Background: As coronavirus disease 2019 (COVID-19) pandemic rages on, there is urgent need for identification of clinical and laboratory predictors for progression towards severe and fatal forms of this illness. In this study we aimed to evaluate the discriminative ability of hematologic, biochemical and immunologic biomarkers in patients with and without the severe or fatal forms of COVID-19. Methods: An electronic search in Medline (PubMed interface), Scopus, Web of Science and China National Knowledge Infrastructure (CNKI) was performed, to identify studies reporting on laboratory abnormalities in patients with COVID-19. Studies were divided into two separate cohorts for analysis: severity (severe vs. non-severe and mortality, i.e. non-survivors vs. survivors). Data was pooled into a meta-analysis to estimate weighted mean difference (WMD) with 95% confidence interval (95% CI) for each laboratory parameter. Results: A total number of 21 studies was included, totaling 3377 patients and 33 laboratory parameters. While 18 studies (n = 2984) compared laboratory findings between patients with severe and non-severe COVID-19, the other three (n = 393) compared survivors and non-survivors of the disease and were thus analyzed separately. Patients with severe and fatal disease had significantly increased white blood cell (WBC) count, and decreased lymphocyte and platelet counts compared to non-severe disease and survivors. Biomarkers of inflammation, cardiac and muscle injury, liver and kidney function and coagulation measures were also significantly elevated in patients with both severe and fatal COVID-19. Interleukins 6 (IL-6) and 10 (IL-10) and serum ferritin were strong discriminators for severe disease. Conclusions: Several biomarkers which may potentially aid in risk stratification models for predicting severe and fatal COVID-19 were identified. In hospitalized patients with respiratory distress, we recommend clinicians closely monitor WBC count, lymphocyte count, platelet count, IL-6 and serum ferritin as markers for potential progression to critical illness.

Identification of predictors of long COVID-19 is essential for managing healthcare plans of patients. This systematic literature review and meta-analysis aimed to identify risk factors not associated with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, but rather potentially predictive of the development of long COVID-19. MEDLINE, CINAHL, PubMed, EMBASE, and Web of Science databases, as well as medRxiv and bioRxiv preprint servers were screened through 15 September 2022. Peer-reviewed studies or preprints evaluating potential pre-SARS-CoV-2 infection risk factors for the development of long-lasting symptoms were included. The methodological quality was assessed using the Quality in Prognosis Studies (QUIPSs) tool. Random-effects meta-analyses with calculation of odds ratio (OR) were performed in those risk factors where a homogenous long COVID-19 definition was used. From 1978 studies identified, 37 peer-reviewed studies and one preprint were included. Eighteen articles evaluated age, sixteen articles evaluated sex, and twelve evaluated medical comorbidities as risk factors of long COVID-19. Overall, single studies reported that old age seems to be associated with long COVID-19 symptoms (n = 18); however, the meta-analysis did not reveal an association between old age and long COVID-19 (n = 3; OR 0.86, 95% CI 0.73 to 1.03, p = 0.17). Similarly, single studies revealed that female sex was associated with long COVID-19 symptoms (n = 16); which was confirmed in the meta-analysis (n = 7; OR 1.48, 95% CI 1.17 to 1.86, p = 0.01). Finally, medical comorbidities such as pulmonary disease (n = 4), diabetes (n = 1), obesity (n = 6), and organ transplantation (n = 1) were also identified as potential risk factors for long COVID-19. The risk of bias of most studies (71%, n = 27/38) was moderate or high. In conclusion, pooled evidence did not support an association between advancing age and long COVID-19 but supported that female sex is a risk factor for long COVID-19. Long COVID-19 was also associated with some previous medical comorbidities.

Since previous evidence has demonstrated that red blood cell distribution width (RDW) may be a useful prognostic parameter in many critical illnesses and infectious diseases, we investigated the utility of RDW for monitoring patients with coronavirus disease 2019 (COVID-19). The study population consisted of 49 COVID-19 patients, including 16 (32.6%) with severe illness, 12 (24.5%) with severe acute kidney injury (AKI), and 8 (16.3%) requiring renal replacement therapy (RRT). The predictive value of blood tests, performed during emergency department evaluation, was then addressed. A progressive increase of RDW was observed with advancing COVID-19 severity. The area under the curve (AUC) of RDW was 0.73 for predicting severe illness, 0.80 for severe AKI, and 0.83 for RRT, respectively. In multivariate analysis, elevated RDW was associated with 9-fold and 16-fold increased odds of severe COVID-19 and AKI, respectively. The results of this study suggest that RDW should be part of routine laboratory assessment and monitoring of COVID-19.