C-reactive protein to albumin ratio is associated with increased risk of mortality in COVID-19 pneumonia patients

Acehan, Selen; Gülen, Müge; Isıkber, Cem; Kaya, Adem; Ünlü, Nurdan; İnce, Çağdaş; Firat, Basak Toptas; Koksaldi, Gonca; Sümbül, Hilmi Erdem; Satar, Salim

doi:10.17826/cumj.977050

Cited by 6 publications

(8 citation statements)

References 54 publications

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“…In ROC analysis, when SII was ≥813.6, AUC was 0.689, sensitivity was 70.8% and specificity was 66% (20). NLR and CAR were higher in the mortality group than in the survival group in the study by Acehan et al (21). CAR was an independent risk factor for mortality.…”

Section: Discussionmentioning

confidence: 84%

The Role of Inflammatory Parameters in the Prognosis of Patients with COVID-19

Canoğlu¹,

Çalışkan²,

Sinmez³

et al. 2022

hamidiyemedj

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Background:The prognostic significance of inflammatory parameters in patients with Coronavirus disease-2019 (COVID-19) has been investigated. Materials and Methods:Neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio, C-reactive protein (CRP) albumin ratio (CAR), systemic inflammation index (SII), CRP-lymphocyte ratio (CRP/L), neutrophil to lymphocyte, platelet ratio (NLPR), red cell volume distribution width index (RDW-SD), and procalcitonin were evaluated in relation to admission to intensive care unit (ICU) and mortality in 419 patients with moderate-to-severe COVID-19.Results: NLR, CAR, CRP/L, NLPR, RDW-SD and procalcitonin levels were higher both in those who needed ICU compared to those who did not (p=0.001, 0.005, 0.002, 0.001, 0.001 and 0.001; respectively), and in those who died compared to the survival group (p=0.001, 0.024, 0.009, 0.001, 0.001 and 0.001; respectively). SII was higher only in those who needed ICU (p=0.001). NLR (0.610, p=0.002), CAR (0.602, p=0.005), SII (0.573, p=0.043), CRP/L (0.593, p=0.010), and NLPR (0.618, p=0.001) were statistically significant for admission to ICU; and NLR (0.637, p=0.006), CAR (0.613, p=0.024), CRP/L (0.605, p=0.035) and NLPR (0.660, p=0.001) were statistically significant for mortality in the evaluation of area under curve in ROC analysis. RDW-SD was an independent risk factor for both ICU admission [odds ratio (OR): 1.194, p=0.024] and mortality (OR: 1.263, p=0.002), and procalcitonin was an independent risk factor for ICU admission (OR: 1.492, p=0.034) in multivariate analysis. Conclusion:NLR, CAR, CRP/L, NLPR, RDW-SD and procalcitonin were determined as prognostic parameters in terms of both the need for ICU and mortality in patients with COVID-19. SII was a prognostic parameter only for the need for ICU.

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Section: Discussionmentioning

confidence: 84%

The Role of Inflammatory Parameters in the Prognosis of Patients with COVID-19

Canoğlu¹,

Çalışkan²,

Sinmez³

et al. 2022

hamidiyemedj

View full text Add to dashboard Cite

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“…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%

“…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%

“…Subsequently, the full texts of 54 potentially eligible articles were reviewed. After exclusions, 23 studies with a total of 7774 participants remained and were ultimately included in the analysis 12–34 . The process of study selection is summarised in Supplementary Figure using the PRISMAflowchart.…”

Section: Resultsmentioning

confidence: 99%

“…The process of study selection is summarised in Supplementary Figure using the PRISMAflowchart. Sixteen studies reported the association of CAR with COVID‐19 outcomes, 12–27 four studies included FAR, 28–31 and three studies included both CAR and FAR 32–34 . 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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Prognostic value of novel serum biomarkers, including C‐reactive protein to albumin ratio and fibrinogen to albumin ratio, in COVID‐19 disease: A meta‐analysis

Rathore¹,

Oberoi

Iqbal

et al. 2022

Reviews in Medical Virology

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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; I 2 = 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; I 2 = 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; I 2 = 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; I 2 = 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; I 2 = 80%) and mortality (AUC = 0.81 [0.74, 0.87]; p < 0.00001; I 2 = 86%). FAR had a fair discriminatory‐power to predict COVID‐19 severity (AUC = 0.73 [0.64, 0.82]; p < 0.00001; I 2 = 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.

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Factors affecting the outcome of older adults followed in the intensive care unit according to age stages

Deniz,

Ayvat

2023

J Surg Med

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Background/Aim: Increased frailty with age along with an increase in comorbidities heighten mortality in intensive care units. According to the World Health Organization, old age is divided into three stages: 65–74 years, 75–84 years, and 85 years and older. The lengthened human lifespan leads to a growth in the number of elderly patients in intensive care units, and the need to know the factors associated with prognosis in the three stages of old age. We aimed to define factors affecting mortality in these three stages of aging and the factors that can help predict prognoses. Methods: In this retrospective cohort, data of patients over the age of 65 who were admitted to the intensive care unit of Bolu Izzet Baysal State Hospital between January 2016 and December 2020 were recorded using the hospital's automation system. Demographic data, blood tests, diagnoses and inflammatory biomarkers, such as RDW, NLR, and CAR were recorded. The data were analyzed using SPSS, and P<0.05 was considered significant. Results: In this study, 46.2% of the 1566 patients died. The most common diagnosis for admission to the intensive care unit was sepsis, and the most common comorbidity was hypertension. While neurological impairment (P<0.001), malignancy (P=0.006), and cardiac disease (P=0.004) were associated with mortality in all three stages of old age, chronic obstructive pulmonary disease was associated with mortality in the 85 years and older age group (P=0.011) and diabetes in those aged 65–74 years and 75–84 years. The APACHE II score (P<0.001) and red cell distribution width (P<0.001) were highly effective in predicting prognoses in all three stages of old age. Conclusion: In examining the factors associated with mortality in older age intensive care unit patients, we found that the APACHE II score and red cell distribution width were effective in establishing prognoses for all age groups.

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C-reactive protein to albumin ratio is associated with increased risk of mortality in COVID-19 pneumonia patients

Cited by 6 publications

References 54 publications

The Role of Inflammatory Parameters in the Prognosis of Patients with COVID-19

The Role of Inflammatory Parameters in the Prognosis of Patients with COVID-19

Prognostic value of novel serum biomarkers, including C‐reactive protein to albumin ratio and fibrinogen to albumin ratio, in COVID‐19 disease: A meta‐analysis

Factors affecting the outcome of older adults followed in the intensive care unit according to age stages

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