Evidence map›Paper›PMID 33541910›Full record

ArticleClinical medicine (London, England)2021

Admission COVID-19 clinical risk assessment for guiding patient placement and diagnostic testing strategy.

Nick K Jones, Isobel Ramsay, Elinor Moore, Jonathan Fuld, Chris Adcock, Edward Banham-Hall, Judith Babar, Effrossyni Gkrania-Klotsas, Hoi Ping Mok

Open access · diamondAbstract read
In one paragraph

Article in Clinical medicine (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 35% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Article
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

9 authors at 1 institution in 1 country.

Nick K JonesAddenbrooke's Hospital, Cambridge, UK nicholas.jones@addenbrookes.nhs.uk.
Isobel RamsayAddenbrooke's Hospital, Cambridge, UK.
Elinor MooreAddenbrooke's Hospital, Cambridge, UK.
Jonathan FuldAddenbrooke's Hospital, Cambridge, UK.
Chris AdcockAddenbrooke's Hospital, Cambridge, UK.
Edward Banham-HallAddenbrooke's Hospital, Cambridge, UK.
Judith BabarAddenbrooke's Hospital, Cambridge, UK.
Effrossyni Gkrania-KlotsasAddenbrooke's Hospital, Cambridge, UK.
Hoi Ping MokAddenbrooke's Hospital, Cambridge, UK.
Addenbrooke's Hospital · GB

Funding

Medical Research Council G0701652
6 · The paper itself

Abstract

introductionWithout universal access to point-of-care SARS-CoV-2 testing, many hospitals rely on clinical judgement alone for identifying cases of COVID-19 early.

methodsCambridge University Hospitals NHS Foundation Trust introduced a 'traffic light' clinical judgement aid to the COVID-19 admissions unit in mid-March 2020. Ability to accurately predict COVID-19 was audited retrospectively across different stages of the epidemic.

resultsOne SARS-CoV-2 PCR positive patient (1/41, 2%) was misallocated to a 'green' (non-COVID-19) area during the first period of observation, and no patients (0/32, 0%) were mislabelled 'green' during the second period. 33 of 62 (53%) labelled 'red' (high risk) tested SARS-CoV-2 PCR positive during the first period, while 5 of 22 (23%) 'red' patients were PCR positive in the second.

conclusionCOVID-19 clinical risk stratification on initial assessment effectively identifies non-COVID-19 patients. However, diagnosing COVID-19 is challenging and risk of overcalling COVID-19 should be recognised, especially when background prevalence is low.

Indexed as

COVID-19COVID-19 TestingRisk AssessmentHumansRetrospective StudiesSARS-CoV-2coronavirusCOVID-19diagnosticsinfection controlSARS-CoV-2triage

Identifiers

PMID33541910
PMCPMC8002788
OpenAlexW3126784501

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.