Covid19 Prognostic Parameters Clinical Trial
Official title:
Identification of a Clinical Score to Support the Clinician in Phase 2 of Covid-19
| Verified date | April 2021 |
| Source | University of L'Aquila |
| Contact | n/a |
| Is FDA regulated | No |
| Health authority | |
| Study type | Observational |
The aim of the study is to define the clinical and biochemical parameters that characterize COVID-19 patients with a negative prognostic evolution. Our clinical score will be capable to recognize patient with favorable prognosis or patient with poor prognosis by statistical data analysis.
| Status | Completed |
| Enrollment | 200 |
| Est. completion date | December 1, 2020 |
| Est. primary completion date | December 1, 2020 |
| Accepts healthy volunteers | No |
| Gender | All |
| Age group | 18 Years and older |
| Eligibility | Inclusion Criteria: - patients over 18 and symptomatic and positive for COVID-19 by polymerase chain reaction assay for rhino-pharingeal swab Exclusion Criteria: - Under 18 |
| Country | Name | City | State |
|---|---|---|---|
| Italy | University of L'Aquila | L'Aquila |
| Lead Sponsor | Collaborator |
|---|---|
| University of L'Aquila |
Italy,
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | Data collection of clinical and demographical parameters of patients affected by COVID-19 | Data about sex, age, symptom start date, vital parameters, comorbidity, symptoms, hematochemicals blood tests, therapy, oxygen support, radiology, condition evaluation will be manual collected. | 8 months | |
| Secondary | Application of statistical analysis on data of patients affected by COVID-19 | The collected data will be analyzed through descriptive statistics analysis, ROC curves, regression analysis, and Machine Learning techniques to predict the prognosis of patients affected by COVID-19. | 2 months |