## Protocol Section
### Identification Module
**NCT ID:** NCT06424925

**Acronym:** AI COVID-19

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

**Official Title:** 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 at the ASST of Lecco.

#### Organization Study ID Info
**ID:** AI COVID-19
#### Organization
**Class:** OTHER
**Full Name:** Azienda Ospedaliera di Lecco
### Status Module
#### Completion Date
**Date:** 2024-12-31

**Type:** ESTIMATED

#### Expanded Access Info
#### Last Update Post Date
**Date:** 2024-05-23

**Type:** ACTUAL

**Last Update Submit Date:** 2024-05-22

**Overall Status:** NOT_YET_RECRUITING

#### Primary Completion Date
**Date:** 2024-09-01

**Type:** ESTIMATED

#### Start Date
**Date:** 2024-06-01

**Type:** ESTIMATED

**Status Verified Date:** 2024-05

#### Study First Post Date
**Date:** 2024-05-22
**Type:** ACTUAL
**Study First Submit Date:** 2024-05-21
**Study First Submit QC Date:** 2024-05-21
### Sponsor Collaborators Module

#### Lead Sponsor

**Class:** OTHER

**Name:** Azienda Ospedaliera di Lecco

#### Responsible Party

**Investigator Affiliation:** Azienda Ospedaliera di Lecco

**Investigator Full Name:** Stefania Piconi

**Investigator Title:** Director of Infectious Diseases Unit

**Type:** PRINCIPAL_INVESTIGATOR

### Oversight Module

**Is FDA Regulated Device:** False

**Is FDA Regulated Drug:** False

### Description Module

**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 Module

**Conditions:**

- COVID-19 Pandemic

### Design Module

#### Design Info

**Observational Model:** COHORT

**Time Perspective:** RETROSPECTIVE

#### Enrollment Info

**Count:** 5000

**Type:** ESTIMATED

**Study Type:** OBSERVATIONAL

### Arms Interventions Module

#### Arm Group 1

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

**Intervention Names:**

- Other: Artificial intelligence for the prediction of clinical outcomes

**Label:** COVID-19 1° wave

#### Arm Group 2

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

**Intervention Names:**

- Other: Artificial intelligence for the prediction of clinical outcomes

**Label:** COVID-19 2° wave

#### Arm Group 3

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

**Intervention Names:**

- Other: Artificial intelligence for the prediction of clinical outcomes

**Label:** COVID-19 3° wave

#### Arm Group 4

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

**Intervention Names:**

- Other: Artificial intelligence for the prediction of clinical outcomes

**Label:** COVID-19 4° wave

### Interventions

#### Intervention 1

**Arm Group Labels:**

- COVID-19 1° wave

- COVID-19 2° wave

- COVID-19 3° wave

- COVID-19 4° wave

**Description:** 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

**Name:** Artificial intelligence for the prediction of clinical outcomes

**Type:** OTHER

### Outcomes Module

#### Primary Outcomes

**Description:** 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.

**Measure:** Construction of predictive models

**Time Frame:** 6 months

### Eligibility Module

**Eligibility Criteria:** Inclusion Criteria:

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

Exclusion Criteria:

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

**Minimum Age:** 18 Years

**Sampling Method:** NON_PROBABILITY_SAMPLE

**Sex:** ALL

**Standard Ages:**

- ADULT

- OLDER_ADULT

**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

### Contacts Locations Module

#### Central Contacts

**Contact 1:**

**Email:** s.piconi@asst-lecco.it

**Name:** Stefania Piconi, MD

**Phone:** +390341489890

**Role:** CONTACT

**Contact 2:**

**Email:** s.pontiggia@asst-lecco.it

**Name:** Silvia Pontiggia, MS

**Phone:** +390341253678

**Role:** CONTACT

#### Locations

**Location 1:**

**City:** Lecco

**Country:** Italy

**Facility:** Stefania Piconi

**Zip:** 23900

## Derived Section

### Condition Browse Module - Ancestors

- ID: D000011024

- Term: Pneumonia, Viral

- ID: D000012141

- Term: Respiratory Tract Infections

- ID: D000007239

- Term: Infections

- ID: D000014777

- Term: Virus Diseases

- ID: D000018352

- Term: Coronavirus Infections

- ID: D000003333

- Term: Coronaviridae Infections

- ID: D000030341

- Term: Nidovirales Infections

- ID: D000012327

- Term: RNA Virus Infections

- ID: D000008171

- Term: Lung Diseases

- ID: D000012140

- Term: Respiratory Tract Diseases

### Condition Browse Module - Browse Branches

- Abbrev: BC01

- Name: Infections

- Abbrev: BC08

- Name: Respiratory Tract (Lung and Bronchial) Diseases

- Abbrev: All

- Name: All Conditions

- Abbrev: BC23

- Name: Symptoms and General Pathology

### Condition Browse Module - Browse Leaves

- ID: M2561

- Name: COVID-19

- Relevance: HIGH

- As Found: COVID-19 Pandemic

- ID: M13904

- Name: Pneumonia

- Relevance: HIGH

- As Found: Pneumonia

- ID: M6845

- Name: Death

- Relevance: LOW

- As Found: Unknown

- ID: M13914

- Name: Pneumonia, Viral

- Relevance: LOW

- As Found: Unknown

- ID: M10283

- Name: Infections

- Relevance: LOW

- As Found: Unknown

- ID: M6368

- Name: Communicable Diseases

- Relevance: LOW

- As Found: Unknown

- ID: M14978

- Name: Respiratory Tract Infections

- Relevance: LOW

- As Found: Unknown

- ID: M17522

- Name: Virus Diseases

- Relevance: LOW

- As Found: Unknown

- ID: M20490

- Name: Coronavirus Infections

- Relevance: LOW

- As Found: Unknown

- ID: M6555

- Name: Coronaviridae Infections

- Relevance: LOW

- As Found: Unknown

- ID: M23685

- Name: Nidovirales Infections

- Relevance: LOW

- As Found: Unknown

- ID: M15149

- Name: RNA Virus Infections

- Relevance: LOW

- As Found: Unknown

- ID: M11168

- Name: Lung Diseases

- Relevance: LOW

- As Found: Unknown

- ID: M14977

- Name: Respiratory Tract Diseases

- Relevance: LOW

- As Found: Unknown

### Condition Browse Module - Meshes

- ID: D000086382

- Term: COVID-19

- ID: D000011014

- Term: Pneumonia

### Misc Info Module

- Version Holder: 2024-05-31
