Abstract
Objectives
The aim of this study was to investigate whether right ventricular longitudinal strain (RVLS) was independently predictive of higher mortality in patients with coronavirus disease-2019 (COVID-19).
Background
RVLS obtained from 2-dimensional speckle-tracking echocardiography has been recently demonstrated to be a more accurate and sensitive tool to estimate right ventricular (RV) function. The prognostic value of RVLS in patients with COVID-19 remains unknown.
Methods
One hundred twenty consecutive patients with COVID-19 who underwent echocardiographic examinations were enrolled in our study. Conventional RV functional parameters, including RV fractional area change, tricuspid annular plane systolic excursion, and tricuspid tissue Doppler annular velocity, were obtained. RVLS was determined using 2-dimensional speckle-tracking echocardiography. RV function was categorized in tertiles of RVLS.
Results
Compared with patients in the highest RVLS tertile, those in the lowest tertile were more likely to have higher heart rate; elevated levels of D-dimer and C-reactive protein; more high-flow oxygen and invasive mechanical ventilation therapy; higher incidence of acute heart injury, acute respiratory distress syndrome, and deep vein thrombosis; and higher mortality. After a median follow-up period of 51 days, 18 patients died. Compared with survivors, nonsurvivors displayed enlarged right heart chambers, diminished RV function, and elevated pulmonary artery systolic pressure. Male sex, acute respiratory distress syndrome, RVLS, RV fractional area change, and tricuspid annular plane systolic excursion were significant univariate predictors of higher risk for mortality (p < 0.05 for all). A Cox model using RVLS (hazard ratio: 1.33; 95% confidence interval [CI]: 1.15 to 1.53; p < 0.001; Akaike information criterion = 129; C-index = 0.89) was found to predict higher mortality more accurately than a model with RV fractional area change (Akaike information criterion = 142, C-index = 0.84) and tricuspid annular plane systolic excursion (Akaike information criterion = 144, C-index = 0.83). The best cutoff value of RVLS for prediction of outcome was −23% (AUC: 0.87; p < 0.001; sensitivity, 94.4%; specificity, 64.7%).
Conclusions
RVLS is a powerful predictor of higher mortality in patients with COVID-19. These results support the application of RVLS to identify higher risk patients with COVID-19.
Key Words: COVID-19, right ventricular function, SARS-CoV-2, speckle tracking echocardiography, strain
Abbreviations and Acronyms: 2D, 2-dimensional; AIC, Akaike information criterion; ARDS, acute respiratory distress syndrome; CI, confidence interval; COVID-19, coronavirus disease-2019; HR, hazard ratio; LS, longitudinal strain; LV, left ventricular; LVEF, left ventricular ejection fraction; PASP, pulmonary artery systolic pressure; ROC, receiver-operating characteristic; RV, right ventricular; RVFAC, right ventricular fractional area change; RVLS, right ventricular longitudinal strain; S’, tricuspid lateral annular systolic velocity; SARS-CoV-2, severe acute respiratory syndrome-coronavirus-2; STE, speckle-tracking echocardiography; TAPSE, tricuspid annular plane systolic excursion; TR, tricuspid regurgitation
Central Illustration
Coronavirus disease-2019 (COVID-19), caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), has reached more than 170 countries, resulting in considerable morbidity and mortality. Although currently available studies have confirmed the presence of myocardial injury and its association with mortality in patients with COVID-19 (1,2), they lack evidence from echocardiography to determine the features of cardiac injury. As the prevalence of acute respiratory distress syndrome (ARDS) has been reported to be 29% to 67% among critically ill patients with COVID-19 (3,4), right ventricular (RV) function is presumed to be more susceptible to impairment because of increased RV afterload. In clinical practice, RV structure and function are evaluated mainly using echocardiography. The conventional echocardiographic parameters have limited diagnostic value, as they may fail to detect early abnormalities of RV systolic function (5). Recently, 2-dimensional (2D) speckle-tracking echocardiography (STE), which evaluates myocardial function accurately and reproducibly (6,7), has been introduced. Because of its capability to detect subclinical impairment of cardiac function, 2D STE has been extensively applied to investigate RV function in different clinical settings (8, 9, 10). Moreover, RV longitudinal strain (RVLS) derived from 2D STE has been demonstrated to be of prognostic value (11). To the best of our knowledge, there are no data regarding the use of RVLS in patients with COVID-19. In addition, confirming the role of RVLS in these patients may be of additional significance, as most patients exhibit preserved conventional echocardiographic parameters, and thus detection and risk stratification among these patients may be challenging. Accordingly, the purpose of this study was to evaluate the prognostic value of RVLS in patients with COVID-19.
Methods
Study population
This observational study was performed at the west branch of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, a designated hospital to treat patients with COVID-19. We included a total of 150 consecutive adult patients with COVID-19 who were diagnosed according to the interim guidance of the World Health Organization (12) from February 12, 2020, to March 15, 2020. Considering the presence of cardiac damage in patients with COVID-19, bedside echocardiography was performed in all patients from 3 wards managed by the investigators for the evaluation of cardiac function. The median time from admission to echocardiography was 7 days (interquartile range: 3 to 10 days). Patients with known cardiomyopathy, previous myocardial infarction, or suboptimal images were excluded. Of these patients, 2 had dilated cardiomyopathy, 4 had old myocardial infarction, and 24 did not have images of sufficient quality for echocardiographic analysis. The remaining 120 patients were included in our final analysis. The control group consisted of 37 healthy volunteers who had no cardiopulmonary disease on the basis of physical examination, electrocardiography, chest radiography, and echocardiography.
The study complied with the edicts of the 1975 Declaration of Helsinki (13) and was approved by the institutional ethics board of Union Hospital Tongji Medical College, Huazhong University of Science and Technology (20200022). The requirement to obtain written informed consent was waived for all participants with emerging infectious diseases.
Clinical data
Patients’ demographic characteristics, medical histories, laboratory examinations, comorbidities, complications, treatments, and outcomes were retrieved from electronic medical records. Cardiac biomarkers measured on admission included hypersensitive troponin I, creatine kinase muscle-brain, and B-type natriuretic peptide. These data were independently reviewed and entered into the computer database by 2 analysts (C.W. and W.S.) The final follow-up date was April 2, 2020.
Transthoracic echocardiography
Bedside transthoracic echocardiographic examinations were performed in all patients using the EPIQ 7C ultrasound system (Philips Medical Systems, Andover, Massachusetts). Two-dimensional and Doppler echocardiography were performed on the basis of the guidelines of the American Society of Echocardiography (14). Images were stored and analyzed by 2 independent observers (Y.C. and L.C.) blinded to clinical data.
Conventional echocardiographic analysis
Left ventricular (LV) end-systolic volume and end-diastolic volume and LV ejection fraction (LVEF) were measured using the biplane Simpson method (15). LV mass was calculated from the parasternal view on the basis of Devereux’s formula. LV diastolic function was estimated using the ratio of early transmitral flow velocity (E) to late transmitral flow velocity (A) and the ratio of transmitral E to early diastolic medial LV septal tissue velocity (e′).
Right atrial and RV size were determined from the apical 4-chamber view. Tricuspid annular plane systolic excursion (TAPSE) was measured as the systolic displacement of the tricuspid lateral annulus, recorded on M-mode imaging. RV end-diastolic and end-systolic areas were obtained from the apical 4-chamber view. RV fractional area change (RVFAC) was calculated as: (RV end-diastolic area − RV end-systolic area)/end-diastolic area × 100%. Tricuspid lateral annular systolic velocity (S′) was assessed using tissue Doppler imaging from the apical 4-chamber view. Estimation of tricuspid regurgitation (TR) incorporated color Doppler imaging and contour of the jet on continuous-wave Doppler imaging. Moderate to severe TR was defined as moderate, moderate to severe, or severe TR. Pulmonary artery systolic pressure (PASP) was assessed from the peak velocity of the TR jet, using the modified Bernoulli equation plus right atrial pressure evaluated from the inferior vena cava size and its collapsibility.
Speckle-tracking echocardiographic analysis
STE was conducted according to the recommendations of the American Society of Echocardiography and the European Association of Cardiovascular Imaging (6). All of the images were analyzed using 2D AutoStrain software (Qlab13, Philips Healthcare, Andover, Massachusetts) in the apical 4-chamber view at a frame rate of 50 to 70 frames/s (Figure 1 ). After tracing the RV endocardial border, the region of interest was automatically generated. Manual corrections were then performed to fit RV myocardial wall thickness. The RV free wall was automatically divided into 3 segments: basal, mid, and apical. RVLS was calculated as the mean of the strain values in the 3 segments of the RV free wall. If it was not feasible to track 1 or more segments, the case was excluded. We took the absolute value for a simpler interpretation, as RVLS is a negative value.
Figure 1.
RVLS Obtained From 2-Dimensional Speckle Tracking Echocardiography in Patients With COVID-19
(A) Representative images of the highest tertile of right ventricular longitudinal strain (RVLS). (B) Representative images of the middle tertile of RVLS. (C) Representative images of the lowest tertile of RVLS.
Interobserver and intraobserver reproducibility
Intraobserver and interobserver variability of RVLS was estimated in 20 randomly selected subjects and evaluated using intraclass correlation coefficients and Bland-Altman analysis. Intraobserver variability was assessed by having 1 observer remeasure after 2 weeks. Interobserver variability was evaluated by a second observer who was blinded to the first observer’s measurements.
Statistical analysis
Continuous numeric variables are expressed as mean ± SD or median (interquartile range) and were compared using a 2-sample Student’s t-test and 1-way analysis of variance (for normally distributed data) or the Mann-Whitney U test and Kruskal-Wallis test (for non-normally distributed data). Categorical variables are expressed as frequency (percentage) and were compared using the chi-square test or the Fisher exact test. To determine the optimal cutoff value (maximum Youden index) of prognostic RV functional parameters for detecting increased mortality, receiver-operating characteristic (ROC) curves were used. Survival curves were obtained in a Kaplan-Meier analysis and compared using the log-rank test. Estimations of the predictors of mortality were performed using univariate and multivariate Cox regression models. All potential predictors of higher mortality were entered into univariate analyses, including sex, age, cardiac injury and inflammatory markers, LVEF, PASP, RV functional echocardiographic parameters, ARDS, and comorbidities (diabetes mellitus, hypertension, cardiovascular artery disease, malignancy, and arrhythmia). Variables with p values <0.05 in univariate analysis were entered into multivariate Cox regression models. For multivariate analysis, a separate Cox proportional hazards model including clinical variables and 1 of the RV function parameters (TAPSE, RVFAC, or RVLS) was used to determine the independent predictors of higher mortality. Model performance was assessed using the Akaike information criterion (AIC) and the C-index. Data were analyzed using SPSS version 24.0 (SPSS Inc., Chicago, Illinois), MedCalc Version 19.0.4 (MedCalc Software, Ostend, Belgium), and R version 3.6.3 (R Foundation for Statistical Computing, Vienna, Austria). A 2-sided p value <0.05 was considered to indicate statistical significance.
Results
Clinical characteristics
Clinical characteristics of patients with COVID-19 according to tertiles of RVLS are shown in Table 1 . The mean age of patients with COVID-19 was 61 ± 14 years, and 57 (48%) were men. Chronic obstructive pulmonary disease was found in 6 patients with COVID-19. None of the patients had histories of pulmonary embolism. No patient was diagnosed with pulmonary embolism. Compared with patients in the highest tertiles, those in the lowest RVLS tertile were more likely to have higher heart rates; elevated levels of D-dimer and C-reactive protein; more high-flow oxygen and invasive mechanical ventilation therapy; higher incidence of acute heart injury, ARDS, and deep vein thrombosis; and higher mortality. There were no significant differences in age, sex, systemic arterial pressure, comorbidities, lymphocyte count, levels of creatine kinase muscle-brain, hypersensitive troponin I and B-type natriuretic peptide, partial pressure of oxygen/fraction of inspiration oxygen, procalcitonin, antiviral, antibiotic, glucocorticoid, and angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker use, number of intensive care unit admissions, and acute kidney injury among the tertiles.
Table 1.
Clinical Characteristics of Patients With COVID-19 According to Tertiles of RVLS
| Total Population: RVLS 10.3%–35.7% (N = 120) | Upper Tertile: RVLS 25.5%–35.7% (n = 40) | Middle Tertile: RVLS 20.6%–25.4% (n = 40) | Lower Tertile: RVLS 10.3%–20.5% (n = 40) | p Value | |
|---|---|---|---|---|---|
| Clinical characteristics | |||||
| Age, yrs | 61 ± 14 | 61 ± 14 | 57 ± 15 | 64 ± 13 | 0.102 |
| Male | 57 (48) | 19 (48) | 16 (40) | 22 (55) | 0.412 |
| Body mass index, kg/m2 | 23.7 ± 3.0 | 24.1 ± 3.2 | 23.0 ± 3.1 | 23.8 ± 2.8 | 0.337 |
| Heart rate, beats/min | 92 ± 17 | 87 ± 17 | 91 ± 17 | 96 ± 17∗ | 0.066 |
| Respiratory rate, breaths/min | 26 ± 9 | 25 ± 5 | 27 ± 13 | 27 ± 6 | 0.607 |
| Systolic arterial pressure, mm Hg | 130 ± 22 | 131 ± 22 | 129 ± 29 | 132 ± 19 | 0.812 |
| Diastolic arterial pressure, mm Hg | 80 ± 14 | 82 ± 11 | 79 ± 18 | 81 ± 12 | 0.623 |
| Smoking | 6 (5.0) | 2 (5.0) | 1 (2.5) | 3 (7.5) | 0.611 |
| Comorbidities | |||||
| Hypertension | 48 (40) | 12 (30) | 16 (40) | 20 (50) | 0.192 |
| Diabetes | 14 (11.7) | 5 (12.5) | 4 (10.0) | 5 (12.5) | 0.924 |
| Obesity | 22 (18.3) | 8 (20.0) | 6 (15.0) | 6 (15.0) | 0.799 |
| COPD | 6 (5.0) | 3 (7.5) | 0 (0.0) | 3 (7.5) | 0.210 |
| Coronary artery disease | 11 (9.2) | 3 (7.5) | 3 (7.5) | 5 (12.5) | 0.689 |
| Chronic kidney disease | 17 (14.2) | 3 (7.5) | 6 (15.0) | 8 (20.0) | 0.369 |
| Chronic liver disease | 4 (3.3) | 2 (5.0) | 2 (5.0) | 0 (0.0) | 0.375 |
| Malignancy | 8 (6.7) | 3 (7.5) | 4 (10.0) | 1 (2.5) | 0.398 |
| Laboratory findings | |||||
| Lymphocyte count, ×109/l | 1.08 ± 0.61 | 1.14 ± 0.48 | 1.04 ± 0.67 | 1.05 ± 0.66 | 0.755 |
| D-dimer, mg/l | 1.45 (0.50–4.91) | 0.76 (0.35–2.64) | 2.10 (0.49–6.72)∗ | 1.84 (0.83–6.13)∗ | 0.053 |
| CK-MB, U/l | 9 (4.5–13.5) | 9 (4.5–13.5) | 9 (5.0–11.3) | 12 (4.5–20.0) | 0.256 |
| hs-TNI, ng/l | 3.5 (1.8–14.4) | 2.4 (1.1–4.7) | 3.5 (1.6–9.3) | 10.8 (2.6–59.5) | 0.330 |
| BNP, pg/ml | 53.1 (28.2–131.4) | 51.4 (28.0–90.9) | 52.6 (39.4–124.7) | 86.1 (24.2–232.7) | 0.518 |
| PaO2/FiO2, mm Hg | 217.8 (152.1–256.8) | 254.1 (221.9–287.9) | 167.5 (152.7–269.6) | 178.8 (140.4–210.8) | 0.282 |
| CRP, mg/l | 24.0 (2.8–65.1) | 11.2 (1.1–48.7) | 23.4 (3.6–71.8) | 29.8 (3.7–64.2)∗ | 0.053 |
| PCT, ng/ml | 0.15 (0.06–0.24) | 0.11 (0.05–0.22) | 0.13 (0.05–0.26) | 0.16 (0.10–0.25) | 0.557 |
| Treatments | |||||
| Antiviral therapy | 112 (93.3) | 38 (95.0) | 37 (92.5) | 37 (92.5) | 0.877 |
| Antibiotic therapy | 85 (70.8) | 25 (62.5) | 28 (70.0) | 32 (80.0) | 0.229 |
| Glucocorticoid therapy | 46 (38.3) | 12 (30.0) | 13 (32.5) | 21 (52.5) | 0.077 |
| ACE inhibitor/ARB | 8 (6.7) | 3 (7.5) | 1 (2.5) | 4 (10.0) | 0.398 |
| Oxygen therapy | 105 (87.5) | 35 (87.5) | 36 (90.0) | 34 (85.0) | 0.800 |
| High-flow oxygen | 58 (48.3) | 16 (40.0) | 16 (40.0) | 26 (65.0)∗† | 0.035 |
| IMV | 15 (12.5) | 0 (0.0) | 5 (12.5)∗ | 10 (25.0)∗ | 0.003 |
| NIMV | 6 (5.0) | 1 (2.5) | 2 (5.0) | 3 (7.5) | 0.593 |
| ICU admission | 22 (21.0) | 4 (10.0) | 8 (20.0) | 10 (25.0) | 0.214 |
| Complications | |||||
| Acute kidney injury | 16 (13.0) | 3 (7.5) | 5 (12.5) | 8 (20.0) | 0.259 |
| Acute heart injury | 37 (30.8) | 5 (12.5) | 10 (25.0)∗ | 22 (55.0)∗† | <0.001 |
| ARDS | 41 (34.2) | 10 (25.0) | 10 (25.0) | 21 (52.5)∗† | 0.011 |
| DVT | 49 (41.0) | 12 (30.0) | 12 (30.0) | 25 (62.5)∗† | 0.003 |
| Prognosis | |||||
| Hospital stay | 3 (2.5) | 0 (0.0) | 2 (5.0) | 1 (2.5) | 0.371 |
| Discharge | 99 (82.5) | 40 (100.0) | 33 (82.5) | 26 (65.0)∗ | 0.077 |
| Death | 18 (15.0) | 0 (0.0) | 5 (12.5)∗ | 13 (32.5)∗† | <0.001 |
Values are mean ± SD, n (%), or median (interquartile range).
ACE = angiotensin-converting enzyme; ARB = angiotensin II receptor blocker; ARDS = acute respiratory distress syndrome; BNP = B-type natriuretic peptide; CK-MB = creatine kinase muscle-brain; COPD = chronic obstructive pulmonary disease; COVID-19 = coronavirus disease-2019; CRP = C-reactive protein; FiO2 = fraction of inspiration oxygen; DVT = deep vein thrombosis; hs-TNI = hypersensitive troponin I; ICU = intensive care unit; IMV = invasive mechanical ventilation; NIMV = noninvasive mechanical ventilation; PCT = procalcitonin; PaO2 = partial pressure of oxygen; RVLS = right ventricular longitudinal strain.
p < 0.05, lowest or middle tertiles vs. highest RVLS tertile.
p < 0.05, lowest tertile vs. middle RVLS tertile.
Echocardiographic characteristics
Echocardiographic characteristics of patients with COVID-19 are described in Tables 2 and 3 . Compared with patients in the highest RVLS tertiles, those in the lowest tertile had similar left atrial and LV size, LV mass, E/A ratio, E/e′ ratio, LV end-diastolic volume, LV end-systolic volume, and LVEF. The distribution of RVLS in patients with COVID-19 is presented in Figure 2 . Patients in the lowest RVLS tertile exhibited dilated right atrium; lower RVLS, RVFAC, and TAPSE; more moderate to severe TR; and higher PASP. However, RV, pulmonary artery, and inferior vena cava dimensions and S′ did not differ among the tertiles. RVLS was lower in patients with ARDS than in those without ARDS (21.3 ± 4.6% vs. 24.6 ± 4.4%; p < 0.001).
Table 2.
Echocardiographic Characteristics of Patients With COVID-19 According to Tertiles of RVLS
| Total Population: RVLS 10.3%–35.7% (N = 120) | Upper Tertile: RVLS 25.5%–35.7% (n = 40) | Middle Tertile: RVLS 20.6%–25.4% (n = 40) | Lower Tertile: RVLS 10.3%–20.5% (n = 40) | p Value | |
|---|---|---|---|---|---|
| Left heart | |||||
| LA dimension, mm | 34.3 ± 5.4 | 35.2 ± 3.9 | 32.9 ± 4.6 | 34.7 ± 6.9 | 0.141 |
| LV dimension, mm | 45.3 ± 4.8 | 45.7 ± 4.0 | 44.6 ± 5.7 | 45.6 ± 4.6 | 0.549 |
| LV mass, g/m2 | 140.1 ± 32.8 | 141.0 ± 29.8 | 134.0 ± 36.0 | 145.2 ± 32.3 | 0.320 |
| E/A ratio | 0.9 ± 0.3 | 0.9 ± 0.3 | 0.9 ± 0.3 | 0.9 ± 0.4 | 0.944 |
| E/e′ ratio | 9.1 ± 3.1 | 8.8 ± 3.3 | 8.6 ± 2.2 | 9.7 ± 3.6 | 0.265 |
| LVEDV, ml | 85.4 ± 25.1 | 90.1 ± 21.8 | 80.7 ± 26.4 | 85.1 ± 27.0 | 0.295 |
| LVESV, ml | 32.8 ± 13.5 | 35.9 ± 11.5 | 29.8 ± 10.8∗ | 32.9 ± 17.2 | 0.199 |
| LVEF, % | 63.4 ± 7.0 | 62.0 ± 5.9 | 64.3 ± 6.4 | 63.9 ± 8.4 | 0.315 |
| Right heart | |||||
| RA dimension, mm | 35.4 ± 4.7 | 34.7 ± 3.5 | 34.2 ± 3.6 | 37.3 ± 6.2∗† | 0.013 |
| RV dimension, mm | 33.6 ± 4.2 | 33.0 ± 3.8 | 33.1 ± 3.8 | 34.8 ± 5.1 | 0.102 |
| PA, mm | 23.5 ± 2.8 | 23.4 ± 1.7 | 23.1 ± 2.8 | 24.0 ± 3.6 | 0.440 |
| IVC, mm | 15.6 ± 3.6 | 16.1 ± 3.7 | 15.4 ± 3.6 | 15.2 ± 3.4 | 0.591 |
| RVLS, % | 23.5 ± 4.7 | 28.6 ± 2.9 | 23.5 ± 1.4∗ | 18.4 ± 1.8∗† | <0.001 |
| RVFAC, % | 45.8 ± 6.1 | 47.5 ± 5.3 | 45.9 ± 6.4 | 43.9 ± 6.0∗ | 0.026 |
| TAPSE, mm | 22.9 ± 3.6 | 23.8 ± 3.5 | 23.0 ± 3.7 | 21.8 ± 3.4∗ | 0.046 |
| S′, cm/s | 13.6 ± 2.4 | 13.6 ± 2.7 | 13.3 ± 2.4 | 13.9 ± 2.2 | 0.461 |
| Moderate to severe TR | 8 (6.7) | 1 (2.5) | 3 (7.5) | 4 (10.0)∗ | 0.398 |
| PASP, mm Hg | 31 (22–45) | 27 (24–37) | 32 (24–46) | 32 (25–48)∗ | 0.311 |
Values are mean ± SD, n (%), or median (interquartile range). RVLS values are absolute values.
IVC = inferior vena cava; LA = left atrial; LV = left ventricular; LVEDV = left ventricular end-diastolic volume; LVESV = left ventricular end-systolic volume; LVEF = left ventricular ejection fraction; PA = pulmonary artery; PASP = pulmonary artery systolic pressure; RA = right atrial; RV = right ventricular; RVFAC = fractional area change; RVLS = right ventricular longitudinal strain; TAPSE = tricuspid annular plane systolic excursion; TR = tricuspid regurgitation.
p < 0.05, lowest or middle tertile vs. highest RVLS tertile.
p < 0.05, lowest tertile vs. middle RVLS tertile.
Table 3.
Echocardiographic Characteristics of Survivors and Nonsurvivors With COVID-19
| All Patients (N = 120) | Survivors (n = 102) | Nonsurvivors (n = 18) | p Value | |
|---|---|---|---|---|
| Left heart | ||||
| LA dimension, mm | 34.3 ± 5.4 | 34.2 ± 5.1 | 34.7 ± 6.7 | 0.696 |
| LV dimension, mm | 45.3 ± 4.8 | 45.4 ± 4.9 | 44.8 ± 4.2 | 0.649 |
| LV mass, g/m2 | 142.8 ± 31.4 | 139.6 ± 33.2 | 142.8 ± 31.4 | 0.710 |
| E/A ratio | 0.29 ± 0.35 | 0.92 ± 0.36 | 0.93 ± 0.30 | 0.902 |
| E/e′ ratio | 9.1 ± 3.1 | 9.0 ± 3.2 | 9.4 ± 3.0 | 0.677 |
| LVEDV, ml | 85.6 ± 24.2 | 87.1 ± 25.2 | 78.3 ± 17.4 | 0.138 |
| LVESV, ml | 24.8 ± 5.7 | 25.1 ± 5.8 | 23.8 ± 5.4 | 0.106 |
| LVEF, % | 63.4 ± 7.0 | 63.0 ± 7.0 | 65.8 ± 6.7 | 0.135 |
| Right heart | ||||
| RA dimension, mm | 35.4 ± 4.7 | 34.8 ± 4.2 | 38.6 ± 6.0 | 0.001 |
| RV dimension, mm | 33.6 ± 4.2 | 33.0 ± 3.8 | 36.4 ± 4.9 | 0.001 |
| PA, mm | 23.5 ± 2.8 | 23.0 ± 2.6 | 26.0 ± 3.0 | <0.001 |
| IVC, mm | 15.5 ± 3.8 | 15.4 ± 3.7 | 16.0 ± 4.3 | 0.572 |
| RVLS, % | 23.5 ± 4.7 | 24.4 ± 4.4 | 18.5 ± 3.1 | <0.001 |
| RVFAC, % | 45.8 ± 6.1 | 46.5 ± 5.7 | 41.6 ± 6.5 | 0.002 |
| TAPSE, mm | 22.9 ± 3.6 | 23.2 ± 3.5 | 21.0 ± 3.3 | 0.016 |
| S′, cm/s | 13.6 ± 2.4 | 13.7 ± 2.5 | 12.9 ± 1.9 | 0.223 |
| Moderate to severe TR | 8 (6.7) | 7 (6.7) | 1 (5.6) | 0.839 |
| PASP, mm Hg | 31 (24–45) | 28 (24–36) | 48 (40–55) | 0.042 |
Values are mean ± SD, n (%), or median (interquartile range). The p values comparing survivors and nonsurvivors are from chi-square test, Fisher exact test, or Mann-Whitney U test; p values <0.05 were considered to indicate statistical significance. RVLS values are absolute values.
Abbreviations as in Table 2.
Figure 2.
Distribution of RVLS in Patients With COVID-19
(A) Distribution of right ventricular longitudinal strain (RVLS) in patients with coronavirus disease-2019 (COVID-19) (blue, highest tertile; green, middle tertile; red, lowest tertile). (B) Tukey box-and-whisker plots of RVLS values in patients with COVID-19 according to the tertiles. (C) Distribution of RVLS in patients with COVID-19 (red) and healthy control subjects (green). RVLS values are absolute values.
After a median follow-up period of 51 days, 18 patients had died. Left heart structure (left atrial and LV end-diastolic dimensions, LV mass and volumes) and LV systolic (LVEF) and diastolic (E/A ratio, E/e′ ratio) function were not different between nonsurvivors and survivors. Compared with survivors, nonsurvivors displayed enlarged right heart chambers and pulmonary arteries; lower RVLS, RVFAC, and TAPSE; and elevated PASP. Inferior vena cava diameter, moderate to severe TR, and S′ were similar in survivors and nonsurvivors.
Predictors of mortality in patients with COVID-19
RVLS and conventional RV function indexes were entered into an ROC analysis to estimate the probability of poor clinical outcome. RVLS, RVFAC, and TAPSE were associated with higher mortality (Figure 3 ). Area under the curve for RVLS (0.87) was greater than that for RVFAC (0.72; p = 0.028) and TAPSE (0.67; p = 0.002). Therefore, RVLS most accurately predicted higher risk for mortality. Optimal cutoff values of RV function parameters for identifying higher mortality were 23% for RVLS, 43.5% for RVFAC, and 23 mm for TAPSE. The best cutoff value of RVLS for detection of increased mortality was 23%, with sensitivity of 94.4% and specificity of 64.7%.
Figure 3.
Receiver-Operating Characteristic Curves of RVLS, FAC, and TAPSE for Adverse Clinical Outcome
FAC = fractional area change; RVLS = right ventricular longitudinal strain; TAPSE = tricuspid annular plane systolic excursion.
Figure 4 and the Central Illustration show Kaplan-Meier survival curves for mortality. Among the patients, when separated by tertiles, mortality was highest in patients with RVLS ≤20.5%, followed by RVLS in the range between 20.6% and 25.4%, and lowest among patients with RVLS ≥25.5% (p < 0.001) (Central Illustration). When stratified by cutoff values, RVLS lower than 23% was associated with higher mortality (p < 0.001) (Central Illustration). It also clearly revealed that survival significantly declined with worsening TAPSE and RVFAC (Figures 4A and 4B).
Figure 4.
Kaplan-Meier Survival Curves Showing the Association of Higher Mortality and Right Ventricular Function
(A) Kaplan-Meier curve of survival in patients stratified by the cutoff value of tricuspid annular plane systolic excursion (TAPSE). (B) Kaplan-Meier curve of survival in patients stratified by the cutoff value of right ventricular fractional area change (FAC).
Central Illustration.
Association of Right Ventricular Longitudinal Strain and Mortality in Patients With COVID-19
In the upper panel, examples of strain plot of right ventricular longitudinal strain (RVLS) are shown: (A) a 42-year-old patient with impaired RVLS (16.8%), who died of coronavirus disease-2019 17 days after the echocardiographic examination; and (B) a 57-year-old patient with preserved RVLS (29.3%), who did not experience an event during 61 days of follow-up. In the lower panel, survival curves for all-cause mortality are shown (C) according to the cutoff value of RVLS (23%) and (D) according to tertiles of RVLS (≤20.5%, 20.6% to 25.4%, and ≥25.5%). RVLS values are absolute values.
A univariate Cox regression analysis showed that male sex (hazard ratio [HR]: 4.49; 95% confidence interval [CI]: 1.48 to 13.66; p = 0.008), ARDS (HR: 10.31; 95% CI: 2.98 to 35.63; p < 0.001), RVLS (HR: 1.45; 95% CI: 1.26 to 1.67; p < 0.001), RVFAC (HR: 0.88; 95% CI: 0.81 to 0.95; p = 0.002), and TAPSE (HR: 0.86; 95% CI: 0.76 to 0.97; p = 0.018) were associated with higher risk for mortality (Table 4 ). However, age, comorbidity, creatine kinase muscle-brain, hypersensitive troponin I, moderate to severe TR, angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker therapy, S′, and LVEF were not predictive of mortality in univariate analysis. In multivariate Cox analysis models, ARDS continued to be of prognostic value. RVLS (HR: 1.33; 95% CI: 1.15 to 1.53; p < 0.001), RVFAC (HR: 0.90; 95% CI: 0.83 to 0.98; p = 0.017), and TAPSE (HR: 0.88; 95% CI: 0.78 to 0.99; p = 0.044) were independent predictors of higher mortality (Table 4). The model with RVLS (AIC = 129, C-index = 0.89) was the best in predicting mortality compared with those with RVFAC (AIC = 142, C-index = 0.84), TAPSE (AIC = 144, C-index = 0.83), and traditional risk factors (AIC = 146, C-index = 0.82).
Table 4.
Predictors of Mortality In Patients With Covid-19 by Cox Proportional Hazard Model
| Univariate Cox Regression |
Model 1 |
Model 2 |
Model 3 |
Model 4 |
||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Gender + ARDS |
Gender + ARDS + TAPSE |
Gender + ARDS + RVFAC |
Gender + ARDS + RVLS |
|||||||
| HR (95% CI) | p Value | HR (95% CI) | p Value | HR (95% CI) | p Value | HR (95% CI) | p Value | HR (95% CI) | p Value | |
| Age | 1.02 (0.99–1.06) | 0.257 | ||||||||
| Male | 4.49 (1.48–13.66) | 0.008 | 3.31 (1.08–10.13) | 0.036 | 0.060 | 3.39 (1.10–10.41) | 0.033 | 0.059 | ||
| Hypertension | 2.51 (0.97–6.47) | 0.057 | ||||||||
| Diabetes mellitus | 0.41 (0.06–3.09) | 0.387 | ||||||||
| Coronary artery disease | 2.93 (0.97–8.92) | 0.058 | ||||||||
| Malignancy | 2.01 (0.46–8.76) | 0.354 | ||||||||
| ARDS | 10.31 (2.98–35.63) | <0.001 | 8.65 (2.48–30.10) | 0.001 | 6.78 (1.86–24.71) | 0.004 | 6.63 (1.87–23.54) | 0.003 | 4.47 (1.25–16.03) | 0.021 |
| CK-MB | 1.02 (0.99–1.05) | 0.208 | ||||||||
| hs-TNI | 0.99 (0.98–1.01) | 0.580 | ||||||||
| LVEF | 1.07 (0.99–1.15) | 0.115 | ||||||||
| RVLS | 1.45 (1.26–1.67) | <0.001 | 1.33 (1.15–1.53) | <0.001 | ||||||
| RVFAC | 0.88 (0.81–0.95) | 0.002 | 0.90 (0.83–0.98) | 0.017 | ||||||
| TAPSE | 0.86 (0.76–0.97) | 0.018 | 0.88 (0.78–0.99) | 0.044 | ||||||
| S′ | 0.88 (0.72–1.08) | 0.215 | ||||||||
| Moderate to severe TR | 1.03 (0.14–7.72) | 0.979 | ||||||||
| ACE inhibitor/ARB | 0.80 (0.11–6.03) | 0.831 | ||||||||
| AIC | — | — | 146 | 144 | 142 | 129 | ||||
| C-index | — | — | 0.82∗ | 0.83 | 0.84∗ | 0.89∗ | ||||
Reproducibility
The intraobserver and interobserver reproducibility of RVLS was excellent, as reflected by high ICC (intraobserver: 0.95; interobserver: 0.91). Bland-Altman analysis demonstrated good intraobserver and interobserver agreement, with small bias (intraobserver: −0.33; interobserver: 0.70) and narrow limits of agreement (intraobserver: −2.19 to 1.54; interobserver: −3.08 to 4.49).
Discussion
To our knowledge, this is the first study to comprehensively evaluate the prognostic value of RV function using conventional echocardiography and 2D STE in patients with COVID-19. Patients with the greatest degree of RV strain impairment were more likely to have higher heart rates; more high-flow oxygen and invasive mechanical ventilation therapy; higher incidence of acute heart injury, ARDS, and deep vein thrombosis; and higher mortality. Compared with survivors, nonsurvivors had enlarged right heart chambers, diminished RV function, and elevated PASP. More important, RVLS was able to predict higher risk for mortality in patients with COVID-19, independently of and incrementally to other echocardiographic parameters. Therefore, a comprehensive assessment of RV function using 2D STE may be essential for risk stratification in patients with COVID-19.
Prognosis of RV function in COVID-19 patients
It is significant to recognize patients with COVID-19 at higher risk for poor outcomes who might benefit from vigilant monitoring. Several risk factors for poor prognosis have been identified in SARS-CoV-2 infection (16,17). The roles of the previously described prognostic markers, in particular ARDS and male sex, were confirmed in the present study. Furthermore, our study revealed important additional prognostic value of RV dysfunction. Most notably, the additional prognostic value of RVLS was substantial, independent of LV systolic functional index, which failed to predict mortality in patients with COVID-19. This is consistent with a previous study of LV performance in severe acute respiratory syndrome, showing that only subclinical LV diastolic impairment was observed in patients with severe acute respiratory syndrome (18). Nevertheless, the prognostic value of RV function was not yet explored in the study of severe acute respiratory syndrome.
RV dysfunction is related to significant morbidity and mortality in a variety of cardiovascular diseases (9,10,19,20). Indeed, in the present study, nonsurvivors displayed RV dilation and dysfunction. It has been reported that SARS-CoV-2 infection could cause both pulmonary and systemic inflammation, which may contribute to RV failure through RV overload and direct damage to cardiomyocytes (17,21). Similarly, in 42 patients with moderate to severe ARDS, Lazzeri et al. (22) demonstrated that troponin release can be related to RV dysfunction, thus emphasizing the clinical role of RV function (22). Moreover, although sharing considerable similarities, myocardial injury and cardiac insufficiency were more frequently reported in patients with COVID-19 than in those with severe acute respiratory syndrome (17,23). Therefore, assessment of RV function and recognition its prognostic significance is necessary in patients with COVID-19. RV dysfunction is not only a sign of increased pulmonary pressures but also directly contributes to cardiac insufficiency.
Evaluation of RV function using echocardiography
Although cardiac magnetic resonance remains the gold standard for quantifying RV function (24), in our study, the highly contagious nature of COVID-19 and patients’ inability to hold their breath for a short time limited the application of cardiac magnetic resonance. Echocardiography is more widely used in daily practice. In clinical practice, it is routine to evaluate RV function using conventional echocardiographic parameters recommended by guidelines (14), which include TAPSE, RVFAC, and S′. However, each index has its own limitations. TAPSE and S′ represent only the longitudinal movement of the basal segment of the RV free wall and may fail to accurately reflect the entire RV performance. RVFAC is dependent on imaging plane, causing considerable interobserver and intraobserver variability in patients with suboptimal endocardial definition. In particular, the insufficient image quality in some patients with COVID-19 limits the accuracy of RVFAC measurement. Recently, 2D STE has been recommended as a superior method for assessment of RV performance, which has the advantage of being angle independent. Moreover, it can detect RV dysfunction more accurately and sensitively than TAPSE or RVFAC. Prior studies have revealed the prognostic utility of RVLS in various clinical settings (5,25,26).
Importantly, we demonstrated the superiority of RVLS over conventional RV functional parameters in identifying associations with outcomes. These findings were in keeping with the study of Carluccio et al. (5), which demonstrated that RVLS provided incremental prognostic information and enhanced risk stratification in patients with heart failure with preserved TAPSE. The superiority of RVLS may be related to several reasons. First, RVLS includes the whole RV free wall (basal, mid, and apical segments), contrary to TAPSE and S′, which assess only basal longitudinal motion. Furthermore, by tracking the myocardium throughout the cardiac cycle, RVLS can easily identify the maximal and minimal values of deformation, whereas RVFAC acquisition depends on end-diastole and end-systole frames. Finally, RVLS has been considered as a strong prognostic indicator for various cardiovascular diseases.
Clinical implications
Our data demonstrated that RVLS was a powerful and independent predictor of higher mortality, providing additive predictive value over other echocardiographic parameters in patients with COVID-19. Accordingly, the present study revealed the important clinical implication of RVLS, as it can be easily obtained during bedside echocardiography. This suggests that evaluation of RV function using conventional echocardiographic measurements (i.e., RVFAC and TAPSE) should be complemented by longitudinal strain analysis to identify patients at higher risk for poor outcomes.
Study limitations
Although our study was a cohort of homogenous and consecutive patients who were hospitalized with COVID-19, it was limited by being a single-center study with a relatively limited sample size. Our hospital is among the hardest hit hospitals by the COVID-19 in Wuhan, thus the patients we included may not represent the populations in other areas. Moreover, we enrolled patients who were hospitalized with COVID-19, and asymptomatic patients who had not been admitted to the hospital were not included. Considering the wide clinical spectrum of SARS-CoV-2 infection, our findings may not be applicable to the entire COVID-19 population. Therefore, future multicenter studies with larger sample sizes are needed to determine the prognostic value of RVLS in patients with COVID-19. Additionally, we excluded 24 patients because of poor image quality precluding strain analysis, which limits the generalizability of our results. Also, our results pertain only to the software used in our study and may not apply to other software algorithms, because the 2D speckle-tracking echocardiographic parameters are hampered by the intervendor variability. We used RV free-wall longitudinal strain instead of global RV strain, because a simultaneous echocardiographic catheterization study demonstrated that free-wall longitudinal strain might better reflect RV function than global RV strain (27). Moreover, the relationship between LV and RV function could not be explored in the present study, as RV function could be affected by subclinical LV dysfunction. Furthermore, obese patients were uncommon in our study, as obesity is preliminarily considered as a high risk factor.
Conclusions
Our study demonstrates that RVLS is an independent determinant of outcomes in patients with COVID-19. Importantly, this index may have additional predictive value over other echocardiographic parameters. Therefore, evaluation of RV function should be implemented by investigation of RVLS for risk stratification in patients with COVID-19.
Perspectives.
COMPETENCY IN PATIENT CARE AND PROCEDURAL SKILLS: RVLS is a powerful and independent predictor of higher mortality, providing additive predictive value over other echocardiographic parameters in patients with COVID-19. Our study demonstrated that comprehensive assessment of RV function by 2D STE may be essential for risk stratification in patients with COVID-19.
TRANSLATIONAL OUTLOOK: Future multicenter studies are needed to verify the value of 2D STE using different software for risk stratification of patients with COVID-19.
Author Relationship With Industry
This work was supported by the National Natural Science Foundation of China (grants 81727805, 81922033, and 81401432). The authors have reported that they have no relationships relevant to the contents of this paper to disclose.
Footnotes
The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the JACC: Cardiovascular Imagingauthor instructions page.
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