The value of urinalysis in predicting acute kidney injury and mortality in COVID-19 patients

Kidney involvement is frequent among patients with coronavirus disease 2019 (COVID-19). However, kidney involvement is varied and mild kidney injury can easily go unnoticed. We aimed to investigate the urinalysis data of COVID-19 patients on admission and to explore the value of urinalysis in the prediction of acute kidney injury (AKI) and inhospital mortality in patients with COVID-19. Methods. The demographic, clinical and laboratory data of patients with confirmed COVID-19 were retrospectively collected from the electronic health records of the hospital. The outcomes were the development of AKI and in-hospital mortality. Results. 244 patients were included in the analysis. The mean age was 59.6 ± 13.7 and 65.2% of patients were male. Serum creatinine on admission was 0.86 (0.72-1.05) mg/dL. Glucosuria, proteinuria and hematuria were found in 36.1%, 22.9% and 22.1% of patients, respectively. AKI was detected in 63 patients (25.8%) at any time of hospitalization. According to multivariate analysis, AKI development was associated with higher WBC and decreased eGFR as well as with proteinuria on admission. During median 8 (IQR, 5-12) days of follow-up, 33 patients (13.5%) died. Older age, higher C-reactive protein levels and proteinuria on admission were also independent predictors of in-hospital mortality. Conclusion. Proteinuria on admission was associated with the development of AKI and inhospital mortality in patients with COVID-19. Urinalysis can be useful for early diagnosis of kidney damage before serum creatinine rise and mortality prediction in COVID-19 patients.

have a broad clinical spectrum, and mild kidney injury can easily go unnoticed. Several studies have found a significant association between AKI and death among COVID-19 infected patients. Early detection of AKI would be beneficial to identify the patients to improve the clinical status of COVID-19 patients [4,5].
Urine analysis may be useful to predict the development of AKI and mortality in COVID-19 patients. Multiple observational studies have reported the presence of proteinuria and hematuria in COVID-19 patients [6,7,8,9,10,11,12]. However, at present, there have been relatively few studies focusing on urinalysis parameters except hematuria and proteinuria in COVID-19 patients [6,9,11].
In this study, we aimed to investigate the urinalysis data of COVID-19 patients on admission and to explore the value of urinalysis in the prediction of AKI and inhospital mortality in patients with COVID-19.
We additionally collected urinalysis with automated microscopy that was obtained within 48 hours after admission. The urine samples were collected in containers, transported and analyzed within 2 h of collection. The analyses were carried out on H-800 and FUS-200 automatic modular urine analyzers (Dirui Industry, Changchun, China). Further microscopic analysis of sediments was performed, if required.
Outcomes data were retrieved until January 10, 2020. By the time of this analysis, all patients had either died or had been discharged from the hospital. The primary outcome was the development of AKI and the secondary outcome was in-hospital mortality.
Study definitions. The date of hospital admission was accepted as the first day. Patients using antihypertensive drugs were accepted as hypertensive, while those using antidiabetic drugs were accepted as diabetic.
AKI on admission or during hospital stay was defined according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria as follows: stage 1, as an increase in SCr level by 0.3 mg/dL within 48 hours or 1.5 to 1.9 times increase in SCr from baseline within 7 days; stage 2, as 2 to 2.9 times increase in SCr within 7 days; stage 3, as 3 or more times increase in SCr within 7 days of initiation of renal replacement therapy (RRT) [15]. Patients were stratified according to the highest AKI stage attained during their hospital stay. Available baseline value for each patient was taken as the mean outpatient value 7-365 days prior to admission [16]. If the baseline value of SCr was not available, the lowest value during hospitalization was taken [15]. We did not use the urine output criteria to define AKI as the documentation of urine output in the electronic health record was unavailable.
Renal glycosuria was defined in a person if blood glucose level rises higher than 170-200 mg/dL who doesn't have diabetes or if blood glucose level rises higher than 200-250 mg/dL who has type 2 diabetes mellitus and the filtered glucose load exceeds the capacity for tubular glucose reabsorption [17].
Proteinuria was defined as the presence of ≥1+ on dipstick urinalysis. Trace proteinuria was considered negative. Microscopic hematuria was accepted as the presence of three or more erythrocytes per high-power field. Pyuria was also accepted as the presence of five or more leukocytes per high-power field.
The follow-up period started from the date of hospitalization and ended the day of discharge or in-hospital mortality.
Statistical analysis. Continuous data are presented as mean with standard deviation (SD) or as median and interquartile range (IQR) in case of non-normal distribution. Categorical data are presented as percentages. For multiple group comparisons of categorical variables, the Chi-square test was used. Continuous variables were first analyzed for normality using the Kolmogorov-Smirnov test and then were compared using the independent sample t-test or the Mann-Whitney U test, when appropriate. To explore the risk factors associated with AKI we performed logistic regression models, with adjustment for risk factors that differed between subjects who developed AKI and those who did not. Also, multivariate logistic regression analyses were used to estimate the risk factors associated with in-hospital mortality. We did not include associates of decreased eGFR (urea, creatinine, eGFR) and Hburia in our prediction models. Kaplan-Meier survival curve analysis was done to determine the correlation between proteinuria and in-hospital mortality and log-rank test was used for survival analysis. All tests were performed using SPSS for Windows, version 17.0 software (SPSS Inc., Chicago, IL, USA). P values of less than 0.05 were considered statistically significant.
Ethics. The study protocol was approved by the Clinical Research Ethics Committee of Kartal Dr. Lutfi Kirdar City Hospital (approval date: 14.10.2020, approval number: 2020/514/187/15) and the Scientific Committee of the Ministry of Health (approval no: 2020-10-08T16_20_20). The study was conducted in accordance with the 1975 Declaration of Helsinki, as revised in 2013.
Results. 695 patients have been hospitalized in infectious clinics with COVID-19 diagnosis in study time. Of these 695 patients, 244 patients were included in the analysis. The flow chart of the study is shown in Figure 1. Compared with patients without AKI, patients who developed AKI were significantly older, had more comorbidities; hypertension and diabetes mellitus and were admitted to emergency in a shorter time after COVID-19 diagnosis. Moreover, patients with AKI had higher leukocytes, CRP and D-dimer values than patients without AKI. The median value of serum urea, SCr, eGFR and percentage of decreased eGFR on admission were significantly higher in patients who developed AKI than patients who did not.
Urinalysis data of study patients are shown in Table 2. The median pH value was 6 (IQR, 5.5-6) and the median urine-specific gravity was 1019.5 (IQR, 1012-1028). After excluding glycosuric patients, the median urine-specific gravity was 1017 (IQR, 1010-1023) in 156 patients. Glycosuria was found in 88 (36.1%) patients and the median blood glucose level at the time of urinalysis was 268 (IQR, 210.5-321.5) (data regarding blood glucose at the time of urinalysis in glucosuric patients were available in 48 patients). Only six patients of glucosuric patients (6/48, 12.5%) had a blood glucose value under the renal threshold defined. By urine dipstick, 189 patients (77.5%) had no heme and 188 patients (77.1%) had no proteinuria. The percentage of patients with proteinuria, hematuria and pyuria was significantly higher in patients with AKI. In contrast, urine pH was significantly lower in patients with AKI than in patients without AKI.
Most patients received antiviral therapy (favipiravir, 93.4%; remdesivir, 5.3%), low-molecular-weight heparin (LMWH) (93.4%) and corticosteroid therapy (dexamethasone, 82.4%, pulse methylprednisolone, 33.6%). Patients with AKI received hydroxychloroquine treatment less frequently than those without AKI. However, the patients with AKI received more antibacterial therapies than patients without AKI. The treatments of the study patients; all patients and patients grouped according to the presence of AKI are shown in Table 3. According to multivariate logistic regression analysis of risk factors on admission associated with the development of AKI in patients with COVID-19 are shown in Table 4. AKI development was associated with higher WBC and decreased eGFR as well as with proteinuria on admission.
Comparison of the demographic, clinical, and laboratory characteristics on admission between patients who survived and who died were shown in Table 5. Compared to the patients who survived, deceased patients were older and they had significantly higher SCr, CRP, ferritin, D-dimer and lower SaO2, lymphocyte and urine pH levels. Moreover, patients who died had significantly higher percentages of AKI, decreased eGFR, proteinuria and hematuria than patients who survived. According to multivariate analysis, patients with older age, higher CRP level, and proteinuria were at a higher risk of death than were patients without those findings (Table 6). Kaplan-Meier analysis revealed a significantly higher in-hospital mortality rate for patients with proteinuria (P=0.013) (Fig. 2). Discussion. In this retrospective analysis, we investigated the urinalysis data of COVID-19 patients, incidence and risk factors of AKI development, and mortality in-hospital in patients with COVID-19.
The importance of urine to show the severity of COVID-19 was firstly reported by Liu et al. In this study they found significantly higher positive rates of hematuria, and proteinuria and higher urine pH in COVID-19 patients compared to healthy controls [41.2% vs. 22.2%, 28.6% vs. 11.1%, 6.27 ± 0.6 vs. 5.94 ±0.7, respectively]. However, in contrast, urine-specific gravity was found significantly lower in COVID-19 patients than healthy controls (1020 ± 0.007 vs. 1023 ± 0.007) [6]. Hirsch et al. found the median value of urine-specific gravity as 1020 (IQR, 1010-1020) [8]. We found urine-specific gravity lower than previous reports especially in patients without glucosuria. Urine ph value was similar to the values reported previously [8,10].
Notably, glucosuria was found in 36.1% of patients similar to a previous report [12]. In our study most of the patients received corticosteroids. However; in only six patients (12.5%), renal glucosuria was found without serum glucose level not exceeding the renal threshold for glucose similar to a previous report [18]. It may be a result of proximal tubule injury in patients with COVID-19.
The rates of other urine parameters such as ketonuria and pyuria were found in our study as 15.6% and 9%, respectively. These changes had not been focussed in previous reports mostly. We found lower rates of pyuria than other studies [6,9]. Hirch et al. had found the frequency of pyuria more than our study in COVID-19 patients with AKI (36.5% vs. 15.9%) [8].
The quantification and characterization of proteinuria were begun to be investigated in recent studies. Huart et al. found proteinuria over 500 mg/g in 68 patients (44%) and they also found urine α1microglobulin (a marker of tubular injury) concentration higher than 15 mg/g in 89% of patients suggesting tubular proteinuria [20]. In a recent analysis, Karras et al. found urine protein-creatinine ratio at admission ≥ 1g/g in 84 patients (42%) with a urine albumin-protein ratio <50% in 92% of patients. They also found urine retinol-binding protein concentrations as ≥ 0.03 mg/ mmol in 62% of patients suggesting that COVID-19 associated proteinuria reflected low-molecular-weight proteins, which cannot be reabsorbed by the proximal kidney tubule due to acute tubular damage [21].
Among our study population, we observed an incidence of AKI of 25.8% similar to other reports [11,[22][23][24]. The reported rates of AKI are extremely variable; however, available evidence suggests that it likely affects >20% of hospitalized patients and >50% of patients in the ICU [25]. In a recent meta-analysis; the incidence of AKI was reported as 13.28% (162/1220) in all included studies [26]. Differences may have resulted from definitions of AKI and the populations studied. The pathogenesis of AKI in patients with COVID-19 is likely multifactorial, involving both the direct effects of the SARS-CoV-2 virus on the kidney such as collapsing glomerulopathy, endothelial damage, coagulopathy, complement activation, and inflammation and the indirect mechanisms resulting from systemic consequences of viral infection or effects of the virus on distant organs including the lung, in addition to mechanisms relating to the management of COVID-19 [27]. Some studies reported the presence of viral particles within both the tubular epithelium and podocytes on electron microscopy, implying the direct infection of the kidney [28,29], others failed to demonstrate the presence of virus in the kidney [30][31][32]. In addition to direct pathophysiological mechanisms, renal dysfunction in the context of COVID-19 may also arise through the systemic effects of SARS-CoV-2 infection and critical illness. Volume depletion, exposure to nephrotoxins, increase in renal ven pressure and reduced filtration due to positive end-expiratory pressure (PEEP), the release of cytokines, vasoactive substances and damage-associated molecular patterns (DAMPs) from lung injury are also other mechanisms for kidney injury [27].
Risk factors of AKI in COVID-19 are diverse and multifactorial. A number of previous studies have suggested that the development of AKI in COVID-19 patients may be affected by multiple risk factors, such as older age, male sex, black race, comorbidities, increased CRP, proteinuria at admission, the need for ventilator support, use of vasopressor drug treatment [3,8,20,23,25]. On the basis of our multivariate logistic regression analysis; higher leukocytes, decreased eGFR and presence of proteinuria were independent predictors of AKI. As reported previously, we observed a high prevalence of hematuria and proteinuria in COVID-19 patients with AKI [3,12,19,21,22]. However, in a recent study, they found no significant differences in proteinuria, hematuria and leukocyturia among patients with AKI compared with non-AKI patients [24].
Several mortality risk scores have been proposed to predict mortality in COVID-19 patients [33,34,35], most of which did not include an evaluation of kidney status. However, kidney indicators seem to be the main predictors of mortality. We found the highest mortality frequencies in patients with AKI compared to patients without AKI (38.1% vs. 5%, P=0.000) consistent with previous reports [19,23,36]. In a recent meta-analysis, COVID-19 patients with AKI had a significantly increased risk of death compared to patients without AKI (OR 30.46, 95% CI 9.29-15.19) [26]. We also found that proteinuria on admission was independently associated with in-hospital mortality and had a 2.7 times higher risk of death similar to previous reports [11,12,37]. Pei et al. showed higher overall mortal-ity in the patients with renal involvement, including hematuria, proteinuria, and AKI, compared with that of patients without renal involvement (11.2% vs 1.2%, P=0.006) [3]. Cheng et al. reported the incidence of mortality in-hospital in the patients with elevated baseline serum creatinine on admission was 33.7%. They also found that proteinuria of any degree, hematuria of any degree, elevated baseline BUN, elevated baseline SCr, peak SCr > 133 mmol/l, and AKI over stage 2 were independently associated with mortality [7]. In another study, Portoles et al. confirmed that elevated baseline SCr, previous chronic kidney disease, hematuria, and in-hospital AKI were independent risk factors for mortality in-hospital after adjusting for age, sex and comorbidity [9]. However; in a recent study, Ouahmi et al. reported that proteinuria was not found as an independent predictor for in-hospital mortality [24].
This study has several limitations. The number of patients included in this study is limited, and there were some missing data. Second, an accurate baseline serum creatinine and urine output was not available, which may have led to an under or overestimation of AKI or erroneous associations. We also were unable to distinguish patients who had preexisting proteinuria and hematuria prior to the presentation from those who had it new-onset on admission due to lack of previous urinalysis in most patients. Third, disease severity was not defined because of missing data. Finally, the quantification of proteinuria could not be investigated.
In conclusion, proteinuria on admission is associated with the development of AKI and in-hospital mortality in patients with COVID-19. We hence reinforce the suggestion that urinalysis may be useful for the evaluation of COVID-19 progression and early diagnosis of kidney damage before SCr rise. Early detection and effective intervention of kidney involvement may help to reduce the development of AKI and to improve the vital prognosis of COVID-19.

Conflicts of interest:
The authors declare no conflict of interest.
Data availability statment. The data that support the findings in this study are available from the corresponding author, [M.O.], upon reasonable request.
Authors contributions. Meric Oruc: conception and design, data acquisition, analysis and interpretation of data, drafting the article, providing intellectual content of critical importance to the work described Ayse Batirel: conception and design, analysis, providing intellectual content of critical importance to the work described Sinan Trabulus: conception and design, analysis, drafting the article, providing intellectual content of critical importance to the work described, final approval of the version to be published.