Materials and Methods: Four-hundred-eighty-two moderate and severe COVID-19 patients who had the data of urinalysis performed in the pre-COVID-19 period at most three months before the onset of COVID-19 diagnosis, during COVID-19 disease, and 15 days after they completely recovered from the COVID-19 disease were included in the study. Parameters of bilirubin, erythrocyte, leukocyte, protein, glucose, acidity (pH), and density were analyzed in urine samples, and the results were recorded.
Results: CRP, e-GFR, fibrinogen and D-dimer values were found to be significantly different between the three groups (for all parameters p<0.05). A negative correlation was found between e-GFR and both CRP (p<0.001, r:-0.289) and D-dimer (p:0.02, r:-0.129) values of the patients during COVID-19. Urine pH, presence of leukocyturia, presence of microscopic hematuria and presence of proteinuria were found to be significantly different between the three groups (for all parameters p<0.05). It was determined that these four parameters increased significantly during the COVID-19 period and decreased in the post-COVID-19 period. A negative correlation between urine density and e-GFR (p:0.04, r:-0.175) and a positive (p:0.02, r:0.195) correlation between urine density and CRP were detected during COVID-19.
Conclusion: The significant presence of hematuria and proteinuria during COVID-19 disease in line with the literature data supports the opinion that the disease causes renal involvement. The tendency of the parameters on the post-COVID 15th day to return to normal ranges shows that the effects of the inflammation are reversible after the patients recover from the disease.
Urinalysis covers quick, economical, useful, and noninvasive tests which provide detailed information on urine. These data can aid in the diagnosis of many diseases including urinary tract infections and can also be used in the monitorization of the outcomes of the treatment used for these diseases [7,8].
The effects of SARS-CoV-2 on urinary biochemical parameters were analyzed through comparing patient and control groups or based on the severity of the disease in previous studies but no research has yet been made both on the effect and change in urinary parameters in periods before, during, and 15 days after recovery from COVID-19 disease and also on the relationship between the change in these parameters and renal function tests and inflammatory markers. This study compared the parameters of urinalysis in periods before, during, and after recovery from pre-COVID-19 disease, and assessed the relationships between the changes in these parameters and renal functions.
RT-PCR-positive oropharyngeal and nasopharyngeal swabs prepared for the detection of SARS-CoV-2 infection revaled the diagnosis of COVID-19. Following the diagnosis of Sars- Cov-2 infection, 15-30 mL clean, middle-flow urine samples were collected for the patients. After the recovery, once the first negative RT-PCR result of these patients was obtained, urinalysis was re-taken on the post-discharge 15th day. Urine samples were drawn from the urinary catheters of the critically ill patients. Urinary parameters of bilirubin, erythrocyte, protein, glucose, acidity (pH), and urine density were analyzed semiquantitatively on Dirui- H800 FUS-2000 (Dirui Industrial Co. Ltd., China) urine biochemical analysis device, digital imaging and automatic particle definition method microscopically and the results were recorded.
Peripheral venous blood samples (5 mL) were drawn into serum separator tubes (Vacuette, Greiner Bio-One, Kremsmuenster, Austria) in the morning between 9:00 am and 10:00 am after 8 hours of fasting. Serum samples were set aside for 30 to 60 minutes to allow the formation of clots prior to centrifugation at 1500G for 10 minutes at room temperature. Results of routine biochemical, hematological, and urine analyzes were obtained by reviewing patients" records. Hematological analyses were performed using XN-1000 Sysmex (Sysmex Corporation, Kobe, Japan) hematology analyzer. All biochemical parameters were analyzed using Abbott kits (Abbott Laboratories, Chicago, IL, USA), which are manufactured for use with an Architect c16000 Auto-Analyzer.
Exclusion Criteria
Patients with underlying chronic diseases such as
hypertension, diabetes mellitus, chronic heart failure, patients
with urinary system oncological and stone disease, mild
COVID-19 that did not require hospitalization, and critically ill
COVID-19 patients that required intensive care unit care were
excluded from the study.
Statistical Analysis
The data were encrypted and entered SPSS (Version 23)
software (IBM, SPSS Inc., Chicago, Illinois, USA). The
categorical values of the patients were expressed as numbers
and percentages and analyzed with a chi-square test. Continuous
variables were presented as mean and standard deviation (SD).
Friedman and Cochrane Q-tests were used for the statistical
analysis of the three groups. P < 0.05 was considered statistically
significant.
Figure 1. Correlation analysis of e-GFR with CRP and D-dimer
Urinalysis parameters of pH value, leukocyturia, microscopic hematuria, and proteinuria differed among the three groups (for all parameters p<0.05). These three parameters had a significant increase during the COVID-19 disease and decreased in the post-COVID-19 period. No difference was detected between other urinalysis parameters. Details of urinalysis parameters are available in Table 2. The correlation analysis showed a negative correlation between urine density and eGFR (p:0.04, r:-0.175), and a positive (p:0.02, r:0.195) correlation between urine density and CRP (Figure 2).
Table 2. Details of pre-COVID-19, COVID-19, and post-COVID-19 15th day urinalysis parameters
Figure 2. Correlation analysis of urine density with e-GFR and CRP
A limited number of studies in the literature have shown the relationship between COVID-19 and urinary parameters. Current studies were conducted through the comparison of Sars-COV-2 positive and negative patients. Our study stands unique as it shows the changes in urine biochemistry in patients before the diagnosis of COVID-19 disease, during, and after recovery from this epidemic. Liu et al. reported higher urine protein, pH values, and erythrocyte counts, but lower urine density in the COVID-19 group compared to the control group [9]. Another study reported kidney involvement in 75% of COVID-19 patients, and 65.8% of these patients had proteinuria and 41.7% had hematuria [10]. Murgod et al. detected a higher rate of hematuria and proteinuria in COVID-19 patients compared to healthy controls and a significant increase in both parameters as the severity of the infection increased [6]. Demirelli et al. assessed 120 COVID-19 patients, and categorized these patients based on the severity of the disease. Respective percentages of these patients had glucosuria (6.7%), proteinuria (13.4%), urobilinogen positivity (5.8%), leukocyturia (8.3%), and hematuria (9.2%) [11].
In our study patients, we detected a significant increase in the rates of proteinuria, hematuria, and leukocyte counts during COVID-19 disease compared to the pre-COVID-19 period and a significant decrease in these parameters after recovery from the disease (p<0.05, for all parameters). Additionally, urine pH levels increased in the COVID-19, and post-COVID-19 periods of the patients. As reported in the studies, we think that the presence of proteinuria and hematuria in our study is related to renal involvement in COVID-19. Contrarily, the detection of leukocyturia associated with COVID-19 can be related to the worsening of infection or the change of bladder flora due to the medications used in hospitalized patients.
Pei et al. reported that proteinuria and microscopic hematuria were more significant in critically ill COVID-19 patients and acute kidney injury was seen at a rate of 42% among these patients while at a rate of 4.5% in the COVID-19 population in general [10]. Bonetti et al. studied the urine samples of 226 patients admitted to the emergency department and proteinuria, and microscopic hematuria were detected in 89%, and 72% of the patients, respectively. They reported that high urea and creatinine values were related to increased mortality rates and analysis of urine sediment was regarded as a useful prognostic test [5]. In their logistic regression analysis, Morell-Garcia et al. reported that among urinalysis parameters microscopic hematuria was a risk factor for acute kidney injury (AKI), intensive care requirement, and mortality [12]. Yıldırım et al. reported the presence of AKI in 4.5% of COVID-19 patients and rates of proteinuria and hematuria were 64% and 64% vs 4.8% and 43% in patients with and without AKI, respectively. Additionally, significantly higher creatinine, CRP, fibrinogen, and D-dimer levels were detected in AKI patients [13].
In this study, we aimed to statistically evaluate the change in kidney function tests in our patients during, and after recovery from the COVID-19 disease. As a matter of fact, it was determined that creatinine values increased and eGFR values decreased (1.17 ± 0.5 vs 1.36 ± 1.37, 92.1 ± 33.2 vs 88.69 ± 33.5 respectively) during COVID-19 disease compared to the pre-COVID-19 period. Although creatinine elevation occurred in most of the patients, this increase could not be described as evidence of renal failure. As a matter of fact, it has been determined that the results of kidney function tests such as eGFR, creatinine, and urea tend to return to pre-COVID-19 values after recovery from this disease. While urea, creatinine, and eGFR levels tend to decrease during COVID-19 disease, they tend to normalize in the post-COVID-19 period, but the change is significant only for eGFR (p:0.03). Although these findings support the claim that COVID-19 negatively affects renal function, our data has shown lack of any permanent change that can cause permanent kidney failure. This study has also showed a negative correlation between levels of some markers of inflammation including eGFR, CRP, and D-dimer (p<0.001, p=0.02 respectively). These findings have indicated that the severity of infection and inflammation may aggravate the adverse effects on kidney functions. Additionally, urine density during COVID-19 disease had a negative correlation with eGFR and a positive correlation with CRP. This fact can be an indicator of the relationship between infection and urine parameters.
Failure to analyze urinary sediment, urine creatinine, and electrolyte values and non-categorization of the severity of COVID-19 disease in our patients are the main limitations of this study.
Ethics Committee Approval: All procedures performed in this study involving human participants were conducted in accordance with the ethical standards of the institutional and/ or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Consent according to the Helsinski declaration was taken from local ethics committee before the study (NEU: 2020/2835; date: 27.01.2021; decision #: 88).
Informed Consent: An informed consent was obtained from all the patients.
Publication: The results of the study were not published in full or in part in form of abstracts.
Peer-review: Externally peer-reviewed.
Authorship Contributions: Any contribution was not made by any individual not listed as an author. Concept - L.O.S., M.G.S.; Design - L.O.S., M.G.S.; Supervision - L.O.S., H.V., M.G.S.; Resources - L.O.S., H.V., G.E., M.G.S.; Materials - L.O.S., H.V., G.E., M.G.S.; Data Collection and/or Processing - L.O.S., H.V., G.E., M.G.S.; Analysis and/or Interpretation - L.O.S., M.G.S.; Literature Search - L.O.S., H.V., G.E., M.G.S.; Writing Manuscript - L.O.S., M.G.S.; Critical Review - L.O.S., M.G.S.
Conflict of Interest: The authors declare that they have no conflicts of interest.
Financial Disclosure: The authors declare that this study received no financial support.
1) Fung TS, Liu DX. Human Coronavirus: Host-Pathogen
Interaction. Annu Rev Microbiol 2019;73:529-57.
https://doi.org/10.1146/annurev-micro-020518-115759
2) World Health Organization. WHO Director-General"s
remarks at the media briefing on 2019-nCoV on 11
February 2020.
https://www.who.int/dg/speeches/detail.Published
February 11, 2020.
3) Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical
features of patients infected with 2019 novel coronavirus
in Wuhan, China. Lancet 2020;395:497-506.
https://doi.org/10.1016/S0140-6736(20)30183-5
4) Kostoff RN, Briggs MB, Porter AL, Spandidos DA,
Tsatsakis A. COVID‑19 vaccine safety. Int J Mol Med
2020;46:1599-602.
https://doi.org/10.3892/ijmm.2020.4733
5) Bonetti G, Manelli F, Bettinardi A, Borrelli G, Fiordalisi
G, Marino A, et al. Urinalysis parameters for predicting
severity in coronavirus disease 2019 (COVID-19). Clin
Chem Lab Med 2020;58: e163-165.
https://doi.org/10.1515/cclm-2020-0576
6) Murgod P, Doshi P, Nimbargi R. Urine Biochemical
Parameters in Predicting Severity of SARS-CoV-2
Infection: an Experience in Tertiary Care Centre in Western
India. Iran J Pathol 2021;16:304-9.
https://doi.org/10.30699/IJP.2021.136576.2496
7) Berger RE. The urine dipstick test useful to rule out
infections. A meta-analysis of the accuracy. J Urol
2005;174:941-2.
https://pubmed.ncbi.nlm.nih.gov/16093998/
8) Erdman P, Anderson B, Zacko JC, Taylor K, Donaldson K.
The accuracy of the Sysmex UF-1000i in urine bacterial
detection compared with the standard urine analysis and
culture. Arch Pathol Lab Med 2017;141:1540-3.
https://doi.org/10.5858/arpa.2016-0520-OA
9) Liu R, Ma Q, Han H, Su H, Liu F, Wu K, et al. The value
of urine biochemical parameters in the prediction of the
severity of coronavirus disease 2019. Clin Chem Lab Med
2020;58:1121-4.
https://doi.org/10.1515/cclm-2020-0220
10) Pei G, Zhang Z, Peng J, Liu L, Zhang C, Yu C, et al. Renal
Involvement and Early Prognosis in Patients with COVID-19
Pneumonia. J Am Soc Nephrol 2020;31:1157-65.
https://doi.org/10.1681/ASN.2020030276
11) Demirelli E, Sönmez MG, Tok DS, Çetin S, Öğreden E,
Usta M, et al. The impact of Coronavirus Disease 2019
(COVID-19) on urinalysis parameters. Minerva Urol
Nephrol 2021 Jun 22. Online ahead of print.
https://pubmed.ncbi.nlm.nih.gov/34156201/