About: The Clinical Utility of Continuous QT Interval Monitoring in Patients Admitted with COVID-19 Compared to Standard of Care: A Prospective Cohort Study

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: The Clinical Utility of Continuous QT Interval Monitoring in Patients Admitted with COVID-19 Compared to Standard of Care: A Prospective Cohort Study Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	The Clinical Utility of Continuous QT Interval Monitoring in Patients Admitted with COVID-19 Compared to Standard of Care: A Prospective Cohort Study
Creator	Johnson, C Johnson, Christopher Nair, Girish Green, C Green, Martin Alqarawi, Wael Birnie, David Davis, D Davis, Darryl Golian, Mehrdad Klein, A Klein, Andres Neilipovitz, David Nery, Pablo Redpath, Calum Sadek, Mouhannad Mbchb, Nair, G Alqarawi, W Birnie, D Calum, Redpath Golian, M Neilipovitz, D Nery, P Redpath, Sadek, M
Source	Elsevier; Medline; PMC
abstract	BACKGROUND: QT interval monitoring has gained much interest during the COVID-19 pandemic given the use of QT-prolonging medications and the concern about viral transmission with serial ECGs. We hypothesized that continuous telemetry- based QT monitoring is associated with better detection of prolonged QT episodes. METHODS: We introduced Continuous Cardiac Telemetry (CCT) with an algorithm for automated QT interval monitoring to our designated COVID-19 units. The daily maximum automated heart-rate corrected QT (Auto-QTc) measurements were recorded. We compared the proportion of marked QTc prolongation episodes (Long-QTc), defined as QTc > 500 ms, in patients with suspected or confirmed COVID-19 who were admitted before and after CCT was implemented (control group vs CCT group, respectively). Manual QTc measurement by electrophysiologists (EP-QTc) was used to verify Auto-QTc. Charts were reviewed to describe the clinical response to Long-QTc episodes. RESULTS: We included 33 consecutive patients (total of 451 monitoring days). Long-QTc episodes were detected more frequently in the CCT group [69/206 (34%) vs 26/245 (11%), P < 0.0001] and ECGs were performed less frequently [32/206 (16%) vs 78/245 (32%), P < 0.0001]. Auto-QTc correlated well with EP-QTc with an excellent agreement in detecting Long-QTc (Kappa=0.8, P<0.008). Only 28% of Long-QTc episodes were treated with recommended therapies. There was one episode of Torsade de Pointes (TdP) in the control group and none in the CCT group. CONCLUSION: Continuous QT interval monitoring is superior to standard of care in detecting episodes of Long-QTc with minimal need for ECGs. The clinical response to Long-QTc episodes is suboptimal.
has issue date	2020-07-22(xsd:dateTime)
bibo:doi	10.1016/j.cjco.2020.07.012
bibo:pmid	32838256
has license	no-cc
sha1sum (hex)	acbddad55b28ed210f3c53a35dfee0eb2f4c5e6d
schema:url	https://doi.org/10.1016/j.cjco.2020.07.012
resource representing a document's title	The Clinical Utility of Continuous QT Interval Monitoring in Patients Admitted with COVID-19 Compared to Standard of Care: A Prospective Cohort Study
has PubMed Central identifier	PMC7374138
has PubMed identifier	32838256
schema:publication	CJC Open
resource representing a document's body	covid:acbddad55b28ed210f3c53a35dfee0eb2f4c5e6d#body_text
is schema:about of	named entity 'Summary' named entity 'Care' named entity 'Study' named entity 'Utility' named entity 'QT Interval' named entity 'control group' named entity 'COVID-19' named entity 'QTc' named entity 'telemetry' named entity 'electrophysiologists' named entity 'ECG' named entity 'EMRs' named entity 'QTc' named entity 'COVID-19' named entity 'COVID-19' named entity 'myocardial injury' named entity 'QTc prolongation' named entity 'QTc' named entity 'statistically significant' named entity 'TdP' named entity 'Pearson's correlation coefficient' named entity 'dot plot' named entity 'hormones' named entity 'QTc' named entity 'electrolytes' named entity 'QT prolongation' named entity 'AMC' named entity 'ventricular arrhythmias' named entity 'COVID-19' named entity 'SAS' named entity 'confounders' named entity 'ECGs' named entity 'QTc' named entity 'electrolytes' named entity 'anti-microbial' named entity 'Azithromycin' named entity 'COVID-19 pandemic' named entity 'telemetry' named entity 'control group' named entity 'Potassium' named entity 'ECGs' named entity 'residual confounding' named entity 'QRS' named entity 'electrocardiograms' named entity 'sample size' named entity 'ECG' named entity 'ECG' named entity 'QT interval' named entity 'viral transmission' named entity 'Philips' named entity 'risk factors' named entity 'QTc' named entity 'QT interval' named entity 'Hydroxychloroquine' named entity 'QTc prolongation' named entity 'critical care'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software