Context: A relevant portion of COVID-19 patients develop severe disease with negative outcomes. Several biomarkers have been proposed to predict COVID-19 severity, but no definite interpretative criteria have been established to date for stratifying risk. Objective: To evaluate six serum biomarkers (C-reactive protein, lactate dehydrogenase, D-dimer, albumin, ferritin and cardiac troponin T) for predicting COVID-19 severity and to define related cut-offs able to aid clinicians in risk stratification of hospitalized patients. Design: A retrospective study of 427 COVID-19 patients was performed. Patients were divided into groups based on their clinical outcome: non-survivors vs. survivors and patients admitted to intensive care unit vs. others. ROC curves and likelihood ratios were employed to define predictive cut-offs for evaluated markers. Results: Marker concentrations at peak were significantly different between groups for both selected outcomes. At univariate logistic regression analysis, all parameters were significantly associated with higher odds of death and intensive care. At the multivariate analysis, high concentrations of lactate dehydrogenase and low concentrations of albumin in serum remained significantly associated with higher odds of death, while only low lactate dehydrogenase activities remained associated with lower odds of intensive care admission. The best cut-offs for death prediction were >731 U/L for lactate dehydrogenase and ≤18 g/L for albumin, while a lactate dehydrogenase activity <425 U/L was associated with a negative likelihood ratio of 0.10 for intensive treatment. Conclusions: Our study identifies which biochemistry tests represent major predictors of COVID-19 severity and defines the best cut-offs for their use.

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ObjectivesProcalcitonin (PCT) has been proposed for differentiating viral vs. bacterial infections. In COVID-19, some preliminary results have shown that PCT testing could act as a predictor of bacterial co-infection and be a useful marker for assessment of disease severity.MethodsWe studied 83 COVID-19 hospitalized patients in whom PCT was specifically ordered by attending physicians. PCT results were evaluated according to the ability to accurately predict bacterial co-infections and death in comparison with other known biomarkers of infection and with major laboratory predictors of COVID-19 severity.ResultsThirty-three (39.8%) patients suffered an in-hospital bacterial co-infection and 44 (53.0%) patients died. In predicting bacterial co-infection, PCT showed a relatively low accuracy (area under receiver-operating characteristic [ROC] curve [AUC]: 0.757; 95% confidence interval [CI]: 0.651–0.845), with a strength for detecting the outcome not significantly different from that of white blood cell count and C-reactive protein (CRP). In predicting patient death, PCT showed an AUC of 0.815 (CI: 0.714–0.892), not better than those of other more common laboratory tests, such as blood lymphocyte percentage (AUC: 0.874, p=0.19), serum lactate dehydrogenase (AUC: 0.860, p=0.47), blood neutrophil count (AUC: 0.845, p=0.59), and serum albumin (AUC: 0.839, p=0.73).ConclusionsProcalcitonin (PCT) testing, even when appropriately ordered, did not provide a significant added value in COVID-19 patients when compared with more consolidated biomarkers of infection and poor clinical outcome. The major application of PCT in COVID-19 is its ability, associated with a negative predictive value >90%, to exclude a bacterial co-infection when a rule-out cut-off (<0.25 μg/L) is applied.

Objectives Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial disease with limited therapeutic options. The measurement of Krebs von den Lungen-6 (KL-6) glycoprotein has been proposed for evaluating the risk of IPF progression and predicting patient prognosis, but the robustness of available evidence is unclear. Methods We searched Medline and Embase databases for peer-reviewed literature from inception to April 2020. Original articles investigating KL-6 as prognostic marker for IPF were retrieved. Considered outcomes were the risk of developing acute exacerbation (AE) and patient survival. Meta-analysis of selected studies was conducted, and quantitative data were uniformed as odds ratio (OR) or hazard ratio (HR) estimates, with corresponding 95% confidence intervals (CI). Results Twenty-six studies were included in the systematic review and 14 were finally meta-analysed. For AE development, the pooled OR (seven studies) for KL-6 was 2.72 (CI 1.22–6.06; p=0.015). However, a high degree of heterogeneity (I2=85.6%) was found among selected studies. Using data from three studies reporting binary data, a pooled sensitivity of 72% (CI 60–82%) and a specificity of 60% (CI 52–68%) were found for KL-6 measurement in detecting insurgence of AE in IPF patients. Pooled HR (seven studies) for mortality prediction was 1.009 (CI 0.983–1.036; p=0.505). Conclusions Although our meta-analysis suggested that IPF patients with increased KL-6 concentrations had a significant increased risk of developing AE, the detection power of the evaluated biomarker is limited. Furthermore, no relationship between biomarker concentrations and mortality was found. Caution is also needed when extending obtained results to non-Asian populations.