Severity-associated markers and assessment model for predicting the severity of COVID-19: a retrospective study in Hangzhou, China

Abstract

Background The severity of COVID-19 associates with the clinical decision making and the prognosis of COVID-19 patients, therefore, early identification of patients who are likely to develop severe or critical COVID-19 is critical in clinical practice. The aim of this study was to screen severity-associated markers and construct an assessment model for predicting the severity of COVID-19. Methods 172 confirmed COVID-19 patients were enrolled from two designated hospitals in Hangzhou, China. Ordinal logistic regression was used to screen severity-associated markers. Least Absolute Shrinkage and Selection Operator (LASSO) regression was performed for further feature selection. Assessment models were constructed using logistic regression, ridge regression, support vector machine and random forest. The area under the receiver operator characteristic curve (AUROC) was used to evaluate the performance of different models. Internal validation was performed by using bootstrap with 500 re-sampling in the training set, and external validation was performed in the validation set for the four models, respectively. Results Age, comorbidity, fever, and 18 laboratory markers were associated with the severity of COVID-19 (all P values < 0.05). By LASSO regression, eight markers were included for the assessment model construction. The ridge regression model had the best performance with AUROCs of 0.930 (95% CI, 0.914–0.943) and 0.827 (95% CI, 0.716–0.921) in the internal and external validations, respectively. A risk score, established based on the ridge regression model, had good discrimination in all patients with an AUROC of 0.897 (95% CI 0.845–0.940), and a well-fitted calibration curve. Using the optimal cutoff value of 71, the sensitivity and specificity were 87.1% and 78.1%, respectively. A web-based assessment system was developed based on the risk score. Conclusions Eight clinical markers of lactate dehydrogenase, C-reactive protein, albumin, comorbidity, electrolyte disturbance, coagulation function, eosinophil and lymphocyte counts were associated with the severity of COVID-19. An assessment model constructed with these eight markers would help the clinician to evaluate the likelihood of developing severity of COVID-19 at admission and early take measures on clinical treatment.

Prognostic value of apolipoproteins in COVID-19 patients: A systematic review and meta-analysis

“…The screening process by titles and abstracts left 32 studies for full-text review (see Excluded articles by full-text in Supplemental Table S1 ). In turn, screening by full-text left 12 studies respecting all eligibility criteria [ [13] , [14] , [15] , [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] ]. This process is summarised in a flow chart ( Fig.…”

Prognostic value of albumin-to-globulin ratio in COVID-19 patients: A systematic review and meta-analysis

“…All 31 included studies were cohort studies, and their characteristics are outlined in Table 2 and Table 3 [ [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] , [46] , [47] , [48] , [49] , [50] , [51] , [52] , [53] , [54] ]. Six studies compared the AGR values upon hospital admission of survival and non-survival COVID-19 patients, and the remaining 25 studies compared the AGR values upon hospital admission between severe and non-severe COVID-19 patients.…”

Gal-3BP in Viral Infections: An Emerging Role in Severe Acute Respiratory Syndrome Coronavirus 2

“…The detection of severity-associated biomarkers is one of the most important tools for the early individuation of patients at risk of developing ARDS, that is crucial for timely treatments [97]. Altered values of various laboratory markers, including increased levels of C-reactive protein, lactate dehydrogenase, serum amyloid A, fibrinogen, D-dimer, adenosine deaminase, and lower levels of lymphocyte, eosinophil, platelet counts, calcium, albumin, albumin/globulin, have been associated with COVID-19 severity [98]. In addition, higher levels of diverse inflammatory cytokines are associated with the disease's severity, especially IL-6, that has been demonstrated to be one of the most accurate predictors of disease course and mortality [99].…”