Evidence map›Paper›PMID 35909058›Full record

ArticleThe Lancet. Digital health2022

Remote COVID-19 Assessment in Primary Care (RECAP) risk prediction tool: derivation and real-world validation studies.

Ana Espinosa-Gonzalez, Denys Prociuk, Francesca Fiorentino, Christian Ramtale, Ella Mi, Emma Mi, Ben Glampson, Ana Luisa Neves, Cecilia Okusi, Laiba Husain and 10 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Lancet. Digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

20 authors at 6 institutions in 1 country.

Ana Espinosa-GonzalezInstitute of Global Health Innovation, Department of Surgery and Cancer, Imperial College London, London, UK.
Denys ProciukInstitute of Global Health Innovation, Department of Surgery and Cancer, Imperial College London, London, UK.
Francesca FiorentinoInstitute of Global Health Innovation, Department of Surgery and Cancer, Imperial College London, London, UK; Nightingale-Saunders Clinical Trials & Epidemiology Unit, King's Clinical Trials Unit, King's College London, London, UK.
Christian RamtaleInstitute of Global Health Innovation, Department of Surgery and Cancer, Imperial College London, London, UK.
Ella MiInstitute of Global Health Innovation, Department of Surgery and Cancer, Imperial College London, London, UK.
Emma MiInstitute of Global Health Innovation, Department of Surgery and Cancer, Imperial College London, London, UK.
Ben GlampsonDepartment of Surgery and Cancer, Imperial College Healthcare NHS Trust, London, UK.
Ana Luisa NevesInstitute of Global Health Innovation, Department of Surgery and Cancer, Imperial College London, London, UK.
Cecilia OkusiNuffield Department of Primary Care, University of Oxford, Oxford, UK.
Laiba HusainNuffield Department of Primary Care, University of Oxford, Oxford, UK.
Jack MacartneyNuffield Department of Primary Care, University of Oxford, Oxford, UK.
Martina BrownSouth Central Ambulance Service NHS Trust, Otterboure, UK.
Ben BrowneSouth Central Ambulance Service NHS Trust, Otterboure, UK.
Caroline WarrenSouth Central Ambulance Service NHS Trust, Otterboure, UK.
Rachna ChowlaKing's Health Partners, London, UK.
Jonty HeaversedgeSouth East London NHS Clinical Commissioning Group, London, UK.
Trisha GreenhalghNuffield Department of Primary Care, University of Oxford, Oxford, UK.
Simon de LusignanNuffield Department of Primary Care, University of Oxford, Oxford, UK.
Erik MayerInstitute of Global Health Innovation, Department of Surgery and Cancer, Imperial College London, London, UK.
Brendan C DelaneyInstitute of Global Health Innovation, Department of Surgery and Cancer, Imperial College London, London, UK. Electronic address: brendan.delaney@imperial.ac.uk.
Imperial College London · GBUniversity of Oxford · GBSouth Western Ambulance Service NHS Foundation Trust · GBKings Health Partners · GBImperial College Healthcare NHS Trust · GBLondon Clinic · GB

Funding

Cancer Research UK 25310Medical Research Council MC_PC_20058
6 · The paper itself

Abstract

backgroundAccurate assessment of COVID-19 severity in the community is essential for patient care and requires COVID-19-specific risk prediction scores adequately validated in a community setting. Following a qualitative phase to identify signs, symptoms, and risk factors, we aimed to develop and validate two COVID-19-specific risk prediction scores. Remote COVID-19 Assessment in Primary Care-General Practice score (RECAP-GP; without peripheral oxygen saturation [SpO

methodsRECAP was a prospective cohort study that used multivariable logistic regression. Data on signs and symptoms (predictors) of disease were collected from community-based patients with suspected COVID-19 via primary care electronic health records and linked with secondary data on hospital admission (outcome) within 28 days of symptom onset. Data sources for RECAP-GP were Oxford-Royal College of General Practitioners Research and Surveillance Centre (RCGP-RSC) primary care practices (development set), northwest London primary care practices (validation set), and the NHS COVID-19 Clinical Assessment Service (CCAS; validation set). The data source for RECAP-O2 was the Doctaly Assist platform (development set and validation set in subsequent sample). The two probabilistic risk prediction models were built by backwards elimination using the development sets and validated by application to the validation datasets. Estimated sample size per model, including the development and validation sets was 2880 people.

findingsData were available from 8311 individuals. Observations, such as SpO

interpretationBoth RECAP models are valid tools to assess COVID-19 patients in the community. RECAP-GP can be used initially, without need for observations, to identify patients who require monitoring. If the patient is monitored and SpO

fundingCommunity Jameel and the Imperial College President's Excellence Fund, the Economic and Social Research Council, UK Research and Innovation, and Health Data Research UK.

Indexed as

COVID-19DyspneaFemaleHumansMalePrimary Health CareProspective StudiesRisk Factors

Identifiers

PMID35909058
PMCPMC9333950
OpenAlexW4288460541

What OpenQuestion holds

Textmetadata
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.