Browse through all publications from the Institute of Global Health Innovation, which our Patient Safety Research Collaboration is part of. This feed includes reports and research papers from our Centre. 

Citation

BibTex format

@article{Espinosa-Gonzalez:2021:10.2196/preprints.29072,
author = {Espinosa-Gonzalez, AB and Neves, AL and Fiorentino, F and Prociuk, D and Husain, L and Ramtale, SC and Mi, E and Mi, E and Macartney, J and Anand, SN and Sherlock, J and Saravanakumar, K and Mayer, E and de, Lusignan S and Greenhalgh, T and Delaney, BC},
doi = {10.2196/preprints.29072},
title = {Predicting Risk of Hospital Admission in Patients With Suspected COVID-19 in a Community Setting: Protocol for Development and Validation of a Multivariate Risk Prediction Tool (Preprint)},
url = {http://dx.doi.org/10.2196/preprints.29072},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - <sec>                    <title>BACKGROUND</title>                        <p>During the pandemic, remote consultations have become the norm for assessing patients with signs and symptoms of COVID-19 to decrease the risk of transmission. This has intensified the clinical uncertainty already experienced by primary care clinicians when assessing patients with suspected COVID-19 and has prompted the use of risk prediction scores, such as the National Early Warning Score (NEWS2), to assess severity and guide treatment. However, the risk prediction tools available have not been validated in a community setting and are not designed to capture the idiosyncrasies of COVID-19 infection.</p>                </sec>                                <sec>                    <title>OBJECTIVE</title>                        <p>The objective of this study is to produce a multivariate risk prediction tool, RECAP-V1 (Remote COVID-19 Assessment in Primary Care), to support primary care clinicians in the identification of those patients with COVID-19 that are at higher risk of deterioration and facilitate the early escalation of their treatment with the aim of improving patient outcomes.</p>                </sec>                                <sec>                    <title>METHODS</title>                        <p>The study follows a prospective cohort observational design, whereby patients presenting in primary care with signs and symptoms suggestive of COVID-19 will be followed and their data linked to hospital outcomes (hospital admission and death). Data collection will be carried out by primary care clinicians in four arms: North West London Clinical Commissioning Groups (NWL CCGs), Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), Covid Clinical Assessment Service (CCAS), and South East London CCGs (Doctaly platform). The study involves the use o
AU  - Espinosa-Gonzalez,AB
AU  - Neves,AL
AU  - Fiorentino,F
AU  - Prociuk,D
AU  - Husain,L
AU  - Ramtale,SC
AU  - Mi,E
AU  - Mi,E
AU  - Macartney,J
AU  - Anand,SN
AU  - Sherlock,J
AU  - Saravanakumar,K
AU  - Mayer,E
AU  - de,Lusignan S
AU  - Greenhalgh,T
AU  - Delaney,BC
DO  - 10.2196/preprints.29072
PY  - 2021///
TI  - Predicting Risk of Hospital Admission in Patients With Suspected COVID-19 in a Community Setting: Protocol for Development and Validation of a Multivariate Risk Prediction Tool (Preprint)
UR  - http://dx.doi.org/10.2196/preprints.29072
ER  -
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