Use of Artificial Intelligence (AI) to Predict Clinical Outcomes in Patients Hospitalized for COVID19 Pneumonia During the 4 Pandemic Waves

NCT06424925 | Not Yet Recruiting

• 1 other identifier: AI COVID-19
• Study Type: observational
• Target: 5,000
• Locations: 1 country
• Sites: 1

Brief Summary

Predictive models can be applied in different areas, during the emergency of the COVID-19 pandemic, in fact, they have proven important in supporting health systems in planning strategic decisions and in formulating health policies for the containment of the disease. The Covid-19 pandemic, in particular, has represented a real challenge for our healthcare system. In Italy, it was divided into four main waves, each characterized by different types of patients and different therapeutic approaches progressively improved based on new scientific evidence. The objective is to carry out a study on the data of patients hospitalized for COVID-19 at the ASST of Lecco during all four pandemic waves, with different degrees of severity of illness, collecting the data of interest and applying it to they use artificial intelligence to identify recurring patterns of clinical outcome in terms of survival and secondary infectious complications, so as to build new reliable predictive statistical models that can be used to predict the outcome of the patients themselves. The strong ambition of this project is that the application of artificial intelligence to data of such significant quantity can allow us to build valid statistical models which can then be hypothetically applied to any patient to predict, based on anamnestic characteristics, blood chemical parameters. at baseline and at the set treatment, the probability of survival and complications

Conditions

COVID-19 Pandemic

Outcome Measures

Primary Outcomes (1)

• Construction of predictive models

  Construction of predictive models to evaluate clinical outcomes such as death and/or onset of secondary infection based on the data collected relating to the 4 COVID-19 waves.

  6 months

Study Arms (4)

COVID-19 1° wave

Hospitalized patients for COVID19 pneumonia during first wave (FEB-MAY 2020)

Other: Artificial intelligence for the prediction of clinical outcomes

COVID-19 2° wave

Hospitalized patients for COVID19 pneumonia during the second wave (OCT-DEC 2020)

Other: Artificial intelligence for the prediction of clinical outcomes

COVID-19 3° wave

Hospitalized patients for COVID19 pneumonia during the third wave (GEN-MAY 2021)

Other: Artificial intelligence for the prediction of clinical outcomes

COVID-19 4° wave

Hospitalized patients for COVID19 pneumonia during the fourth wave (NOV 2021-MAR 2022)

Other: Artificial intelligence for the prediction of clinical outcomes

Interventions

Artificial intelligence for the prediction of clinical outcomes OTHER

Use of artificial intelligence (AI) for the prediction of clinical outcomes such as death and complications in patients hospitalized for COVID pneumonia during the 4 pandemic waves

COVID-19 1° wave; COVID-19 2° wave; COVID-19 3° wave; COVID-19 4° wave

Eligibility Criteria

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

Study Population

For each patient, information will be collected regarding: * Personal data (i.e. age, sex, nationality); * Date of hospitalization and discharge (or death) * Comorbidities; * Treatments undertaken for Covid19; * Possible vaccination for Covid19, date and number of doses; * Possible onset of secondary infections and/or complications; * Blood chemistry tests upon admission

You may qualify if:

• Age \> 18 years;
• Hospitalization for COVID-19 pneumonia at ASST Lecco.

You may not qualify if:

• Hospitalization or finding of asymptomatic SARS CoV-2 infection.

Sponsors & Collaborators

• Azienda Ospedaliera di Lecco: lead

Study Sites (1)

Stefania Piconi

Lecco, 23900, Italy

Location

MeSH Terms

Conditions

COVID-19

Interventions

Artificial Intelligence

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

Intervention Hierarchy (Ancestors)

Algorithms; Mathematical Concepts

Central Study Contacts

Stefania Piconi, MD

CONTACT

+390341489890; s.piconi@asst-lecco.it

Silvia Pontiggia, MS

CONTACT

+390341253678; s.pontiggia@asst-lecco.it

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director of Infectious Diseases Unit

Study Record Dates

• First Submitted: May 21, 2024
• First Posted: May 22, 2024
• Study Start: June 1, 2024
• Primary Completion: September 1, 2024
• Study Completion: December 31, 2024
• Last Updated: May 23, 2024

Record last verified: 2024-05

Locations

IT (1)