Skip to main content

Lung ultrasound findings in hospitalized COVID-19 patients in relation to venous thromboembolic events: the ECHOVID-19 study

Abstract

Purpose

Several studies have reported thromboembolic events to be common in severe COVID-19 cases. We sought to investigate the relationship between lung ultrasound (LUS) findings in hospitalized COVID-19 patients and the development of venous thromboembolic events (VTE).

Methods

A total of 203 adults were included from a COVID-19 ward in this prospective multi-center study (mean age 68.6 years, 56.7% men). All patients underwent 8-zone LUS, and all ultrasound images were analyzed off-line blinded. Several LUS findings were investigated (total number of B-lines, B-line score, and LUS-scores).

Results

Median time from admission to LUS examination was 4 days (IQR: 2, 8). The median number of B-lines was 12 (IQR: 8, 18), and 44 (21.7%) had a positive B-line score. During hospitalization, 17 patients developed VTE (4 deep-vein thrombosis, 15 pulmonary embolism), 12 following and 5 prior to LUS. In fully adjusted multivariable Cox models (excluding participants with VTE prior to LUS), all LUS parameters were significantly associated with VTE (total number of B-lines: HR = 1.14, 95% CI (1.03, 1.26) per 1 B-line increase), positive B-line score: HR = 9.79, 95% CI (1.87, 51.35), and LUS-score: HR = 1.51, 95% CI (1.10, 2.07), per 1-point increase). The B-line score and LUS-score remained significantly associated with VTE in sensitivity analyses.

Conclusion

In hospitalized COVID-19 patients, pathological LUS findings were common, and the total number of B-lines, B-line score, and LUS-score were all associated with VTE. These findings indicate that the LUS examination may be useful in risk stratification and the clinical management of COVID-19. These findings should be considered hypothesis generating.

Clinicaltrials.gov ID

NCT04377035

Introduction

COVID-19 is associated with the development of acute respiratory distress syndrome (ARDS), intensive care unit admission, multi-organ failure, and death, especially in the elderly [1, 2]. Elevated D-dimer and dysregulated coagulation have been reported in a significant proportion of hospitalized COVID-19 patients in multiple studies [3, 4] and found to be associated with a more severe course of the disease [5, 6]. As the pandemic has progressed, multiple case-reports, reviews, and observational studies have reported an increased incidence of venous thromboembolic events (VTE) in hospitalized COVID-19 patients [7,8,9,10,11,12]. It has been proposed that the increased risk of VTE is caused by a diffuse pulmonary intravascular coagulopathy resulting from pulmonary macrophage activation syndrome. In addition, a degree of cytokine storm-induced disseminated intravascular coagulation may add to the diffuse pulmonary intravascular coagulopathy beyond that of the macrophage activation [13, 14]. Moreover, disease severity is associated with prolonged periods of inactivity which in turn increases the risk of VTE. Thus, it has been suggested that COVID-19 patients should be monitored for possible development of VTE [15].

Lung ultrasound (LUS) is a sensitive method for detecting pneumonia and ARDS [16, 17] and is an inexpensive, fast, and readily available technique that can be performed bedside. The COVID-19 induced increased pulmonary coagulopathy causes pulmonary extravasation of fluid which is detectable by both LUS as B-lines and consolidations and by computed tomography (CT) [11, 18, 19]. In addition, CT-studies have shown that most pulmonary lesions related to COVID-19 are distributed peripherally in the lungs causing pulmonary edema detectable with LUS [20, 21]. Initial reports have demonstrated LUS findings to correlate with the severity of disease among patients with COVID-19 [22, 23] which in turn have shown to correlate with increased coagulopathy [14]. Thus, as LUS is associated with severity of disease which is associated with the COVID-19 induced coagulopathy, we hypothesize that LUS findings are associated with the development of VTE in patients hospitalized with COVID-19. Consequently, the present analysis aimed to assess the association between LUS findings and the development of VTE in a prospective cohort of hospitalized COVID-19 patients.

Methods

Population

The ECHOVID-19 study [24, 25] is a prospective cohort study of consecutively hospitalized COVID-19 patients from all hospitals in Eastern Denmark. A team of investigators visited eight predefined hospitals from two administrative regions in Denmark twice a week to recruit patients. The investigators performing the ultrasound examinations were blinded to the clinical data of all potential participants prior to including them. All eligible patients accepting participation in the study underwent echocardiography, LUS, laboratory testing, answered a questionnaire, and had their electronic health records reviewed. The LUS was performed on all patients according to a predefined protocol independently of their health status. Patients were included from March 30th to June 3rd, 2020. Inclusion criteria were hospitalized for laboratory-confirmed COVID-19, age ≥ 18 years, and provided written informed consent. We included patients from dedicated COVID-19 wards, but not from intensive care units. Of the 215 patients included into the ECHOVID-19 study, 12 patients did not have a LUS examination performed and were thus excluded from the present study. The study was approved by the regional ethics board and was conducted in accordance with the 2nd Helsinki Declaration. The ECHOVID-19 study is registered at Clinicaltrials.gov (NCT04377035).

Clinical data and baseline information

Methodology regarding the retrieval of clinical and baseline information is described in Supplemental Data.

Outcomes

The primary outcome was VTE, defined as incident of computed tomography confirmed pulmonary embolism (N = 15, 7.0%) and/or ultrasound confirmed deep-vein thrombosis (N = 4). The date of follow-up was 17th of June 2020. Information on outcome was obtained through the electronic health records.

LUS protocol and image analysis

All LUS examinations were performed by trained investigators using the portable Vivid IQ 4D Ultrasound System (GE Healthcare, Horten, Norway) using a phased array 1.7/3.3 MHz transducer in sagittal orientation. A standardized LUS protocol was employed with the imaging depth set to 18 cm with patients in a semi-recumbent position. A total of 8 LUS zones (4 on each hemithorax) were recorded for 6 s each as previously described [17]. All ultrasound images were reviewed and scored by two experienced investigators together (EP & CE).

Three different methods were examined to assess the extent of lung ultrasound findings as a sign of increased density of the lung parenchyma in study participants: (1) the total number of B-lines per patient was calculated as the sum of the maximum number of B-lines from each zone regardless of the number of missing zones, (2) a positive B-line score (interstitial syndrome) was defined as ≥ 3 B-lines in ≥ 2 zones on each hemithorax which has previously been employed in patients with acute heart failure [26] and (3) a LUS-score incorporating several LUS findings from each zone was utilized in which patients could be assigned a LUS-score between 0 and 16 points (Supplementary Table 1). Patients would receive 1 point for a LUS zone if the LUS zone had at least one of the following findings: ≥ 3 B-lines, confluent B-lines (if a confluent B-line took up ≥ 50% of the intercostal space and could not be counted as separate B-lines at any time during the six sec. clip), subpleural consolidations or lobar consolidations with air bronchograms. If two findings or more were present in the same zone (e.g. ≥ 3 B-lines + subpleural consolidation), a patient would receive 2 points for this zone. In these main analyses, all patients were included. Figure 1 illustrates three examples of pathological LUS findings. The median number of missing zones was 0 (IQR: 0, 1) and 19.7% had ≥ 2 missing zones. To account for missing LUS zones, three sensitivity analyses were carried out. In the first sensitivity analysis, the number of missing LUS zones was included as a variable in the demographic regression model. In a second sensitivity analysis, only 6 LUS zones were used (3 on each hemithorax, excluding the lower lateral zones), and third, patients with at least one missing zone in the 8-zone model were excluded (75 patients left out of this analysis due to these criteria). The sensitivity analyses were carried out as some LUS zones (lower lateral zones) are more difficult to acquire adequate images of for LUS analysis. This is especially true for patients with severe respiratory distress. Thus, several models were used to control for the possibility of systematic missing data driving the statistical findings of the main results.

Fig. 1
figure1

Pathological LUS findings. Examples of multiple B-lines (A), confluent B-lines and subpleural consolidations (B), and lobar consolidations (C) assessed with LUS. LUS lung ultrasonography

Echocardiography

The echocardiographic examinations were performed bedside with portable Vivid IQ Ultrasound Systems (GE Healthcare, Horten, Norway). All echocardiographic measurements were performed according to existing guidelines [4, 5]. A detailed description of the echocardiography analysis methods has previously been published [6]. Left ventricular ejection fraction (LVEF) was measured using the Simpson’s biplane method. Pulsed-wave Doppler was used to measure early peak inflow velocity (E) in the apical four-chamber view with the sample area placed between the tips of the mitral leaflets. Early diastolic tissue Doppler velocities (e') were measured in the apical four-chamber view at the septal and lateral wall of the mitral annulus and e' was indexed to E to obtain E/e'. Tricuspid annular plane systolic excursion (TAPSE) was measured using M-mode in the apical 4-chamber projection optimized for TAPSE. Tricuspid regurgitation peak gradient was assessed with continuous-wave Doppler imaging with a sample place in the regurgitant jet.

Statistics

Baseline data (Table 1) were stratified according to the development of VTE during their hospitalization. Continuous Gaussian distributed variables are presented as mean ± standard deviations (SD) and non-Gaussian distributed variables as median with inter-quartile range (IQR). Categorical variables are presented as counts and proportions. Differences in baseline characteristics across the two groups were assessed using an extension of the Wilcoxon Rank Sum test [27] and Student’s t test as appropriate. Univariable linear regressions were utilized to assess the relationship between LUS-score and conventional echocardiographic left and right ventricular parameters. Cox proportional hazard regression models (univariable and multivariable) were used to assess the continuous association between total number of B-lines and subsequent VTE, B-line score and subsequent VTE, and LUS-score and subsequent VTE, respectively, excluding participants with VTE prior to LUS (N = 5). A multivariable demographic model was adjusted for age and sex. The fully adjusted multivariable model included additional possible confounding covariates; age, sex, C-reactive protein (CRP), body mass index (BMI), D-dimer ≥ 0.50 mg/L and level of oxygen therapy (liters of O2/minute). These covariates were chosen based on their clinical importance and their known association with VTE. A limited number of variables were utilized to prevent overfitting. Logistic regression models (univariable and multivariable) were carried out following the same procedure, not excluding VTE participants prior to LUS. Sensitivity analyses were performed, as described in the LUS section. Restricted cubic spline models were constructed using a Poisson model to visualize the association between total number of B-lines and VTE, and LUS-score and subsequent VTE, respectively. The number of knots was chosen according to the lowest Akaike information criterion. The optimal cut-off values for total number of B-lines (≥ 15) and LUS-score (≥ 5) were determined through receiver operating characteristics curves with the maximal sensitivity and specificity. STATA statistics/data analysis, SE 15.0 (StataCorp, College Station, TX, USA) was used for all data work. Statistical significance was defined as a P value ≤ 0.05.

Table 1 Baseline demographic, clinical, and biochemical characteristics

Results

A total of 203 hospitalized COVID-19 patients were included in the study. The mean age was 68.6 ± 13.5 years, and 56.7% were males. The median time from hospitalization to LUS examination was 4 days (IQR: 2, 8). In total, 17 patients demonstrated VTE during hospitalization, 12 of these events were following LUS examination (median time from LUS examination to VTE was 4 days (IQR: 1, 9), while 5 events were prior to LUS examination. The median time to VTE from hospitalization was 9 days (IQR: 5, 17). Finally, participants experienced symptoms of COVID-19 median 7 days (IQR: 3, 10) prior to the day of admission.

Median LUS-score was 3 (IQR: 1, 5), median number of B-lines was 12 (IQR: 8, 18), and 44 (22%) had positive B-line score. Most participants (99.5%) had at least 1 B-line in one zone, 18.7% had at least one group of confluent B-lines in one zone, 14.8% had at least 1 subpleural or lobar consolidation, and 83.3% had a LUS-score ≥ 1. Pleural effusion was not observed in any of the included patients. Demographic, clinical, laboratory and LUS characteristics are compared between patients who developed VTE and patients who did not in Table 1. Several significant differences were observed between the two groups. Participants developing VTE were more likely to have a higher heart rate, level of oxygen therapy, and elevated D-dimer (5.0 [IQR: 1.3, 6.4] mg/L vs 1.2 [IQR: 0.7, 2.2] mg/L, P = 0.002). Patients with VTE also had a higher number of B-lines (17 [IQR: 10, 23] vs 12 [IQR: 7, 17], P = 0.044), more frequently positive B-line score (9 (52.9%) vs 35 (18.8%), P = 0.001), and higher LUS-score (6 [IQR: 2, 7], vs 2 [IQR: 1, 5], P = 0.021).

Relationship between LUS-score and echocardiographic parameters

The relationships between LUS-score and conventional echocardiographic left and right ventricular parameters were assessed with univariable linear regression models. High LUS-score was not associated with elevated TR gradient (stand. β.coefficient: 0.16, P = 0.051), elevated E/E’ (stand. β.coefficient: 0.00, P = 0.99), reduced LVEF (stand. β.coefficient: − 0.03, P = 0.74) or reduced TAPSE (stand. β.coefficient: − 0.11, P = 0.14).

Relationship between LUS findings and VTE

Uni- and multivariable Cox and logistic regression models investigating the association between LUS findings (number of B-lines, B-line score, and LUS-score) and VTE are listed in Table 2. In univariable Cox (only VTE cases following the LUS examination) and logistic (all cases of VTE) regressions, an increasing number of B-lines, positive B-line score, and LUS-score were all significant markers of outcome.

Table 2 The relationship between VTE and LUS findings

Number of B-lines was significantly associated with higher risk of VTE in multivariable Cox regression (HR = 1.14, 95% CI (1.03, 1.26), P = 0.016, per 1 B-line increase). This was also the case in multivariable logistic regression (OR = 1.09, 95% CI (1.01, 1.19), P = 0.038, per 1 B-line increase). B-line score also remained a significant marker of VTE during hospitalization in both multivariable Cox and logistic regression models (Cox regression: (HR = 9.79, 95% CI (1.87, 51.35), P = 0.007; logistic regression: OR = 6.10, 95% CI (1.69, 22.05), P = 0.006). Finally, LUS-score remained independently associated with VTE during hospitalization in the fully adjusted models (Cox regression: HR = 1.51, 95% CI (1.10, 2.07), P = 0.010 per 1-point increase; logistic regression: OR = 1.39, 95% CI (1.09, 1.79), P = 0.009, per 1-point increase). The associations between LUS findings and VTE are illustrated in Fig. 2.

Fig. 2
figure2

Association between LUS findings and future VTE during hospitalization. Displaying the unadjusted incidence rates of VTE during hospitalization for COVID-19 (with 95% confidence intervals) for the population in relation to total number of B-lines (A) and LUS-score (B). LUS lung ultrasonography, VTE venous thromboembolic event

Three sensitivity analyses were conducted using the same multivariable model. B-line score and LUS-score both remained significantly associated with the outcome in all sensitivity analyses. Meanwhile, the total number of B-lines only remained significant in logistic regression sensitivity analysis 2 and 3, (Table 2).

Optimal cutoff values for total number of B-lines and LUS-score were found to be, respectively, ≥ 15 B-lines and a LUS-score ≥ 5. The cutoff value for total number of B-lines demonstrated a sensitivity of 58.8% (IQR: 32.9; 81.6) and specificity of 76.1% (69.6; 81.9). Meanwhile, a positive B-line score had a sensitivity of 52.9% (IQR: 27.8; 77) and specificity of 82.2% (IQR: 76.2; 87.3). Finally, a LUS-score ≥ 5 had a sensitivity and specificity of, respectively, 58.8% (IQR: 32.9; 81.6) and specificity of 76.1% (69.6; 81.9).

Discussion

The present study was designed with the objective of assessing the association between lung ultrasound findings and development of VTE in hospitalized COVID-19 patients. We particularly aimed to assess the association between LUS findings and development of VTE, as several studies have coupled the severity of the SARS-CoV-2 infection with LUS findings [22, 23], and severity of disease with dysregulated coagulation [5, 6]. To the best of our knowledge, this is the first prospective cohort study investigating the association between LUS and VTE in hospitalized patients with COVID-19. There were several important findings. First, LUS findings are common and numerous in hospitalized patients with COVID-19. Second, we found that the total number of B-lines, B-line score, and LUS-score were all significantly associated with the development of VTE during hospitalization. Finally, we did not find any significant relationship between LUS-score and conventional echocardiographic left and right ventricular parameters.

Diffuse pulmonary intravascular coagulopathy causes extravasation of fluids in the pulmonary parenchyma which can be detected by LUS as B-lines and consolidations. The viral pneumonia in itself together with a possible bacterial superinfection also causes pulmonary edema giving rise to LUS findings.

We observed that a large proportion (83.3%) of the prospectively included hospitalized COVID-19 patients in our study had ≥ 1 point on the LUS-score. In addition, 99.5% of the included patients had at least one B-line in one of the LUS zones. Several small cohort studies have investigated the presence of pathological LUS findings in patients with COVID-19 and their relation to computed tomography findings [28, 29]. One retrospective cohort study investigated whether LUS could be used to detect COVID-19 in 42 patients with COVID-19 and 24 controls without COVID-19. In that study, the B-line score had a similar sensitivity to detect COVID-19 than chest X-ray and CT and improved specificity compared to chest radiograph [29]. However, the sample size was quite small, and they did not investigate how LUS findings were associated with the development of VTE. The results described in a systematic review[28] looking at the utility of LUS in COVID-19 suggest that LUS findings are very common in COVID-19 and that their mere presence in themselves may help detect COVID-19 but are not optimal for risk stratification. Rather, it seems the cumulative amount of LUS findings (B-lines, subpleural and lobar consolidations) may be more useful as a tool for risk stratification in hospitalized patients with COVID-19.

Using only the total number of B-lines may be inadequate as we observed many cases of confluent B-lines and subpleural and lobar consolidations, making it difficult to count the number of B-lines correctly. It seems the LUS findings in COVID-19 are numerous, and we, therefore, suggest a scoring system of the kind presented in this study to account for both the number of zones affected and the possibility of multiple LUS findings per zone. A scoring system like this requires external validation, but we hope that the present study can be hypothesis generating for future LUS studies in COVID-19 and help in elucidating the prognostic potential of LUS in COVID-19.

While we in the present study have found that LUS findings were associated with VTE, the study cannot answer the question of causality as there is a potential risk of reverse causation. That is, it may be that our LUS findings are present due to VTE instead of LUS findings occurring prior to later development of VTE. We used both Cox proportional hazard regression with the outcome being restricted to VTE diagnosed after the LUS examination and logistic regression with the outcome being development of VTE during the entire hospitalization as to observe possible differences that could be due to reverse causation. However, regardless of the method used to analyze the data, LUS findings were significantly associated with the outcome in both scenarios and remained so even after adjusting for possible confounding parameters.

In the present study, we observe that the patients who developed VTE had a higher number of pathological LUS findings. What the LUS detects is increased density of the lung parenchyma most likely due to inflammation related to pneumonitis rather than lung infarction due to emboli which is usually seen as triangular, hypoechoic, subpleural consolidations. Though, diffuse pulmonary intravascular coagulopathy also adds to the increased density of the parenchyma. Our findings suggest that patients who develop VTE have a more severe pneumonitis and probably also increased endotheliitis. Thus, the risk of developing VTE is related to the clinical stage and severity of the disease and not to the extent of the pathological findings itself.

We used an 8-zone model as has previously been recommended [30] in our study. The lower lateral zones are, however, known to be difficult to obtain, in patients with prevalent respiratory failure in the semi-recumbent position. We, therefore, carried out sensitivity analyses to make sure that our results were not driven by inadequate lower lateral image clips in patients with the worst respiratory function. Still, the LUS findings remained significantly associated with the outcome in the majority of sensitivity analyses underscoring that our findings were not driven by differences in missing LUS zones. As the association between LUS findings and VTE remained significant in a 6-zone model, a lower number of zones may suffice in the clinical setting. However, further studies are needed to confirm this observation.

Strengths and limitations

This study is limited by a relatively small sample size. However, we used a multi-center design in which we included patients from all hospitals (8 hospitals) in Eastern Denmark. The multi-center design further strengthens our results as it makes our sample population much more representative of the general population. An important limitation to this study is that the observative design meant that not all participants had a CT angiography performed and thus some of the patients in the non-VTE group may actually have had an undetected VTE. As many of the patients had severe respiratory distress, the LUS examination was at times difficult to perform, especially in the lower lateral zones. Due to this, some of the patients had inadequate lower lateral zones for LUS analysis. In addition, many of the patients were too ill to collaborate to be in a seated position. All of this meant that we chose not to use a 12-zone LUS model which would otherwise have allowed us to assess the posterior zones and instead chose to only assess 8 zones (frontal and lateral zones) which limits our findings although the 8-zone model has been successfully used in several other studies [31, 32]. However, several sensitivity analyses were carried out which confirmed our findings in the primary analyses. A low-frequency probe was used for the study; however, a higher frequency probe would have improved resolution and may have aided in identifying even smaller subpleural consolidations which may have been missed. Due to the relatively small sample size, the number of events was low. However, our results remained stable in several different multivariable regression models and sensitivity models. Lastly, an important limitation is the variability in days from admission to LUS examination. A small team of investigators visiting two of the eight sites each day meant that each site was visited twice per week. Due to this approach, the median time from admission to ultrasound examination was 4 days, and as a result, a subset of our cohort probably represents a subset of COVID-19 patients requiring a longer hospital stay. This limits the generalizability of our results as they most likely reflect patients requiring longer hospital stays. The LUS investigators were experts in ultrasound and physicians without LUS experience may demonstrate poorer diagnostic performance. However, acquisition of LUS images is fairly simple and B-lines are easily recognized.

Conclusion

In hospitalized COVID-19 patients, pathological LUS findings were common, and the total number of B-lines, B-line score, and LUS-score were all associated with VTE. These findings indicate that the LUS examination may be useful in risk stratification and the clinical management of COVID-19. These findings should be considered hypothesis generating.

Data availability

Data are available upon request.

Code availability

Coding is available upon request.

References

  1. 1.

    Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, Qiu Y, Wang J, Liu Y, Wei Y, Xia J, Yu T, Zhang X, Zhang L (2020) Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 395:507–513. https://doi.org/10.1016/S0140-6736(20)30211-7

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Totura AL, Baric RS (2012) SARS coronavirus pathogenesis: host innate immune responses and viral antagonism of interferon. Curr Opin Virol 2:264–275. https://doi.org/10.1016/j.coviro.2012.04.004

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Guan W-J, Ni Z-Y, Hu Y, Liang W-H, Ou C-Q, He J-X, Liu L, Shan H, Lei C-L, Hui DSC, Du B, Li L-J, Zeng G, Yuen K-Y, Chen R-C, Tang C-L, Wang T, Chen P-Y, Xiang J, Li S-Y, Wang J-L, Liang Z-J, Peng Y-X, Wei L, Liu Y, Hu Y-H, Peng P, Wang J-M, Liu J-Y, Chen Z, Li G, Zheng Z-J, Qiu S-Q, Luo J, Ye C-J, Zhu S-Y, Zhong N-S (2020) China medical treatment expert group for Covid-19, clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 382:1708–1720. https://doi.org/10.1056/NEJMoa2002032

    CAS  Article  Google Scholar 

  4. 4.

    Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, Xiang J, Wang Y, Song B, Gu X, Guan L, Wei Y, Li H, Wu X, Xu J, Tu S, Zhang Y, Chen H, Cao B (2020) Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 395:1054–1062. https://doi.org/10.1016/S0140-6736(20)30566-3

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, Zhao Y, Li Y, Wang X, Peng Z (2020) Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. https://doi.org/10.1001/jama.2020.1585

    Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Tang N, Li D, Wang X, Sun Z (2020) Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia. J Thromb Haemost 18:844–847. https://doi.org/10.1111/jth.14768

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Fox SE, Akmatbekov A, Harbert JL, Li G, Quincy Brown J, Vander Heide RS (2020) Pulmonary and cardiac pathology in African American patients with COVID-19: an autopsy series from New Orleans. Lancet Respir Med. https://doi.org/10.1016/S2213-2600(20)30243-5

    Article  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Cui S, Chen S, Li X, Liu S, Wang F (2020) Prevalence of venous thromboembolism in patients with severe novel coronavirus pneumonia. J Thromb Haemost 18:1421–1424. https://doi.org/10.1111/jth.14830

    CAS  Article  PubMed  Google Scholar 

  9. 9.

    Klok FA, Kruip MJHA, van der Meer NJM, Arbous MS, Gommers D, Kant KM, Kaptein FHJ, van Paassen J, Stals MAM, Huisman MV, Endeman H (2020) Confirmation of the high cumulative incidence of thrombotic complications in critically ill ICU patients with COVID-19: An updated analysis. Thromb Res 191:148–150. https://doi.org/10.1016/j.thromres.2020.04.041

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Stoneham SM, Milne KM, Nuttall E, Frew GH, Sturrock BR, Sivaloganathan H, Ladikou EE, Drage S, Phillips B, Chevassut TJ, Eziefula AC (2020) Thrombotic risk in COVID-19: a case series and case-control study. Clin Med (Lond) 20:e76–e81. https://doi.org/10.7861/clinmed.2020-0228

    Article  Google Scholar 

  11. 11.

    Flor N, Tonolini M (2020) From ground-glass opacities to pulmonary emboli. A snapshot of the evolving role of a radiology unit facing the COVID-19 outbreak. Clin Radiol 75:556–557. https://doi.org/10.1016/j.crad.2020.04.009

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Middeldorp S, Coppens M, van Haaps TF, Foppen M, Vlaar AP, Müller MCA, Bouman CCS, Beenen LFM, Kootte RS, Heijmans J, Smits LP, Bonta PI, van Es N (2020) Incidence of venous thromboembolism in hospitalized patients with COVID-19. J Thromb Haemost 18:1995–2002. https://doi.org/10.1111/jth.14888

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    McGonagle D, Sharif K, O’Regan A, Bridgewood C (2020) The role of cytokines including interleukin-6 in COVID-19 induced pneumonia and macrophage activation syndrome-like disease. Autoimmun Rev 19:102537. https://doi.org/10.1016/j.autrev.2020.102537

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    McGonagle D, O’Donnell JS, Sharif K, Emery P, Bridgewood C (2020) Immune mechanisms of pulmonary intravascular coagulopathy in COVID-19 pneumonia. Lancet Rheumatol 2:e437–e445. https://doi.org/10.1016/S2665-9913(20)30121-1

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Tavazzi G, Civardi L, Caneva L, Mongodi S, Mojoli F (2020) Thrombotic events in SARS-CoV-2 patients: an urgent call for ultrasound screening. Intensive Care Med 46:1121–1123. https://doi.org/10.1007/s00134-020-06040-3

    CAS  Article  PubMed  Google Scholar 

  16. 16.

    Nazerian P, Volpicelli G, Vanni S, Gigli C, Betti L, Bartolucci M, Zanobetti M, Ermini FR, Iannello C, Grifoni S (2015) Accuracy of lung ultrasound for the diagnosis of consolidations when compared to chest computed tomography. Am J Emerg Med 33:620–625. https://doi.org/10.1016/j.ajem.2015.01.035

    Article  PubMed  Google Scholar 

  17. 17.

    Volpicelli G, Elbarbary M, Blaivas M, Lichtenstein DA, Mathis G, Kirkpatrick AW, Melniker L, Gargani L, Noble VE, Via G, Dean A, Tsung JW, Soldati G, Copetti R, Bouhemad B, Reissig A, Agricola E, Rouby JJ, Arbelot C, Liteplo A, Sargsyan A, Silva F, Hoppmann R, Breitkreutz R, Seibel A, Neri L, Storti E, Petrovic T (2012) International liaison committee on lung ultrasound (ILC-LUS) for international conference consensus on lung ultrasound (ICC-LUS), International evidence-based recommendations for point-of-care lung ultrasound. Intensive Care Med 38:577–591. https://doi.org/10.1007/s00134-012-2513-4

    Article  PubMed  Google Scholar 

  18. 18.

    Hu L, Wang C (2020) Radiological role in the detection, diagnosis and monitoring for the coronavirus disease 2019 (COVID-19). Eur Rev Med Pharmacol Sci 24:4523–4528. https://doi.org/10.26355/eurrev_202004_21035

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Volpicelli G, Lamorte A, Villén T (2020) What’s new in lung ultrasound during the COVID-19 pandemic. Intensive Care Med. https://doi.org/10.1007/s00134-020-06048-9

    Article  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Shi H, Han X, Jiang N, Cao Y, Alwalid O, Gu J, Fan Y, Zheng C (2020) Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. Lancet Infect Dis 20:425–434. https://doi.org/10.1016/S1473-3099(20)30086-4

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Pan F, Ye T, Sun P, Gui S, Liang B, Li L, Zheng D, Wang J, Hesketh RL, Yang L, Zheng C (2020) Time course of lung changes at chest CT during recovery from coronavirus disease 2019 (COVID-19). Radiology 295:715–721. https://doi.org/10.1148/radiol.2020200370

    Article  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Xing C, Li Q, Du H, Kang W, Lian J, Yuan L (2020) Lung ultrasound findings in patients with COVID-19 pneumonia. Crit Care 24:174. https://doi.org/10.1186/s13054-020-02876-9

    Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Sultan LR, Sehgal CM (2020) A review of early experience in lung ultrasound in the diagnosis and management of COVID-19. Ultrasound Med Biol. https://doi.org/10.1016/j.ultrasmedbio.2020.05.012

    Article  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Lassen MCH, Skaarup KG, Lind JN, Alhakak AS, Sengeløv M, Nielsen AB, Espersen C, Ravnkilde K, Hauser R, Schöps LB, Holt E, Johansen ND, Modin D, Djernaes K, Graff C, Bundgaard H, Hassager C, Jabbari R, Carlsen J, Lebech A-M, Kirk O, Bodtger U, Lindholm MG, Joseph G, Wiese L, Schiødt FV, Kristiansen OP, Walsted ES, Nielsen OW, Madsen BL, Tønder N, Benfield T, Jeschke KN, Ulrik CS, Knop F, Lamberts M, Sivapalan P, Gislason G, Marott JL, Møgelvang R, Jensen G, Schnohr P, Søgaard P, Solomon SD, Iversen K, Jensen JUS, Schou M, Biering-Sørensen T (2020) Echocardiographic abnormalities and predictors of mortality in hospitalized COVID-19 patients: the ECHOVID-19 study. ESC Heart Fail. https://doi.org/10.1002/ehf2.13044

    Article  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Skaarup KG, Lassen MCH, Lind JN, Alhakak AS, Sengeløv M, Nielsen AB, Espersen C, Hauser R, Schöps LB, Holt E, Johansen ND, Modin D, Sharma S, Graff C, Bundgaard H, Hassager C, Jabbari R, Lebech A-M, Kirk O, Bødtger U, Lindholm MG, Joseph G, Wiese L, Schiødt FV, Kristiansen OP, Walsted ES, Nielsen OW, Madsen BL, Tønder N, Benfield TL, Jeschke KN, Ulrik CS, Knop F, Pallisgaard J, Lamberts M, Sivapalan P, Gislason G, Solomon SD, Iversen K, Jensen JUS, Schou M, Biering-Sørensen T (2020) Myocardial impairment and acute respiratory distress syndrome in hospitalized patients with coronavirus disease-2019: The ECHOVID-19 study. JACC Cardiovasc Imaging. https://doi.org/10.1016/j.jcmg.2020.08.005

    Article  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Pivetta E, Goffi A, Nazerian P, Castagno D, Tozzetti C, Tizzani P, Tizzani M, Porrino G, Ferreri E, Busso V, Morello F, Paglieri C, Masoero M, Cassine E, Bovaro F, Grifoni S, Maule MM, Lupia E (2019) Study group on lung ultrasound from the Molinette and Careggi hospitals, lung ultrasound integrated with clinical assessment for the diagnosis of acute decompensated heart failure in the emergency department: a randomized controlled trial. Eur J Heart Fail 21:754–766. https://doi.org/10.1002/ejhf.1379

    CAS  Article  PubMed  Google Scholar 

  27. 27.

    Lui KJ, Cumberland WG (1995) A Wilcoxon-type test for trend. Stat Med 14:445–446. https://doi.org/10.1002/sim.4780140409

    CAS  Article  PubMed  Google Scholar 

  28. 28.

    Trauer MM, Matthies A, Mani N, McDermott C, Jarman R (2020) The utility of lung ultrasound in COVID-19: a systematic scoping review. Ultrasound. https://doi.org/10.1177/1742271X20950779

    Article  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Favot M, Malik A, Rowland J, Haber B, Ehrman R, Harrison N (2020) Point-of-care lung ultrasound for detecting severe presentations of coronavirus disease 2019 in the emergency department: A retrospective analysis. Crit Care Explor 2:e0176. https://doi.org/10.1097/CCE.0000000000000176

    Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Platz E, Campbell RT, Claggett B, Lewis EF, Groarke JD, Docherty KF, Lee MMY, Merz AA, Silverman M, Swamy V, Lindner M, Rivero J, Solomon SD, McMurray JJV (2019) Lung ultrasound in acute heart failure: prevalence of pulmonary congestion and short- and long-term outcomes. JACC Heart Fail 7:849–858. https://doi.org/10.1016/j.jchf.2019.07.008

    Article  PubMed  Google Scholar 

  31. 31.

    Platz E, Lewis EF, Uno H, Peck J, Pivetta E, Merz AA, Hempel D, Wilson C, Frasure SE, Jhund PS, Cheng S, Solomon SD (2016) Detection and prognostic value of pulmonary congestion by lung ultrasound in ambulatory heart failure patients. Eur Heart J 37:1244–1251. https://doi.org/10.1093/eurheartj/ehv745

    Article  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Espersen C, Campbell RT, Claggett B, Lewis EF, Groarke JD, Docherty KF, Lee MMY, Lindner M, Biering-Sørensen T, Solomon SD, McMurray JJV, Platz E (2021) Sex differences in congestive markers in patients hospitalized for acute heart failure. ESC Heart Fail 8:1784–1795. https://doi.org/10.1002/ehf2.13300

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

TBS, together with KGS and MHL, received a research grant from the Novo Nordisk Foundation to conduct the study. Europcar Denmark provided cars for KGS and MHL to transport the equipment from hospital to hospital. TBS received funds from Herlev and Gentofte Hospital and the Lundbeck foundation while conducting this study. The sponsors had no role in the design and interpretation of the data.

Author information

Affiliations

Authors

Contributions

All the authors have contributed to the study in a manner that merits authorship as described in the journals’ “guideline for authors”.

Corresponding author

Correspondence to Tor Biering-Sørensen.

Ethics declarations

Conflict of interest

TBS reports receiving research grants from Sanofi Pasteur and GE Healthcare, is a Steering Committee member of the Amgen financed GALACTIC-HF trial, on advisory boards for Sanofi Pasteur and Amgen, and speaker honorariums from Novartis and Sanofi Pasteur. EP has received research support from the NIH outside the submitted work, and consulting fees from scPharmaceuticals outside the submitted work. Her employer has received support from Novartis for consulting work outside the submitted work. The remaining authors have nothing to disclose in relation to the present project.

Ethics approval

The study was approved by the regional ethics board and was conducted in accordance with the 2nd Helsinki Declaration. The ECHOVID-19 study is registered at Clinicaltrials.gov (NCT04377035).

Consent to participate

Informed consent was obtained from all participants.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

All the authors take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Skaarup, K.G., Lassen, M.C.H., Espersen, C. et al. Lung ultrasound findings in hospitalized COVID-19 patients in relation to venous thromboembolic events: the ECHOVID-19 study. J Ultrasound (2021). https://doi.org/10.1007/s40477-021-00605-8

Download citation

Keywords

  • COVID-19
  • Lung ultrasound
  • B-lines
  • Venous thromboembolic events