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Reviews in Cardiovascular Medicine  2020, Vol. 21 Issue (3): 345-352     DOI: 10.31083/j.rcm.2020.03.120
Special Issue: Utilizing Technology in the COVID 19 era
Review Previous articles | Next articles
Usefulness of machine learning in COVID-19 for the detection and prognosis of cardiovascular complications
Allison Zimmerman1, Dinesh Kalra1, *()
1Division of Cardiology, Rush University Medical Center, Chicago, IL 60612, USA
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Abstract:

Since January 2020, coronavirus disease 2019 (COVID-19) has rapidly become a global concern, and its cardiovascular manifestations have highlighted the need for fast, sensitive and specific tools for early identification and risk stratification. Machine learning is a software solution with the ability to analyze large amounts of data and make predictions without prior programming. When faced with new problems with unique challenges as evident in the COVID-19 pandemic, machine learning can offer solutions that are not apparent on the surface by sifting quickly through massive quantities of data and making associations that may have been missed. Artificial intelligence is a broad term that encompasses different tools, including various types of machine learning and deep learning. Here, we review several cardiovascular applications of machine learning and artificial intelligence and their potential applications to cardiovascular diagnosis, prognosis, and therapy in COVID-19 infection.

Key words:  COVID-19      artificial intelligence      machine learning      cardiovascular     
Submitted:  28 June 2020      Revised:  06 September 2020      Accepted:  08 September 2020      Published:  30 September 2020     
*Corresponding Author(s):  Dinesh K. Kalra     E-mail:  dinesh_kalra@rush.edu

Cite this article: 

Allison Zimmerman, Dinesh Kalra. Usefulness of machine learning in COVID-19 for the detection and prognosis of cardiovascular complications. Reviews in Cardiovascular Medicine, 2020, 21(3): 345-352.

URL: 

https://rcm.imrpress.com/EN/10.31083/j.rcm.2020.03.120     OR     https://rcm.imrpress.com/EN/Y2020/V21/I3/345

Table 1.  Summary of the literature for cardiac acute myocardial injury in COVID19
StudyNStudy DesignFindings
Guo et al., 2020187Case series 52 patients suffered acute myocardial injury with a mean CK-MB fraction of 3.34 ng/ml and mean myoglobin of 128.7 μg/ml. 8 patients (4.3%) developed cardiomyopathy with a mean troponin T level of 15.4 pg/ml and mean NT-proBNP of 817.4 pg/ml
Arentz et al., 202021Case series 7 patients (33%) developed cardiomyopathy
Zhou et al., 2020191Retrospective cohort 44 patients (23%) developed heart failure. 33 (17%) had acute cardiac injury with 24 patients having a hs-Troponin I level of > 28 pg/ml
Puntmann et al., 2020100Prospective cohort 78% of patients who had recently recovered from COVID had abnormal CMR findings and ongoing inflammation was seen in 60% of patients
Li et al., 20201527Meta-analysis 122 patients (8%) showed signs of cardiac injury
Huang et al., 202041Case series 5 patients (12%) were diagnosed with acute myocardial injury with an increased troponin I level > 28 pg/ml
Wang et al., 2020138Case series 16.7% of patients developed arrhythmia and 7.2% experienced acute cardiac injury
Shi et al., 2020416Prospective cohort 82 patients (19.7%) developed cardiac injury
Table 3.  Clinical trials on COVID-19 and the CV system using artificial intelligence
Study (year)NPrimary outcome measuresLocationStatus
QT-Logs: a Clinical Study to Monitor Cardiac Safety, With Artificial Intelligence for QT Interval Analysis of ECG Data From Smartwatches, in Patients Receiving Hydroxychloroquine Treatment for COVID-19 (2020) (Assistance Publique Hopitaux De Marseille., 2020)100Measurement of QTc using an artificial intelligence (AI)-based solution and ECG data collected via smartwatches, compare to standard 12 leads EKG reviewed by cardiologist Assistance Publique Hôpitaux de Marseille, France Complete
CARDICoVRISK:Cardiovascular Risk in COVID-19 Patients: Metabolic, Prothrombotic and Proinflammatory Mechanisms Associated with Outcome and with Cardiorespiratory Features During the Acute Viral Disease and at Short Term Follow-up (2020) (Parati, 2020)5500To Identify the clinical, immunological, inflammatory, viral, cardiorespiratory consequences of COVD-19 that may persist a few months after discharge and may affect mid- and long-term prognosis Istituto Auxologico Italiano Milan, Italy Not yet recruiting
Coviva: Coronavirus Disease-19 Survival - The COVIVA Study (Twerenbold and Pfister, 2020)1500i) perform extensive clinical and biomarker phenotyping in COVID-19 suspects presenting to the emergency department (ED) and in COVID-19 patients with subsequent ICU admission, ii) compare clinical and biomarker profiles of COVID-19 patients with a control group, iii) derive and validate personalized risk prediction models for early clinical decision support, and iv) explore pathophysiological mechanisms including inflammatory and CV pathways. University Hospital Basel Basel, Switzerland Recruiting
Table 4.  Diagnostic tests in patients with COVID-19 and cardiovascular involvement
TestDiagnostic considerations in COVID19 patients
NT-pro BNP/BNP Frequently elevated in patients with COVID-19 even in the absence of clinical heart failure or elevated filling pressures and associated with unfavorable course among patients with ARDS. Should not trigger evaluation for heart failure unless there is clinical evidence per ACC guidelines.
Troponin May be helpful in risk assessment in patients requiring ICU level care and can be an indicator of myocardial injury. Should be considered if the diagnosis of MI is being considered on clinical grounds per ACC guidelines.
Procalcitonin A marker of bacterial infection. Reports from Wuhan demonstrated an association between elevation in its levels with cardiac injury and requiring ICU care
IL-6 High concentrations associated with worse outcome
Complete blood count Acute cardiac injury and higher mortality are associated with lymphopenia and thrombocytopenia
EKG Dynamic ischemic appearing changes when there is myocardial involvement
Echocardiography May show hyperdynamic changes in the early stages, and global or regional systolic and diastolic dysfunction later on. Stress cardiomyopathy like wall motion abnormalities and pericardial effusion may occur.
CMR Patients often show lower LVEF, higher left ventricular volumes, higher left ventricular mass, raised native T1 and T2 values, late gadolinium enhancement (LGE). Likely useful in monitoring the long-term CV consequences of COVID-19
Cardiac CT May be helpful in the setting of elevated troponin when CAD needs to be ruled out noninvasively.
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