Urinary renal tubular epithelial cells and casts as predictors of renal outcomes in patients with biopsy-proven diabetic nephropathy.

BACKGROUND: Urine sediment examination is a time-tested and non-invasive diagnostic tool. This study investigated the characteristics of urine sediment and its association with severity and renal outcomes in diabetic nephropathy (DN) patients. METHODS: A total of 201 biopsy-proven diabetic nephropathy patients (according to the pathological classification of diabetic nephropathy proposed by the Renal Pathology Society in 2010) who underwent manual urine sediment microscopic examination were included. We compared the clinicopathological characteristics of diabetic nephropathy patients with and without urinary renal tubular epithelial cells (RTECs) or renal tubular epithelial cell casts. The predictive value of urinary renal tubular epithelial cells or renal tubular epithelial cell casts for renal outcomes in diabetic nephropathy was analyzed. RESULTS: Fifty of 201 (24.9%) diabetic nephropathy patients had renal tubular epithelial cells or renal tubular epithelial cell casts in urine sediment. Diabetic nephropathy patients with renal tubular epithelial cells or renal tubular epithelial cell casts in urine sediment had a significantly higher level of proteinuria [6.0 (3.1, 9.7) vs. 3.6 (1.8, 6.8) g/24 h, p = 0.001], higher serum creatinine [227.9 (151.6, 338.1) vs. 177.0 (104.4, 288.4) µmol/L, p = 0.016] and lower estimated glomerular filtration rate (eGFR) [25.8 (15.8, 44.8) vs. 35.7 (19.9, 65.0) mL/min/1.73 m2, p = 0.025] than those without. Cox regression analysis demonstrated that the presence of urinary renal tubular epithelial cells or renal tubular epithelial cell casts was independently associated with the development of end-stage kidney disease (ESKD) in diabetic nephropathy patients [HR 1.670, 95% CI (1.042, 2.676), p = 0.033]. Adding the presence of urinary renal tubular epithelial cells or renal tubular epithelial cell casts to the predictive model could improve the effectiveness of the model for predicting the risk of ESKD within one year after renal biopsy. CONCLUSIONS: The presence of urinary renal tubular epithelial cells or renal tubular epithelial cell casts was associated with more severe kidney injury and worse renal outcomes in patients with diabetic nephropathy, thus perhaps providing a noninvasive biomarker for predicting diabetic nephropathy.

Complex phenotype in Fanconi renotubular syndrome type 1: Hypophosphatemic rickets as the predominant presentation.

GATM-related Fanconi renotubular syndrome 1 (FRTS1) is a form of renal Fanconi syndrome (RFS), which is a disorder of solute and water reabsorption caused by defects in the function of the entire proximal tubule. Recent findings reveal the molecular basis of FRTS1: Intramitochondrial fiber aggregation triggered by mutant GATM provides a starting point for proximal tubule damage and drives disease progression. As a rare and newly recognized inherited kidney disease, the complex manifestations of FRTS1 are easily underdiagnosed or misdiagnosed. We discuss the complex phenotype of a 26-year-old woman with onset in infancy and a long history of hypophosphatemic rickets. We also identified a novel heterozygous missense variant in the GATM gene in this patient. The novel variant and phenotype we report expand the disease spectrum of FRTS1. We recommend screening for GATM in children with RFS, especially in patients with resistant rickets who have previously had negative genetic testing. In addition, we found pathological deposition of mutant GATM proteins within mitochondria in the patient's urinary sediment cells by a combination of electron microscopy and immunofluorescence. This unique urine cytology experiment has the potential to be a valuable tool for identifying patients with RRTS1.

[TWO CASES OF ALLERGIC VULVOVAGINITIS DIAGNOSED BY DIRECT MICROSCOPIC URINE SEDIMENT EXAMINATION].

Cedar pollen is known as a typical allergen that causes various allergic symptoms in the nasal mucosa, conjunctiva, and skin. However, inflammation of the vulvar mucosa due to sensitization to cedar pollen is not well-known. We experienced two cases in which the detection of cedar pollen during microscopic urine sediment examination led to the diagnosis of allergic vulvovaginitis caused by cedar pollen. The cases involved a 4-year-old girl and a 10-year-old girl. In both cases, the patients presented with chief complaints of pruritis in the vulva and insomnia due to frequent urination during the season of cedar pollen dissemination. Both patients were afebrile. No inflammatory skin changes such as erythema, swelling, or non-purulent discharge from mucous membranes of the vulva were observed. Microscopic urine sediment examination revealed large amounts of shed cedar pollen. The patients' conditions improved after treatment with oral antihistamines and instruction to dry their underwear indoors. Follow-up blood tests revealed high levels of specific anti-IgE antibodies to cedar pollen, thus confirming a diagnosis of allergic vulvovaginitis due to cedar pollen. Cedar pollen can cause allergic vulvovaginitis. Microscopic urine sediment examination is useful, and when combined with specific IgE antibody testing, leads to an appropriate diagnosis. This disease should also be considered in patients with complaints of vulvar discomfort during the season of cedar pollen dissemination.

Evaluation of the fully automated urine particle analyzer UF-1500.

BACKGROUND AND AIMS: This study primarily assessed the performance of the UF-1500, the novel and compact model of the fully automated urine particle analyzer and evaluated its performance against the existing UF-5000 instrument. MATERIALS AND METHODS: A total of 648 residual urine specimens were randomly collected and examined using both the UF-1500 and UF-5000 instruments as well as manual microscopy. For each parameter, the concordance rates and detection accuracy of the UF-1500 against manual microscopy were compared with the UF-5000. RESULTS: The concordance rates between the UF-1500 and manual microscopy were 75.3%-98.5%. The UF-1500 concordance rates within one group agreement were observed to be >90%, for all parameters except for YLCs. The differences within one group agreement between the UF-1500 and manual microscopy were insignificant, in comparison to the UF-5000, with exceptions noted for ECs and YLCs. The sensitivity and specificity of the UF-1500 for RBCs, WBCs, Squa.ECs, and BACT exceeded 80%, while the positive predictive values of ECs and CASTs were below 70%. CONCLUSION: The UF-1500 exhibited a performance that was comparable to the existing instrument, the UF-5000, and was suitable to be introduced in clinical practice. For the samples with suspected false-positive or false-negative results, a manual microscopic examination is required for accurate testing.

Acute Kidney Injury and BK Polyomavirus in Urine Sediment Cells.

Polyomaviruses are widespread, with BK viruses being most common in humans who require immunosuppression due to allotransplantation. Infection with BK polyomavirus (BKV) may manifest as BK virus-associated nephropathy and hemorrhagic cystitis. Established diagnostic methods include the detection of polyomavirus in urine and blood by PCR and in tissue biopsies via immunohistochemistry. In this study, 79 patients with pathological renal retention parameters and acute kidney injury (AKI) were screened for BK polyomavirus replication by RNA extraction, reverse transcription, and virus-specific qPCR in urine sediment cells. A short fragment of the VP2 coding region was the target of qPCR amplification; patients with (n = 31) and without (n = 48) a history of renal transplantation were included. Urine sediment cell immunofluorescence staining for VP1 BK polyomavirus protein was performed using confocal microscopy. In 22 patients with acute renal injury, urinary sediment cells from 11 participants with kidney transplantation (KTX) and from 11 non-kidney transplanted patients (nonKTX) were positive for BK virus replication. BK virus copies were found more frequently in patients with AKI stage III (n = 14). Higher copy numbers were detected in KTX patients having experienced BK polyoma-nephropathy (BKPyVAN) in the past or diagnosed recently by histology (5.6 × 109-3.1 × 1010). One patient developed BK viremia following delayed graft function (DGF) with BK virus-positive urine sediment. In nonKTX patients with BK copies, decoy cells were absent; however, positive staining of cells was found with epithelial morphology. Decoy cells were only found in KTX patients with BKPyVAN. In AKI, damage to the tubular epithelium itself may render the epithelial cells more permissive for polyoma replication. This non-invasive diagnostic approach to assess BK polyomavirus replication in urine sediment cells has the potential to identify KTX patients at risk for viremia and BKPyVAN during AKI. This method might serve as a valuable screening tool for close monitoring and tailored immunosuppression decisions.

Comparison of the clinical performance of the Atyp.C parameter of the UF-5000 fully automated urine particle analyzer with that of microscopic urine sediment analysis.

a Objectives: Urinalysis is one of the most common laboratory screening tests to detect problems in the renal and urinary system; however, they cannot detect atypical cells (Atyp.Cs). The Sysmex UF-5000, a fully automated urine particle analyzer, can detect Atyp.Cs via its Atyp.C parameter. This study aimed to compare the clinical value of the Atyp.C parameter with that of urine sediment microscopy. b Method: A total of 471 leftover urine samples were submitted to the Department of Clinical Laboratory at the University of Tokyo Hospital for urinalysis by manual sediment microscopy examination and UF-5000 Atyp.C analysis. c Result: Of 471 submitted samples, 117 were positive for Atyp.Cs by urine sediment and 354 samples were negative. The histological subtypes of the Atyp.Cs included 105 cases of suspected urothelial carcinoma cells, 10 suspected squamous carcinoma cells, and 2 of suspected adenocarcinoma cells. The Atyp.C values for the Atyp.C-positive and -negative groups were 2.64 ± 0.69 and 0.38 ± 0.16, respectively. The optimal Atyp.C cutoff value determined by the receiver operating characteristic curve analysis was 0.4/µL. The area under the curve was 0.856, with a sensitivity of 79.5% and specificity of 85.1%. Atyp.C values of the UF-5000 showed high predictive performance for Atyp.C-positive specimens identified by urine sediment microscopy. d Conclusions: This study shows that a combination of UF-5000 analysis and microscopic examination of urine sediment improves Atyp.C detection in urine sediment analysis. These results suggest that Atyp.C measured by UF-5000 could be a useful screening parameter in routine testing of urine samples.

Utilidad del citoquímico urinario en cuidados intensivos, una herramienta olvidada

El sedimento urinario es una herramienta utilizada hace tantos años para caracterizar manifestaciones renales de enfermedades primarias y secundarias, que es necesario realizar una estandarización y aprender a interpretar el mismo. En los pacientes ingresados a la unidad de cuidados intensivos, muchas veces no se realiza, o hay que tener en cuenta varios factores para su interpretación debido al estado hemodinámico del paciente a la filtración glomerular, la excreción tubular, la reabsorción de agua y los solutos además del equilibrio acido-base, los cuales pueden variar significativamente en pacientes en estado crítico con diferentes condiciones fisiopatológicas. Se presenta una revisión de las condiciones para la interpretación del urianálisis.

A urinary sediment is a tool used for years to characterize renal manifestations of primary and secondary diseases, which requires standardization and learning to interpret it. In patients admitted to the intensive care unit, it is often not performed, or several factors must be taken into account for its interpretation due to the patient's hemodynamic status, glomerular filtration, tubular excretion, water reabsorption, and solutes. In addition to the acid-base balance, which can vary significantly in critically ill patients with different pathophysiological conditions? A review of the conditions for the interpretation of urinalysis is presented.

Utilidad del citoquímico urinario en cuidados intensivos, una herramienta olvidada / The usefulness of urinary sediment in intensive care, a forgotten tool

El sedimento urinario es una herramienta utilizada hace tantos años para caracterizar manifestaciones renales de enfermedades primarias y secundarias, que es necesario realizar una estandarización y aprender a interpretar el mismo. En los pacientes ingresados a la unidad de cuidados intensivos, muchas veces no se realiza, o hay que tener en cuenta varios factores para su interpretación debido al estado hemodinámico del paciente a la filtración glomerular, la excreción tubular, la reabsorción de agua y los solutos además del equilibrio acido-base, los cuales pueden variar significativamente en pacientes en estado crítico con diferentes condiciones fisiopatológicas. Se presenta una revisión de las condiciones para la interpretación del urianálisis.

A urinary sediment is a tool used for years to characterize renal manifestations of primary and secondary diseases, which requires standardization and learning to interpret it. In patients admitted to the intensive care unit, it is often not performed, or several factors must be taken into account for its interpretation due to the patient's hemodynamic status, glomerular filtration, tubular excretion, water reabsorption, and solutes. In addition to the acid-base balance, which can vary significantly in critically ill patients with different pathophysiological conditions? A review of the conditions for the interpretation of urinalysis is presented.

Evaluation of automated microscopy sediment analysis in urinary tract infection screening: a practical insight in adjusting fixed cut-off values for urine culture.

PURPOSE: The aim of our study was to evaluate a procedure in which urine culture was only being performed based on fixed cut-off values of urine sediment analysis with intention to prevent unnecessary negative urine cultures. METHODS: From January 2018 to August 2018, all urine samples from patients visiting the urology outpatient department were analyzed. Urine culture was only performed if urine sediment contained more than 130 bacteria per microliter and/or more than 50 leukocytes per microliter. RESULTS: In total, 2821 urine cultures with accompanying urine sediments were analyzed. 2098 cultures (74.4%) were defined negative and 723 (25.6%) positive. By adjusting cut-off values of sediment analysis > 20 per microliter or bacteria more than 330 per microliter, 1051 cultures would have been saved with an estimated cost reduction of € 31.470. Eleven clinically relevant urine cultures would have been missed (1%). CONCLUSION: Using cut-offs values leads to a notable decrease of the total number of urine cultures. According to our analysis, adjusting cut-off values could result in 37% less urine cultures and almost 50% less negative cultures. Hereby, unnecessary cost can be prevented [in our department estimated €31.470 in eight months (€ 47.205/year)].

Automated Urine Cell Image Classification Model Using Chaotic Mixer Deep Feature Extraction.

Microscopic examination of urinary sediments is a common laboratory procedure. Automated image-based classification of urinary sediments can reduce analysis time and costs. Inspired by cryptographic mixing protocols and computer vision, we developed an image classification model that combines a novel Arnold Cat Map (ACM)- and fixed-size patch-based mixer algorithm with transfer learning for deep feature extraction. Our study dataset comprised 6,687 urinary sediment images belonging to seven classes: Cast, Crystal, Epithelia, Epithelial nuclei, Erythrocyte, Leukocyte, and Mycete. The developed model consists of four layers: (1) an ACM-based mixer to generate mixed images from resized 224 × 224 input images using fixed-size 16 × 16 patches; (2) DenseNet201 pre-trained on ImageNet1K to extract 1,920 features from each raw input image, and its six corresponding mixed images were concatenated to form a final feature vector of length 13,440; (3) iterative neighborhood component analysis to select the most discriminative feature vector of optimal length 342, determined using a k-nearest neighbor (kNN)-based loss function calculator; and (4) shallow kNN-based classification with ten-fold cross-validation. Our model achieved 98.52% overall accuracy for seven-class classification, outperforming published models for urinary cell and sediment analysis. We demonstrated the feasibility and accuracy of deep feature engineering using an ACM-based mixer algorithm for image preprocessing combined with pre-trained DenseNet201 for feature extraction. The classification model was both demonstrably accurate and computationally lightweight, making it ready for implementation in real-world image-based urine sediment analysis applications.

Bland Urine Sediment in a Child with Acute Kidney Injury.

Tubulointerstitial nephritis (TIN) or acute interstitial nephritis (AIN) is a renal lesion characterized by inflammatory infiltrate limited to the renal interstitium and tubules. Three-fourths of the cases are drug induced, other causes being systemic and autoimmune diseases, and infections. Various drugs have been implicated, the most common being antibiotics such as ß-lactams. Cephalosporins causing AIN have been reported uncommonly, particularly in children. Although renal biopsy confirms the diagnosis, urinalysis provides pertinent diagnostic clues against the backdrop of the clinico-laboratory profile. The presence of white blood cells, white cell casts, and red blood cells in urine sediment have been described in literature. However, a relatively normal urinalysis may be present in some cases and may pose a diagnostic challenge. We present a case of ceftriaxone-induced AIN in a child with bland urine sediment at initial presentation. To the best of our knowledge, this is the first report of ceftriaxone-induced AIN in the pediatric age group.

Automatic Classification of Particles in the Urine Sediment Test with the Developed Artificial Intelligence-Based Hybrid Model.

Urine sediment examination is one of the main tests used in the diagnosis of many diseases. Thanks to this test, many diseases can be detected in advance. Examining the results of this test is an intensive and time-consuming process. Therefore, it is very important to automatically interpret the urine sediment test results using computer-aided systems. In this study, a data set consisting of eight classes was used. The data set used in the study consists of 8509 particle images obtained by examining the particles in the urine sediment. A hybrid model based on textural and Convolutional Neural Networks (CNN) was developed to classify the images in the related data set. The features obtained using textural-based methods and the features obtained from CNN-based architectures were combined after optimizing using the Minimum Redundancy Maximum Relevance (mRMR) method. In this way, we aimed to extract different features of the same image. This increased the performance of the proposed model. The CNN-based ResNet50 architecture and textural-based Local Binary Pattern (LBP) method were used for feature extraction. Finally, the optimized and combined feature map was classified at different machine learning classifiers. In order to compare the performance of the model proposed in the study, results were also obtained from different CNN architectures. A high accuracy value of 96.0% was obtained in the proposed model.

Calcium salt crystalluria in a captive chimpanzee (Pan troglodytes) population.

BACKGROUND: Urinalysis is a rapid, non-invasive method used to obtain diagnostic information on primates. While several studies have investigated dipstick and specific gravity values in chimpanzees, urine sediment analysis is often excluded. Crystalluria, observed during urine sediment analysis, can be benign or indicate renal pathologies. METHODS: In total, 665 urine samples from sanctuary-housed chimpanzees were analyzed over the course of 17 months for pH, specific gravity, time of collection, and crystalluria. RESULTS AND CONCLUSIONS: Calcium salt crystalluria was seen in 9.0% of the samples from 23.7% of the individuals in the study. Urinary pH and specific gravity were significantly higher in samples with crystalluria than in those lacking crystalluria, while time of collection did not differ between the two groups. While diet is the most likely cause of the crystalluria in this population, several medications could also cause urinary crystallization. Further exploration of the significance of calcium salt crystalluria in chimpanzees is warranted.

Identification and validation of methylated PENK gene for early detection of bladder cancer using urine DNA.

BACKGROUND: Early detection of bladder cancer (BCa) offers patients a favorable outcome and avoids the need for cystectomy. Development of an accurate and sensitive noninvasive BCa diagnostic test is imperative. DNA methylation is an early epigenetic event in the development of BCa. Certain specific aberrant methylations could serve as useful biomarkers. The aim of this study was to identify methylation biomarkers for early detection of BCa. METHODS: CpG methylation microarray analysis was conducted on primary tumors with varying stages (T1-T4) and paired nontumor tissues from nine BCa patients. Bisulfite-pyrosequencing was performed to confirm the methylation status of candidate genes in tissues and urine sediments (n = 51). Among them, PENK was selected as a potential candidate and validated using an independent set of 169 urine sediments (55 BCa, 25 benign urologic diseases, 8 other urologic cancers, and 81 healthy controls) with a quantitative methylation-specific real time PCR (mePENK-qMSP). All statistical analyses were performed using MedCalc software version 9.3.2.0. RESULTS: CpG methylation microarray analysis and stepwise validation by bisulfite-pyrosequencing for tissues and urine sediments supported aberrant methylation sites of the PENK gene as potential biomarkers for early detection of BCa. Clinical validation of the mePENK-qMSP test using urine sediment-DNA showed a sensitivity of 86.5% (95% CI: 71.2 - 95.5%), a specificity of 92.5% (95% CI: 85.7 - 96.7%), and an area under ROC of 0.920 (95% CI: 0.863 - 0.959) in detecting Ta high-grade and advanced tumor stages (T1-T4) of BCa patients. Sensitivities for Ta low-grade, Ta high-grade, T1 and T2-T4 were 55.6, 83.3, 88.5, and 100%, respectively. Methylation status of PENK was not correlated with sex, age or stage, while it was associated with the tumor grade of BCa. CONCLUSIONS: In this study, we analyzed the comprehensive patterns of DNA methylation identified that PENK methylation possesses a high potential as a biomarker for urine-based early detection of BCa. Validation of PENK methylation confirms that it could significantly improve the noninvasive detection of BCa.

Improving clinical performance of urine sediment analysis by implementation of intelligent verification criteria.

OBJECTIVES: Urinary test strip and sediment analysis integrated with intelligent verification criteria can help to select samples that need manual review. This study aimed to evaluate the improvement in the diagnostic performance of combined urinary test strip and urinary sediment analysis using intelligent verification criteria on the latest generation automated test strip and urinary fluoresce flow cytometry (UFFC) analysers. METHODS: Urine test strip and sediment analysis were performed using the Sysmex UC-3500 and UF-5000 (Kobe, Japan) on 828 urinary samples at the clinical laboratory of the Ghent University Hospital. The results were compared to manual microscopy using phase-contrast microscopy as a reference. After the application of the intelligent verification criteria, we determined whether the diagnostic performance of urine sediment analysis could be improved. RESULTS: Application of intelligent verification criteria resulted in an increase in specificity from 88.5 to 96.8% and from 88.2 to 94.9% for red blood cells and white blood cells, respectively. Implementing review rules for renal tubular epithelial cells and pathological casts increased the specificity from 66.7 to 74.2% and from 96.2 to 100.0%, respectively; and improved the diagnostic performance of urinary crystals and atypical cells. CONCLUSIONS: The implementation of review rules improved the diagnostic performance of UFFC, thereby increasing the reliability and quality of urine sediment results.

Consistency analysis of the Sysmex UF-5000 and Atellica UAS 800 urine sedimentation analyzers.

OBJECTIVE: To evaluate the consistency between the results of Sysmex UF-5000 system and Atellica® UAS 800 Urine Sediment Analyzer. METHODS: A total of 636 random urine samples were collected from inpatients and outpatients from March to September 2021. Urine was collected for analysis by the Sysmex UF-5000, Atellica UAS 800 systems, and manual microscopic examination. The results of manual microscopy as the gold standard, the coincidence rate and false-negative rate of Sysmex UF-5000 and Atellica UAS 800 systems in the detection of red blood cells, white blood cells, and casts were calculated. RESULTS: The coincidence rates of red blood cells, white blood cells, and cast, crystals, and other sediment components for the Sysmex UF-5000 system were 85.37%, 87.89%, 91.67%, 88.36%, and 71.86%. The false-negative rates were 28.47%, 3.75%, 68.97%, 37.25%, and 30.63%. The coincidence rates of red blood cells, white blood cells, and cast, crystals, and other sediment components for the Atellica UAS 800 system were 85.06%, 90.25%, 59.12%, 91.67%, and 67.45% and the false-negative rates were 60.42%, 21.25%, 36.21%, 19.64%, and 35.80%. CONCLUSION: Two instruments are superior in the detection of red blood cells and white blood cells. The Atellica UAS 800 system with image review has a good coincidence rate in the identification of crystals and casts. The identification of various sediment components in urine by both instruments meets the laboratory requirements. Two instruments with different methodologies have their own characteristics, and we should reasonably use them according to the conditions of the laboratory.

Concomitant Identification of Muddy Brown Granular Casts and Low Fractional Excretion of Urinary Sodium in AKI.

Background: Fractional excretion of urinary sodium (FENa) is a widely utilized clinical test to evaluate acute kidney injury (AKI). A low FENa (<1%) is deemed consistent with prerenal azotemia and inconsistent with acute tubular injury (ATI). Muddy brown granular casts (MBGC) on microscopic examination of urinary sediment (MicrExUrSed) are highly suggestive of ATI. We hypothesized that there is poor concordance between the presence of MBGC and FENa in ATI. Methods: We conducted a prospective observational study in patients with AKI seen during inpatient consultation. We extracted patients who underwent assessment of percentage of low power fields (LPFs) with MBGC by MicrExUrSed and concomitant measurement of FENa. Diagnostic concordance between MBGC and FENa and their individual prognostic value were examined. Results: Our cohort included 270 patients, 111 (41%) of whom were women. Median age was 61 years (range 27-92 years), and median serum creatinine was 3.7 mg/dl ( range1.2-22.0 mg/dl). MBGC were found in 49% (133/270). FENa <1% (inconsistent with ATI) was found in 50/133 (38%), 38/115 (33%), and 16/45 (36%) of those with >0%, ≥10%, and ≥50% LPFs with MBGC, respectively. Concordance between FENa and MBGC for ATI diagnosis was deemed fair (estimated κ-coefficient=0.2), and poor (κ=-0.11) within a subgroup of patients with preexisting chronic kidney disease (n=139). In patients with biopsy-proven ATI (n=49), MBGC had 100% specificity and 100% positive predictive value for ATI. MBGC were associated with greater risk for ≥50% increase in creatinine from baseline at discharge (acute kidney disease [AKD]). Conclusions: About two of five patients with MBGC identified by MicrExUrSed presented with FENa <1%. Presence of MBGC was consistent with ATI, as verified by biopsy, and were predictive of AKD. These data suggest that the sole reliance in low FENa to exclude ATI should be abandoned, and MicrExUrSed should be pursued for AKI diagnosis.