key: cord-0749885-qfeuvgfv authors: Erdogan, Omer; Ok, Fesih; Carkci, Serkan; Durmus, Emrullah title: Is there an association between urine biochemical parameters on admission and the severity OF COVID‐19? date: 2021-09-18 journal: Int J Clin Pract DOI: 10.1111/ijcp.14809 sha: 077e6ad0d3d97e6980ef8af87ef37d5020619d1f doc_id: 749885 cord_uid: qfeuvgfv AIM: To determine the importance of urinary biochemical parameters on the severity of coronavirus disease‐2019 (COVID‐19). METHODS: One hundred and thirty‐three patients who were diagnosed with COVID‐19 were retrospectively included. Groups were formed according to the severity of their disease (moderate [n = 85], severe [n = 29] and critical = [n = 19]), and an additional control group was created from healthy individuals (n = 50). We investigated the correlation between urine biochemical parameters and the severity of the disease. RESULTS: Erythrocyturia, proteinuria and glucosuria rates were significantly higher in patients than in the controls. In patients, the median urine specific gravity (SG) was lower (P < .001), and the median potential of hydrogen (pH) value was higher compared with the controls (P < .001). In correlation analyses, there were strong positive correlations between disease severity and age (r = 0.545, P < .001), RR (r = 0.838, P < .001) and proteinuria (r = 0.462, P < .001), while there was a strong negative correlation with SpO(2) (r = −0.839, P = .001). On multivariate analysis, age (OR: 1.06, 95% CI 1.03‐1.10, P = .035), respiratory rate ≥30 breaths/min (OR: 4.72, 95% CI 1.26‐6.24, P < .0031), SpO(2) ≤ 93% (OR: 3.82, 95% CI 1.18‐5.82, P = .001) and proteinuria (OR: 1.13, 95%CI 1.02‐2.1, P = .023) were independent predictive factors for disease severity. CONCLUSION: Proteinuria in routine urine analysis, which is one of the parameters that can be easily applied in the application, may be related to the severity of the COVID‐19 disease. has been identified in their genetic makeup. Their surfaces have rodlike extensions. 6 Urine examinations are fast, convenient and economical. They can be used as an assay to diagnose many diseases, such as urinary tract infections (UTIs), kidney diseases and stone diseases, through the various biochemical parameters of urine. [7] [8] [9] So far, one study has been conducted showing the relationship between the biochemical parameters of urine and COVID-19. 10 We aimed to determine the association between the biochemical parameters of urine and COVID-19 disease severity. Pre-work permits were obtained by the Turkish Ministry of Health and the local ethics committee of Siirt University (decision no: 2020/05.02). Patients hospitalised in Siirt State Hospital between April and May 2020 and whose COVID-19 polymerase chain reaction (PCR) tests were positive were included in the study. A control group was also formed from 50 healthy individuals. Urine potential of hydrogen (pH), specific gravity (SG), leukocyte, erythrocyte, protein, nitrite, glucose and bacteria were recorded by asking the patients for a full urine examination. In addition, body temperature, respiratory rate (RR), heart rate (HR), mean arterial pressure (MAP) and peripheral capillary oxygen saturation (SpO 2 ) data were recorded from patients' files. The patients were further sub-divided into four groups (mild, moderate, severe and critical) according to the Diagnostic Treatment Program of New Coronavirus Pneumonia (7th trial version). Patients within the mild group were excluded from the study because they were treated as outpatients. Patients with chronic renal failure, asthma, hypertension (HT), diabetes mellitus (DM) and chronic obstructive pulmonary disease (COPD) thought to affect the study results were excluded from the study. In addition, the urine of all patient groups was nitrite negative and bacteria were absent. Therefore, patients with urinary tract infections were excluded from the study. In addition, low molecular weight heparin treatment was given prophylactically to all Covid positive hospitalised patients. We compared the patient group with healthy controls. Severe and critical groups in the patient group were combined and defined as severe group and moderate group as non-severe group. After the patients were hospitalised in Siirt State Hospital, about 30 mL of clean mid-flow urine samples were taken from the patients on the same day. A urine sample was taken from critical COVID-19 patients by inserting a catheter. Urinary biochemical parameters, such as urine occult blood, urine glucose, nitrite, SG, pH, proteinuria and leukocytes, were tested using a fully automatic urine biochemical analyser (DIRUI FUS 200/H-800, DIRUI Industrial Co.). Variables such as proteinuria and erythrocyteuria were used as categorical variables as present or absent. All collected samples were studied within 2 h. Fisher's exact tests were used for categorical variables. Spearman correlation coefficients were used to describe the association between disease severity and urine and other easily applicable parameters. Binary logistic regression analysis was used to determine the predictive role of clinical and urine biochemical parameters on disease severity. The optimal cut-off value for age was calculated by applying a receiver operating curve (ROC) analysis. A P value <.05 was considered statistically significant. In our study, there were 85 (63.9%) patients in the moderate group, 29 (21.8%) in the severe group and 19 (14.3%) in the critical group. For the control group, 50 healthy people without COVID-19 were selected. There was no significant difference between the patient and control groups in terms of age (P = .070) or sex (P = .125; Table 1 ). • COVID-19 disease is a serious problem in society. • The severity of the COVID-19 disease varies in patients. • Laboratory and vital parameters are investigated to predict the course of COVID-19 disease. • There is one study that supports our work. • COVİD-19 disease is a serious social problem and it is important to predict its severity. • We think that when urine analysis and vital signs are evaluated together, it can be useful in predicting the severity of Covid-19 disease. The rates of erythrocyturia (P < .001), proteinuria (P = .015) and glucosuria (P = .020) were significantly higher in patients than in the controls. In the patient group, the median SG value was significantly lower than in the control group (P < .001). The median pH value was significantly higher in the patient group compared to the control group (P < .001; Table 1 ). While the mean RR (P < .001), HR (P < .001) and MAP (P = .003) were significantly higher in the patient group than in the control group, the SpO 2 (P < .001) was significantly lower (Table 1 ). In terms of SG (P = .334) and pH (P = .229), there was no significant difference between the three patient groups. Patients in the moderate group had a significantly lower average age than patients in the severe and critical groups (P < .001). The rate of proteinuria was significantly higher in patients in the severe and critical groups compared with the moderate group (P < .001). The erythrocyturia ratio was significantly higher in the critical group than in the moderate group (P < .001), but there was no significant difference between the severe group and the other two groups (P > .05). Proteinuria and glucosuria rates were significantly higher in the severe and critical groups than in the moderate group (P < .001). Proteinuria and glucosuria rates were significantly higher in the critical group than in the severe group (P < .05). There was no significant difference between the patient groups in terms of fever (P = .098). The mean RR was significantly higher in the severe and critical groups than in the moderate group (P < .05). The mean RR was significantly higher in the critical group than in the severe group (P < .05). The mean SpO 2 was significantly lower in the severe and critical groups than in the moderate group (P < .05). The mean SpO 2 was significantly lower in the critical group than in the severe group (P < .05; Table 1 ). The severe and critical groups were classified as severe, while the moderate group was classified as non-severe. Age, RR, SpO 2 , erythrocyturia, proteinuria and glucosuria were significantly higher in the severe group than in the non-severe group (P < .001; Table 2) On Spearman correlation analysis, there was a strong positive correlation between disease severity and age (r = 0.545, P < .001), RR (r = 0.838, P < .001) and proteinuria (r = 0.462, P < .001), while there was a strong negative correlation with SpO 2 (r = −0.839, P = .001; Table 3 were independent predictive factors for disease severity ( Table 4 ). The optimum cut-off value of age for predicting severe disease was 53.5 years. The AUC of age was 0.828 (95% CI: 0.756-0.899; P < .001). The highest sensitivity and specificity for age were 0.854 and 0.647, respectively ( Figure 1 ). sure. 12 They also develop a large right-to-left shunt. 13 Ultimately, the increase in respiratory drive exacerbates both the inflammation and the lung injury caused by the virus itself. 12 The worsening hypoxia increases respiratory rate, and underlying lung damage accelerates overt respiratory failure. Patient deaths are generally caused by acute respiratory failure, cardiac dysrhythmia because of severe hypoxemia and thrombosis. 13 Similarly, we observed that patients with high RR and low SpO 2 at presentation progressively worsened. In a study that compared the COVID-19 patients and controls, the incidence of protein and erythrocyte in the urine of patients was higher than in the controls (P < .05). Furthermore, urine pH and SG were considerably different from the controls. However, the incidence of leukocytes in urine did not differ between the patient and the healthy group. This is because SARS-CoV-2 infection has been linked to non-bacterial. 10 In our study, the positive rates of erythrocyturia (P < .001), proteinuria (P = .015) and glucosuria (P = .020) were higher in patients than in controls. SG was considerably lower in the patients than in the controls. Moreover, the urine pH value of patients was significantly higher than the controls. However, urine pH and SG values were similar in the patient groups. 16 In the severe and critical group, we believe that kidney damage caused by this mechanism causes proteinuria and erythrocyturia. This study had some limitations. First, this was a retrospective, single-center clinical trial and, therefore, had a small sample size. In addition, since our study was a retrospective study, it was excluded because the mild patient group included outpatients who did not require hospitalisation. .874 Statistically significant values are indicated in bold. The receiver operating characteristic (ROC) Curve analysis of age for COVID-19 disease severity All procedures in studies with human participants complied with the Ethical standards of the Corporate Research Committee and the 1964 Helsinki Declaration and subsequent updates. The authors thank the healthcare staff and the hospital management who worked intensively during the pandemic process. The authors declare that they have no conflict of interest. The data that support the findings of this study are available from the corresponding author upon reasonable request. Coronavirus disease 2019: what we know Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. The Lancet Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan Advances in MERS-CoV vaccines and therapeutics based on the receptor-binding domain The urine dipstick test useful to rule out infections. A meta-analysis of the accuracy The accuracy of the sysmex uf-1000i in urine bacterial detection compared with the standard urine analysis and culture Bacteriuria screening by automated whole-field-image-based microscopy reduces the number of necessary urine cultures The value of urine biochemical parameters in the prediction of the severity of coronavirus disease 2019 Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study COVID-19 pneumonia: different respiratory treatments for different phenotypes? COVID-19 does not lead to a "typical" acute respiratory distress syndrome Urine biomarkers for the prediction of mortality in COVID-19 hospitalized patients Renal involvement and early prognosis in patients with COVID-19 pneumonia Coronavirus disease 19 infection does not result in acute kidney injury: an analysis of 116 hospitalized patients from Wuhan, China Is there an association between urine biochemical parameters on admission and the severity OF COVID-19?