Urine abnormalities predict acute kidney injury in COVID-19 patients: An analysis of 110 cases in Chennai, South India. Issue 1 (January 2021)

• Record Type: Journal Article
• Authors: Sundaram, Supraja; Soni, Mamta; Annigeri, Rajeev
• Is Part Of: Diabetes & metabolic syndrome. Volume 15:Issue 1(2021)
• Page Start: 187
• Page End: 191
• Publication Date: 2021-01
• Subjects: Acute kidney injury -- Covid-19 -- Diabetes -- Haematuria -- Proteinuria -- Urine examination; Diabetes -- Periodicals; Metabolism -- Disorders -- Periodicals; Diabetes Mellitus -- Periodicals; Metabolic Diseases -- Periodicals; Diabète -- Périodiques; Métabolisme, Troubles du -- Périodiques; Endocrinologie -- Périodiques; Diabète -- Physiopathologie -- Périodiques; Diabetes; Metabolism -- Disorders; Electronic journals; Periodicals; 616.462
• DOI: 10.1016/j.dsx.2020.12.021
• Languages: English
• ISSNs: 1871-4021

Abstract

Abstract: Background and aims: Renal involvement in Covid-19 infection is varied and can affect glomeruli, tubules, interstitium and can cause acute kidney injury (AKI). AKI is a strong predictor of mortality. Routine urinalysis gives an insight into the renal pathology of the patient. We studied the incidence of urinary abnormalities in hospitalised Covid-19 patients and analysed their impact on development of AKI and mortality. Methods: Information on 110 hospitalised patients with confirmed Covid-19 was retrospectively collected and analysed. The demographic data such as age, gender, comorbid conditions such as diabetes mellitus, the need for dialysis and laboratory data such as urine for albumin, glucose, RBC and WBC, and serum creatinine were collected. The diagnosis of AKI was based on the KDIGO criteria. The outcomes studied were development of AKI and hospital mortality. Results: Urine abnormalities were seen in 71% of the patients. Proteinuria in 58.2%, haematuria in 17.3%, pyuria in 8.2% of patients and concurrent proteinuria and haematuria was seen in 13.6% of patients. AKI was seen in 28.2% of patients and hospital mortality was 24.5%. AKI was strongly associated with mortality. Proteinuria and haematuria were good predictors of development of AKI, more strongly when they occurred concurrently (p < 0.01). Conclusion: Our results suggest that urine analysis is a simple test, which can be used to predict development of AKI and mortality and may be used for risk stratification of Covid-19 patients, especially in low resource settings. Highlights: Urine examination helps in early detection of acute kidney injury (AKI) in COVID 19. AKI is a poor prognostic indicator among hospitalised patients. Proteinuria and haematuria are significant predictors of AKI among hospitalised patients of COVID 19.