Implementation of a practice plan for the outpatient cardiac evaluation of children after acute SARS-CoV-2 infection and a report of outcomes

Dailey-Schwartz, Andrew L.; Dyal, Jameson A.; Mahle, William T.; Oster, Matthew E.

doi:10.1016/j.ahj.2021.06.014

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…The relatively high likelihood of cardiac involvement among MIS-C patients compared to acute COVID-19 patients reinforces our standardized practice of performing full cardiac evaluations and follow-up in all patients with MIS-C but only in acute COVID-19 patients with signs or symptoms of cardiac involvement. 17 Future study is needed to determine how acute COVID-19 and MIS-C may be associated with long-term cardiac health in these patients.…”

Section: Discussionmentioning

confidence: 99%

Cardiac complications in children with acute COVID-19 vs multisystem inflammatory syndrome in children (MIS-C)

Hensley

Goodman

Madani

et al. 2023

American Heart Journal

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Section: Discussionmentioning

confidence: 99%

Cardiac complications in children with acute COVID-19 vs multisystem inflammatory syndrome in children (MIS-C)

Hensley

Goodman

Madani

et al. 2023

American Heart Journal

Self Cite

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Automated Medical Care: Bradycardia Detection and Cardiac Monitoring of Preterm Infants

et al. 2021

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Background and Objectives: Prematurity of birth occurs before the 37th week of gestation and affects up to 10% of births worldwide. It is correlated with critical outcomes; therefore, constant monitoring in neonatal intensive care units or home environments is required. The aim of this work was to develop solutions for remote neonatal intensive supervision systems, which should assist medical diagnosis of premature infants and raise alarm at cardiac abnormalities, such as bradycardia. Additionally, the COVID-19 pandemic has put a worldwide stress upon the medical staff and the management of healthcare units. Materials and Methods: A traditional medical diagnosing scheme was set up, implemented with the aid of powerful mathematical operators. The algorithm was tailored to the infants’ personal ECG characteristics and was tested on real ECG data from the publicly available PhysioNet database “Preterm Infant Cardio-Respiratory Signals Database”. Different processing problems were solved: noise filtering, baseline drift removal, event detection and compression of medical data using the à trous wavelet transform. Results: In all 10 available clinical cases, the bradycardia events annotated by the physicians were correctly detected using the RR intervals. Compressing the ECG signals for remote transmission, we obtained compression ratios (CR) varying from 1.72 to 7.42, with the median CR value around 3. Conclusions: We noticed that a significant amount of noise can be added to a signal while monitoring using standard clinical sensors. We tried to offer solutions for these technical problems. Recent studies have shown that persons infected with the COVID-19 disease are frequently reported to develop cardiovascular symptoms and cardiac arrhythmias. An automatic surveillance system (both for neonates and adults) has a practical medical application. The proposed algorithm is personalized, no fixed reference value being applied, and the algorithm follows the neonate’s cardiac rhythm changes. The performance depends on the characteristics of the input ECG. The signal-to-noise ratio of the processed ECG was improved, with a value of up to 10 dB.

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Implementation of a practice plan for the outpatient cardiac evaluation of children after acute SARS-CoV-2 infection and a report of outcomes

Cited by 2 publications

References 11 publications

Cardiac complications in children with acute COVID-19 vs multisystem inflammatory syndrome in children (MIS-C)

Cardiac complications in children with acute COVID-19 vs multisystem inflammatory syndrome in children (MIS-C)

Automated Medical Care: Bradycardia Detection and Cardiac Monitoring of Preterm Infants

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