Evidence map›Paper›PMID 37020492›Full record

ArticleFrontiers in medical technology2023

A descriptive study of the clinical impacts on COVID-19 survivors using telemonitoring (The TeleCOVID Study).

Josephine Sau Fan Chow, Annamarie D'Souza, Megan Ford, Sonia Marshall, Susana San Miguel, Ahilan Parameswaran, Mark Parsons, Jacqueline Ramirez, Rumbidzai Teramayi, Nutan Maurya

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medical technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
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  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Josephine Sau Fan ChowClinical Innovation & Business Unit, South Western Sydney Local Health District, Sydney, NSW, Australia.
Annamarie D'SouzaResearch Directorate, South Western Sydney Local Health District, Liverpool, NSW, Australia.
Megan FordClinical Trial Support Unit, Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia.
Sonia MarshallDistrict Nursing and Midwifery Office, South Western Sydney Local Health District, Liverpool, NSW, Australia.
Susana San MiguelClinical Innovation & Business Unit, South Western Sydney Local Health District, Sydney, NSW, Australia.
Ahilan ParameswaranEmergency Department, Bankstown Hospital, South Western Sydney Local Health District, Liverpool, NSW, Australia.
Mark ParsonsFaculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
Jacqueline RamirezClinical Innovation & Business Unit, South Western Sydney Local Health District, Sydney, NSW, Australia.
Rumbidzai TeramayiNeurology Research Unit, South Western Sydney Local Health District, Liverpool, NSW, Australia.
Nutan MauryaClinical Innovation & Business Unit, South Western Sydney Local Health District, Sydney, NSW, Australia.
South Western Sydney Local Health District · AUUNSW Sydney · AUIngham Institute · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There is increasing evidence that COVID-19 survivors are at increased risk of experiencing a wide range of cardiovascular complications post infection; however, there are no validated models or clear guidelines for remotely monitoring the cardiac health of COVID-19 survivors. Objective: This study aims to test a virtual, in-home healthcare monitoring model of care for detection of clinical symptoms and impacts on COVID-19 survivors. It also aims to demonstrate system usability and feasibility. Methods: This open label, prospective, descriptive study was conducted in South Western Sydney. Included in the study were patients admitted to the hospital with the diagnosis of COVID-19 between June 2021 and November 2021. Eligible participants after consent were provided with a pulse oximeter to measure oxygen saturation and a S-Patch EX to monitor their electrocardiogram (ECG) for a duration of 3 months. Data was transmitted in real-time to a mobile phone Outcome measure: This study was designed for feasibility in real clinical setting implementation, enabling the study team to develop and utilise a virtual, in-home healthcare monitoring model of care to detect post COVID-19 clinical symptoms and impacts on COVID-19 survivors. Results: During the study period, 23 patients provided consent for participation. Out of which 19 patients commenced monitoring. Sixteen patients with 81 (73.6%) valid tests were included in the analysis and amongst them seven patients were detected by artificial intelligence to have cardiac arrhythmias but not clinically symptomatic. The patients with arrhythmias had a higher occurrence of supraventricular ectopy, and most of them took at least 2 tests before detection. Notably, patients with arrhythmia had significantly more tests than those without [ Conclusions: Preliminary observations have identified cardiac arrhythmias on prolonged cardiac monitoring in 7 out of the first 16 participants who completed their 3 months follow-up. This has allowed early escalation to their treating doctors for further investigations and early interventions.

Indexed as

COVID survivorslong COVIDmodel of carepost-COVID clinical symptomvirtual monitoring

Identifiers

PMID37020492
PMCPMC10067568
OpenAlexW4327979593

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.