Evidence map›Paper›PMID 35090527›Full record

ArticleScandinavian journal of trauma, resuscitation and emergency medicine2022

Epidemiology of emergency ambulance service calls related to COVID-19 in Scotland: a national record linkage study.

David Fitzpatrick, Edward A S Duncan, Matthew Moore, Catherine Best, Federico Andreis, Martin Esposito, Richard Dobbie, Alasdair R Corfield, David J Lowe

Open access · goldAbstract read
In one paragraph

Article in Scandinavian journal of trauma, resuscitation and emergency medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
4.1field-weighted citation impact, top 6% 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

8 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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 5 institutions in 1 country.

David FitzpatrickScottish Ambulance Service, Education and Professional Development Department, Grangemouth Road, Falkirk, Fk2 9AA, UK. david.fitzpatrick4@nhs.scot.ORCID http://orcid.org/0000-0003-0653-8445
Edward A S DuncanFaculty of Health Sciences and Sport, Pathfoot Building, University of Stirling, Stirling, FK9 4LA, UK.
Matthew MooreFaculty of Health Sciences and Sport, Pathfoot Building, University of Stirling, Stirling, FK9 4LA, UK.
Catherine BestFaculty of Social Science, University of Stirling, Stirling, FK9 4LA, UK.
Federico AndreisNesta, Data Analytics Practice, The Bayes Centre 47, Potterrow, Edinburgh, EH8 9BT, UK.
Martin EspositoScottish Ambulance Service Clinical Directorate, 1 South Gyle Crescent, Edinburgh, EH12 9EB, UK.
Richard DobbiePublic Health Scotland, Gyle Square, 1 South Gyle Cresent, Edinburgh, EH12 9EB, UK.
Alasdair R CorfieldEmergency Department, Royal Alexandra Hospital, Paisley, PA2 9PN, UK.
David J LoweEmergency Department, Queen Elizabeth University Hospital, Glasgow, G51 4TF, UK.
University of Stirling · GBNesta · GBPublic Health Scotland · GBQueen Elizabeth University Hospital · GBRoyal Alexandra Hospital · GB

Funding

Chief Scientist Office, Scottish Government Health and Social Care Directorate COV/STG/20/02
6 · The paper itself

Abstract

backgroundCOVID-19 has overwhelmed health services across the world; its global death toll has exceeded 5.3 million and continues to grow. There have been almost 15 million cases of COVID-19 in the UK. The need for rapid accurate identification, appropriate clinical care and decision making, remains a priority for UK ambulance service. To support identification and conveyance decisions of patients presenting with COVID-19 symptoms the Scottish Ambulance Service introduced the revised Medical Priority Dispatch System Protocol 36, enhanced physician led decision support and prehospital clinical guidelines. This study aimed to characterise the impact of these changes on the pathways and outcomes of people attended by the SAS) with potential COVID-19.

methodsA retrospective record linkage cohort study using National Data collected from NHS Scotland over a 5 month period (April-August 2020).

resultsThe SAS responded to 214,082 emergency calls during the study time period. The positive predictive value of the Protocol 36 to identify potentially COVID-19 positive patients was low (17%). Approximately 60% of those identified by Protocol 36 as potentially COVID-19 positive were conveyed. The relationship between conveyance and mortality differed between Protocol 36 Covid-19 positive calls and those that were not. In those identified by Protocol 36 as Covid-19 negative, 30 day mortality was higher in those not conveyed (not conveyed 9.2%; conveyed 6.6%) but in the Protocol 36 Covid-19 positive calls, mortality was higher in those conveyed (not conveyed 4.3% conveyed 8.8%). Thirty-day mortality rates of those with COVID-19 diagnosed through virology was between 28.8 and 30.2%.

conclusionThe low positive predictive value (17%) of Protocol 36 in identifying potential COVID-19 in patients emphasises the importance of ambulance clinicians approaching each call as involving COVID-19, reinforcing the importance of adhering to existing policy and continued use of PPE at all calls. The non-conveyance rate of people that were categorised as COVID-19 negative was higher than in the preceding year in the same service. The reasons for the higher rates of non-conveyance and the relationship between non conveyance rates and death at 3 and 30 days post index call are unknown and would benefit from further study.

Indexed as

AmbulancesCOVID-19Cohort StudiesHumansRetrospective StudiesSARS-CoV-2Scotland

Identifiers

PMID35090527
PMCPMC8795941
OpenAlexW4210732915

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.