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\begin{document}

\title{Erroneous Electrocardiographic Interpretations and its Clinical
Implications}



\author[1]{Ayesha Shaik}%
\author[1]{Nirav Patel}%
\author[1]{Chikezie Alvarez}%
\author[2]{Gregory Panza}%
\author[1]{William Baker}%
\author[1]{Sean McMahon}%
\author[1]{Jeffrey Kluger}%
\affil[1]{Hartford Hospital}%
\affil[2]{Hartford HealthCare Medical Group}%


\vspace{-1em}



  
  \date{May 25, 2024}


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\selectlanguage{english}
\begin{abstract}
\textbf{Introduction:} The advancement of artificial intelligence (AI)
has aided clinicians in the interpretation of electrocardiograms (ECGs)
serving as an essential tool to provide rapid triage and care. However,
in some cases, AI can misinterpret an ECG and may mislead the
interpreting physician. Therefore, we aimed to describe the rate of ECG
misinterpretation and its potential clinical impact in patient's
management. \textbf{Methods:} We performed a retrospective descriptive
analysis of misinterpreted ECGs and its clinical impact from May 28,
2020 to May 9, 2021. An electrophysiologist screened ECGs with confirmed
diagnosis of atrial fibrillation (AF), sinus tachycardia (ST), sinus
bradycardia (SB), intraventricular conduction delay (IVCD), and
premature atrial contraction (PAC) that were performed in the emergency
department. We then classified the misinterpreted ECGs as pseudo-AF, ST,
SB, IVCD, or PAC into the correct diagnosis and reviewed the
misinterpreted ECGs and medical records to evaluate inappropriate use of
antiarrhythmic drugs (AAD), beta-blockers (BB), calcium channel blockers
(CCB), anticoagulation, or resource utilization of cardiology and/or
electrophysiology (EP) consultation. \textbf{Results:} A total of 4,969
ECGs were screened with diagnoses of AF (2,282), IVCD (296), PAC (972),
SB (895), and ST (638). Among these, 101 ECGs (2.0\%) were
misinterpreted. Pseudo-AF (58.4\%) was the most common followed by
pseudo-PAC (14.9\%), pseudo-ST (12.9\%), pseudo-IVCD (7.9\%) and
pseudo-SB (6.0\%). Patients with misinterpreted ECGs were aged
76.6\selectlanguage{ngerman}±11.6yr with male (52.5\%) predominance and hypertension being the
most prevalent (83.2\%) comorbid condition. The misinterpretation of
ECGs led to the inappropriate use of BB (19.8\%), CCB (5.0\%), AAD
therapy (7.9\%), anticoagulation (6.9\%) in patients with pseudo-AF, as
well as inappropriate resource utilization including cardiology (41.6\%)
and EP (8.9\%) consultations. \textbf{Conclusions:} Misinterpretation of
ECGs may lead to inappropriate medical therapies and increased resource
utilization. Therefore, it is essential to encourage physicians to
carefully examine AI interpreted ECG's, especially those interpreted as
having AF.%
\end{abstract}\selectlanguage{ngerman}%



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\verb`ErroneousECG - manuscript.docx`  available at \url{https://authorea.com/users/604951/articles/634610-erroneous-electrocardiographic-interpretations-and-its-clinical-implications}

\selectlanguage{english}
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