Clinical and electrocardiographic characteristics at admission of COVID-19/SARS-CoV2 pneumonia infection

A COVID-19 specific multiparametric and ECG-based score for the prediction of in-hospital mortality: ELCOVID score

We aimed to develop and validate a COVID-19 specific scoring system, also including some ECG features, to predict all-cause in-hospital mortality at admission. Patients were retrieved from the ELCOVID study (ClinicalTrials.gov identifier: NCT04367129), a prospective, multicenter Italian study enrolling COVID-19 patients between May to September 2020. For the model validation, we randomly selected two-thirds of participants to create a derivation dataset and we used the remaining one-third of participants as the validation set. Over the study period, 1014 hospitalized COVID-19 patients (mean age 74 years, 61% males) met the inclusion criteria and were included in this analysis. During a median follow-up of 12 (IQR 7-22) days, 359 (35%) patients died. Age (HR 2.25 [95%CI 1.72-2.94], p < 0.001), delirium (HR 2.03 [2.14-3.61], p = 0.012), platelets (HR 0.91 [0.83-0.98], p = 0.018), D-dimer level (HR 1.18 [1.01-1.31], p = 0.002), signs of right ventricular strain (RVS) (HR 1.47 [1.02-2.13], p = 0.039) and ECG signs of previous myocardial necrosis (HR 2.28 [1.23-4.21], p = 0.009) were independently associated to in-hospital all-cause mortality. The derived risk-scoring system, namely EL COVID score, showed a moderate discriminatory capacity and good calibration. A cut-off score of ≥ 4 had a sensitivity of 78.4% and 65.2% specificity in predicting all-cause in-hospital mortality. ELCOVID score represents a valid, reliable, sensitive, and inexpensive scoring system that can be used for the prognostication of COVID-19 patients at admission and may allow the earlier identification of patients having a higher mortality risk who may be benefit from more aggressive treatments and closer monitoring.

Prevalence of pre-existing peripheral artery disease in COVID-19 patients and relative mortality risk: Systematic review and meta-analysis

INTRODUCTION

This study aims to assess prevalence and prognostic implications of pre-existing peripheral artery disease (PAD) in patients infected by the SARS-CoV-2 by means of a systematic review and meta-analysis.

MATERIAL AND METHODS

We searched MEDLINE and Scopus to locate all the articles published up to 10 December 2021, reporting data on pre-existing PAD among COVID-19 survivors (S) and non survivors (NS). The pooled prevalence of pre-existing PAD in COVID-19 patients was calculated using a random effects model and presenting the related 95% confidence interval (CI), while the mortality risk was estimated using the Mantel-Haenszel random effects models with odds ratio (OR) and related 95% CI. Statistical heterogeneity was measured using the Higgins I2 statistic.

RESULTS

Eight investigations, enrolling 13,776 COVID-19 patients (mean age: 67.1 years, 3.863 males), met the inclusion criteria and were included in the final analysis. The pooled prevalence of pre-existing PAD was 5.7% of cases (95% CI: 3.8-8.4%, p < 0.0001), with high heterogeneity (I2 = 84.5%), which was directly correlated with age (p < 0.0001), previous hypertension (p = 0.003), and dyslipidaemia (p = 0.02) as demonstrated by the meta-regression. Moreover, pre-existing PAD was significantly associated with higher risk of short-term death in patients with SARS-CoV-2 infection (OR: 2.78, 95% CI: 2.37-3.27, p < 0.0001 I2 = 0%); the sensitivity analysis confirmed yielded results.

CONCLUSIONS

Pre-existing PAD represents a comorbidity in about 1 out of 6 COVID-19 patients, but it is associated with a twofold higher risk of short-term mortality.

The effect of COVID-19 on the thromboembolic outcomes in atrial fibrillation patients in the long run

BACKGROUND

While there has been a wealth of reports concerning the acute effects of the coronavirus disease 2019 (COVID-19), further information is needed to see how things unfold in the long run. This research aimed to ascertain whether the COVID-19 pandemic has increased the probability of thromboembolic events in atrial fibrillation (AF) patients.

METHODS

In this retrospective study, we scanned 952 AF patients and classified 643 eligible ones per their history of catching COVID-19. Two hundred thirty-nine of 643 patients had a history of COVID-19 (Group 1), and 404 did not (Group 2). We then compared two years of thromboembolic events between the groups.

RESULTS

Composite thromboembolic outcomes were seen in 76 (11.8%) patients. Of those, 32 (13.4%) were in Group 1, and 44 (10.8%) were in Group 2 (p = .03). 10 of 32 patients (31%) in Group 1 and 11 of 44 (25%) in Group 2 died because of thromboembolic events (p = .02). Histories of diabetes mellitus, chronic obstructive pulmonary disease, and COVID-19 independently predicted thromboembolic events in AF patients.

CONCLUSIONS

Having caught COVID-19 is likely to be associated with increased long-term thromboembolic outcomes in AF patients. Albeit the study design does not permit us to infer causality, our results question the necessity of more intensive anticoagulant therapy and closer follow-up in AF patients with past COVID-19.

Long-Term Mortality after New-Onset Atrial Fibrillation in COVID-19

Background: Atrial fibrillation (AF) has been described as a common cardiovascular manifestation in patients suffering from coronavirus disease 2019 (COVID-19) and has been suggested to be a potential risk factor for a poor clinical outcome. Methods: In this observational study, all patients hospitalized due to COVID-19 in 2020 in the Cantonal Hospital of Baden were included. We assessed clinical characteristics, in-hospital outcomes as well as long-term outcomes with a mean follow-up time of 278 (±90) days. Results: Amongst 646 patients diagnosed with COVID-19 (59% male, median age: 70 (IQR: 59-80)) in 2020, a total of 177 (27.4%) patients were transferred to the intermediate/intensive care unit (IMC/ICU), and 76 (11.8%) were invasively ventilated during their hospitalization. Ninety patients (13.9%) died. A total of 116 patients (18%) showed AF on admission of which 34 (29%) had new-onset AF. Patients with COVID-19 and newly diagnosed AF were more likely to require invasive ventilation (OR: 3.5; p = 0.01) but did not encounter an increased in-hospital mortality. Moreover, AF neither increased long-term mortality nor the number of rehospitalizations during follow-up after adjusting for confounders. Conclusions: In patients suffering from COVID-19, the new-onset of AF on admission was associated with an increased risk of invasive ventilation and transfer to the IMC/ICU but did not affect in-hospital or long-term mortality.

Five waves of COVID-19 pandemic in Italy: results of a national survey evaluating the impact on activities related to arrhythmias, pacing, and electrophysiology promoted by AIAC (Italian Association of Arrhythmology and Cardiac Pacing)

BACKGROUND

The subsequent waves of the COVID-19 pandemic in Italy had a major impact on cardiac care.

METHODS

A survey to evaluate the dynamic changes in arrhythmia care during the first five waves of COVID-19 in Italy (first: March-May 2020; second: October 2020-January 2021; third: February-May 2021; fourth: June-October 2021; fifth: November 2021-February 2022) was launched.

RESULTS

A total of 127 physicians from arrhythmia centers (34% of Italian centers) took part in the survey. As compared to 2019, a reduction in 40% of elective pacemaker (PM), defibrillators (ICD), and cardiac resynchronization devices (CRT) implantations, with a 70% reduction for ablations, was reported during the first wave, with a progressive and gradual return to pre-pandemic volumes, generally during the third-fourth waves, slower for ablations. For emergency procedures (PM, ICD, CRT, and ablations), recovery from the initial 10% decline occurred in most cases during the second wave, with some variability. However, acute care for atrial fibrillation, electrical cardioversions, and evaluations for syncope showed a prolonged reduction of activity. The number of patients with devices which started remote monitoring increased by 40% during the first wave, but then the adoption of remote monitoring declined.

CONCLUSIONS

The dramatic and profound derangement in arrhythmia management that characterized the first wave of the COVID-19 pandemic was followed by a progressive return to the volume of activities of the pre-pandemic periods, even if with different temporal dynamics and some heterogeneity. Remote monitoring was largely implemented during the first wave, but full implementation is needed.

Electrocardiogram QRS Complex Duration as a Predictor of Hospital Prognosis in Patients With COVID-19

Aim      To determine the effect of major electrocardiographic (ECG) parameters on the prognosis of patients with COVID-19.Material and methods  One of systemic manifestations of COVID-19 is heart injury. ECG is the most simple and available method for diagnosing the heart injury, which influences the therapeutic approach. This study included 174 hospitalized patients with COVID-19. Major ECG parameters recorded on admission and their changes before the discharge from the hospital or death of the patient, were analyzed, and the effect of each parameter on the in-hospital prognosis was determined. Results were compared with the left ventricular ejection fraction (LV EF), laboratory data, and results of multispiral computed tomography (MSCT) of the lungs.Results ECG data differed on admission and their changes differed for deceased and discharged patients. Of special interest was the effect of the QRS complex duration at baseline and at the end of treatment on the in-hospital survival and mortality rate. The Cox regression analysis showed that the QRS complex duration (relative risk (RR) 2.07, 95% confidence interval (CI): 1.17-3.66; р=0.01), MSCT data (RR, 1.54; 95 % CI: 1.14-2.092; р=0.005), and glomerular filtration rate (GFR) (RR, 0.98; 95 % CI: 0.96-0.99; р=0.001) had the highest predictive significance. In further comparison of these three indexes, the QRS duration and GFR retained their predictive significance, and a ROC analysis showed that the cut-off QRS complex duration was 125 ms (р=0.001). Patients who developed left bundle branch block (LBBB) in the course of disease also had an unfavorable prognosis compared to other intraventricular conduction disorders (р=0.038). The presence of LBBB was associated with reduced LV EF (р=0.0078). The presence of atrial fibrillation (AF) significantly predetermines a worse outcome both at the start (р=0.011) and at the end of observation (р=0.034). A higher mortality was observed for the group of deceased patients with ST segment deviations, ST elevation (р=0.0059) and ST depression (р=0.028).Conclusion      Thus, the QTc interval elongation, LBBB that developed during the treatment, AF, and increased QRS complex duration are the indicators that determine the in-hospital prognosis of patients with COVID-19. The strongest electrocardiographic predictor for an unfavorable prognosis was the QRS complex duration that allowed stratification of patients to groups of risk.

Admissions to the Emergency Department Due to Atrial Fibrillation/Atrial Flutter Incidents during the Third Wave of COVID-19 Pandemic

(1) Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection increases the risk of atrial fibrillation/flutter (AF/AFL) incident. The study aimed to present the characteristics of admissions to the emergency department (ED) due to AF/AFL incidents during the third COVID-19 pandemic wave. (2) Methods: A retrospective analysis of the medical records of the ED patients: 8399 during 3 months of the second and 11,144 during the 3 months of the third pandemic wave. (3) Results: SARS-CoV-2 positive patients there were 295 (3.5%) during the second wave and 692 (6.2%) during the third wave (p < 0.001). Among patients with SARS-CoV-2 infection, there were 44 (14.9%) patients with known AF/AFL during the second wave and 75 (10.8%) during the third wave, respectively (0.07). There were 116 visits with a diagnosis of AF/AFL incident during the third wave (study group) and 76 visits during the second wave (control group). The SARS-CoV-2 test was positive in 11 (9.5%) visits in the study group and in 1 (1.3%) visit in the control group p = 0.047. During the third wave, the patients with AF/AFL incidents with positive tests were older and more often had new-onset AF/AFL than those with negative tests: 76.3 (13.2) years vs. 71.8 (12.6) years; and 4 (36.4%) patients vs. 7 (7.6%) patients, respectively. (5) Conclusions: During the third pandemic wave, the number of patients with SARS-CoV-2 infection increased in comparison to the second wave. Additionally, among patients with AF/AFL incidents, the percentage of SARS-CoV-2-positive patients increased. During the third wave, the patients with positive tests and AF/AFL incident were older and more often had new-onset AF/AFL than those with AF/AFL incident and negative test which indicate the arrhythmogenic effect at the onset of the disease, especially in the older population.

Electrocardiogram abnormalities and prognosis in COVID-19

Background

COVID-19 is a major pandemic with potential cardiovascular complications. Few studies have focused on electrocardiogram (ECG) modifications in COVID-19 patients.

Method and results

We reviewed from our database all patients referred to our hospital for COVID-19 between January 1st, 2020, and December 31st, 2020: 669 patients were included and 98 patients died from COVID-19 (14.6%). We systematically analyzed ECG at admission and during hospitalization if available. ECG was abnormal at admission in 478 patients (71.4%) and was more frequently abnormal in patients who did not survive (88.8 vs. 68.5%, p < 0.001). The most common ECG abnormalities associated with death were left anterior fascicular block (39.8 vs. 20.0% among alive patients, p < 0.001), left and right bundle branch blocks (p = 0.002 and p = 0.02, respectively), S1Q3 pattern (14.3 vs. 6.0%, p = 0.006). In multivariate analysis, at admission, the presence of left bundle branch block remained statistically related to death [OR = 3.82, 95% confidence interval (CI): 1.52–9.28, p < 0.01], as well as S1Q3 pattern (OR = 3.17, 95% CI: 1.38–7.03, p < 0.01) and repolarization abnormalities (OR = 2.41, 95% CI: 1.40–4.14, p < 0.01).

On ECG performed during hospitalization, the occurrence of new repolarization abnormality was significantly related to death (OR = 2.72, 95% CI: 1.14–6.54, p = 0.02), as well as a new S1Q3 pattern (OR = 13.23, 95% CI: 1.49–286.56, p = 0.03) and new supraventricular arrhythmia (OR = 3.8, 95% CI: 1.11–13.35, p = 0.03).

Conclusion

The presence of abnormal ECG during COVID-19 is frequent. Physicians should be aware of the usefulness of ECG for risk stratification during COVID-19.

Preexisting coronary artery disease among coronavirus disease 2019 patients: a systematic review and meta-analysis

AIMS

The prevalence and prognostic implications of coronary artery disease (CAD) in patients infected by the novel coronavirus 2019 (COVID-19) disease remain unclear.

METHODS

We conducted a systematic review and meta-analysis to investigate the prevalence and mortality risk in COVID-19 patients with preexisting CAD. We searched Medline and Scopus to locate all articles published up to December 8, 2021, reporting data of COVID-19 survivors and nonsurvivors with preexisting CAD. Data were pooled using the Mantel-Haenszel random effects models with odds ratio (OR) as the effect measure with the related 95% confidence interval (CI).

RESULTS

Thirty-eight studies including 27 435 patients (mean age 61.5 and 70.9 years) were analysed. The pooled prevalence of preexisting CAD was 12.6% (95% CI: 11.2-16.5%, I2 : 95.6%), and resulted as higher in intensive care unit patients (17.5%, 95% CI: 11.9-25.1, I2 : 88.4%) and in European cohorts (13.1%, 95% CI: 7.8-21.6%, P  < 0.001, I2 : 98.4%). COVID-19 patients with preexisting CAD had a two-fold risk of short-term mortality (OR 2.61, 95% CI 2.10-3.24, P  < 0.001, I2  = 73.6%); this risk was higher among Asian cohorts (OR: 2.66, 95% CI: 1.79-3.90, P  < 0.001, I2 : 77.3%) compared with European (OR: 2.44, 95% CI: 1.90-3.14, P  < 0.001, I2 : 56.9%) and American (OR: 1.86, 95% CI: 1.41-2.44, P  < 0.001, I2 : 0%) populations. The association between CAD and poor short-term prognosis was influenced by age, prevalence of hypertension (HT), DM and CKD.

CONCLUSIONS

Preexisting CAD is present in approximately 1 in 10 patients hospitalized for COVID-19 and significantly associated with an increased risk of short-term mortality, which is influenced by age, HT, DM and CKD.

Electrocardiographic Features and Outcome: Correlations in 124 Hospitalized Patients With COVID-19 and Cardiovascular Events

OBJECTIVES

Electrocardiographic (ECG) changes have been associated with coronavirus disease 2019 (COVID-19) severity. However, the progression of ECG findings in patients with COVID-19 has not been studied. The purpose of this study was to describe ECG features at different stages of COVID-19 cardiovascular (CV) events and to examine the effects of specific ECG parameters and cardiac-related biomarkers on clinical outcomes in COVID-19.

DESIGN

Retrospective, cohort study.

SETTING

Major tertiary-care medical centers and community hospitals in Louisville, KY.

PARTICIPANTS

A total of 124 patients with COVID-19 and CV events during hospitalization.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Twelve-lead ECG parameters, biomarkers of cardiac injuries, and clinical outcomes were analyzed with Spearman correlation coefficients and Kruskal-Wallis 1-way analysis of variance. Atrial fibrillation/atrial flutter was more frequent on the ECG obtained at the time of the CV event when compared with admission ECG (9.5% v 26.9%; p = 0.007). Sinus tachycardia was higher in the last available hospital ECG than the CV event ECG (37.5% v 20.4%; p = 0.031). Admission ECG-corrected QT interval was significantly associated with admission troponin levels (R = 0.52; p < 0.001). The last available hospital ECG showed nonsurvivors had longer QRS duration than survivors (114.6 v 91.2 ms; p = 0.026), and higher heart rate was associated with longer intensive care unit length of stay (Spearman ρ = 0.339; p = 0.032).

CONCLUSIONS

In hospitalized patients with COVID-19 and CV events, ECGs at various stages of COVID-19 hospitalization showed significantly different features with dissimilar clinical outcome correlations.

Myocardial Ischemia in Patients with COVID-19 Infection: Between Pathophysiological Mechanisms and Electrocardiographic Findings

Given the possible pathophysiological links between myocardial ischemia and SARS-CoV-2 infection, several studies have focused attention on acute coronary syndromes in order to improve patients’ morbidity and mortality. Understanding the pathophysiological aspects of myocardial ischemia in patients infected with SARS-CoV-2 can open a broad perspective on the proper management for each patient. The electrocardiogram (ECG) remains the easiest assessment of cardiac involvement in COVID-19 patients, due to its non-invasive profile, accessibility, low cost, and lack of radiation. The ECG changes provide insight into the patient’s prognosis, indicating either the worsening of an underlying cardiac illnesses or the acute direct injury by the virus. This indicates that the ECG is an important prognostic tool that can affect the outcome of COVID-19 patients, which important to correlate its aspects with the clinical characteristics and patient’s medical history. The ECG changes in myocardial ischemia include a broad spectrum in patients with COVID-19 with different cases reported of ST-segment elevation, ST-segment depression, and T wave inversion, which are associated with severe COVID-19 disease.

Effect of Coronary Artery Disease on COVID-19-Prognosis and Risk Assessment: A Systematic Review and Meta-Analysis

Coronary artery disease (CAD) is the leading cause of death worldwide. Patients with pre-existing CAD were shown to have a more severe course of COVID-19, but this association has not been clarified. We performed a meta-analysis to determine the association between CAD and COVID-19 outcomes. We searched Scopus, Medline (PubMed), Web of Science, Embase, and Cochrane databases up to 2 November 2021. There were 62 studies with a total population of 49,286 patients included in the meta-analysis. CAD occurrence in survivor vs. non-survivor groups varied and amounted to 9.2% vs. 22.9%, respectively (OR = 0.33; 95%CI: 0.29 to 0.39; I² = 70%; p < 0.001). CAD was also associated with increased severity of COVID-19 disease and was (10.8% vs. 5.6%, respectively, for severe vs. non-severe groups (OR = 2.28; 95%CI: 1.59 to 3.27; I² = 72%; p < 0.001). The role of history of CAD in mortality and severe condition in COVID-19 presents itself as prominent-although a risk of bias in retrospective trials needs to be assessed, in case of our meta-analysis the statistically significant results when it comes to higher mortality among patients with CAD compared to non-CAD patients, a more severe condition observed in patients with CAD, and a visibly more frequent admission to intensive care unit in patients with CAD, it seems that an incidence of cardiovascular events plays a role in COVID-19 prognosis.

ECG-BiCoNet: An ECG-based pipeline for COVID-19 diagnosis using Bi-Layers of deep features integration

The accurate and speedy detection of COVID-19 is essential to avert the fast propagation of the virus, alleviate lockdown constraints and diminish the burden on health organizations. Currently, the methods used to diagnose COVID-19 have several limitations, thus new techniques need to be investigated to improve the diagnosis and overcome these limitations. Taking into consideration the great benefits of electrocardiogram (ECG) applications, this paper proposes a new pipeline called ECG-BiCoNet to investigate the potential of using ECG data for diagnosing COVID-19. ECG-BiCoNet employs five deep learning models of distinct structural design. ECG-BiCoNet extracts two levels of features from two different layers of each deep learning technique. Features mined from higher layers are fused using discrete wavelet transform and then integrated with lower-layers features. Afterward, a feature selection approach is utilized. Finally, an ensemble classification system is built to merge predictions of three machine learning classifiers. ECG-BiCoNet accomplishes two classification categories, binary and multiclass. The results of ECG-BiCoNet present a promising COVID-19 performance with an accuracy of 98.8% and 91.73% for binary and multiclass classification categories. These results verify that ECG data may be used to diagnose COVID-19 which can help clinicians in the automatic diagnosis and overcome limitations of manual diagnosis.

The role of admission electrocardiogram in predicting outcome in patients hospitalized for COVID-19

BACKGROUND

Abnormal electrocardiogram (ECG) has been associated with poor outcome in patients hospitalized for COVID-19. However, the independent association between admission ECG and the risk of a poor outcome remains to be established. Our aim was to determine if abnormal admission ECG predicts treatment at intensive care unit or in-hospital death within 30 days in patients hospitalized for COVID-19.

METHODS

We analyzed the propensity weighted association between abnormal admission ECG and outcome in patients hospitalized for COVID-19 (March to May 2020). All adult patients hospitalized for COVID-19 at the three centers of Sahlgrenska University Hospital (Gothenburg, Sweden) were eligible for inclusion (N = 439). Patients with available admission ECG within six hours from admission were included.

RESULTS

238 patients (age 62 ± 16 years, 74% male) were included. 103 patients had normal ECG and 135 patients had abnormal ECG. 99 patients were admitted to intensive care unit or died in-hospital within 30 days. Abnormal ECG was associated with increased risk of the outcome (odds ratio 2.11 [95% confidence interval 1.21-3.66]).

CONCLUSIONS

Abnormal admission ECG was associated with increased risk of treatment at intensive care unit or in-hospital death within 30 days; and could be considered a high-risk criterion in patients hospitalized for COVID-19.

Outcomes of atrial fibrillation in patients with COVID-19 pneumonia: A systematic review and meta-analysis

BACKGROUND

Recently, emerging evidence has suggested that atrial fibrillation (AF) has an epidemiological correlation with coronavirus disease 2019 (COVID-19). However, the clinical outcomes of AF in COVID-19 remain inconsistent and inconclusive. The aim of this study was to provide a comprehensive description of the impact of AF on the prognosis of patients with COVID-19 pneumonia.

METHODS

Three electronic databases (PubMed, Embase, and Web of Science) were searched for eligible studies as of March 1, 2021. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the associations between AF (preexisting and new-onset) and in-hospital mortality, post-discharge mortality, and ventilator use.

RESULTS

A total of 36 individual studies were incorporated into our meta-analysis. The combined results revealed that preexisting AF was associated with increased in-hospital mortality (pooled OR: 2.07; 95% CI: 1.60-2.67; p < 0.001), post-discharge mortality (pooled OR: 2.69; 95% CI: 1.24-5.83; p < 0.05), and ventilator utilization (pooled OR: 4.53; 95% CI: 1.33-15.38; p < 0.05) in patients with COVID-19. In addition, our data demonstrated that new-onset AF during severe acute respiratory syndrome coronavirus 2 infection was significantly correlated with increased mortality (pooled OR: 2.38; 95% CI: 2.04-2.77; p < 0.001).

CONCLUSIONS

The presence of AF is correlated with adverse outcomes in patients with COVID-19 pneumonia, which deserves increased attention and should be managed appropriately to prevent adverse outcomes.

Fragmented QRS is a marker of mortality in patients with severe COVID-19: A retrospective observational study

OBJECTIVE

In this study, we aimed to investigate the association of fragmented QRS (f-QRS) with in-hospital death in patients with severe novel coronavirus disease 2019 (COVID-19).

METHODS

This was a retrospective and observational study. A total of 201 consecutive patients with severe COVID-19 were enrolled. Demographic data, laboratory parameters, medications, electrocardiographic (ECG) findings, and clinical outcomes were recorded. Patients with and without f-QRS were compared, and predictors of all-cause in-hospital mortality were analyzed.

RESULTS

A total of 135 patients without f-QRS (mean age of 64 years, 43% women) and 66 patients with f-QRS (mean age of 66 years, 39% women) were included. C-reactive protein (CRP), D-dimer, troponin I, ferritin levels, and CRP to albumin ratio were significantly higher in patients with f-QRS. The need for invasive mechanical ventilation (63.6% vs. 41.5%, p=0.003) and all-cause in-hospital mortality [54.5% vs. 28.9%, log rank p=0.001, relative risk 1.88, 95% confidence interval (CI) 1.16-4.78] were significantly higher in patients with f-QRS. A number value of f-QRS leads ≥2 yields sensitivity and specificity (85.3% and 86.7%, respectively) for predicting in-hospital all-cause mortality. Multivariable analysis showed that f-QRS (odds ratio: 1.041, 95% Cl: 1.021-1.192, p=0.040) were independently associated with in-hospital death.

CONCLUSION

This study revealed that the presence of f-QRS in ECG is associated with higher in-hospital all-cause mortality in patients with severe COVID-19. f-QRS is an easily applicable simple indicator to predict the risk of death in these patients.

Implications of atrial fibrillation on the clinical course and outcomes of hospitalized COVID-19 patients: results of the Cardio-COVID-Italy multicentre study

AIMS

To assess the clinical relevance of a history of atrial fibrillation (AF) in hospitalized patients with coronavirus disease 2019 (COVID-19).

METHODS AND RESULTS

We enrolled 696 consecutive patients (mean age 67.4 ± 13.2 years, 69.7% males) admitted for COVID-19 in 13 Italian cardiology centres between 1 March and 9 April 2020. One hundred and six patients (15%) had a history of AF and the median hospitalization length was 14 days (interquartile range 9-24). Patients with a history of AF were older and with a higher burden of cardiovascular risk factors. Compared to patients without AF, they showed a higher rate of in-hospital death (38.7% vs. 20.8%; P < 0.001). History of AF was associated with an increased risk of death after adjustment for clinical confounders related to COVID-19 severity and cardiovascular comorbidities, including history of heart failure (HF) and increased plasma troponin [adjusted hazard ratio (HR): 1.73; 95% confidence interval (CI) 1.06-2.84; P = 0.029]. Patients with a history of AF also had more in-hospital clinical events including new-onset AF (36.8% vs. 7.9%; P < 0.001), acute HF (25.3% vs. 6.3%; P < 0.001), and multiorgan failure (13.9% vs. 5.8%; P = 0.010). The association between AF and worse outcome was not modified by previous or concomitant use of anticoagulants or steroid therapy (P for interaction >0.05 for both) and was not related to stroke or bleeding events.

CONCLUSION

Among hospitalized patients with COVID-19, a history of AF contributes to worse clinical course with a higher mortality and in-hospital events including new-onset AF, acute HF, and multiorgan failure. The mortality risk remains significant after adjustment for variables associated with COVID-19 severity and comorbidities.

Prevalence and Impact of Atrial Fibrillation in Hospitalized Patients with COVID-19: A Systematic Review and Meta-Analysis

BACKGROUND

In patients with COVID-19, cardiovascular complications are common and associated with poor prognosis. Among these, an association between atrial fibrillation (AF) and COVID-19 has been described; however, the extent of this relationship is unclear. The aim of this study is to investigate the epidemiology of AF in COVID-19 patients and its impact on all-cause mortality.

METHODS

A systematic review and meta-analysis were performed and reported according to PRISMA guidelines, and a protocol for this study was registered on PROSPERO (CRD42021227950). PubMed and EMBASE were systematically searched for relevant studies. A random-effects model was used to estimate pooled odds ratios (OR) and 95% confidence intervals (CI).

RESULTS

Overall, 31 studies were included in the analysis, with a total number of 187,716 COVID-19 patients. The prevalence of AF was found to be as high as 8% of patients with COVID-19 (95% CI: 6.3-10.2%, 95% prediction intervals (PI): 2.0-27.1%), with a high degree of heterogeneity between studies; a multiple meta-regression model including geographical location, age, hypertension, and diabetes showed that these factors accounted for more than a third of the heterogeneity. AF COVID-19 patients were less likely to be female but more likely older, hypertensive, and with a critical status than those without AF. Patients with AF showed a significant increase in the risk of all-cause mortality (OR: 3.97, 95% CI: 2.76-5.71), with a high degree of heterogeneity. A sensitivity analysis focusing on new-onset AF showed the consistency of these results.

CONCLUSIONS

Among COVID-19 patients, AF is found in 8% of patients. AF COVID-19 patients are older, more hypertensive, and more likely to have a critical status. In COVID-19 patients, AF is associated with a 4-fold higher risk of death. Further studies are needed to define the best treatment strategies to improve the prognosis of AF COVID-19 patients.

Pre-existing atrial fibrillation is associated with increased mortality in COVID-19 Patients

Purpose

The impacts of pre-existing atrial fibrillation (AF) on COVID-19-associated outcomes are unclear. We conducted a systematic review and meta-analysis to investigate the pooled prevalence of pre-existing AF and its short-term mortality risk in COVID-19 patients.

Methods

Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed in abstracting data and assessing validity. We searched MEDLINE and Scopus to locate all the articles published up to January 31, 2021, reporting data on pre-existing AF among COVID-19 survivors and non-survivors. The pooled prevalence of pre-existing AF was calculated using a random effects model and presenting the related 95% confidence interval (CI), while the mortality risk was estimated using the Mantel-Haenszel random effects models with odds ratio (OR) and related 95% CI. Statistical heterogeneity was measured using the Higgins I² statistic.

Results

Twelve studies, enrolling 15.562 COVID-19 patients (mean age 71.6 years), met the inclusion criteria and were included in the final analysis. The pooled prevalence of pre-existing AF was 11.0% of cases (95% CI: 7.8–15.2%, p < 0.0001) with high heterogeneity (I² = 95.2%). Pre-existing AF was associated with higher risk of short-term death (OR 2.22, 95% CI 1.47–3.36, p < 0.0001), with high heterogeneity (I² = 79.1%).

Conclusion

Pre-existing AF is present in about 11% of COVID-19 cases but results associated with an increased risk of short-term mortality.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10840-021-00992-2.