2021
DOI: 10.32322/jhsm.945522
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Predictive value of C-reactive protein/albumin ratio in predicting poor outcome of hospitalized patients with COVID-19

Abstract: Introduction: For more than a year, COVID-19 has caused a high number of mortality and morbidity, and negatively affects life all over the world. Early detection tools that can be used to predict prognosis are particularly important in patients who need critical care. Among the acute phase reactants, CRP can be higher without any other findings. Otherwise, the cytokine storm that occurs in hospitalized COVID-19 cases can cause critical hypoalbuminemia, and low albumin levels can predict the course of the disea… Show more

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Cited by 4 publications
(5 citation statements)
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“…Our study presents similar findings with the studies evaluating the relationship between CRP/Albumin ratio and MV need in COVID-19 patients [24]. While it has been stated in the literature that a higher CRP/Albumin ratio increases mortality, in our study, the CRP/Albumin ratio is found similar in deceased and survived patients [25]. In another study evaluating mortality in COVID-19 patients with hypertension, it was found that the CRP/Albumin ratio was significantly associated with the length of hospitalization [28].…”
Section: Discussionsupporting
confidence: 91%
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“…Our study presents similar findings with the studies evaluating the relationship between CRP/Albumin ratio and MV need in COVID-19 patients [24]. While it has been stated in the literature that a higher CRP/Albumin ratio increases mortality, in our study, the CRP/Albumin ratio is found similar in deceased and survived patients [25]. In another study evaluating mortality in COVID-19 patients with hypertension, it was found that the CRP/Albumin ratio was significantly associated with the length of hospitalization [28].…”
Section: Discussionsupporting
confidence: 91%
“…Likewise, our study shows that CRP/Albumin ratio is significantly related to the lung infiltration, the need for ICU and/or MV. Additionally, prognostic parameter to predict the increasing risk for poor prognosis may be useful for reducing the burden of the disease on functioning of health systems [25].…”
Section: Discussionmentioning
confidence: 99%
“…After exclusions, 23 studies with a total of 7774 participants remained and were ultimately included in the analysis. 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 The process of study selection is summarised in Supplementary Figure 1 using the PRISMAflowchart. Sixteen studies reported the association of CAR with COVID‐19 outcomes, 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 four studies included FAR, 28 , 29 , 30 , 31 and three studies included both CAR and FAR.…”
Section: Resultsmentioning
confidence: 99%
“… 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 The process of study selection is summarised in Supplementary Figure 1 using the PRISMAflowchart. Sixteen studies reported the association of CAR with COVID‐19 outcomes, 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 four studies included FAR, 28 , 29 , 30 , 31 and three studies included both CAR and FAR. 32 , 33 , 34 Table 1 outlines the study characteristics of the included articles, while Table 2 summarises the optimal cut‐off, the area under the curve (AUC), sensitivity, and specificity of CAR and FAR for predicting COVID‐19 mortality and severity.…”
Section: Resultsmentioning
confidence: 99%
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