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\begin{document}

\title{A systematic review and meta-analysis of new-onset atrial fibrillation
in the context of COVID-19}



\author[1]{Sawai Singh Rathore}%
\author[2]{Akanksha Atulkar}%
\author[3]{Kavya Remala}%
\author[4]{Vanessa Vidaurre Corrales}%
\author[5]{Ameer Mustafa Farrukh}%
\author[6]{Ravinderjeet Kaur Puar}%
\author[7]{Sem Josue Nsanh Yao}%
\author[8]{Vijaya Durga Pradeep Ganipineni}%
\author[9]{Nirmal Patel}%
\author[10]{Naganath Thota}%
\author[11]{Ashish Kumar}%
\author[12]{Abhishek Deshmukh}%
\affil[1]{Dr Sampurnanand Medical College}%
\affil[2]{Global Remote Research Scholars Program}%
\affil[3]{Konaseema Institute of Medical Sciences and Research Foundation Hospital}%
\affil[4]{Universidad del Valle}%
\affil[5]{National University of Ireland Galway Academic Department of Paediatrics}%
\affil[6]{Vardhman Mahavir Medical College and Safdarjung Hospital}%
\affil[7]{Cincinnati Children's Hospital Medical Center Winslow}%
\affil[8]{Andhra Medical College}%
\affil[9]{St George's University School of Medicine}%
\affil[10]{Baptist Memorial Rehabilitation Hospital}%
\affil[11]{Cleveland Clinic Akron General Department of Internal Medicine}%
\affil[12]{Mayo Clinic Department of Cardiovascular Medicine}%


\vspace{-1em}



  
  \date{May 25, 2024}


\begingroup
\let\center\flushleft
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\endgroup





\selectlanguage{english}
\begin{abstract}
\textbf{Background:} New-onset atrial fibrillation (NOAF) in COVID-19
raises significant clinical and public health issues. This systematic
review and meta-analysis aims to compile and analyze the current
literature on NOAF in COVID-19 and give a more comprehensive
understanding of the prevalence and outcomes of NOAF in COVID-19.
\textbf{Methods:} A comprehensive literature search was carried out
using several databases. The random effect model using inverse variance
method and DerSimonian and Laird estimator of Tua2 was used to calculate
the pooled prevalence and associated 95\% confidence interval (CI).
Results for outcome analysis were presented as odds ratios (ORs) with
95\% CI and pooled using the Mantel-Haenszel random-effects model.
\textbf{Results:} The pooled prevalence of NOAF in COVID-19 was 7.8\%
(95\% CI, 6.54\% to 9.32\%), pooled estimate from 30 articles (81,929
COVID-19 patients). Furthermore, our analysis reported that COVID-19
patients with NOAF had a higher risk of developing severe disease
compared with COVID--19 patients without a history of atrial
fibrillation (OR= 4.78, 95\% CI 3.75 to 6.09) and COVID-19 patients with
a history of pre-existing atrial fibrillation (OR= 2.75, 95\% CI 2.10 to
3.59) . Similarly, our analysis also indicated that COVID--19 patients
with NOAF had a higher risk of all-cause mortality compared with,
COVID--19 patients without a history of atrial fibrillation (OOR= 3.83,
95\% CI 2.99 to 4.92) and COVID-19 patients with a history of
pre-existing atrial fibrillation (OR= 2.32, 95\% CI 1.35 to 3.96). The
meta-analysis did not reveal any significant publication bias.
\textbf{Conclusion:} The results of the current meta-analysis a high
prevalence rate of NOAF among COVID-19 patients. Further the study
reported higher disease severity with NOAF compared with COVID-19
patients without a history of atrial fibrillation and with a history of
atrial fibrillation.%
\end{abstract}%



\sloppy


\textbf{A systematic review and meta-analysis of new-onset atrial
fibrillation in the context of COVID-19}

\textbf{Running head:} \emph{NOAF in COVID-19}

Sawai Singh Rathore\textsuperscript{1}, Akanksha
Atulkar\textsuperscript{2}, Kavya Remala\textsuperscript{3}, Vanessa
Vidaurre Corrales\textsuperscript{4}, Ameer Mustafa
Farrukh\textsuperscript{5}, Ravinderjeet Kaur Puar\textsuperscript{6},
Sem Josue Nsanh Yao\textsuperscript{7}, Vijaya Durga Pradeep
Ganipineni\textsuperscript{8}, Nirmal Patel\textsuperscript{9}, Naganath
Thota\textsuperscript{10}, Ashish Kumar \textsuperscript{11,} Abhishek
Deshmukh, \textsuperscript{12}

\textsuperscript{1} Department of Internal Medicine, Dr. Sampurnanand
Medical College, Jodhpur, Rajasthan, India; \textsuperscript{2} Global
Remote Research Scholars Program,~St. Paul, Minnesota,
USA;\textsuperscript{3} Department of Internal Medicine, Konaseema
Institute of Medical Sciences, Amalapuram, India; \textsuperscript{4}
Department of Internal Medicine, Universidad Privada del
Valle,Cochabamba, Bolivia;\textsuperscript{5} Department of Internal
Medicine, University of Galway School of Medicine, Galway, Ireland;
\textsuperscript{6}Department of Internal Medicine, Vardhman Mahavir
Medical College \& Safdarjung Hospital, New Delhi, India;
\textsuperscript{7} Department of Internal Medicine, Cincinnati
Children's Hospital Medical Center, Cincinnati, Ohio, USA;
\textsuperscript{8} Department of Internal Medicine, Andhra Medical
College, Visakhapatnam, India;\textsuperscript{9} Department of Internal
Medicine, St. George's University School of Medicine, Grenada;
\textsuperscript{10} Department of Internal Medicine, Baptist Memorial
Hospital, Memphis, Tennessee, USA; \textsuperscript{11}Department of
Internal Medicine, Cleveland Clinic Akron General, Akron, OH, USA;
\textsuperscript{12} Department of Cardiovascular Medicine, Mayo Clinic,
Rochester, MN, USA.

\textbf{Total Word Count:} 2015 (Excluding title page, abstract,
abbreviations, references, and figure legends)

\textbf{Funding:} None

\textbf{Disclosure:} None

\textbf{Corresponding Author:}

Abhishek J Deshmukh MBBS

Department of Cardiovascular Diseases

Mayo Clinic,

200 1\textsuperscript{st} Street SW

Rochester, MN 55905

Deshmukh.abhishek@mayo.edu

\textbf{ABSTRACT}

\textbf{Background:} New-onset atrial fibrillation (NOAF) in COVID-19
raises significant clinical and public health issues. This systematic
review and meta-analysis aims to compile and analyze the current
literature on NOAF in COVID-19 and give a more comprehensive
understanding of the prevalence and outcomes of NOAF in COVID-19.

\textbf{Methods:} A comprehensive literature search was carried out
using several databases. The random effect model using inverse variance
method and DerSimonian and Laird estimator of Tua2 was used to calculate
the pooled prevalence and associated 95\% confidence interval (CI).
Results for outcome analysis were presented as odds ratios (ORs) with
95\% CI and pooled using the Mantel-Haenszel random-effects model.

\textbf{Results:} The pooled prevalence of NOAF in COVID-19 was 7.8\%
(95\% CI, 6.54\% to 9.32\%), pooled estimate from 30 articles (81,929
COVID-19 patients). Furthermore, our analysis reported that COVID-19
patients with NOAF had a higher risk of developing severe disease
compared with COVID--19 patients without a history of atrial
fibrillation (OR= 4.78, 95\% CI 3.75 to 6.09) and COVID-19 patients with
a history of pre-existing atrial fibrillation (OR= 2.75, 95\% CI 2.10 to
3.59) . Similarly, our analysis also indicated that COVID--19 patients
with NOAF had a higher risk of all-cause mortality compared with,
COVID--19 patients without a history of atrial fibrillation (OOR= 3.83,
95\% CI 2.99 to 4.92) and COVID-19 patients with a history of
pre-existing atrial fibrillation (OR= 2.32, 95\% CI 1.35 to 3.96). The
meta-analysis did not reveal any significant publication bias.

\textbf{Conclusion:} The results of the current meta-analysis a high
prevalence rate of NOAF among COVID-19 patients. Further the study
reported higher disease severity with NOAF compared with COVID-19
patients without a history of atrial fibrillation and with a history of
atrial fibrillation.

\textbf{KEYWORDS} : New-onset atrial fibrillation; COVID-19; SARS-CoV-2;
atrial arrhythmias; heart rhythm; mortality

\textbf{ABBREVIATIONS}

\textbf{COVID-19-} Coronavirus disease- 2019

\textbf{SARS-CoV-2} - Severe acute respiratory syndrome coronavirus 2

\textbf{NOAF-} New-onset atrial fibrillation

\textbf{1. INTRODUCTION}

SARS-CoV-2 causing COVID-19 has affected millions worldwide till date.
Although initially described for its respiratory symptoms and
complications, new research has highlighted the virus's wide-ranging
effects, which go well beyond the respiratory system. The cardiovascular
system has drawn much attention because of the various cardiac
manifestations, calling for more research and comprehension

The development of new-onset atrial fibrillation (NOAF) in COVID-19 is
one such cardiac manifestation. Several underlying cardiovascular and
systemic conditions have been linked to atrial fibrillation. However,
the intriguing link between COVID-19 and AF has created a particular
focus in cardiovascular medicine, providing additional information about
the underlying mechanisms, clinical implications, and potential
therapeutic options. Although there are variations in the prevalence of
NOAF in COVID-19 as documented by prior studies, it is clear that it can
affect how the disease manifests clinically.\textsuperscript{,}

The presence of NOAF in COVID-19 raises significant clinical and public
health issues, related to the effect of NOAF in COVID-19 outcomes, such
as mortality, hospitalization rates, and the course of the disease.
Hence, we present a systematic review and meta-analysis to compile and
analyze the current literature on NOAF in COVID-19. By combining data
from various studies, we aim to provide a more comprehensive
understanding of the prevalence, clinical importance, and potential
underlying mechanisms of NOAF in COVID-19.

\textbf{2. METHODS}

Preferred Reporting Items for Systematic Reviews and Meta-analyses
(PRISMA) guidelines are followed in communicating and processing the
current systematic review and meta-analysis.

\textbf{2.1 Search strategy:}

A comprehensive literature search was conducted with PubMed and Embase
until September 5, 2023. The MedRxiv and SSNR preprint servers were also
filtered. We combined Medical Subject Headings (MeSH) terms and
keywords, and subsequent search terms were, \emph{(( {[}Coronavirus{]}
or {[}Covid-19{]} or {[}SARS-CoV-2{]} AND {[}New-onset atrial
fibrillation{]} or {[}Atrial Fibrillation{]} or {[}Arrythmias{]} or
{[}Outcomes{]}))} . There were no language or geographic restrictions.
We manually searched the reference lists of the included studies and the
relevant literature for additional qualifying studies. After removing
duplicate citations, the eligibility of the remaining articles was
evaluated by looking at their titles and abstracts. The PRISMA flow
diagram is depicted in Figure 1.

\textbf{2.2 Eligibility Criteria}

All qualified studies were included in this meta-analysis. To be
included in the present meta-analysis, the article must have full filled
the following inclusion criteria: (a) an observational article reporting
COVID-19 and prevalence of NOAF; (b) studies with a sample size of [?] 5
patients. These studies were included irrespective of the patient's age,
gender, or ethnicity.

The following were the exclusion requirements: (a) lacking data on the
outcome of COVID-19, (b) duplicate publications, (c) letters to the
editor, case reports, commentaries, reviews, and posters.

\textbf{2.3 Study selection and quality assessment:}

Two authors () individually reviewed the titles and abstracts of the
literature extracted from database search. Each author filtered the
studies based on the predetermined eligibility criteria. Any conflict
was resolved through discussion and an earlier agreement that a third
author (AK) would evaluate the differences in opinion. The
Newcastle-Ottawa Scale (NOS) was utilized to assess the risk of bias of
the included studies. Two authors (KR, RKP) independently performed and
reported the Newcastle-Ottawa Scale (NOS), differences resolved by
discussion and after consultation with the third author (AK). The
studies were categorized as: low bias risk (8-9 points), moderate bias
risk (5-7 points), and high bias risk (0-4 points).

\textbf{2.4 Data extraction:}

Two authors (SSR, AMF, VDPG) independently performed data extraction
from included studied, which was then cross-checked by the third author
(AK) to reduce errors. From each included study, the following details
were retrieved, the first author's name, the origin country of the
analysis, study design, number of COVID-19 patients, median age, gender
(female sex proportion), patients with NOAF, data on patients with
pre-existing atrial fibrillation if available, ICU admitted patients or
patients with respiratory failure, and all-cause mortality. Criteria for
severe disease was ICU admission or respiratory failure.

\textbf{2.5 Statistical Analysis:}

MedCalc\selectlanguage{ngerman}® Statistical Software version 19.6.4 (MedCalc Software Ltd,
Ostend, Belgium; https://www.medcalc.org; 2021) was utilized for all
statistical analyses. The random effect model using inverse variance
method and DerSimonian and Laird estimator of Tua2 was used to calculate
the pooled prevalence and associated 95\% confidence interval (CI).
Results for outcome analysis were presented as odds ratios (ORs) with
95\% CI and pooled using the Mantel-Haenszel random-effects model. The
I2 statistics were used to assess the heterogeneity of effect size
estimates across included studies (low heterogeneity: I2 \selectlanguage{english}[?] 25\%;
moderate: 25--50\%; high \textgreater{} 75\%). Publication bias was
explored using funnel plots, Egger's regression test, and
Begg-Mazumdar's rank correlation test.

\textbf{3. RESULT:}

\textbf{3.1 Characteristics of the included studies:}

The preliminary search reported 1689 articles. Seven hundred thirty-five
studies were included after removing duplicates. After considering the
title and abstract, 663 articles were eliminated, leaving 72 papers that
were regarded as plausible for this analysis. Following review of these
studies based on the inclusion and exclusion criteria, 30 articles
totaling 81,929 COVID-19 patients were eventually included in this
meta-analysis.\textsuperscript{,} Table 1 summarizes the baseline
characteristics of the included studies.

\textbf{3.2 Meta-analysis for the prevalence of NOAF in COVID-19
infection:}

The overall pooled prevalence of NOAF in patients with COVID-19 across
multiple studies was 7.8\%, with a 95\% confidence interval (CI) ranging
from 6.54\% to 9.32\%. (Figure 2)

\textbf{3.3 Meta-analysis for Severity Outcome:}

The current meta-analysis results indicated that NOAF in the COVID-19
was associated with an increased incidence of severe disease compared
with COVID-19 patients without any history of atrial fibrillation (OR=
4.78, 95\% CI 3.75 to 6.09). The outcome had high associated
heterogeneity (\emph{I} 2 = 82\%). The result was pooled from 15
studies, comprising 54,051 COVID-19 patients (Figure 3 A).

Similarly, our analysis reported that NOAF in COVID-19 patients was
associated with an increased incidence of severe disease compared with
COVID-19 patients with a history of pre-existing atrial fibrillation
(OR= 2.75, 95\% CI 2.10 to 3.59). The outcome had moderate associated
heterogeneity (\emph{I} 2 = 41\%). The result was pooled from 7 studies,
comprising 2625 COVID-19 patients (Figure 3 B).

\textbf{3.4 Meta-analysis for mortality outcome:}

The current meta-analysis results indicated that NOAF in the COVID-19
was associated with an increased mortality compared with COVID-19
patients presenting without NOAF or history of atrial fibrillation (OR=
3.83, 95\% CI 2.99 to 4.92). The outcome had high associated
heterogeneity (\emph{I} 2 = 87\%). The result was pooled from 25
studies, comprising 56,283 COVID-19 patients (Figure 4 A).

Similarly, our analysis revealed that COVID-19 patients with NOAF had an
increased mortality when compared with COVID-19 patients with a history
of pre-existing atrial fibrillation (OR= 2.32, 95\% CI 1.35 to 3.96).
This outcome had high associated heterogeneity (\emph{I} 2 = 87\%). The
result was pooled from 13 studies, comprising 3,882 COVID-19 patients
(Figure 4 B).

\textbf{3.6 Risk of bias assessment:}

The risk of bias assessment of included observational studies was done
with the aid of the Newcastle-Ottawa Scale (NOS). Of 30 studies, 14 were
high quality, and 16 were moderate quality, with an average score of 7.4
(Supplementary Table 1). Overall, it was determined that the evidence
used in these analyses was of moderate quality.

\textbf{3.7 Publication Bias:}

Visual inspection of the standard funnel plots for all the analyses was
identified as having moderate symmetry. With the aid of Egger's
regression test and Begg-Mazumdar's rank correlation test, further
assessment of publication bias was done. For both these tests,
p\textless{} 0.05 was considered significant, and the analysis was
considered positive for publication bias. No evident publication bias
was witnessed for most analyses done in this study. However,
Begg-Mazumdar's rank correlation test for NOAF prevalence outcomes had a
p \textless{} 0.05. The corresponding Egger's regression test showed no
evidence of publication bias for this outcome. Hence, the current
analyses were without any evidence for publication bias (Supplementary
table 2).

\textbf{4. DISCUSSION:}

Our comprehensive meta-analysis reported NOAF to be a major occurrence
in patients with COVID-19. Across 30 studies encompassing a total of
81,929 COVID-19 patients, we found the overall pooled random effects
estimate of NOAF prevalence to be 7.8\% (95\% CI: 6.54\% to 9.32\%).
Published literature shows that the prevalence of NOAF in COVID-19
patients ranges from 1\% to 19\%. \textsuperscript{,} This finding
underscores the importance of monitoring cardiac rhythm in COVID-19
patients. In literature, the incidence of NOAF in surgical and medical
mixed intensive care units ranged from 1.7\% to 29.5\%. However, little
information is available regarding the occurrence of NOAF in critically
ill COVID-19 patients.

One of the key findings of our analysis was the significant association
between NOAF and disease severity in COVID-19 patients. Compared with
COVID-19 patients without any history of atrial fibrillation, those who
developed NOAF during their illness had a substantially increased risk
of severe disease Our analysis also demonstrated that NOAF in COVID-19
patients posed a greater risk of severe disease when compared with
patients who had a pre-existing history of atrial fibrillation.
Furthermore, a correlation between NOAF and elevated mortality risk in
COVID-19 patients was reported in our meta-analysis. NOAF significantly
increased the risk of death compared with COVID-19 patients without
atrial fibrillation. In addition, our analysis reported that COVID-19
patients with NOAF had a higher mortality risk than those with
pre-existing atrial fibrillation. This result suggests that NOAF, a
COVID-19 complication, may have unique implications for disease severity
beyond what is typically associated with pre-existing atrial
fibrillation. This finding emphasizes the need for more focused
investigations and further studies to better comprehend the underlying
mechanisms causing severe disease among COVID-19 patients with NOAF,
potentially guiding customized clinical management strategies for these
patients.

Effective clinical management and intervention depend on understanding
the pathophysiologic mechanisms underlying NOAF in COVID-19 patients.
Even though numerous theories have been put forth, the precise
mechanisms causing NOAF in COVID-19 patients are unknown. An extremely
inflammatory response brought on by the SARS-CoV-2 virus defines
COVID-19. This cytokine storm can result in myocardial injury and
disruption of the heart's typical electrical conduction system. Atrial
fibrillation pathogenesis has been linked to inflammatory mediators like
interleukin-6 (IL-6) and tumor necrosis factor-alpha. Elevated levels of
these cytokines in COVID-19 patients may contribute to the development
of NOAF by promoting atrial remodeling and electrical instability. Aside
from this, the autonomic nervous system is crucial in controlling heart
rhythm. Critically ill COVID-19 patients frequently exhibit
dysregulation of sympathetic and parasympathetic activity, which can
foster the development of NOAF. Hypoxia, stress response, and drugs used
for the management of COVID-19 (such as catecholamines) may all cause
autonomic dysfunction, leading to NOAF. Further according to recent
reports, COVID-19 can cause myocardial injury and ischemia due to
various factors, including direct viral damage, micro thrombosis, and
hypoxia. These circumstances can affect the atria's electrical
stability, creating the perfect environment for atrial fibrillation to
start and continue. Myocardial injury may also affect the atrial
refractory period and promote reentry circuits, facilitating atrial
fibrillation. Viral entry into myocardial cells can disrupt the heart's
typical electrical properties, predisposing to atrial
fibrillation.\textsuperscript{,} A comprehensive understanding of these
mechanisms is essential for developing targeted preventive and
therapeutic strategies for NOAF in COVID-19 patients, ultimately
improving their clinical outcomes.

It is critical to acknowledge some of the limitations of this
meta-analysis. First, we found significant heterogeneity associated with
the pooled estimates; as the included studies differed in design,
patient characteristics, and location, which may have introduced some
variation. The method used for atrial fibrillation surveillance varied
across included studies. Strains of SARS-CoV-2 virus, co-morbidities of
included patients, vaccination status were not accounted for in the
present analysis. The present study didn't account for type of atrial
fibrillation based on the duration. Finally this is a study level
meta-analysis and hence is limited in its ability to account for
heterogeneity observed among the pooled estimate.

In conclusion, our meta-analysis provides valuable insights into the
prevalence and clinical implications of NOAF in COVID-19 patients. The
results indicate a strong correlation between NOAF and a higher risk of
severe illness and mortality among COVID-19. These findings highlight
the value of careful surveillance, early detection, and tailored NOAF
management strategies among COVID-19 patients to enhance clinical
outcomes. Further research is warranted to elucidate the mechanisms
underlying this association and guide clinical practice.

\textbf{5. REFERENCES:}

\textbf{6. Figure legends:}

\textbf{Figure 1:} Preferred Reporting Items for Systematic Reviews and
Meta-analyses (PRISMA) flow diagram

\textbf{Figure 2:} Forest plot for prevalence of NOAF in COVID-19
Patients

\textbf{Figure 3A:} Forest plot for severity of COVID-19 patients among
NOAF and without a history of atrial fibrillation as controls

\textbf{Figure 3B:} Forest plot for severity of COVID-19 patients among
NOAF and with a history of pre-existing atrial fibrillation as
control\textbf{s}

\textbf{Figure 4A:} Forest plot for mortality of COVID-19 patients among
NOAF and without a history of atrial fibrillation as controls

\textbf{Figure 4B:} Forest plot for mortality of COVID-19 patients among
NOAF and with a history of pre-existing atrial fibrillation as controls\selectlanguage{english}
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