Evidence map›Paper›PMID 33974106›Full record

ArticleIntensive care medicine2021

Natural history, trajectory, and management of mechanically ventilated COVID-19 patients in the United Kingdom.

Brijesh V Patel, Shlomi Haar, Rhodri Handslip, Chaiyawan Auepanwiriyakul, Teresa Mei-Ling Lee, Sunil Patel, J Alex Harston, Feargus Hosking-Jervis, Donna Kelly, Barnaby Sanderson and 11 more

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

Article in Intensive care medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 3 pooled it
9.5field-weighted citation impact, top 1% 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

34 citing papers in PubMed, 3 syntheses or guidelines pooled it, 68 citations in OpenAlex.

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  12. Coronavirus Disease-2019 in Pregnancy.Clinics in chest medicine · 2023
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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

21 authors at 9 institutions in 1 country.

Brijesh V Patel *Division of Anaesthetics, Pain Medicine & Intensive Care, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London, UK. brijesh.patel@imperial.ac.uk.ORCID http://orcid.org/0000-0002-5573-2503
Shlomi Haar *Brain & Behaviour Lab, Dept. Of Computing, Imperial College London, London, UK.
Rhodri Handslip *Division of Anaesthetics, Pain Medicine & Intensive Care, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London, UK.
Chaiyawan AuepanwiriyakulBrain & Behaviour Lab, Dept. Of Computing, Imperial College London, London, UK.
Teresa Mei-Ling LeeDivision of Anaesthetics, Pain Medicine & Intensive Care, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London, UK.
Sunil PatelDivision of Anaesthetics, Pain Medicine & Intensive Care, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London, UK.
J Alex HarstonBrain & Behaviour Lab, Dept. Of Computing, Imperial College London, London, UK.
Feargus Hosking-JervisDepartment of Surgery & Cancer, Faculty of Medicine, Imperial College London, London, UK.
Donna KellyDepartment of Critical Care, Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK.
Barnaby SandersonDepartment of Critical Care, Guy's and St Thomas' NHS Foundation Trust, St Thomas' Hospital, London, UK.
Barbara BorgattaDepartment of Critical Care, Aintree University Hospital Foundation Trust, Liverpool, UK.
Kate TathamDivision of Anaesthetics, Pain Medicine & Intensive Care, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London, UK.
Ingeborg WeltersDepartment of Critical Care, Liverpool University Hospitals NHS Foundation Trust and University of Liverpool, Liverpool, UK.
Luigi CamporotaDepartment of Critical Care, Guy's and St Thomas' NHS Foundation Trust, St Thomas' Hospital, London, UK.
Anthony C GordonDivision of Anaesthetics, Pain Medicine & Intensive Care, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London, UK.
Matthieu KomorowskiDivision of Anaesthetics, Pain Medicine & Intensive Care, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London, UK.
David AntcliffeDivision of Anaesthetics, Pain Medicine & Intensive Care, Department of Surgery & Cancer, Faculty of Medicine, Imperial College London, London, UK.
John R Prowle *Critical Care and Peri-Operative Medicine Research Group, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Zudin Puthucheary *Critical Care and Peri-Operative Medicine Research Group, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Aldo A Faisal *Brain & Behaviour Lab, Dept. Of Computing, Imperial College London, London, UK. aldo.faisal@imperial.ac.uk.
United Kingdom COVID-ICU National Service Evaluation
Imperial College Healthcare NHS Trust · GBRoyal Brompton & Harefield NHS Foundation Trust · GBSt Thomas' Hospital · GBImperial College London · GBQueen Mary University of London · GBNewcastle upon Tyne Hospitals NHS Foundation Trust · GBRoyal Marsden NHS Foundation Trust · GBUK Dementia Research Institute · GBUniversity of Liverpool · GB

Funding

Imperial College London Covid response awardRoyal Brompton and Harefield NHS Foundation Trust RB&H Charity
6 · The paper itself

Abstract

purposeThe trajectory of mechanically ventilated patients with coronavirus disease 2019 (COVID-19) is essential for clinical decisions, yet the focus so far has been on admission characteristics without consideration of the dynamic course of the disease in the context of applied therapeutic interventions.

methodsWe included adult patients undergoing invasive mechanical ventilation (IMV) within 48 h of intensive care unit (ICU) admission with complete clinical data until ICU death or discharge. We examined the importance of factors associated with disease progression over the first week, implementation and responsiveness to interventions used in acute respiratory distress syndrome (ARDS), and ICU outcome. We used machine learning (ML) and Explainable Artificial Intelligence (XAI) methods to characterise the evolution of clinical parameters and our ICU data visualisation tool is available as a web-based widget ( https://www.CovidUK.ICU ).

resultsData for 633 adults with COVID-19 who underwent IMV between 01 March 2020 and 31 August 2020 were analysed. Overall mortality was 43.3% and highest with non-resolution of hypoxaemia [60.4% vs17.6%; P < 0.001; median PaO

conclusionsRefractory hypoxaemia remains a major association with mortality, yet evidence based ARDS interventions, in particular prone positioning, were not implemented and had delayed application with an associated reduced responsiveness. Real-time service evaluation techniques offer opportunities to assess the delivery of care and improve protocolised implementation of evidence-based ARDS interventions, which might be associated with improvements in survival.

Indexed as

COVID-19Respiration, ArtificialAdultArtificial IntelligenceHumansProne PositionSARS-CoV-2United KingdomARDSArtificial intelligenceCOVID-19Mechanical ventilationMortality riskProne position

Identifiers

PMID33974106
PMCPMC8111053
OpenAlexW3160577315

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.