 patients with an estimated sensitivity of 40% for CXR and 70% for LUS yields 81% power with an alpha of 0.05 assuming 70% disease prevalence. We used an estimated sensitivity of 40% based on results of CXR findings in influenza, as the referenced paper of 69% was not available at the time this study was designed.5,15 We compared sensitivities of LUS and CXR using a two-sided McNemar’s test. Patient demographics were evaluated with descriptive statistics, Fisher’s exact tests, Wilcoxon sum-ranked test, chi-squared tests, and Welch’s t-test. Inter-rater reliability for the primary outcome between the two primary reviewers was assessed by Cohen’s kappa.16 In addition, 95% Agresti-Coull confidence intervals (CI) were calculated for CXR and LUS test characteristics. We performed all analyses using SAS v9.4 (SAS Institute Inc., Cary, NC). Sample size calculations were conducted using PASS 19 (PASS 2019 Power Analysis and Sample Size Software (2019). NCSS, LLC. Kaysville, UT).

RESULTS

Characteristics of Study Subjects

A total of 304 ultrasound studies were completed over the 18-day study period (Figure 2). Of these, 81 had LUS performed. Among these, 43 met inclusion criteria, and 27/43 tested positive for COVID-19 by RT-PCR (63%). Four patients admitted with initial negative results were retested, and two were found to be positive. These two subjects were classified in the 27 total patients with COVID-19. Table 1 describes the demographic and clinical information of the included patients.
Figure 2

Flow chart of enrollment in lung ultrasound study.

CI, confidence interval; CXR, chest radiograph; LUS, lung ultrasound; CHF, congestive heart failure; ESRD, end-stage renal disease; TP, true positive; FP, false positive; TN, true negative; FN, false negative.

Table 1

Demographic and clinical variables of patients enrolled in study to evaluate test characteristics of lung ultrasound for coronavirus disease 2019 (COVID-19).

Overall (N=43)COVID-19 (+) (N=27)COVID-19 (−) (N=16)P-value
Demographics
 Age (years), median (IQR)52.0 (25.0)53.0 (20.0)50.0 (28.5)0.880*
 Race, n (%)< 0.001
  White12 (27.9)3 (11.1)9 (56.3)
  Black15 (34.9)8 (29.6)7 (43.8)
  Asian0 (0.0)0 (0.0)0 (0.0)
  Other/unknown16 (37.2)16 (59.3)0 (0.0)
 Ethnicity, n (%)< 0.001
  Hispanic12 (27.9)12 (44.4)0 (0.0)
  Non-Hispanic27 (62.8)11 (40.7)16 (100.0)
  Unknown4 (9.3)4 (14.8)0 (0.00)
 Gender, n (%)0.076
  Male21 (48.8)16 (59.3)5 (31.3)
  Female22 (51.2)11 (40.7)11 (68.8)
BMI (kg/m2), mean (SD)31.6 (8.4)31.7 (9.0)31.3 (7.5)0.891§
Symptom duration at time of LUS (days), mean (SD)5.4 (4.8)6.0 (4.9)4.4 (4.6)0.311§
Diabetes, n (%)11 (25.6)10 (37.0)1 (6.3)0.033
Asthma, n (%)9 (20.9)4 (14.8)5 (31.3)0.257
Obesity, n (%)19 (44.2)12 (44.4)7 (43.8)1.000
Coronary artery disease, n (%)2 (4.7)0 (0.0)2 (12.5)0.133
COPD, n (%)3 (7.0)1 (3.7)2 (12.5)0.545
Vital Signs
 SpO2 (%), median (IQR)96.0 (3.0)95.0 (2.0)96.5 (3.0)0.082*
 Temperature (°F), median (IQR)99.1 (2.1)99.9 (2.1)98.3 (0.9)0.001*
 Systolic blood pressure (mmHg), mean (SD)128.7 (20.3)126.2 (15.5)132.8 (26.6)0.376§
 Diastolic blood pressure (mmHg), mean (SD)76.8 (13.3)75.0 (12.0)79.9 (15.3)0.255§
 Initial heart rate (bpm), mean (SD)91.2 (18.3)96.2 (18.4)82.8 (15.2)0.018§
 Respiratory rate (rpm), mean (SD)21.0 (5.5)22.0 (6.7)19.4 (1.6)0.070§
Diagnostic testing
 Abnormal WBC K/μL (<4 or >11), n (%)16 (43.2)10 (41.7)6 (46.2)1.000
 Abnormal polys K/μL (<1.8 or >7.0), n (%)13 (35.1)9 (37.5)4 (30.8)0.734
 Abnormal lymphocytes K/μL (<1.1 or >3.5), n (%)15 (40.5)12 (50.0)3 (23.1)0.166
 Abnormal platelets K/μL (<150 or >400), n (%)5 (13.5)2 (8.3)3 (23.1)0.321
 Abnormal sodium mmol/L (<135 or >145), n (%)8 (21.6)7 (29.2)1 (7.7)0.216
 Abnormal ferritin ng/ml (>109), n (%)24 (80.0)20 (90.9)4 (50.0)0.029
 Abnormal LDH U/L (>308), n (%)16 (51.6)14 (63.6)2 (22.2)0.054
 Abnormal D-dimer ng/mL DDU (>243), n (%)17 (54.8)13 (61.9)4 (40.0)0.441
 Abnormal Fibrinogen mg/dL (>460), n (%)20 (66.7)15 (71.4)5 (55.6)0.431
 Abnormal ESR mm/hr (>30), n (%)26 (83.9)21 (91.3)5 (62.5)0.093
 Abnormal CRP mg/L (>5), n (%)29 (90.6)21 (91.3)8 (88.9)1.000
 Abnormal Brain-Natriuretic Peptide pg/ml (>72.3), n (%)2 (6.7)2 (9.1)0 (0.0)1.000
Clinical results
 Type of CXR, n (%)1.000
  Portable42 (97.7)26 (96.3)16 (100.0)
  Two-view1 (2.3)1 (3.7)0 (0.0)
Admitted, n (%)0.092
 Yes31 (72.1)22 (81.5)9 (56.3)
 No (discharged)12 (27.9)5 (18.5)7 (43.75)
If admitted, location, n (%)0.834
 Floor22 (71.0)15 (68.2)7 (77.8)
 IMCU3 (9.7)2 (9.1)1 (11.1)
 ICU6 (19.4)5 (22.7)1 (11.1)
If admitted, transferred to ICU within 48 hours, n (%)0.286
 Yes5 (16.1)5 (22.7)0 (0.0)
 No26 (83.9)17 (77.3)9 (100.0)
Required supplemental oxygen in ED, n (%)0.054
 Yes16 (37.2)13 (48.2)3 (18.8)
 No27 (62.8)14 (51.9)13 (81.3)
LUS images recorded, mean (SD)6.21 (3.3)5.93 (3.7)6.69 (2.5)0.472§
Ultrasound probe used, n (%)0.069
 Phased array6 (14.0)6 (22.2)0 (0.0)
 Curvilinear37 (86.1)21 (77.8)16 (100.0)
 Linear0 (0.00)0 (0.0)0 (0.0)
LUS: B-lines, n (%)< 0.001
 012 (27.9)3 (11.1)9 (56.3)
 1–24 (9.3)1 (3.7)3 (18.8)
 ≥327 (62.8)23 (85.2)4 (25.0)
LUS: pleural thickening, n (%)24 (55.8)21 (77.8)3 (18.8)< 0.001
LUS: sub-pleural consolidation, n (%)12 (27.9)10 (37.0)2 (12.5)0.158

Wilcoxon rank-sum test

Chi-squared test of independence

Fisher’s exact test

Two-independent samples t-test

IQR, interquartile range; BMI, body mass index; kg, kilogram; m, meter squared; SD, standard deviation; LUS, lung ultrasound; COPD, chronic obstructive pulmonary disease; SpO, oxygen saturation; °F, Fahrenheit; mmHg, millimeters of mercury; WBC, white blood cell count; K/μL, thousands per microliter; mmol, millimoles; L, liter; ng, nanograms; ml, milliliter; LDH, lactate dehydrogenase; U, units; DDU, D-dimer units; mg, milligram; dl, deciliter; polys, polymorphonuclear leukocytes.

ESR, erythrocyte sedimentation rate; mm, millimiter; hr, hour; CRP, C-reactive protein; mg, milligram; L, liter; PG, picogram; ml, milliliter; CXR, chest radiograph; IMCU, intermediate care unit; ICU, intensive care unit; ED, emergency department; LUS, lung ultrasound; SD, standard deviation.

Main Results

The sensitivity and specificity of B-lines on LUS associated with COVID-19 were 88.9% (95% CI, 71.1–97.0) and 56.3% (95% CI, 33.2–76.9), respectively. The association between CXR and COVID-19 results had a sensitivity and specificity (Appendix) of 51.9% (95% CI, 34.0–69.3) and 75.0% (95% CI, 50.0–90.3). LUS was more sensitive than CXR for the association of pulmonary findings of COVID-19 (p = 0.013). While there was a trend for CXR to be more specific for the associated diagnosis of COVID-19, this was not found to be statistically significant (p = 0.453). Additional LUS test characteristics are provided in Table 2. Cohen’s kappa for inter-rater agreement between the two expert LUS reviewers for the primary outcome was strong (κ = 0.83, 95% CI, 0.65–1.00). There were only three cases out of 43 where there was disagreement on the primary outcome between the two reviewers. These involved cases where B-lines were more subtle.
Table 2

Association of lung ultrasound and chest radiograph findings of COVID-19.

Value95% CI
Sensitivity (%)
 Lung ultrasound88.971.1 – 97.0
 Chest radiograph56.333.2 – 76.9
Specificity (%)
 Lung ultrasound51.934.0 – 69.3
 Chest radiograph75.050.0 – 90.3
Positive predictive value (%)
 Lung ultrasound77.459.9 – 88.9
 Chest radiograph77.854.3 – 91.5
Negative predictive value (%)
 Lung ultrasound75.046.2 – 91.7
 Chest radiograph48.030.0 – 66.5
Positive likelihood ratio
 Lung ultrasound2.030.84 – 3.23
 Chest radiograph2.070.10 – 4.05
Negative likelihood ratio
 Lung ultrasound0.200 – 0.43
 Chest radiograph0.640.32 – 0.96

CI, confidence interval.

B-lines were more frequently detected in patients with COVID-19 (24/27 patients with COVID-19 and 7/16 patients without, p < 0.001). Of the 27 patients with confirmed COVID-19 infection, 21 had pleural abnormalities (77.8%) and 10 had subpleural consolidations (37%). Of the 16 subjects without COVID-19, three had pleural irregularities (18.8%) and two had subpleural consolidations (12.5%). There was a mean of 6.2 LUS images recorded per patient, which was not significantly different between COVID-19 results, and a median of 6 LUS images taken per patient. Images were more frequently obtained with a curvilinear probe 37/43, (86%), than the phased array probe, 6/43 (14.0%). Of the LUS studies, 8/43 (18.6%) were completed by residents or physician assistants, 4/43 (9.3%) by an ultrasound fellow, 17/43 (39.5%) by ultrasound faculty, and 14/43 (32.6%) by non-fellowship trained EPs. Of the CXRs performed, 42/43 (97.7%) were performed as portable examinations. The one 2-view CXR was a false negative.

DISCUSSION

To our knowledge this is the first study to evaluate the test characteristics of LUS for COVID-19. We also are the first to compare the diagnostic performance of LUS to the more conventional use of CXR. Although preliminary, this work provides important results for the application of LUS for detection of COVID-19. This investigation offers compelling evidence that B-lines detected by LUS are more frequently associated with COVID-19 than an abnormal CXR. This finding is in line with the performance of LUS in other pulmonary disease entities.6,10 We used RT-PCR as the reference standard for diagnosis of COVID-19. However, it is known that the test characteristics of RT-PCR are dependent on collection technique, timing in disease process, and processing technique. In our population there were two negative RT-PCR tests that were positive on repeat testing. Both patients with initially negative RT-PCR tests had positive LUS findings; thus, it is possible LUS is more sensitive than RT-PCR for COVID-19. Further research would be necessary to substantiate this theory. Our study reports a sensitivity of 52% for CXR, which is lower than the reported 69% for portable CXR. It is unknown whether the radiologists in that previous study were blinded, and it is also unclear how body mass index or other variables may have resulted in our reported lower sensitivity for CXR. It is unknown how two-view CXRs would perform for the detection of lung involvement from COVID-19, as it might outperform portable CXR. However, given the infectious nature of COVID-19 portable CXR is the recommended diagnostic test for patients with suspected COVID-19, and these results demonstrate a generally low sensitivity. Evidence that LUS is more sensitive for the associated diagnosis of COVID-19 than CXR has potential global implications. These results may be of particular importance to settings with significant delays in viral RT-PCR testing, settings in which RT-PCR testing is restricted or not available, or where CXR or CT are not accessible. Further scientific investigation could determine how LUS at the time of initial evaluation may aid the physician in counseling patients with regard to findings suggestive of COVID-19. Our investigation provides important new data for the role of LUS relative to CXR for patients being evaluated for COVID-19. Conversely, LUS did have a lower specificity than CXR. As noted, 1–2 B-lines may be non-pathologic; however, only one patient in this study was found to have 1–2 B-lines that did in fact have COVID-19. It is possible that using LUS with only one or two B-lines to direct care for patients suspected of having COVID-19 could lead to unnecessary isolation or further medical testing. Additionally, there are other etiologies for LUS B-lines, and our results will likely be most valuable when interpreted in the clinical context of the medical evaluation. Physicians should have an estimation of pretest probability when performing and interpreting diagnostic testing, and LUS for COVID-19 is no exception to this rule. In this population with a high prevalence of disease (as judged by RT-PCR results), a positive LUS was a good predictor of disease. Further work is necessary to better delineate how to incorporate these findings into screening for asymptomatic patients, diagnostic algorithms, and clinical management strategies.

LIMITATIONS

Since this was a retrospective study, it is unclear why physicians chose to perform both CXR and LUS. It is also unknown whether the result of either diagnostic test affected the physician’s choice to perform the other test. Additionally, the treating physician was not blinded to the patient’s history, exam, or CXR. It is possible that knowledge of these data points would change the extent to which the physician performed their LUS. Despite this, there were a similar number of images recorded for patients with and without COVID-19. Over half of the studies performed were performed by non-fellowship trained EPs. Further work is needed to validate these findings in a population of EPs without fellowship training. Identification of B-lines is a core skill of EPs; therefore, we anticipate the findings would be similar. Another limitation was the use of RT-PCR for the diagnosis of COVID-19, as it likely misses some cases. Some of the tests classified as false positive may have actually been true positives. RT-PCR was chosen as the reference standard since that is what is currently used at our, and most, institutions nationally, and viral culture is not feasible at this time. Inconclusive CXRs were scored as negative, which might favor the analysis toward LUS. This was done, in accordance with STARD guidelines, because inconclusive CXRs do not provide diagnostic guidance in real time.11 We used B-lines in this study as a reliable marker for COVID-19. It is possible a comprehensive evaluation including pleural abnormalities and subpleural consolidations would improve the test characteristics of LUS. We chose to only include B-lines for our assessment as B-lines are already familiar to EPs and would be easier to implement. We included any number of B-lines (one or more) as abnormal; however, it has been reported 1–2 B-lines may not be pathologic. We selected this approach to maximize the sensitivity of LUS at the cost of specificity.

CONCLUSION

This investigation provides evidence that LUS is more sensitive for the associated diagnosis of COVID-19 than CXR when excluding patients with other expected causes of B-lines. This work could have important implications where viral testing is restricted or alternative diagnostic imaging is not available. Further work may find LUS for the evaluation and care of COVID-19 patients to be of clinical benefit and may also have a role to guide testing as screening and contact tracing are expanded.
  11 in total

Review 1.  Diagnosing Acute Heart Failure in the Emergency Department: A Systematic Review and Meta-analysis.

Authors:  Jennifer L Martindale; Abel Wakai; Sean P Collins; Phillip D Levy; Deborah Diercks; Brian C Hiestand; Gregory J Fermann; Ian deSouza; Richard Sinert
Journal:  Acad Emerg Med       Date:  2016-02-13       Impact factor: 3.451

2.  Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China.

Authors:  Dawei Wang; Bo Hu; Chang Hu; Fangfang Zhu; Xing Liu; Jing Zhang; Binbin Wang; Hui Xiang; Zhenshun Cheng; Yong Xiong; Yan Zhao; Yirong Li; Xinghuan Wang; Zhiyong Peng
Journal:  JAMA       Date:  2020-03-17       Impact factor: 56.272

3.  Pulmonary imaging of pandemic influenza H1N1 infection: relationship between clinical presentation and disease burden on chest radiography and CT.

Authors:  L Abbo; A Quartin; M I Morris; G Saigal; E Ariza-Heredia; P Mariani; O Rodriguez; L S Muñoz-Price; M Ferrada; E Ramee; M I Rosas; I A Gonzalez; J Fishman
Journal:  Br J Radiol       Date:  2010-06-15       Impact factor: 3.039

4.  Transforming growth factor beta-1 as a predictor of fibrosis in tuberculous pleurisy.

Authors:  Márcia Seiscento; Francisco S Vargas; Leila Antonangelo; Milena M P Acencio; Sidney Bombarda; Vera L Capelozzi; Lisete R Teixeira
Journal:  Respirology       Date:  2007-09       Impact factor: 6.424

5.  Relevance of lung ultrasound in the diagnosis of acute respiratory failure: the BLUE protocol.

Authors:  Daniel A Lichtenstein; Gilbert A Mezière
Journal:  Chest       Date:  2008-04-10       Impact factor: 9.410

6.  Acute respiratory distress syndrome: the Berlin Definition.

Authors:  V Marco Ranieri; Gordon D Rubenfeld; B Taylor Thompson; Niall D Ferguson; Ellen Caldwell; Eddy Fan; Luigi Camporota; Arthur S Slutsky
Journal:  JAMA       Date:  2012-06-20       Impact factor: 56.272

Review 7.  Accuracy of Lung Ultrasonography versus Chest Radiography for the Diagnosis of Adult Community-Acquired Pneumonia: Review of the Literature and Meta-Analysis.

Authors:  Xiong Ye; Hui Xiao; Bo Chen; SuiYang Zhang
Journal:  PLoS One       Date:  2015-06-24       Impact factor: 3.240

8.  STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration.

Authors:  Jérémie F Cohen; Daniël A Korevaar; Douglas G Altman; David E Bruns; Constantine A Gatsonis; Lotty Hooft; Les Irwig; Deborah Levine; Johannes B Reitsma; Henrica C W de Vet; Patrick M M Bossuyt
Journal:  BMJ Open       Date:  2016-11-14       Impact factor: 2.692

9.  Can Lung US Help Critical Care Clinicians in the Early Diagnosis of Novel Coronavirus (COVID-19) Pneumonia?

Authors:  Erika Poggiali; Alessandro Dacrema; Davide Bastoni; Valentina Tinelli; Elena Demichele; Pau Mateo Ramos; Teodoro Marcianò; Matteo Silva; Andrea Vercelli; Andrea Magnacavallo
Journal:  Radiology       Date:  2020-03-13       Impact factor: 11.105

10.  The many estimates of the COVID-19 case fatality rate.

Authors:  Dimple D Rajgor; Meng Har Lee; Sophia Archuleta; Natasha Bagdasarian; Swee Chye Quek
Journal:  Lancet Infect Dis       Date:  2020-03-27       Impact factor: 25.071

View more
  21 in total

Review 1.  Thoracic imaging tests for the diagnosis of COVID-19.

Authors:  Sanam Ebrahimzadeh; Nayaar Islam; Haben Dawit; Jean-Paul Salameh; Sakib Kazi; Nicholas Fabiano; Lee Treanor; Marissa Absi; Faraz Ahmad; Paul Rooprai; Ahmed Al Khalil; Kelly Harper; Neil Kamra; Mariska Mg Leeflang; Lotty Hooft; Christian B van der Pol; Ross Prager; Samanjit S Hare; Carole Dennie; René Spijker; Jonathan J Deeks; Jacqueline Dinnes; Kevin Jenniskens; Daniël A Korevaar; Jérémie F Cohen; Ann Van den Bruel; Yemisi Takwoingi; Janneke van de Wijgert; Junfeng Wang; Elena Pena; Sandra Sabongui; Matthew Df McInnes
Journal:  Cochrane Database Syst Rev       Date:  2022-05-16

2.  Usefulness of Hospital Admission Chest X-ray Score for Predicting Mortality and ICU Admission in COVID-19 Patients.

Authors:  Trieu-Nghi Hoang-Thi; Duc-Tuan Tran; Hai-Dang Tran; Manh-Cuong Tran; Tra-My Ton-Nu; Hong-Minh Trinh-Le; Hanh-Nhi Le-Huu; Nga-My Le-Thi; Cong-Trinh Tran; Nhat-Nam Le-Dong; Anh-Tuan Dinh-Xuan
Journal:  J Clin Med       Date:  2022-06-20       Impact factor: 4.964

3.  Point-of-care lung ultrasonography for early identification of mild COVID-19: a prospective cohort of outpatients in a Swiss screening center.

Authors:  Siméon Schaad; Thomas Brahier; Noémie Boillat-Blanco; Mary-Anne Hartley; Jean-Baptiste Cordonnier; Luca Bosso; Tanguy Espejo; Olivier Pantet; Olivier Hugli; Pierre-Nicolas Carron; Jean-Yves Meuwly
Journal:  BMJ Open       Date:  2022-06-24       Impact factor: 3.006

Review 4.  The diagnostic performance of lung ultrasound for detecting COVID-19 in emergency departments: A systematic review and meta-analysis.

Authors:  Reem Jari; Abdulrahman M Alfuraih; James R McLaughlan
Journal:  J Clin Ultrasound       Date:  2022-03-09       Impact factor: 0.869

Review 5.  Multi-organ point-of-care ultrasound for COVID-19 (PoCUS4COVID): international expert consensus.

Authors:  Arif Hussain; Gabriele Via; Lawrence Melniker; Alberto Goffi; Guido Tavazzi; Luca Neri; Tomas Villen; Richard Hoppmann; Francesco Mojoli; Vicki Noble; Laurent Zieleskiewicz; Pablo Blanco; Irene W Y Ma; Mahathar Abd Wahab; Abdulmohsen Alsaawi; Majid Al Salamah; Martin Balik; Diego Barca; Karim Bendjelid; Belaid Bouhemad; Pablo Bravo-Figueroa; Raoul Breitkreutz; Juan Calderon; Jim Connolly; Roberto Copetti; Francesco Corradi; Anthony J Dean; André Denault; Deepak Govil; Carmela Graci; Young-Rock Ha; Laura Hurtado; Toru Kameda; Michael Lanspa; Christian B Laursen; Francis Lee; Rachel Liu; Massimiliano Meineri; Miguel Montorfano; Peiman Nazerian; Bret P Nelson; Aleksandar N Neskovic; Ramon Nogue; Adi Osman; José Pazeli; Elmo Pereira-Junior; Tomislav Petrovic; Emanuele Pivetta; Jan Poelaert; Susanna Price; Gregor Prosen; Shalim Rodriguez; Philippe Rola; Colin Royse; Yale Tung Chen; Mike Wells; Adrian Wong; Wang Xiaoting; Wang Zhen; Yaseen Arabi
Journal:  Crit Care       Date:  2020-12-24       Impact factor: 9.097

6.  Diagnostic accuracy of physician's gestalt in suspected COVID-19: Prospective bicentric study.

Authors:  Peiman Nazerian; Fulvio Morello; Alessio Prota; Laura Betti; Enrico Lupia; Luc Apruzzese; Matteo Oddi; Federico Grosso; Stefano Grifoni; Emanuele Pivetta
Journal:  Acad Emerg Med       Date:  2021-03-15       Impact factor: 5.221

Review 7.  The role of PoCUS in the assessment of COVID-19 patients.

Authors:  John Karp; Karina Burke; Sarah-Marie Daubaras; Cian McDermott
Journal:  J Ultrasound       Date:  2021-04-19

8.  Thoracic imaging tests for the diagnosis of COVID-19.

Authors:  Nayaar Islam; Sanam Ebrahimzadeh; Jean-Paul Salameh; Sakib Kazi; Nicholas Fabiano; Lee Treanor; Marissa Absi; Zachary Hallgrimson; Mariska Mg Leeflang; Lotty Hooft; Christian B van der Pol; Ross Prager; Samanjit S Hare; Carole Dennie; René Spijker; Jonathan J Deeks; Jacqueline Dinnes; Kevin Jenniskens; Daniël A Korevaar; Jérémie F Cohen; Ann Van den Bruel; Yemisi Takwoingi; Janneke van de Wijgert; Johanna Aag Damen; Junfeng Wang; Matthew Df McInnes
Journal:  Cochrane Database Syst Rev       Date:  2021-03-16

9.  Higher Accuracy of Lung Ultrasound over Chest X-ray for Early Diagnosis of COVID-19 Pneumonia.

Authors:  Javier Martínez Redondo; Carles Comas Rodríguez; Jesús Pujol Salud; Montserrat Crespo Pons; Cristina García Serrano; Marta Ortega Bravo; Jose María Palacín Peruga
Journal:  Int J Environ Res Public Health       Date:  2021-03-27       Impact factor: 3.390

Review 10.  Is Lung Ultrasound Helpful in COVID-19 Neonates?-A Systematic Review.

Authors:  Emil Robert Stoicescu; Ioana Mihaiela Ciuca; Roxana Iacob; Emil Radu Iacob; Monica Steluta Marc; Florica Birsasteanu; Diana Luminita Manolescu; Daniela Iacob
Journal:  Diagnostics (Basel)       Date:  2021-12-08
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.