Discussion
Our study including a single center cohort of 390 COVID-19 patients
revealed 28/390 (7.2%) cases with documented cardiac arrhythmias,
including 20 cases of AF, 3 atrial flutter, 1 VF (in a patient who also
had paroxysmal AF), 1 VT case and 3 bradyarrhythmic cases. The study
showed significant correlation between disease severity and arrhythmia
prevalence, revealing significant increase in arrhythmia prevalence with
increasing disease severity [11/116 (9.5%); 5/37 (13.5%); 8/34
(23.5%) for moderate, severe, and critical severity, respectively,
p< 0.001] with a very low prevalence of arrhythmias among
patients with mild COVID-19 disease (4/203; 2%). Multivariate forward
regression analysis showed that background CHF and disease severity are
independently associated with overall arrhythmias while age, background
CHF, disease severity, and arrhythmic symptoms (syncope or palpitations)
are associated with tachy-arrhythmias. Importantly, a classification
tree using specific age (>70 years old) and troponin (≥ 48
ng/L) cutoffs, as well as disease severity, and history of CHF could
further stratify patients into high and low risk for developing
arrhythmia. To our knowledge, these relevant cutoffs were not previously
described and our presented classification tree is novel in this regard.
The overall arrhythmia prevalence in our study was 7.2%, which is lower
than reported in some studies1,12 and similar to
others.13,14 Notably, the initial study from China
reported an overall prevalence of 16.7% among 138 hospitalized COVID-19
patients in Wuhan,1 but there was a significant
difference of arrhythmia incidence between non-ICU and ICU patients
(6.3%, vs. 44.4%; p 0.001) and their relatively high overall
prevalence was clearly influenced by the high number of ICU patients
(36/138, 26%) in whom there was very high prevalence of arrhythmias.
Similarly, among 115 American COVID-19 patients,12 a
dramatic change in arrhythmia prevalence was noticed between non-ICU and
ICU patients (0% versus 27.5%, p 0.0002), with an overall arrhythmia
prevalence of 16.5% given the fact that 69/115 study patients (60%)
were ICU patients.12 In contrast, an Italian study
focusing on 132 stable non-ICU COVID-19 patients, reported 12/132 (9%)
new arrhythmias documented during the admission
period.13 Our overall arrhythmic prevalence is similar
to Wuhan’s non-ICU group and to the Italian stable non-ICU patients,
probably reflecting the low percentage of ICU patients (9.7%) in our
cohort. Notably, the arrhythmic prevalence among our ICU patients was
significantly greater than our non-ICU patients (21% versus 5.7%; p
0.003), in accordance with the previous studies. Similar findings were
reported in a single center study including 700 patients (11% ICU
patients), revealing an overall arrhythmia prevalence of 7.5% with
marked difference of arrhythmia prevalence between ICU and non-ICU
patients.14 Lastly, the low arrhythmic prevalence
among the non-ICU group compared with the ICU one, suggests that need
for mechanical ventilation or presence of multi-organ dysfunction
necessitating ionotropic support, which characterized our ”critical”
severity and most of our ICU patients, have major impact on arrhythmic
prevalence as was suggested by previous
studies.1,6,9,12.14
AF or atrial flutter was the dominant arrhythmia in our study, occurring
for 23/28 (82%) of cases with documented arrhythmia, while only a
minority of these cases had previous arrhythmias (5/23, 22%). This
result is in line with multiple previous studies, revealing AF to be the
most prevalent arrhythmia in COVID-19
disease.1,6,12,13,14,15 The absence of previous atrial
arrhythmias in most of these patients and the fact that some of these
new arrhythmia was timely correlated with respiratory deterioration, may
suggest an association or perhaps even a causative relation between
COVID illness and arrhythmia development. Indeed, some have suggested
that the increased cytokine levels among severe COVID patients may
trigger atrial arrhythmias.7,8 Nevertheless, one
should not interpret the above results as a definite cause and effect
relation between COVID disease and AF, as most of these patients are
elderly with multiple comorbidities as HTN, diabetes and IHD and most if
not all have significant respiratory symptoms, all of which are well
known risk factors for AF occurrence. Thus, we like
others,13,14 find it hard to confirm a necessary
pathophysiologic link between AF occurrence and COVID-19 infection.
Regardless of whether AF is a direct result of COVID or circumstantial
to the multiple comorbidities of these patients, multiple publications
suggest AF to predict bad prognosis among COVID-19
patients.8,12,14,16
There were 3 cases with new onset bradyarrhythmias in our study,
including two cases with advanced AVB and one with a transient slow
ventricular escape rhythm. Notably, 2 of these cases were relatively
young male patients (50 and 33 year old) without prior conduction
abnormalities who presented with advanced AVB or developed a slow
ventricular escape rhythm, respectively. Both did not receive any
negative dromotropic or chronotropic drug. Both had normal electrolytes
and markedly elevated inflammatory markers with mildly increased or
normal hsTnI. Accordingly, we raise the possibility, which we cannot
prove, that these bradyarrhythmias had been related to the cytokine
storm and exacerbated inflammatory state associated with COVID-19
illness. Interestingly, inflammatory-mediated conduction abnormalities
have been suggested in previous reports of COVID-19 patients who
developed otherwise unexplained AVB during the acute COVID illness, with
markedly elevated inflammatory markers.8,9
Disease severity, categorized by the level of respiratory support
needed, was the most robust clinical predictor for new-onset arrhythmia
among COVID-19 patients in our study. This correlation was shown in most
previous studies, with special attention to the remarkably high
arrhythmia prevalence among COVID-19 ICU patients, many of whom were
mechanically ventilated and/or with multi-organ failure necessitating
inotropic support.1,2,3,12,14 The other clinical
predictor for new-onset overall arrhythmias was background CHF, which is
well-established risk factor for atrial and ventricular
arrhythmias.17,18
Regarding laboratory predictors, previous studied suggested both
myocardial injury as well as inflammatory process to have impact on
arrhythmic prevalence or even underlie arrhythmia
development,7,12 with the notion of ”inflammatory and
cardiac injury mediated atrial tachycardia and conduction
disturbances”.7,8,9 Indeed, in our study both hsTnI
and CRP were significantly associated with new arrhythmias in the
univariate analysis. However, in the classification tree model, hsTnI
per se was found to best differentiate between low and high arrhythmic
activities (Fig 5). This is in line with many previous studies
suggesting myocardial injury, assessed via troponin levels, to correlate
with need for mechanical ventilation, ICU admission, mortality and
arrhythmias.1,2,3,4,9,19
Importantly, our classification trees (Fig 4&5) are noval and
clinically relevant as they can discriminate between patients with high
and low risk for new onset arrhythmia. Although, some of these variables
as age and troponin are clinically intuitive and were previously
reported,2,4,9,14 no cutoffs were previously given to
guide clinical decisions. Accordingly, we suggest that patients whose
age is below 70 with mild to moderate disease (1.6% arrhythmic
prevalence) or with negative hsTnI (2.1% arrhythmic prevalence) may be
hospitalized to a ”non-monitored bed” and even discharged early; while
patients aged ≥70 (18.1% arrhythmic prevalence) or patients with hsTnI
≥ 48 ng/L (34.1% arrhythmic prevalence) should be carefully monitored
for the occurrence of arrhythmias. These algorithms might be of crucial
importance to direct optimal utilization of medical staff and monitoring
equipment in COVID-19 outbreaks, especially in areas with limited
medical resources.