Evidence map›Paper›PMID 34812731›Full record

ArticleeLife2021

Ten months of temporal variation in the clinical journey of hospitalised patients with COVID-19: An observational cohort.

ISARIC Clinical Characterisation Group, Matthew D Hall, Joaquín Baruch, Gail Carson, Barbara Wanjiru Citarella, Andrew Dagens, Emmanuelle A Dankwa, Christl A Donnelly, Jake Dunning, Martina Escher and 7 more

Abstract read
In one paragraph

Article in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

  1. Trial
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Article
  7. Deep Survival Analysis With Clinical Variables for COVID-19.IEEE journal of translational engineering in health and medicine · 2023
    Article
  8. Article
  9. Observational
  10. 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

17 authors.

ISARIC Clinical Characterisation Group
Matthew D HallBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0002-2671-3864
Joaquín BaruchISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Gail CarsonISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Barbara Wanjiru CitarellaISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Andrew DagensISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Emmanuelle A DankwaDepartment of Statistics, University of Oxford, Oxford, United Kingdom.
Christl A DonnellyDepartment of Statistics, University of Oxford, Oxford, United Kingdom.
Jake DunningISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Martina EscherISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Christiana KartsonakiMRC Population Health Research Unit, Clinical Trials Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Laura MersonISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0002-4168-1960
Mark PritchardISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Jia WeiBig Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Peter W HorbyISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Amanda RojekISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Piero L OlliaroISARIC Global Support Centre, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.

Funding

Medical Research Council MC_PC_19012Medical Research Council MC_PC_19025Medical Research Council MC_PC_19059Medical Research Council MR/R015600/1Medical Research Council MR/S032304/1Wellcome Trust 200927Wellcome Trust 205228/Z/16/ZWellcome Trust 215091/Z/18/Z
6 · The paper itself

Abstract

Background: There is potentially considerable variation in the nature and duration of the care provided to hospitalised patients during an infectious disease epidemic or pandemic. Improvements in care and clinician confidence may shorten the time spent as an inpatient, or the need for admission to an intensive care unit (ICU) or high dependency unit (HDU). On the other hand, limited resources at times of high demand may lead to rationing. Nevertheless, these variables may be used as static proxies for disease severity, as outcome measures for trials, and to inform planning and logistics. Methods: We investigate these time trends in an extremely large international cohort of 142,540 patients hospitalised with COVID-19. Investigated are: time from symptom onset to hospital admission, probability of ICU/HDU admission, time from hospital admission to ICU/HDU admission, hospital case fatality ratio (hCFR) and total length of hospital stay. Results: Time from onset to admission showed a rapid decline during the first months of the pandemic followed by peaks during August/September and December 2020. ICU/HDU admission was more frequent from June to August. The hCFR was lowest from June to August. Raw numbers for overall hospital stay showed little variation, but there is clear decline in time to discharge for ICU/HDU survivors. Conclusions: Our results establish that variables of these kinds have limitations when used as outcome measures in a rapidly evolving situation. Funding: This work was supported by the UK Foreign, Commonwealth and Development Office and Wellcome [215091/Z/18/Z] and the Bill & Melinda Gates Foundation [OPP1209135]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Indexed as

AdolescentAdultAgedAged, 80 and overChildChild, PreschoolCOVID-19FemaleHospitalizationHumansInfantIntensive Care UnitsLength of StayMaleMiddle AgedOutcome Assessment, Health CareCOVID-19epidemiologyglobal healthhospitalisationhumanICUmedicineSARS-CoV-2viruses

Identifiers

PMID34812731
PMCPMC8791638

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.