This study will evaluate the associations between vascular parameters and clinical outcomes in patients hospitalized with COVID-19. The vascular function and structure of individuals with COVID-19 admitted to the General Hospital of the University of Sao Paulo will be assessed in the first 72 hours of hospitalization. Then, participants will be followed up until hospital discharge/death. Logistical regressions will be run to evaluate if vascular function/structure can predict ICU admissions, intubation, thrombosis or death.
This is a prospective cohort study conducted at the General Hospital of the University of São
Paulo Medical School (HCFMUSP). Male and female participants with SARS-CoV-2 and recently
admitted to the hospital (≤ 72 hours) will be recruited at the emergency department and
outpatient clinics at the HCFMUSP. Immediately upon recruitment, participants will perform
the assessment of flow mediated dilation of the brachial artery and the assessment of carotid
intima-media thickness. Subsequently, they will be followed during the entire period of
hospitalization.
The present study will employ as primary endpoint a composite of ICU admission, intubation or
mortality during the period of hospitalization. Cardiovascular complications, such as
arterial (AE), deep venous (DVP) or pulmonary embolism (PE) , acute myocardial infarction
(AMI), stroke, cardiac arrest, atrial fibrillation and acute kidney injury will be considered
secondary endpoints.
The association between the vascular parameters and clinical outcomes will be examined by a
multivariate logistic regression.
Inclusion Criteria:
- Patients diagnosed with SARS-CoV-2
- Recently admitted to the hospital (≤ 72 hours)
- Not yet proceeded to ICU care
Exclusion Criteria:
- Patients transferred from other hospitals
- Participants in delirium state
- Participants with a recent history of endotracheal intubation
Hospital das Clínicas da Faculdade de Medicina da USP - HCFMUSP
Sao Paulo, Brazil
Investigator: Tiago Peçanha, PhD
Contact: 5511948243542
tiagopecanha@usp.br
Tiago Peçanha, PhD
11948243542
tiagopecanha@usp.br