Evidence map›Paper›PMID 36952555›Full record

ArticlePloS one2023

Combining viral genomics and clinical data to assess risk factors for severe COVID-19 (mortality, ICU admission, or intubation) amongst hospital patients in a large acute UK NHS hospital Trust.

Max Foxley-Marrable, Leon D'Cruz, Paul Meredith, Sharon Glaysher, Angela H Beckett, Salman Goudarzi, Christopher Fearn, Kate F Cook, Katie F Loveson, Hannah Dent and 13 more

Open access · goldFull text read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 36% 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, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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

23 authors at 2 institutions in 1 country.

Max Foxley-MarrableInstitute of Cosmology and Gravitation, University of Portsmouth, Portsmouth, Hampshire, United Kingdom.
Leon D'CruzPortsmouth Hospitals University NHS Trust, Portsmouth, Hampshire, United Kingdom.ORCID 0000-0001-8684-6231
Paul MeredithPortsmouth Hospitals University NHS Trust, Portsmouth, Hampshire, United Kingdom.
Sharon GlaysherPortsmouth Hospitals University NHS Trust, Portsmouth, Hampshire, United Kingdom.
Angela H BeckettSchool of Biological Science, University of Portsmouth, Portsmouth, Hampshire, United Kingdom.
Salman GoudarziSchool of Pharmacy and Biomedical Science, University of Portsmouth, Portsmouth, Hampshire, United Kingdom.
Christopher FearnSchool of Pharmacy and Biomedical Science, University of Portsmouth, Portsmouth, Hampshire, United Kingdom.
Kate F CookSchool of Pharmacy and Biomedical Science, University of Portsmouth, Portsmouth, Hampshire, United Kingdom.
Katie F LovesonSchool of Pharmacy and Biomedical Science, University of Portsmouth, Portsmouth, Hampshire, United Kingdom.
Hannah DentSchool of Pharmacy and Biomedical Science, University of Portsmouth, Portsmouth, Hampshire, United Kingdom.
Hannah PaulSchool of Pharmacy and Biomedical Science, University of Portsmouth, Portsmouth, Hampshire, United Kingdom.
Scott ElliottPortsmouth Hospitals University NHS Trust, Portsmouth, Hampshire, United Kingdom.
Sarah WylliePortsmouth Hospitals University NHS Trust, Portsmouth, Hampshire, United Kingdom.
Allyson LloydPortsmouth Hospitals University NHS Trust, Portsmouth, Hampshire, United Kingdom.
Kelly BicknellPortsmouth Hospitals University NHS Trust, Portsmouth, Hampshire, United Kingdom.ORCID 0000-0002-4709-9162
Sally LumleyPortsmouth Hospitals University NHS Trust, Portsmouth, Hampshire, United Kingdom.
James McNicholasPortsmouth Hospitals University NHS Trust, Portsmouth, Hampshire, United Kingdom.ORCID 0000-0002-5973-7782
David PrytherchCentre for Healthcare Modelling and Informatics, University of Portsmouth, Portsmouth, Hampshire, United Kingdom.ORCID 0000-0003-2621-6451
COVID-19 Genomics UK (COG-UK) consortium
Andrew LundgrenInstitute of Cosmology and Gravitation, University of Portsmouth, Portsmouth, Hampshire, United Kingdom.
Or GraurInstitute of Cosmology and Gravitation, University of Portsmouth, Portsmouth, Hampshire, United Kingdom.ORCID 0000-0002-4391-6137
Anoop J ChauhanPortsmouth Hospitals University NHS Trust, Portsmouth, Hampshire, United Kingdom.
Samuel C RobsonSchool of Biological Science, University of Portsmouth, Portsmouth, Hampshire, United Kingdom.ORCID 0000-0001-5702-9160
University of Portsmouth · GBPortsmouth Hospitals NHS Trust · GB

Funding

Medical Research Council MC_PC_19027Wellcome Trust
6 · The paper itself

Abstract

Throughout the COVID-19 pandemic, valuable datasets have been collected on the effects of the virus SARS-CoV-2. In this study, we combined whole genome sequencing data with clinical data (including clinical outcomes, demographics, comorbidity, treatment information) for 929 patient cases seen at a large UK hospital Trust between March 2020 and May 2021. We identified associations between acute physiological status and three measures of disease severity; admission to the intensive care unit (ICU), requirement for intubation, and mortality. Whilst the maximum National Early Warning Score (NEWS2) was moderately associated with severe COVID-19 (A = 0.48), the admission NEWS2 was only weakly associated (A = 0.17), suggesting it is ineffective as an early predictor of severity. Patient outcome was weakly associated with myriad factors linked to acute physiological status and human genetics, including age, sex and pre-existing conditions. Overall, we found no significant links between viral genomics and severe outcomes, but saw evidence that variant subtype may impact relative risk for certain sub-populations. Specific mutations of SARS-CoV-2 appear to have little impact on overall severity risk in these data, suggesting that emerging SARS-CoV-2 variants do not result in more severe patient outcomes. However, our results show that determining a causal relationship between mutations and severe COVID-19 in the viral genome is challenging. Whilst improved understanding of the evolution of SARS-CoV-2 has been achieved through genomics, few studies on how these evolutionary changes impact on clinical outcomes have been seen due to complexities associated with data linkage. By combining viral genomics with patient records in a large acute UK hospital, this study represents a significant resource for understanding risk factors associated with COVID-19 severity. However, further understanding will likely arise from studies of the role of host genetics on disease progression.

Indexed as

COVID-19HospitalsHumansIntensive Care UnitsIntubation, IntratrachealPandemicsRisk FactorsSARS-CoV-2State MedicineTrustUnited Kingdom

Identifiers

PMID36952555
PMCPMC10035897
OpenAlexW4360608821

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read355
table measurements read2
reference markers read1
identifiers read12
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.