Your browser doesn't support javascript.
The Predictive Ability of the C-reactive Protein to Albumin Ratio As A Mortality Predictor in Hospitalized Severe SARS-CoV-2 Infected Patients with Cardiovascular Diseases
Haseki Tip Bulteni-Medical Bulletin of Haseki ; 60(2):152-160, 2022.
Article in English | Web of Science | ID: covidwho-1798823
ABSTRACT

Aim:

Although there are few studies on the predictive value of C-reactive protein-to-albumin ratio (CAR) in coronavirus disease-2019 (COVID-19) patients, to the best of our knowledge, there are no studies specifically conducted in COVID-19 patients with cardiovascular disease (CVD). This study assessed the use of baseline CAR levels to predict death in hospitalized COVID-19 patients with CVD.

Methods:

This study was designed as a single-center cross-sectional study. Patients diagnosed with COVID-19 who were admitted to the University of Health Sciences Turkey, Bagcilar Training and Research Hospital between April 16 and May 20, 2020 were analyzed retrospectively. The patients were divided into 2 groups those who died and those who survived, considering the follow-up period. The CAR values of the study population, as well as patients with CVD, were calculated, and the association of CAR with in-hospital mortality was evaluated.

Results:

The in-hospital mortality rate was 11.1% (49/442 pts) in all populations. Deceased patients had significantly more frequent CVD (p<0.001) and the mortality rate was 34.4% (30/96 pts) in those patients. Median CAR values were higher in nonsurvivors than among survivors (p<0.001). Multivariate analysis demonstrated that CAR was an independent predictor of mortality in patients with CVD [hazard ratio 1.013 (95% confidence interval 1.002-1.022), p=0.018].

Conclusion:

CAR is an inflammatory risk marker that independently predicts mortality in all COVID-19 hospitalized patients and patients with CVD.
Keywords

Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Prognostic study Language: English Journal: Haseki Tip Bulteni-Medical Bulletin of Haseki Year: 2022 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Prognostic study Language: English Journal: Haseki Tip Bulteni-Medical Bulletin of Haseki Year: 2022 Document Type: Article