Development and Validation of a Prediction Model for the Transition From Mild to Moderate Form of COVID-19, Using Data From Chest CT

NCT04481620 | Completed

• 1 other identifier: CHUBX 2020/23
• Study Type: observational
• Target: 1,329
• Locations: 1 country
• Sites: 7

Brief Summary

Only 5% of patients infected with COVID-19 develop severe or critical Coronavirus disease 2019 (COVID-19) and there is no reliable risk stratification tool for non-severe COVID-19 patients at admission. Finding a way to predict which patients with an initial mild to moderate presentation of COVID-19 would develop severe or critical form of COVID-19 according to CT-scan data, simple clinical and biological parameters is challenging. In this multicentric study, the study aims to construct a predictive score for early identification of cases at high risk of progression to moderate, severe or critical COVID-19 combining simple clinical and biological parameters and qualitative, quantitative or artificial intelligence (AI) data from the initial CT from non-severe patients.

Conditions

COVID-19

Keywords

COVID-19; SARS-CoV-2; CT; prediction score; prognosis; mild-to moderate form

Outcome Measures

Primary Outcomes (1)

• occurrence of significant clinical degradation

  The primary outcome is defined by the occurrence of significant clinical degradation within 30 days following the initial chest CT. Significant clinical degradation is defined by the transition from the mild to the moderate form of COVID-19, i.e., according to the WHO criteria, the requirement of oxygen between 3 and 5 L / min to achieve saturation greater than 97% and a respiratory rate \<25 / min without the need for invasive ventilation.

  Day 30 following the initial chest CT

Secondary Outcomes (6)

• occurrence of a severe form

  Day 30 following the initial chest CT

• occurrence of an orotracheal intubation

  Day 30 following the initial chest CT

• occurrence of an Acute Respiratory Distress Syndrom

  Day 30 following the initial chest CT

• average length of stay in hospital

  Month 1

• mortality

  Day 30 following the initial chest CT

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients with suspicion of Covid-19

You may qualify if:

• First chest CT, assessed for respiratory symptoms, without injection of contrast agent for respiratory symptoms, and whose results of the CT subjective visual analysis are compatible or typical of COVID-19
• biological diagnosis of COVID-19 (RT-PCR) or clinical suspicion (cough and / or dyspnea and / or fever and / or need to use oxygen therapy as part of routine care) at the time of the examination
• Authorization of the patient for the processing of his personal data, except CNIL exemption

You may not qualify if:

• Patient with a moderate (oxygen between 3 and 5 L / min to achieve saturation greater than 97% and a respiratory rate \<25 / min without the need for invasive ventilation), severe form (oxygen therapy\> 5L / min to obtain a SpO2\> 97%) or critical form (need to resort to ventilation and / or orotracheal intubation) at the date of the first chest CT
• Age \< 18 years old
• Patient deprived of liberty by judicial decision

Sponsors & Collaborators

• University Hospital, Bordeaux: lead
• Programme Hospitalier de Recherche Clinique Inter-Régionale (PHRC-I): collaborator

Study Sites (7)

CHU Bordeaux

Bordeaux, France

Location

Clinique Bordeaux Nord

Bordeaux, France

Location

Clinique Saint Augustin

Bordeaux, France

Location

CHU de Grenoble Alpes

Grenoble, France

Location

Hôpital Arnaud-de-Villeneuve CHU de Montpellier

Montpellier, France

Location

Hôpitaux de Brabois CHU de Nancy

Nancy, France

Location

Hôpital de la Milétrie CHU de Poitiers

Poitiers, France

Location

Related Publications (1)

• Zysman M, Asselineau J, Saut O, Frison E, Oranger M, Maurac A, Charriot J, Achkir R, Regueme S, Klein E, Bommart S, Bourdin A, Dournes G, Casteigt J, Blum A, Ferretti G, Degano B, Thiebaut R, Chabot F, Berger P, Laurent F, Benlala I. Development and external validation of a prediction model for the transition from mild to moderate or severe form of COVID-19. Eur Radiol. 2023 Dec;33(12):9262-9274. doi: 10.1007/s00330-023-09759-x. Epub 2023 Jul 5.

  PMID: 37405504 DERIVED

MeSH Terms

Conditions

COVID-19

Condition Hierarchy (Ancestors)

Pneumonia, Viral; Pneumonia; Respiratory Tract Infections; Infections; Virus Diseases; Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; RNA Virus Infections; Lung Diseases; Respiratory Tract Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 20, 2020
• First Posted: July 22, 2020
• Study Start: August 31, 2020
• Primary Completion: May 4, 2021
• Study Completion: May 4, 2021
• Last Updated: April 12, 2022

Record last verified: 2022-04

Data Sharing

• IPD Sharing: Will not share

Locations

FR (7)