C-reactive protein and albumin association with mortality of hospitalised SARS-CoV-2 patients: A tertiary hospital experience

Bannaga, Ayman; Tabuso, Maria; Farrugia, Alexia; Chandrapalan, Subashini; Somal, Karenjit; Lim, Voon Kune; Mohamed, Shahd; Nia, Gohar J.; Mannath, Jayan; Wong, John; Noufaily, Angela; Disney, Benjamin; Arasaradnam, Ramesh P.

doi:10.7861/clinmed.2020-0424

Cited by 38 publications

(35 citation statements)

References 23 publications

(30 reference statements)

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“…Hypoalbuminemia followed by massive fluid loss due to severe infection is also responsible for hypovolemia and shock in these patients [23]. Correlation of albumin levels and severity of the infection is presented through the specific CRP/albumin ratio, already marked as an independent risk factor for severe COVID-19 infection [24,25]. IL-6 induces oxidative stress and endothelial dysfunction by overexpression of the Angiotensin II type 1 receptor, which was presented 15 years ago in paperwork by Wassman et al [26].…”

Section: Discussionmentioning

confidence: 99%

Predictors of Mortality in Critically Ill COVID‐19 Patients Demanding High Oxygen Flow: A Thin Line between Inflammation, Cytokine Storm, and Coagulopathy

Popadić

Klašnja

Milić

et al. 2021

Oxidative Medicine and Cellular Longevity

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Introduction. Mortality among critically ill COVID-19 patients remains relatively high despite different potential therapeutic modalities being introduced recently. The treatment of critically ill patients is a challenging task, without identified credible predictors of mortality. Methods. We performed an analysis of 160 consecutive patients with confirmed COVID-19 infection admitted to the Respiratory Intensive Care Unit between June 23, 2020, and October 2, 2020, in University Hospital Center Bezanijska kosa, Belgrade, Serbia. Patients on invasive, noninvasive ventilation and high flow oxygen therapy with moderate to severe ARDS, according to the Berlin definition of ARDS, were selected for the study. Demographic data, past medical history, laboratory values, and CT severity score were analyzed to identify predictors of mortality. Univariate and multivariate logistic regression models were used to assess potential predictors of mortality in critically ill COVID-19 patients. Results. The mean patient age was 65.6 years (range, 29–92 years), predominantly men, 68.8%. 107 (66.9%) patients were on invasive mechanical ventilation, 31 (19.3%) on noninvasive, and 22 (13.8%) on high flow oxygen therapy machine. The median total number of ICU days was 10 (25th to 75th percentile: 6–18), while the median total number of hospital stay was 18 (25th to 75th percentile: 12–28). The mortality rate was 60% (96/160). Univariate logistic regression analysis confirmed the significance of age, CRP, and lymphocytes at admission to hospital, serum albumin, D-dimer, and IL-6 at admission to ICU, and CT score. Serum albumin, D-dimer, and IL-6 at admission to ICU were independently associated with mortality in the final multivariate analysis. Conclusion. In the present study of 160 consecutive critically ill COVID-19 patients with moderate to severe ARDS, IL-6, serum albumin, and D-dimer at admission to ICU, accompanied by chest CT severity score, were marked as independent predictors of mortality.

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Section: Discussionmentioning

confidence: 99%

Predictors of Mortality in Critically Ill COVID‐19 Patients Demanding High Oxygen Flow: A Thin Line between Inflammation, Cytokine Storm, and Coagulopathy

Popadić

Klašnja

Milić

et al. 2021

Oxidative Medicine and Cellular Longevity

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“…Kawasaki disease and acute respiratory distress syndrome are of concern to clinicians, and inclusion of CAR in the initial evaluation of hospital admissions may make it possible to identify and closely monitor patients in whom these conditions may develop. In addition, although there are currently no standardized criteria for COVID-19 patients to be admitted to intensive care units [31] , it may be possible to classify patients requiring strict monitoring and early possible therapeutic intervention by using CAR as a risk factor.…”

Section: Discussionmentioning

confidence: 99%

Diagnostic utility of C-reactive protein to albumin ratio as an early warning sign in hospitalized severe COVID-19 patients

Karakoyun

Çolak

Türken

et al. 2021

International Immunopharmacology

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“…Unlike our results which showed paraclinical and biochemical data have limited predictive value, in the model developed by Zhao et al (AUC 0.83), lactate dehydrogenase and procalcitonin were among the top mortality prediction factors [ 20 ], and the COVID-AID study showed that renal failure at presentation (defined by creatinine > 2 mg/dL), regardless of chronicity has a high impact on in-hospital mortality in hospitalized COVID-19 patients [ 21 ]. Recent studies have reported that prothrombin and CRP are associated with COIVD severity and mortality [ 22 , 23 ]. In this study, we showed the correlation of decreased O2 and increased lactate that may indicate the higher level of the anaerobic metabolism [ 24 ] in patients with COVID-19 that are associated with mortality.…”

Section: Discussionmentioning

confidence: 99%

Machine-learning-based COVID-19 mortality prediction model and identification of patients at low and high risk of dying

et al. 2021

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Background The coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-Cov2 virus has become the greatest health and controversial issue for worldwide nations. It is associated with different clinical manifestations and a high mortality rate. Predicting mortality and identifying outcome predictors are crucial for COVID patients who are critically ill. Multivariate and machine learning methods may be used for developing prediction models and reduce the complexity of clinical phenotypes. Methods Multivariate predictive analysis was applied to 108 out of 250 clinical features, comorbidities, and blood markers captured at the admission time from a hospitalized cohort of patients (N = 250) with COVID-19. Inspired modification of partial least square (SIMPLS)-based model was developed to predict hospital mortality. Prediction accuracy was randomly assigned to training and validation sets. Predictive partition analysis was performed to obtain cutting value for either continuous or categorical variables. Latent class analysis (LCA) was carried to cluster the patients with COVID-19 to identify low- and high-risk patients. Principal component analysis and LCA were used to find a subgroup of survivors that tends to die. Results SIMPLS-based model was able to predict hospital mortality in patients with COVID-19 with moderate predictive power (Q2 = 0.24) and high accuracy (AUC > 0.85) through separating non-survivors from survivors developed using training and validation sets. This model was obtained by the 18 clinical and comorbidities predictors and 3 blood biochemical markers. Coronary artery disease, diabetes, Altered Mental Status, age > 65, and dementia were the topmost differentiating mortality predictors. CRP, prothrombin, and lactate were the most differentiating biochemical markers in the mortality prediction model. Clustering analysis identified high- and low-risk patients among COVID-19 survivors. Conclusions An accurate COVID-19 mortality prediction model among hospitalized patients based on the clinical features and comorbidities may play a beneficial role in the clinical setting to better management of patients with COVID-19. The current study revealed the application of machine-learning-based approaches to predict hospital mortality in patients with COVID-19 and identification of most important predictors from clinical, comorbidities and blood biochemical variables as well as recognizing high- and low-risk COVID-19 survivors.

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C-reactive protein and albumin association with mortality of hospitalised SARS-CoV-2 patients: A tertiary hospital experience

Cited by 38 publications

References 23 publications

Predictors of Mortality in Critically Ill COVID‐19 Patients Demanding High Oxygen Flow: A Thin Line between Inflammation, Cytokine Storm, and Coagulopathy

Predictors of Mortality in Critically Ill COVID‐19 Patients Demanding High Oxygen Flow: A Thin Line between Inflammation, Cytokine Storm, and Coagulopathy

Diagnostic utility of C-reactive protein to albumin ratio as an early warning sign in hospitalized severe COVID-19 patients

Machine-learning-based COVID-19 mortality prediction model and identification of patients at low and high risk of dying

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