PHenotyping patiENts Admitted to Hospital With cOvid-19 Infection and idenTifYing Prognostic markErs

NCT ID: NCT04459351

Last Updated: 2021-08-09

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

500 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-06-19

Study Completion Date

2023-06-30

Brief Summary

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PHENOTYPE is an investigator-led, observational cohort study which aims to explore the long-term outcomes of patients with COVID-19 infection and to identify potential risk factors and biomarkers that can prognosticate disease severity and trajectory.

Detailed Description

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In 2019, a novel coronavirus, SARS-CoV-2 was first identified in Wuhan, China. SARS-CoV-2 infection, denominated COVID-19, causes a predominantly respiratory illness, which varies from mild respiratory symptoms to multi-organ failure and death. In March 2020, COVID-19 was designated pandemic status and as of May 2020 there have been more than 3.7 million cases reported worldwide and 257,000 deaths attributed. In the UK, COVID-19 has caused more than 30,000 deaths to date.

Although respiratory symptoms are the commonest presentation, numerous systemic complications of COVID-19 have been identified, including those affecting the cardiovascular, neurological, gastroenterological, and renal systems. The long-term impact of these complications on survivors and the risk factors for long term sequelae is not presently known. It is likely that increased frailty and psychological sequelae will be significant, which could lead to a persistent reduction in quality of life, as observed in the previous SARS pandemic.

This cohort study aims to evaluate the respiratory, cardiac, renal and psychological outcomes of patients diagnosed with COVID-19 infection and determine the pathophysiological mechanisms that contribute to disease severity and disease burden.

Conditions

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Coronavirus Corona Virus Infection COVID-19 2019nCoV 2019 Novel Coronavirus Infection

Study Design

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Observational Model Type

COHORT

Study Time Perspective

OTHER

Eligibility Criteria

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Inclusion Criteria

* Aged 18 years or older
* Confirmed COVID-19 infection (as per national guidelines)
* Attending follow-up outpatient visit post hospital attendance with COVID-19 infection
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Chelsea and Westminster NHS Foundation Trust

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Pallav Shah, MBBS, MD

Role: PRINCIPAL_INVESTIGATOR

Chelsea and Westminster NHS Foundation Trust

Locations

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Chelsea and Westminster Hospital

London, , United Kingdom

Site Status RECRUITING

Countries

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United Kingdom

Central Contacts

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Research Delivery Operations Manager

Role: CONTACT

020 3315 6825

Pallav Shah, MBBS, MD

Role: CONTACT

02087468063

Facility Contacts

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Research Delivery Operations Manager

Role: primary

020 3315 6825

References

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Wong, S., Vaughan, A., Quilty-Harper, C. & Liverpool,L. Black people in England and Wales twice as likely to die with covid-19. New Scientist. 2020. Available from: https://www.newscientist.com/article/2237475-covid-19-news-uk-economy-shrank-at-fastest-pace-since-2008/[Accessed: 10th May 2020]

Reference Type BACKGROUND

Chan KS, Zheng JP, Mok YW, Li YM, Liu YN, Chu CM, Ip MS. SARS: prognosis, outcome and sequelae. Respirology. 2003 Nov;8 Suppl(Suppl 1):S36-40. doi: 10.1046/j.1440-1843.2003.00522.x.

Reference Type BACKGROUND
PMID: 15018132 (View on PubMed)

Vijayakumar B, Tonkin J, Devaraj A, Philip KEJ, Orton CM, Desai SR, Shah PL. CT Lung Abnormalities after COVID-19 at 3 Months and 1 Year after Hospital Discharge. Radiology. 2022 May;303(2):444-454. doi: 10.1148/radiol.2021211746. Epub 2021 Oct 5.

Reference Type DERIVED
PMID: 34609195 (View on PubMed)

Other Identifiers

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C&W20/035

Identifier Type: -

Identifier Source: org_study_id

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