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Objective: COVID-19 is life-threatening, and the main cause of mortality is immune organ damage, especially ARDS, which develops because of an uncontrolled inflammatory response. Although a timely and effective anti-inflammatory treatment reflects positively on the prognosis, early markers are needed for aggressive treatment. Therefore, we examined the predictive role of fibrinogen/Albumin ratio (FAR) and D-dimer/Albumin ratio (DAR), which are suggest as valuable markers in systemic inflammation, for COVID-19 mortality in intensive care patients. Materials-Methods: In our study, patients hospitalized in the intensive care unit with the diagnosis of COVID-19 between 20.10.2021-27.03.2022 were evaluated retrospectively and 101 patients were included in the study. Fibrinogen, D-dimer, and albumin (ALB) levels of the patients during admission to and discharge from the intensive care unit (discharge- at most one day before death) were recorded. Our patients were divided into two subgroups as surviving (n: 53) and non-surviving (n: 48). DAR and FAR were calculated as ug/g and mg/g units respectively. The SPSS IMB program was used for statistical analysis. Result(s): In our study, the mean age of our patients was 71.1+/-.16.5 (69.9+/-17.8 for women, 72.4+/-15.3 for men). 51% (n:52) of the patients were female, 49% (n:49) were male, and 12% had no additional disease. The mean hospital stay of the patients was 23.90 (3-108) days, and there was no significant difference between the surviving and non-surviving groups (0.765). When we compared the survivor and non-survivor patient groups, there was no significant difference between the hospitalization FAR and DAR of the patients. However, a significant difference was found between the output FAR and DAR. (P = 0.012 and P = 0.001, respectively). The area under the curve (AUC) to predict COVID-19 mortality for DAR was higher than the FAR. In the multivariate Cox regression analysis, the odds ratio was 1.003 (1.000-.1.005) for FAR and 1.001 (1.000-1.002) for DAR and was determined as an independent risk in predicting mortality. Conclusion(s): DAR may be more useful than FAR in the early differentiation of mortality in COVID-19 patients, but the explanatory power of DAR is not high enough. In addition, our study is a preliminary study.Copyright © 2022 De Gruyter. All rights reserved.
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BACKGROUND: Coronavirus disease 2019 (COVID-19) pandemic unmasked the huge deficit in healthcare resources worldwide. It highlighted the need for efficient risk stratification in management of cardiovascular emergencies. AIM: To study the applicability of the old, available and affordable nonconventional biomarkers: albumin and fibrinogen in their ability to predict angiographic severity and clinical outcomes in patients with acute coronary syndrome (ACS). METHODS: In this prospective, observational study, 166 consecutive patients with ACS were enrolled. Fibrinogen, albumin and their ratio were determined from serum. Patients with underlying chronic liver disease, active malignancy, autoimmune disease, active COVID-19 infection and undergoing thrombolysis were excluded. RESULTS: Mean age of the population was 60.5 ± 1.5 years, 74.1% being males. ST elevation myocardial infarction (STEMI) was most common presentation of ACS seen in 57% patients. Fibrinogen albumin ratio (FAR) ≥ 19.2, had a sensitivity of 76.9% and specificity of 78.9 % [area under the receiver operating characteristic curves (AUROC) = 0.8, P = 0.001] to predict ≤ thrombolysis in myocardial infarction (TIMI) 1 flow in culprit artery in STEMI patients. Even in non-STEMI patients, FAR ≥ 18.85 predicted the same with 80% sensitivity and 63% specificity (AUROC = 0.715, P = 0.006). CONCLUSION: Novel biomarkers, with their high cost, lack of availability and long turn over time are impractical for real-world use. Identifying ≤ TIMI 1 flow in the culprit artery has significant impact of management and outcome. Our study has shown that readily available biomarkers like fibrinogen and albumin can help identify these high-risk patients with good accuracy. This allows risk-stratification and individualization of treatment in ACS.
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With COVID-19 still hovering around and threatening the lives of many at-risk patients, an effective, quick, and inexpensive prognostic method is required. Few studies have shown fibrinogen to albumin ratio (FAR) and C-reactive protein to albumin ratio (CAR) to be promising as prognostic markers for COVID-19 disease. However, their implications remain unclear. This meta-analysis aimed to elucidate the prognostic role of FAR and CAR in COVID-19 disease. A systematic literature search was undertaken using PubMed and Embase till April 2022. Inverse variance standardised mean difference (SMD) was calculated to report the overall effect size using random effect models. The generic inverse variance random-effects method was used to pool the area under the curve (AUC) values. All statistical analyses were performed on Revman and MedCalc Software. A total of 23 studies were included. COVID-19 non-survivors had a higher CAR on admission compared with survivors (SMD = 1.79 [1.04, 2.55]; p < 0.00001; I2 = 97%) and patients with a severe COVID-19 infection had a higher CAR on admission than non-severe patients (SMD = 1.21 [0.54, 1.89]; p = 0.0004; I2 = 97%). Similarly, higher mean FAR values on admission were significantly associated with COVID-19 mortality (SMD = 0.55 [0.32, 0.78]; p < 0.00001; I2 = 82%). However, no significant association was found between mean FAR on admission and COVID-19 severity (SMD = 0.54 [-0.09, 1.18]; p = 0.09; I2 = 91%). The pooled AUC values found that CAR had a good discriminatory-power to predict COVID-19 severity (AUC = 0.81 [0.75, 0.86]; p < 0.00001; I2 = 80%) and mortality (AUC = 0.81 [0.74, 0.87]; p < 0.00001; I2 = 86%). FAR had a fair discriminatory-power to predict COVID-19 severity (AUC = 0.73 [0.64, 0.82]; p < 0.00001; I2 = 89%). Overall, CAR was a good predictor of both severity and mortality associated with COVID-19 infection. Similarly, FAR was a satisfactory predictor of COVID-19 mortality but not severity.
Subject(s)
C-Reactive Protein , COVID-19 , Humans , C-Reactive Protein/metabolism , Prognosis , COVID-19/diagnosis , Biomarkers , Fibrinogen/analysisABSTRACT
Although the fibrinogen-to-albumin ratio (F/R ratio) has been used as an inflammation marker to predict clinical outcomes in patients with cardiovascular diseases, its association with the prognosis of patients with coronavirus disease 2019 (COVID-19) remains unclear. Electronic databases including EMBASE, MEDLINE, Google Scholar, and Cochrane Library were searched from inception to 20 June 2022. The associations of F/R ratio with poor prognosis (defined as the occurrence of mortality or severe disease) were investigated in patients with COVID-19. A total of 10 studies (seven from Turkey, two from China, one from Croatia) involving 3675 patients published between 2020 and 2022 were eligible for quantitative syntheses. Merged results revealed a higher F/R ratio in the poor prognosis group (standardized mean difference: 0.529, p < 0.001, I2 = 84.8%, eight studies) than that in the good prognosis group. In addition, a high F/R ratio was associated with an increased risk of poor prognosis (odds ratio: 2.684, I2 = 59.5%, five studies). Pooled analysis showed a sensitivity of 0.75, specificity of 0.66, and area under curve of 0.77 for poor prognosis prediction. In conclusion, this meta-analysis revealed a positive correlation between F/A ratio and poor prognostic outcomes of COVID-19. Because of the limited number of studies included, further investigations are warranted to support our findings.
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INTRODUCTION: Coronavirus disease 2019 (COVID-19) is an inflammatory disease, and serum albumin and fibrinogen are two important factors in systemic inflammation. We aimed to investigate the relationship between the fibrinogen-to-albumin ratio (FAR) and in-hospital mortality in COVID-19 patients admitted to the intensive care unit (ICU). MATERIAL AND METHODS: Patients diagnosed with COVID-19 admitted to the Adiyaman Training and Research Hospital from August to November 2020 were enrolled in this retrospective cohort study. They were divided into 2 groups based on in-hospital mortality: a survivor group (n = 188) and a non-survivor group (n = 198). FAR was calculated by dividing the fibrinogen value by the albumin value. Mortality outcomes were followed up until December 15, 2020. RESULTS: The average age of the patients was 71.2 ± 12.9 years, and 54% were male. On multivariate logistic analysis, diabetes mellitus (OR: 1.806; 95% CI: 1.142-2.856; p = 0.011), troponin I levels (OR: 1.776; 95% CI: 1.031-3.061; p = 0.038), and FAR (OR: 1.004; 95% CI: 1.004-1.007; p = 0.010) at ICU admission were independent predictors of in-hospital mortality in patients with COVID-19. CONCLUSIONS: The FAR at admission was associated with mortality in patients infected with SARS-CoV-2 in the ICU.
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Concomitant coagulation disorder can occur in severe patients withCOVID-19, but in-depth studies are limited. This study aimed to describe the parameters of coagulation function of patients with COVID-19 and reveal the risk factors of developing severe disease. This study retrospectively analyzed 113patients with SARS-CoV-2 infection in Taizhou Public Health Center. Clinical characteristics and indexes of coagulation function were collected. A multivariate Cox analysis was performed to identify potential biomarkers for predicting disease progression. Based on the results of multivariate Cox analysis, a Nomogram was built and the predictive accuracy was evaluated through the calibration curve, decision curve, clinical impact curve, and Kaplan-Meier analysis. Sensitivity, specificity, predictive values were calculated to assess the clinical value. The data showed that Fibrinogen, FAR, and D-dimer were higher in the severe patients, while PLTcount, Alb were much lower. Multivariate Cox analysis revealed that FAR and PLT count were independent risk factors for disease progression. The optimal cutoff values for FAR and PLT count were 0.0883 and 135*109/L, respectively. The C-index [0.712 (95% CI = 0.610-0.814)], decision curve, clinical impact curve showed that Nomogram could be used to predict the disease progression. In addition, the Kaplan-Meier analysis revealed that potential risk decreased in patients with FAR<0.0883 and PLT count>135*109/L.The model showed a good negative predictive value [(0.9474 (95%CI = 0.845-0.986)].This study revealed that FAR and PLT count were independent risk factors for severe illness and the severity of COVID-19 might be excluded when FAR<0.0883 and PLT count>135*109/L.