Using dipstick urinalysis to predict development of acute kidney injury in patients with COVID-19

McAdams, Meredith; Li, Michael; Xu, Pin; Gregg, L. Parker; Patel, Jiten; Willett, Duwayne L; Velasco, Ferdinand; Lehmann, Christoph U.; Hedayati, S. Susan

doi:10.1186/s12882-022-02677-y

Cited by 11 publications

(10 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This may be attributable to many factors, including the time point of testing and different proportion of severe cases in studied countries, and/or different scales of patient sampling. Furthermore, several publications reported the important role of urine tests in evaluating the severity, occurrence of AKI, and clinical course of COVID-19 patients, supporting the utility of urine as an informative biospecimen [29][30][31].…”

Section: Discussionmentioning

confidence: 91%

Urinalysis, but Not Blood Biochemistry, Detects the Early Renal Impairment in Patients with COVID-19

et al. 2022

View full text Add to dashboard Cite

Background: Coronavirus 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2), has created a tremendous economic and medical burden. The prevalence and prognostic value of SARS-CoV-2-induced kidney impairment remain controversial. The current study aimed to provide additional evidence on the incidence of acute kidney injury (AKI) in COVID-19 patients and propose the use of urinalysis as a tool for screening kidney impairment. Methods: 178 patients with confirmed COVID-19 were enrolled in this retrospective cohort study. The laboratory examinations included routine blood tests, blood biochemical analyses (liver function, renal function, lipids, and glucose), blood coagulation index, lymphocyte subset and cytokine analysis, urine routine test, C-reactive protein, erythrocyte sedimentation, and serum ferritin. Results: No patient exhibited a rise in serum creatinine or Cystatin C and occurrence of AKI, and only 2.8% of patients were recorded with an elevated level of blood urea nitrogen among all cases. On the contrary, 54.2% of patients who underwent routine urine testing presented with an abnormal urinalysis as featured by proteinuria, hematuria, and leucocyturia. Conclusions: Kidney impairment is prevalent among COVID-19 patients, with an abnormal urinalysis as a clinical manifestation, implying that a routine urine test is a stronger indication of prospective kidney complication than a blood biochemistry test.

show abstract

Section: Discussionmentioning

confidence: 91%

Urinalysis, but Not Blood Biochemistry, Detects the Early Renal Impairment in Patients with COVID-19

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Proteinuria and hematuria are not as critical clinically as AKI, but their influence on COVID-19 prognosis cannot be overlooked. Proteinuria and hematuria can be used as independent predictors of COVID-19 severity [ 26 , 27 ]. Our study demonstrated that proteinuria was significantly associated with Omicron variant infection.…”

Section: Discussionmentioning

confidence: 99%

The Investigation of Kidney Involvement in 430 Hospitalized Patients with Omicron COVID-19 in Tianjin, China

Teng

Chang

2023

Blood Purif

View full text Add to dashboard Cite

Introduction: This study evaluated the incidence, clinical characteristics, and risk factors of kidney involvement in patients with the Omicron variant infection in the post-acute treatment phase in Tianjin, China. Methods: Data were collected from 430 patients with Omicron variant infection in Tianjin, China. Demographics, comorbidities, laboratory blood tests, urinalysis, vaccination status, and COVID-19 clinical classification were assessed. Patients were grouped based on kidney involvement, and associated risk factors of kidney involvement were also investigated. Results: Asymptomatic, mild, ordinary, and severe patients with Omicron COVID-19 variant comprised 1.5%, 49.1%, 48.9%, and 0.5% of the sample population, respectively, without critical illness or death. The incidences of hematuria, proteinuria, and concurrent hematuria and proteinuria were 14.7%, 14.2%, and 5.1%, respectively. Patients with and without kidney involvement differed in age, body mass index (BMI), comorbidity, creatinine levels, estimated glomerular filtration rate, and C-reactive protein (CRP) levels. Age, hypertension, higher CRP levels, and higher BMI were linked with kidney involvement. Conclusion: The majority of the patients suffered from mild or ordinary symptoms of Omicron COVID-19 infection. The primary kidney involvement was hematuria and proteinuria. Proteinuria was significantly associated with Omicron variant infection, and patients with hypertensive comorbidity, higher CRP, and higher creatinine levels were at increased risk of proteinuria after Omicron variant infection.

show abstract

“…Naomi et al ( 32 ) reported the application of serum biomarkers (SB), including serum NGAL and serum creatinine, for the prediction of AKI in 52 COVID-19 patients, with AUCs of 0.81 and 0.87, respectively. A prediction model for AKI based on proteinuria and hematuria yielded an AUC of 0.64 (95% CI: 0.62–0.67) in a large cohort study containing 5,980 COVID-19 patients; moreover, the predictive capability of the model was improved when creatinine and the presence of CKD were incorporated ( 33 ). In addition, studies have validated the predictive value of other indicators, such as D-dimer and albumin/creatinine ratio, for AKI in hospitalized COVID-19 patients ( 34 ).…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a nomogram for the early prediction of acute kidney injury in hospitalized COVID-19 patients

Wang

Sun

et al. 2022

Front. Public Health

View full text Add to dashboard Cite

IntroductionAcute kidney injury (AKI) is a prevalent complication of coronavirus disease 2019 (COVID-19) and is closely linked with a poorer prognosis. The aim of this study was to develop and validate an easy-to-use and accurate early prediction model for AKI in hospitalized COVID-19 patients.MethodsData from 480 COVID-19-positive patients (336 in the training set and 144 in the validation set) were obtained from the public database of the Cancer Imaging Archive (TCIA). The least absolute shrinkage and selection operator (LASSO) regression method and multivariate logistic regression were used to screen potential predictive factors to construct the prediction nomogram. Receiver operating curves (ROC), calibration curves, as well as decision curve analysis (DCA) were adopted to assess the effectiveness of the nomogram. The prognostic value of the nomogram was also examined.ResultsA predictive nomogram for AKI was developed based on arterial oxygen saturation, procalcitonin, C-reactive protein, glomerular filtration rate, and the history of coronary artery disease. In the training set, the nomogram produced an AUC of 0.831 (95% confidence interval [CI]: 0.774–0.889) with a sensitivity of 85.2% and a specificity of 69.9%. In the validation set, the nomogram produced an AUC of 0.810 (95% CI: 0.737–0.871) with a sensitivity of 77.4% and a specificity of 78.8%. The calibration curve shows that the nomogram exhibited excellent calibration and fit in both the training and validation sets. DCA suggested that the nomogram has promising clinical effectiveness. In addition, the median length of stay (m-LS) for patients in the high-risk group for AKI (risk score ≥ 0.122) was 14.0 days (95% CI: 11.3–16.7 days), which was significantly longer than 8.0 days (95% CI: 7.1–8.9 days) for patients in the low-risk group (risk score <0.122) (hazard ratio (HR): 1.98, 95% CI: 1.55–2.53, p < 0.001). Moreover, the mortality rate was also significantly higher in the high-risk group than that in the low-risk group (20.6 vs. 2.9%, odd ratio (OR):8.61, 95%CI: 3.45–21.52).ConclusionsThe newly constructed nomogram model could accurately identify potential COVID-19 patients who may experience AKI during hospitalization at the very beginning of their admission and may be useful for informing clinical prognosis.

show abstract

Using dipstick urinalysis to predict development of acute kidney injury in patients with COVID-19

Cited by 11 publications

References 35 publications

Urinalysis, but Not Blood Biochemistry, Detects the Early Renal Impairment in Patients with COVID-19

Urinalysis, but Not Blood Biochemistry, Detects the Early Renal Impairment in Patients with COVID-19

The Investigation of Kidney Involvement in 430 Hospitalized Patients with Omicron COVID-19 in Tianjin, China

Development and validation of a nomogram for the early prediction of acute kidney injury in hospitalized COVID-19 patients

Contact Info

Product

Resources

About