Evidence map›Paper›PMID 42767748›Full record

ArticleBMJ open2026

Defining the preadmission factors that modify risk of acute complications, survival and long-term recovery from COVID-19: prospective, longitudinal, multisite, cohort study based in England.

H E Baxendale, Martin Law, Claire Matthews, Janet Piggott, Rama Vancheeswaran, Alain Vuylsteke, Catherine Wilson, Erin Hopley, Mark Toshner, Iryna Boubriak and 10 more

Abstract readMulticenter Study
In one paragraph

Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

20 authors.

H E BaxendaleRoyal Papworth Hospital, Cambridge, England, UK hbaxendale@nhs.net.ORCID http://orcid.org/0000-0003-3838-3900
Martin LawRoyal Papworth Hospital, Papworth Trials Unit Collaboration, Cambridge, England, UK.ORCID http://orcid.org/0000-0001-9594-348X
Claire MatthewsRoyal Papworth Hospital, Papworth Trials Unit Collaboration, Cambridge, England, UK.
Janet PiggottNIHR LCRN Eastern Core Team, London, England, UK.
Rama VancheeswaranWest Hertfordshire Teaching Hospitals NHS Trust, Respiratory Medicine Watford, Cambridge, England, UK.
Alain VuylstekeRoyal Papworth Hospital, Cambridge, England, UK.ORCID http://orcid.org/0000-0002-6749-9251
Catherine WilsonRoyal Papworth Hospital, Cambridge, England, UK.
Erin HopleyRoyal Papworth Hospital, Cambridge, England, UK.ORCID http://orcid.org/0000-0001-9447-8416
Mark ToshnerRoyal Papworth Hospital, Cambridge, England, UK.ORCID http://orcid.org/0000-0002-3969-6143
Iryna BoubriakRoyal Papworth Hospital, Cambridge, England, UK.
Joseph NewmanRoyal Papworth Hospital, Cambridge, England, UK.
Nasir HannanPriory Gardens Surgery, Luton and Dunstable Community Healthcare Trust. Dunstable, Cambridge, England, UK.
Alexander Jk WilkinsonPriory Gardens Surgery, Luton and Dunstable Community Healthcare Trust. Dunstable, Cambridge, England, UK.ORCID http://orcid.org/0000-0002-1808-3663
Andrew BarlowWest Hertfordshire Teaching Hospitals NHS Trust, Respiratory Medicine Watford, Cambridge, England, UK.
Nicole HarriottPriory Gardens Surgery, Luton and Dunstable Community Healthcare Trust. Dunstable, Cambridge, England, UK.
Nicola JonesRoyal Papworth Hospital, Cambridge, England, UK.
Stephen WebbRoyal Papworth Hospital, Cambridge, England, UK.ORCID http://orcid.org/0000-0002-2413-7883
William SchwaebleDepartment of Veterinary Medicine, University of Cambridge, Cambridge, UK.
Jonathan HeeneyDepartment of Veterinary Medicine, University of Cambridge, Cambridge, UK.
Dominique CouturierRoyal Papworth Hospital, Papworth Trials Unit Collaboration, Cambridge, England, UK.ORCID http://orcid.org/0000-0001-5774-5036

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo understand the pre-admission factors associated with COVID-19 clinical outcome with and without controlling for acute COVID-19 severity score.

designWe ran a prospective, longitudinal, multicentre cohort study.

settingPatients were recruited from four hospitals and one community General Practice in England

participants425 patients with COVID-19 from the start of the UK pandemic in April 2020 through the first three waves with study completing in 2022. PRIMARY AND SECONDARY OUTCOME MEASURES: Data were collected and analysed to identify demographic factors and preadmission symptoms for hospitalised patients that were associated with COVID-19 disease severity at recruitment, acute clinical course and long-term recovery. Analysis methods included logistic regression, time-to-event analysis, mixed-effect models and K-medoids clustering.

resultsThe cohort was skewed to patients with severe COVID (60%). Preadmission symptom cluster was associated with risk of thrombosis (OR 2.7 (95% CI 1.6 to 6.1), p=0.021) and renal disease (OR 3.3 (95% CI 1.4 to 8.0), p=0.008). Duration of symptoms less than 1 week was associated with pneumothorax (OR 3.1 (95% CI 1.2 to 8.3), p=0.025). Renal complications were more likely to be seen in the first wave compared with the second wave of the pandemic (OR 3.4 (95% CI 1.5 to 7.5), p=0.003). Using a logistic regression model, survival to discharge was associated with white (vs unknown) ethnicity (OR 6.6 (95% CI 2.8 to 15.2), p<0.0001), lower age (<40 years vs >60 years, OR 4.9 (95% CI 1.2 to 20.0), p=0.027) and absence of comorbidities (OR 2.7 (95% CI 1.2 to 5.9), p=0.016). However, using a survival model, hazard of death was increased for all hospitalised who had duration of symptoms less than 1 week (HR 5.6 (95% CI 1.3 to 24.4), p=0.023) or had comorbidities (HR 33.3 (95% CI 3.1 to 333.3), p=0.0035). Over 80% of patients reported long-term sequelae with neuromuscular and cognitive effects dominating early on and mood disturbance and breathlessness persisting to 12 months. Gender had the strongest association with dyspnoea (OR 99.8 (95% CI 2.4 to 4123.1, p=0.02) and persistent mood disorder (OR 8.3 (95% CI 1.7 to 39.9), p=0.008) and associated with persistent gastrointestinal problems (loose bowels (OR 3.3 (95% CI 1.1 to 10.8), p=0.045), abdominal pain (OR 5.0 (95% CI 1.4 to 18.1), p=0.014), constipation (OR 3.8 (95% CI 1.6 to 9.2), p=0.003)) and cognitive problems (OR 2.3 (95% CI 1.1 to -4.8), p=0.024).

conclusionsThese results support an association between specific demographic factors and early infection symptoms that impact on acute and long-term outcomes of COVID-19 in this cohort after accounting for COVID-19 disease severity at enrolment. Understanding the disease mechanisms that explain these relationships is needed to inform targeted therapeutics to prevent and/or manage these complications.

Indexed as

COVID-19AdultAgedEnglandFemaleHospitalizationHumansLogistic ModelsLongitudinal StudiesMaleMiddle AgedProspective StudiesRisk FactorsSARS-CoV-2Severity of Illness IndexAdult intensive & critical careCOVID-19EPIDEMIOLOGYPost-Acute COVID-19 Syndrome

Identifiers

PMID42767748
PMCPMC13599834

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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.