Serum Cystatin C and Coronavirus Disease 2019: A Potential Inflammatory Biomarker in Predicting Critical Illness and Mortality for Adult Patients

Chen, Dan; Sun, Wenwu; Li, Jia; Wei, Bohua; Liu, Wei; Xiao-pin, Wang; Fan, Saijun; Chen, Liangkai; Yang, Junhui; Yu, Li

doi:10.1155/2020/3764515

Cited by 19 publications

(22 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At the time of admission, a sCys C value over 1.245 (mg/L) was highly predictive of developing a severe COVID-19 disease. Our findings were in line with a previous hospital-based study that showed the highest baseline sCys C level was associated with more severe inflammatory status and unfavorable outcomes among COVID-19 patients 22 . These findings suggest that sCys C could serve as a potential inflammatory target for preventing COVID-19 from the likely progression of critical illness and mortality, in addition to representing early renal insufficiency.…”

Section: Discussionsupporting

confidence: 93%

The predictive value of serum level of cystatin C for COVID-19 severity

lin

Chen

et al. 2021

Sci Rep

View full text Add to dashboard Cite

To investigate the potential prognostic value of Serum cystatin C (sCys C) in patients with COVID-19 and determine the association of sCys C with severe COVID-19 illness. We performed a retrospective review of medical records of 162 (61.7 ± 13.5 years) patients with COVID-19. We assessed the predictive accuracy of sCys C for COVID-19 severity by the receiver operating characteristic (ROC) curve analysis. The participants were divided into two groups based on the sCys C cut-off value. We evaluated the association between high sCys C level and the development of severe COVID-19 disease, using a COX proportional hazards regression model. The area under the ROC curve was 0.708 (95% CI 0.594–0.822), the cut-off value was 1.245 (mg/L), and the sensitivity and specificity was 79.1% and 60.7%, respectively. A multivariable Cox analysis showed that a higher level of sCys C (adjusted HR 2.78 95% CI 1.25–6.18, p = 0.012) was significantly associated with an increased risk of developing a severe COVID-19 illness. Patients with a higher sCys C level have an increased risk of severe COVID-19 disease. Our findings suggest that early assessing sCys C could help to identify potential severe COVID-19 patients.

show abstract

Section: Discussionsupporting

confidence: 93%

The predictive value of serum level of cystatin C for COVID-19 severity

lin

Chen

et al. 2021

Sci Rep

View full text Add to dashboard Cite

show abstract

“…In a study of a mixed ICU, Dyanne et al verified the prognosis value of CysC in the illness severity in critically ill patients [46]. The predictive value of Cys C in the prognosis of COVID-19 patients has also been reported by Yan Li et al [45] and Dan Chen et al [38] separately. It seemed interesting that eGFRcysc is a poor predictive factor while CysC itself could be a good predictor of mortality in critically ill patients with COVID-19.…”

Section: Discussionmentioning

confidence: 80%

“…Stevens et al [ 19 ] indicated that higher levels of serum CysC were associated with hsCRP levels and WBC counts. Recently, Chen et al [ 38 ] found the relationship between high CysC levels and severe inflammatory conditions in COVID-19 thus concluded that CysC could act as a potential inflammatory biomarker in COVID-19 patients. Based on these evidences indicating the association between CysC level and inflammation, it is reasonable that inflammatory state increased the divergence between eGFRcr and eGFRcysc.…”

Section: Discussionmentioning

confidence: 99%

“…In critically ill group, a total of 56 (73.7 %) patients died in hospital. The median time from illness onset and ICU admission to death was 29 (21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38) days and 9 (5-18) days, respectively (Table 2). Compared with survivors, non-survivors had higher levels of APACHEII, SOFA scores, D-dimer category and inflammatory markers, including WBC, IL-6, IL-8 and hsCRP (Table 3 The units of sCr and CysC were umol/L and mg/L, respectively.…”

Section: The Associations Between Egfr and Outcomementioning

confidence: 99%

See 1 more Smart Citation

Divergence between serum creatine and cystatin C in estimating glomerular filtration rate of critically ill COVID-19 patients

et al. 2021

View full text Add to dashboard Cite

Background: The clinical use of serum creatine (sCr) and cystatin C (CysC) in kidney function evaluation of critically ill patients has been in continuous discussion. The difference between estimated glomerular filtration rate calculated by sCr (eGFRcr) and CysC (eGFRcysc) of critically ill COVID-19 patients were investigated in this study. Methods: This is a retrospective, single-center study of critically ill patients with COVID-19 admitted in intensive care unit (ICU) at Wuhan, China. Control cases were moderate COVID-19 patients matched in age and sex at a ratio of 1:1. The eGFRcr and eGFRcysc were compared. The association between eGFR and death were analyzed in critically ill cases. The potential factors influencing the divergence between eGFRcr and eGFRcysc were explored. Results: A total of 76 critically ill COVID-19 patients were concluded. The mean age was 64.5 ± 9.3 years. The eGFRcr (85.45 (IQR 60.58-99.23) ml/min/1.73m 2 ) were much higher than eGFRcysc (60.6 (IQR 34.75-79.06) ml/min/1.73m 2 ) at ICU admission. About 50 % of them showed eGFRcysc < 60 ml/min/1.73 m 2 while 25% showed eGFRcr < 60 ml/min/1.73 m 2 (v 2 ¼ 10.133, p ¼ 0.001). This divergence was not observed in moderate group. The potential factors influencing the divergence included serum interleukin-6 (IL-6), tumor necrosis factor (TNF-a) level as well as APACHEII, SOFA scores. Reduced eGFRcr (<60 mL/min/1.73 m 2 ) was associated with death (HR ¼ 1.939, 95%CI 1.078-3.489, p ¼ 0.027). Conclusions: The eGFRcr was generally higher than eGFRcysc in critically ill COVID-19 cases with severe inflammatory state. The divergence might be affected by inflammatory condition and illness severity. Reduced eGFRcr predicted in-hospital death. In these patients, we advocate for caution when using eGFRcysc.

show abstract

“…Research reports have shown that Cystatin C can be used as a potential biomarker to predict the adverse outcomes of SARS-CoV-2 infection. 24 It is also an independent risk factor predicting the death of COVID-19's critically ill patients. 22 In addition, it is generally believed that SARS-CoV-2 can induce immune disorders and excessive inflammation, 25,26 which is mainly manifested in the depletion of peripheral blood lymphocytes and cytokine cascades.…”

Section: Variable Characteristics Of Patients With Mild and Severe Cases Of The Illnessmentioning

confidence: 99%

Using different machine learning models to classify patients into mild and severe cases of COVID‐19 based on multivariate blood testing

Zhang

Xiao

Zhu

et al. 2021

Journal of Medical Virology

View full text Add to dashboard Cite

COVID-19 is a serious respiratory disease. The ever-increasing number of cases is causing heavier loads on the health service system. Using 38 blood test indicators on the first day of admission for the 422 patients diagnosed with COVID-19 (from January 2020 to June 2021) to construct different machine learning (ML) models to classify patients into either mild or severe cases of COVID-19. All models show good performance in the classification between COVID-19 patients into mild and severe disease. The area under the curve (AUC) of the random forest model is 0.89, the AUC of the naive Bayes model is 0.90, the AUC of the support vector machine model is 0.86, and the AUC of the KNN model is 0.78, the AUC of the Logistic regression model is 0.84, and the AUC of the artificial neural network model is 0.87, among which the naive Bayes model has the best performance. Different ML models can classify patients into mild and severe cases based on 38 blood test indicators taken on the first day of admission for patients diagnosed with COVID-19.

show abstract

Serum Cystatin C and Coronavirus Disease 2019: A Potential Inflammatory Biomarker in Predicting Critical Illness and Mortality for Adult Patients

Cited by 19 publications

References 33 publications

The predictive value of serum level of cystatin C for COVID-19 severity

The predictive value of serum level of cystatin C for COVID-19 severity

Divergence between serum creatine and cystatin C in estimating glomerular filtration rate of critically ill COVID-19 patients

Using different machine learning models to classify patients into mild and severe cases of COVID‐19 based on multivariate blood testing

Contact Info

Product

Resources

About