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Cardiac Dysfunction and Arrhythmias 3 Months After Hospitalization for COVID‐19

2022; Wiley; Volume: 11; Issue: 3 Linguagem: Inglês

10.1161/jaha.121.023473

2047-9980

Charlotte B. Ingul, Jostein Grimsmo, Albulena Mecinaj, Divna Trebinjac, Magnus Berger Nossen, Simon Andrup, Bjørnar Grenne, Håvard Dalen, Gunnar Einvik, Knut Stavem, Turid Follestad, Tony Josefsen, Torbjørn Omland, Torstein Jensen,

Cardiac Arrest and Resuscitation

HomeJournal of the American Heart AssociationVol. 11, No. 3Cardiac Dysfunction and Arrhythmias 3 Months After Hospitalization for COVID‐19 Open AccessResearch ArticlePDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissionsDownload Articles + Supplements ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toSupplemental MaterialOpen AccessResearch ArticlePDF/EPUBCardiac Dysfunction and Arrhythmias 3 Months After Hospitalization for COVID‐19 Charlotte B. Ingul, Jostein Grimsmo, Albulena Mecinaj, Divna Trebinjac, Magnus Berger Nossen, Simon Andrup, Bjørnar Grenne, Håvard Dalen, Gunnar Einvik, Knut Stavem, Turid Follestad, Tony Josefsen, Torbjørn Omland and Torstein Jensen Charlotte B. IngulCharlotte B. Ingul * Correspondence to: Charlotte B. Ingul, MD, PhD, Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Postboks 8905, 7491 Trondheim, Norway. E‐mail: E-mail Address: [email protected] https://orcid.org/0000-0002-3251-9494 Department of Circulation and Medical Imaging, , Norwegian University of Science and Technology, , Trondheim, , Norway The National Association for Heart, Lung diseases Hospital Gardermoen, , Jessheim, , Norway , Jostein GrimsmoJostein Grimsmo https://orcid.org/0000-0003-2009-4764 The National Association for Heart, Lung diseases Hospital Gardermoen, , Jessheim, , Norway , Albulena MecinajAlbulena Mecinaj Department of Cardiology, , Division of Medicine, , Akershus University Hospital, , Lørenskog, , Norway , Divna TrebinjacDivna Trebinjac https://orcid.org/0000-0003-3962-231X The National Association for Heart, Lung diseases Hospital Gardermoen, , Jessheim, , Norway , Magnus Berger NossenMagnus Berger Nossen Department of Cardiology, , Østfold Hospital Trust Kalnes, , Grålum, , Norway , Simon AndrupSimon Andrup Department of Cardiology, , Østfold Hospital Trust Kalnes, , Grålum, , Norway , Bjørnar GrenneBjørnar Grenne Department of Circulation and Medical Imaging, , Norwegian University of Science and Technology, , Trondheim, , Norway Clinic of Cardiology, , St. Olavs University Hospital, , Trondheim, , Norway , Håvard DalenHåvard Dalen Department of Circulation and Medical Imaging, , Norwegian University of Science and Technology, , Trondheim, , Norway Clinic of Cardiology, , St. Olavs University Hospital, , Trondheim, , Norway Department of Medicine, , Levanger Hospital, , Nord‐Trøndelag Hospital Trust, , Levanger, , Norway , Gunnar EinvikGunnar Einvik Pulmonary Department, , Akershus University Hospital, , Lørenskog, , Norway Institute for Clinical Medicine, , University of Oslo, , Norway , Knut StavemKnut Stavem https://orcid.org/0000-0003-4512-8000 Pulmonary Department, , Akershus University Hospital, , Lørenskog, , Norway Institute for Clinical Medicine, , University of Oslo, , Norway Health Services Research Unit, , Akershus University Hospital, , Lørenskog, , Norway , Turid FollestadTurid Follestad Department of Clinical and Molecular Medicine, , Norwegian University of Science and Technology, , Trondheim, , Norway , Tony JosefsenTony Josefsen Department of Cardiology, , Østfold Hospital Trust Kalnes, , Grålum, , Norway , Torbjørn OmlandTorbjørn Omland https://orcid.org/0000-0002-6452-0369 Department of Cardiology, , Division of Medicine, , Akershus University Hospital, , Lørenskog, , Norway Institute for Clinical Medicine, , University of Oslo, , Norway and Torstein JensenTorstein Jensen Department of Cardiology, , Oslo University Hospital Ullevål, , Oslo, , Norway Originally published20 Jan 2022https://doi.org/10.1161/JAHA.121.023473Journal of the American Heart Association. 2022;11:e023473Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: January 20, 2022: Ahead of Print AbstractBackgroundThe extent of cardiac dysfunction post‐COVID‐19 varies, and there is a lack of data on arrhythmic burden.Methods and ResultsThis was a combined multicenter prospective cohort study and cross‐sectional case‐control study. Cardiac function assessed by echocardiography in patients with COVID‐19 3 to 4 months after hospital discharge was compared with matched controls. The 24‐hour ECGs were recorded in patients with COVID‐19. A total of 204 patients with COVID‐19 consented to participate (mean age, 58.5 years; 44% women), and 204 controls were included (mean age, 58.4 years; 44% women). Patients with COVID‐19 had worse right ventricle free wall longitudinal strain (adjusted estimated mean difference, 1.5 percentage points; 95% CI, −2.6 to −0.5; P=0.005) and lower tricuspid annular plane systolic excursion (−0.10 cm; 95% CI, −0.14 to −0.05; P<0.001) and cardiac index (−0.26 L/min per m2; 95% CI, −0.40 to −0.12; P 8 hours with a discharge diagnosis of COVID‐19 or viral pneumonia combined with a positive severe acute respiratory syndrome coronavirus 2 polymerase chain reaction test, were considered eligible. Exclusion criteria included living outside the hospitals' catchment areas, inability to provide informed consent, or participation in the World Health Organization Solidarity trial.A total of 388 patients were eligible for PROLUN, and of these, 69 patients did not respond to the invitation, and 55 patients declined participation.This substudy included patients from 5 hospitals because 1 hospital (n=28) lacked the resources to perform echocardiography. In total, 236 consenting patients in PROLUN were invited to this substudy (Figure S1). Informed consent was obtained by returning a written signed consent form or through a secure digital consent form (Services for Sensitive Data, services for sensitive data [TSD], University of Oslo). The study was approved by the Regional Ethics Committee for South‐Eastern Norway (no. 125384) and by data protection officers at each participating center and registered with the ClinicalTrials.gov database (NCT04535154).Clinical Data CollectionBaseline demographic characteristics (sex, age), comorbidities, and data from the COVID‐19 hospital admissions were obtained from the electronic patient records. World Health Organization Ordinal Scale for Clinical Improvement was used to score the severity of the COVID‐19.14 Height, weight, body mass index (BMI), current smoking status, and history of hypertension were collected by interview at follow‐up after 3 months.Controls and MatchingThe controls comprised participants from HUNT4 (the fourth wave of the Trøndelag Health Study; 2017–2019), a Norwegian population‐based cohort. The HUNT4 echocardiography study collected data from a random sample and included 2448 participants.15 A total of 204 patients with COVID‐19 were matched with 204 controls from the HUNT4 echocardiography study on age, sex, BMI, systolic blood pressure, and comorbidity (previous myocardial infarction, congestive heart disease, chronic obstructive pulmonary disease, diabetes; Figure S1). A mixed model was used to match the controls with the patients with COVID‐19. Sex and comorbidity were matched individually and age, BMI, and systolic blood pressure on a group level. From the total population of 2448 HUNT4 echocardiography study participants, the control population was matched according to mean (SD) for age, BMI, and systolic blood pressure.Echocardiography in Patients With COVID‐19A 2‐dimensional transthoracic echocardiography of patients in the left lateral decubitus position was performed by 4 experienced operators according to standard methods16 using commercially available ultrasound systems (Vivid E 95, GE Horten, Norway). Motion‐mode was used in the apical 4‐chamber view to measure tricuspid annular plane systolic excursion (TAPSE) and mitral annular plane systolic excursion. Pulsed tissue Doppler S', e', and A' velocities were obtained from the septal and lateral walls of the mitral annulus. Left atrial volume and end‐diastolic volume (EDV) were measured in the apical 4‐chamber and 2‐chamber views and indexed to body surface area (EDV index). LV ejection fraction (EF) was calculated using Simpson's biplane method. Mitral valve E/A ratio, diastolic dysfunction, and E/e' were assessed according to the international recommendations from 201617 (Data S1). Systolic pulmonary artery pressure was calculated from the peak tricuspid regurgitant velocity and adding this to an estimate of right atrial pressure. LV global longitudinal strain (LV GLS) and RV free wall longitudinal strain (RVLS) were quantified by semiautomatic 2‐dimensional speckle tracking software Automated functional imaging (AFI) based on the apical 4‐chamber, 2‐chamber, and long‐axis views and the RV focus view.18 Data were stored digitally for offline analysis (GE EchoPAC PC SWO versions 203 and 204). Analyses were performed blinded, and only study‐specific patient identifications were known. The LHL Hospital Gardermoen served as the echocardiography core laboratory.Echocardiography HUNT4 Reference PopulationEchocardiographic recordings were performed according to standard operating procedures aligned with the current recommendations, which were the same used for the COVID‐19 group.16A total of 2 sonographers performed the echocardiography. Of these sonographers, 1 experienced in strain analyses performed offline analysis using the AFI package in EchoPAC SWO (203 version). The RV strain analyses were performed offline as for the patients using EchoPAC 204 version by a cardiologist experienced in strain analyses. The same ultrasound systems were used as for the patients with COVID‐19.Ambulatory 24‐Hour Electrocardiography RegistrationA 24‐hour ECG was obtained using Schiller Medilog FD12 Plus (Germany) and Philips DigiTrak XT (Germany) in the patients with COVID‐19, but not in controls. Schiller Medilog Darwin 2 (Germany) and Philips Holter 2010 Plus (Germany) with Zymed Algorithm (Release 3.0.1.1. 2015) were used for the analysis. Clinically significant arrhythmias were defined as ventricular tachycardia (nonsustained or sustained), premature ventricular contractions (PVCs) >200/24 hours or coupled PVCs, atrial fibrillation/flutter, second‐degree atrioventricular block type 2, complete atrioventricular block, sinoatrial block >3 seconds, premature atrioventricular nodal beats in bigeminy, supraventricular tachycardia >30 seconds, and extreme sinus bradycardia with <30 beats/min.BiochemistryNonfasting venous blood samples were collected during the hospital stay and at the 3‐month follow‐up to measure NT‐proBNP (N‐terminal pro–brain natriuretic peptide) and hs‐cTnT (high‐sensitive cardiac troponin T) (Roche Diagnostics, Rotkreuz, Switzerland).Assessment of DyspneaThe modified Medical Research Council (dyspnea scale is a self‐rating tool to measure the degree of disability that breathlessness poses on day‐to‐day activities on a scale from 0 (no dyspnea) to 4 (maximum dyspnea).19Assessment of FatigueFatigue was assessed using the Chalder Fatigue Scale.20 A bimodal scoring algorithm was used, where each item response was dichotomized 0 (0–1) or 1 (2–3) and summed to a scale of 0 to 11. Conventionally, fatigue case status (fatigued versus nonfatigued) was defined using this scale with ≥4 denoted as fatigued.20, 21Outcome MeasuresThe primary outcome measures were RVLS, LV GLS, and arrhythmias. The secondary outcome measures were RV dimension, TAPSE, systolic pulmonary artery pressure, pulmonary vein flow, mitral annular plane systolic excursion, S', EF, EDV index, cardiac index, mitral valve E/A ratio, e´, E/e', and diastolic dysfunction.Data StorageAll collected data were stored in Services for Sensitive Data (TSD, University of Oslo, Norway), designed for storing and postprocessing sensitive data in compliance with the Norwegian Personal Data Act22 and Health Research Act.23Statistical AnalysisData are summarized as mean (SD), median (25th–75th percentiles), or number (percentage), as appropriate. Echocardiography variables were compared between the patients with COVID‐19 and the controls using multiple regression analysis, adjusting for age, sex, BMI, resting systolic blood pressure, chronic obstructive pulmonary disease, diabetes, previous heart failure, and previous myocardial infarction. Because of the partly individual matching of controls, linear mixed models were first fitted to account for potential within‐pair correlations. However, these correlations turned out to be very small, and thus ordinary regression models were used. The normal distribution for residuals from linear regression models was assessed by the Anderson‐Darling test and visual inspection of normal QQ‐plots. Generalized linear regression models using a gamma distribution with identity link were used when such models improved residual model fit compared with linear models. Logistic regression was used for dichotomized diastolic dysfunction. Similar models were used to compare the echocardiography variables between non‐ICU and ICU patients with COVID‐19, patients with or without dyspnea, and with or without fatigue, adjusting for age and sex. Correlations between variables were assessed using the Spearman correlation coefficient (ρ).Normal values from similar populations before the pandemic were used to compare the echocardiographic variables for the patients with COVID‐19 and controls using z scores, that is, the z score indicates the difference from the mean of the age‐specific and sex‐specific stratums of the reference population reported in number of SDs. Where possible, we used age‐specific and sex‐specific reference values from the Norwegian HUNT4 study, a large population‐based cohort.24, 25Other large population‐based cohorts were used in addition.16, 26, 27The z scores for the patients with COVID‐19 and the matched controls were calculated from normal values for means and SDs, specified by age group ( 60 years) and sex. The z scores are summarized as medians with 2.5 and 97.5 percentiles.All statistical analyses were performed using R version 3.4.4 (R Foundation for Statistical Computing, Vienna, Austria) or Stata version 16.1 (StataCorp., College Station, TX). To give some protection against false‐positive results attributed to multiple testing, P values <0.01 were considered statistically significant.ResultsParticipant CharacteristicsIn total, 204 consented to participate in the substudy. The examinations were conducted a median of 102 days (range, 70–172 days) after discharge from the hospital. Of the patients, 3 did not undergo a 24‐hour ECG and were excluded from this analysis. Baseline demographics and data from the hospital stay, laboratory measures, dyspnea rating, fatigue score, and World Health Organization ordinal scale are presented in Table 1.Table 1. Baseline Demographics, Data From Hospital, Risk Factors, and Comorbidity (n=204)No. (%)Mean (SD) (range)Median (25th–75th percentiles)Age at hospital discharge, y58.5 (13.6) (30–83)Laboratoryhs‐cTn peak, hospitalization, ng L−1169 (83)10 (6–17)hs‐cTn at 3 mo, ng L−1169 (83)8 (5–11)NT‐proBNP peak, hospitalization, ng L−1174 (85)186 (70–526)NT‐proBNP at 3 mo, ng L−1174 (85)58 (41–120)CRP peak, hospitalization, mg L−1201 (99)112 (39–190)ICU stay41 (20)Intubated and invasively ventilated25 (12)No. of days in ICU4110.7 (2–22)No. of days on ventilator2411.9 (5–18)Length of stay in hospital, d20310.2 (1–55)mMRC dyspnea scale163 (80)077 (47)150 (31)226 (16)38 (5)42 (1)mMRC 0 vs 1–486 (53)Chalder Fatigue Scale163 (80) 30 kg/m2) was found in 70 patients (34%). In total, 32/236 (14%) of the patients invited from the main study did not participate in our substudy. The nonparticipants were older (61.3 years), and there were more men (73%) compared with the participants. There was no difference in comorbidity, World Health Organization severity scale, or dyspnea, but fewer nonparticipants had fatigue (41%).Cardiac Function and MorphologyCardiac function and morphology are detailed in Table 3.Table 3. Summary Statistics and Estimated Mean Differences Between COVID‐19 and Reference Population From Multiple Regression for the Echocardiographic VariablesControlCOVID‐19COVID‐19 vs controlNo.Mean (SD) or n (%)No.Mean (SD) or n (%)No.Estimate* (95% CI)P valueLV systolic functionLV GLS, %171−17.8 (2.6)187−18.5 (2.8)338−0.8 (−1.3 to −0.2)0.008Ejection fraction, %19458.4 (7.2)19656.5 (6.7)368−1.7 (−3.1 to −0.3)0.015MAPSE, cm2021.5 (0.3)2011.4 (0.2)382−0.10 (−0.14 to −0.05)<0.001S', cm/s1998.3 (1.8)1838.0 (1.6)361−2.4 (−5.6 to 0.8)0.135Cardiac index, L/min per m21962.9 (0.8)1932.6 (0.7)369−0.26 (−0.40 to −0.12)<0.001LV volumesEDV index, mL/m219458.7 (15.9)18649.5 (13.8)360−8.8 (−11.4 to −6.1)<0.001LV diastolic functionMV E/A ratio1911.1 (0.4)2001.1 (0.4)3710.01 (−0.06 to 0.07)0.860e', cm/s1989.1 (2.7)1938.4 (2.4)370−6.0 (−9.8 to −2.2)0.002E/e'1948.3 (2.3)1888.4 (3.1)362−0.03 (−0.46 to 0.40)0.886RV function and dimensionsRV free wall strain, %168−26.2 (4.7)165−24.6 (5.0)3151.5 (0.5 to 2.6)0.005RVD, cm1363.8 (0.7)1963.9 (0.6)3140.11 (−0.03 to 0.25)0.111TAPSE, cm1872.5 (0.5)1992.4 (0.5)366−0.16 (−0.27 to −0.06)0.002SPAP, mm Hg9628 (6.8)15723.8 (8.7)239−3.9 (−6.1 to −1.8)<0.001Left atrial size and PV flowLA volume index, mL/m219833.1 (14.3)19027.1 (8.3)368−5.0 (−7.0 to −3.1) 3 seconds was only observed in 1 patient.Table 5. Cardiac Arrhythmias (n=201)No.PercentageNonsustained ventricular tachycardia105.0Premature ventricular contractions >200/24 h3718Atrial fibrillation/flutter*74Second degree or complete atrioventricular block00Extreme sinus bradycardia ( 3 s10Premature atrioventricular‐nodal beats in bigeminy00Supraventricular tachycardia >30 s32John Wiley & Sons, Ltdbpm indicates beats per minute.*Paroxysmal, persisting, or chronic.Cardiac Function, Arrhythmias, and Correlations With Biochemical MarkersP