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1.
Am J Physiol Renal Physiol ; 325(6): F888-F898, 2023 12 01.
Article in English | MEDLINE | ID: mdl-37733876

ABSTRACT

Significant loss of kidney function is not easily identified by serum creatinine (sCr)-based measurements. In the presence of normal sCr, decreased kidney functional reserve (KFR) may identify a significant loss of function. We evaluated KFR in experimental subclinical chronic kidney disease (sCKD) before and after brief ischemia-reperfusion injury (IRI). Using fluorescein isothiocyanate-labeled sinistrin, glomerular filtration rate (GFR) was measured transcutaneously before and after adenine-induced sCKD, and 1 and 2 wk after brief IRI, and compared with urinary kidney damage biomarkers. sCKD reduced stimulated and unstimulated GFR by ∼20% while reducing KFR by 50%. IRI reduced unstimulated GFR for 14 days, but KFR remained relatively unchanged in sCKD and transiently increased in control kidneys at 7 days. sCr increased and creatinine clearance (CrCl) decreased only immediately after IRI; sCr and CrCl correlated poorly with measured GFR except on day 1 after IRI. Heterogeneity in sCr and CrCl resulted from variation in tubular creatinine secretion. The increase in damage biomarker concentrations persisted for up to 14 days after IRI, allowing retrospective detection of sCKD before AKI by urine clusterin/urine kidney injury molecule-1 with an area under the curve of 1.0. sCr and CrCl are unreliable unless sCr is acutely elevated. Measurement of KFR and urine damage biomarker excretion detected sCKD despite normal sCr and CrCl. After IRI, the urine clusterin-to-urine kidney injury molecule-1 ratio may identify prior sCKD.NEW & NOTEWORTHY Early kidney function loss is poorly identified by serum creatinine (sCr)-based measurements. Direct kidney functional reserve (KFR) measurement before kidney injury and elevated urinary biomarkers clusterin and kidney injury molecule-1 detect subclinical chronic kidney disease (sCKD) after kidney injury despite normal range sCr and creatinine clearance. Reliance on sCr masks underlying sCKD. Acute kidney injury risk evaluation requires direct glomerular filtration rate measurement and KFR, whereas kidney damage biomarkers facilitate identification of prior subclinical injury.


Subject(s)
Acute Kidney Injury , Renal Insufficiency, Chronic , Humans , Creatinine , Clusterin , Retrospective Studies , Kidney , Acute Kidney Injury/chemically induced , Renal Insufficiency, Chronic/diagnosis , Glomerular Filtration Rate , Biomarkers
2.
Nephrol Dial Transplant ; 38(3): 610-617, 2023 02 28.
Article in English | MEDLINE | ID: mdl-35438795

ABSTRACT

BACKGROUND: Early recognition of hospital-acquired acute kidney injury (AKI) may improve patient management and outcomes. METHODS: This multicentre study was conducted at three hospitals (H1-intervention; H2 and H3-controls) served by a single laboratory. The intervention bundle [an interruptive automated alerts (aAlerts) showing AKI stage and baseline creatinine in the eMR, a management guide and junior medical staff education] was implemented only at H1. Outcome variables included length-of-stay (LOS), all-cause in-hospital mortality and management quality. RESULTS: Over 6 months, 639 patients developed AKI (265 at H1 and 374 at controls), with 94.7% in general wards; 537 (84%) patients developed Stage 1, 58 (9%) Stage 2 and 43 (7%) Stage 3 AKI. Median LOS was 9 days (IQR 4-17) and was not different between intervention and controls. However, patients with AKI stage 1 had shorter LOS at H1 [median 8 versus 10 days (P = 0.021)]. Serum creatinine had risen prior to admission in most patients. Documentation of AKI was better in H1 (94.8% versus 83.4%; P = 0.001), with higher rates of nephrology consultation (25% versus 19%; P = 0.04) and cessation of nephrotoxins (25.3 versus 18.8%; P = 0.045). There was no difference in mortality between H1 versus controls (11.7% versus 13.0%; P = 0.71). CONCLUSIONS: Most hospitalized patients developed Stage 1 AKI and developed AKI in the community and remained outside the intensive care unit (ICU). The AKI eAlert bundle reduced LOS in most patients with AKI and increased AKI documentation, nephrology consultation rate and cessation of nephrotoxic medications.


Subject(s)
Acute Kidney Injury , Patient Care Bundles , Humans , Cohort Studies , Australia/epidemiology , Acute Kidney Injury/diagnosis , Acute Kidney Injury/therapy , Hospitalization , Intensive Care Units , Creatinine , Retrospective Studies
3.
Ann Lab Med ; 42(2): 178-187, 2022 03 01.
Article in English | MEDLINE | ID: mdl-34635611

ABSTRACT

Background: Urine tissue inhibitor of metalloproteinases-2/insulin-like growth factor-binding protein 7 (TIMP-2/IGFBP7) (NephroCheck, Ortho Clinical Diagnostics, Raritan, NJ, USA) is a US Food and Drug Administration-approved biomarker for risk assessment of acute kidney injury (AKI) in critically ill adult patients in intensive care units; however, its clinical impact in the emergency department (ED) remains unproven. We evaluated the utility of NephroCheck for predicting AKI development and short-term mortality in the ED. Methods: This was a prospective, observational, five-center international study. We consecutively enrolled ED patients admitted with ≥30% risk of AKI development (assessed by ED physician: ED score) or acute diseases. Serum creatinine was tested on ED arrival (T0), day 1, and day 2 (T48); urine for NephroCheck was collected at T0 and T48. We performed ROC curve and reclassification analyses. Results: Among the 529 patients enrolled (213 females; median age, 65 years), AKI developed in 59 (11.2%) patients. The T0 NephroCheck value was higher in the AKI group than in the non-AKI group (median 0.77 vs. 0.29 (ng/m)2/1,000, P=0.001), and better predicted AKI development than the ED score (area under the curve [AUC], 0.64 vs. 0.53; P=0.04). In reclassification analyses, adding NephroCheck to the ED score improved the prediction of AKI development (P<0.05). The T0 NephroCheck value predicted 30-day mortality (AUC, 0.68; P<0.001). Conclusions: NephroCheck can predict both AKI development and short-term mortality in at-risk ED patients. NephroCheck would be a useful biomarker for early ruling-in or ruling-out of AKI in the ED.


Subject(s)
Acute Kidney Injury , Insulin-Like Growth Factor Binding Proteins/urine , Tissue Inhibitor of Metalloproteinase-2 , Acute Disease , Acute Kidney Injury/diagnosis , Aged , Biomarkers , Emergency Service, Hospital , Female , Humans , Male , Prospective Studies , Tissue Inhibitor of Metalloproteinase-2/urine , United States
4.
Nephrology (Carlton) ; 26(10): 782-789, 2021 Oct.
Article in English | MEDLINE | ID: mdl-34176181

ABSTRACT

AIM: Kinetic estimated Glomerular Filtration Rate (KeGFR) approximates GFR under non-steady-state conditions. We investigated whether the ratio of KeGFR difference to baseline eGFR could predict acute kidney injury (AKI) earlier than a creatinine-based algorithm that triggered an AKI electronic Alert (eAlert). METHODS: This retrospective, single-centre, proof-of-concept cohort study assessed all patients diagnosed with AKI by an automated serum creatinine-based eAlert. The kinetic eGFR, the kinetic eGFR difference from baseline and the ratio of difference to baseline was calculated in subjects with at least two serum creatinine (sCr) measurements within 72 h of AKI. RESULTS: Patients in the AKI cohort (n = 140) had a significant decline in KeGFR ratio (AKI: 17% IQR 7% to 29%, Non-AKI: 0 IQR -12% to 9%; P-value <.0001). A decrease of the ratio greater than 10% predicted AKI with a sensitivity of 66%, a specificity of 77%, a positive predictive value of 63%, and negative predictive value of 80%. The median lead time between KeGFR ratio decrease and AKI was 24 h (IQR: 19-27 h). CONCLUSIONS: KeGFR ratio is a cheap, simple method that predicted AKI 24 h before laboratory detection. KeGFR may facilitate triaging patients to increased monitoring or intervention.


Subject(s)
Acute Kidney Injury/diagnosis , Creatinine/blood , Glomerular Filtration Rate , Kidney/physiopathology , Acute Kidney Injury/blood , Acute Kidney Injury/physiopathology , Aged , Aged, 80 and over , Biomarkers/blood , Early Diagnosis , Female , Hospitalization , Humans , Kinetics , Male , Middle Aged , New South Wales , Predictive Value of Tests , Proof of Concept Study , Retrospective Studies
5.
PLoS One ; 15(5): e0233109, 2020.
Article in English | MEDLINE | ID: mdl-32437461

ABSTRACT

Normalisation to standard reference gene(s) is essential for quantitative real-time polymerase chain reaction (RT-qPCR) to obtain reproducible and comparable results of a gene of interest (GOI) between subjects and under varying experimental conditions. There is limited evidence to support selection of the commonly used reference genes in rat ischaemic and toxicological kidney models. Employing these models, we determined the most stable reference genes by comparing 4 standard methods (NormFinder, qBase+, BestKeeper and comparative ΔCq) and developed a new 3-way linear mixed-effects model for evaluation of reference gene stability. This new technique utilises the intra-class correlation coefficient as the stability measure for multiple continuous and categorical covariates when determining the optimum normalisation factor. The model also determines confidence intervals for each candidate normalisation gene to facilitate selection and allow sample size calculation for designing experiments to identify reference genes. Of the 10 candidate reference genes tested, the geometric mean of polyadenylate-binding nuclear protein 1 (PABPN1) and beta-actin (ACTB) was the most stable reference combination. In contrast, commonly used ribosomal 18S and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) were the most unstable. We compared the use of PABPN1×ACTB and 2 commonly used genes 18S and GAPDH on the expression of 4 genes of interest know to vary after renal injury and expressed by different kidney cell types (KIM-1, HIF1α, TGFß1 and PECAM1). The less stable reference genes gave varying patterns of GOI expression in contrast to the use of the least unstable reference PABPN1×ACTB combination; this improved detection of differences in gene expression between experimental groups. Reduced within-group variation of the now more accurately normalised GOI may allow for reduced experimental group size particularly for comparison between various models. This objective selection of stable reference genes increased the reliability of comparisons within and between experimental groups.


Subject(s)
Gene Expression Regulation , Ischemia/metabolism , Kidney Diseases/metabolism , Kidney/blood supply , Kidney/metabolism , Real-Time Polymerase Chain Reaction/standards , Reverse Transcriptase Polymerase Chain Reaction/standards , Actins/biosynthesis , Animals , Ischemia/pathology , Kidney/pathology , Kidney Diseases/pathology , Poly(A)-Binding Protein I/biosynthesis , RNA, Ribosomal, 18S/biosynthesis , Rats , Reference Standards
6.
Mol Diagn Ther ; 23(3): 333-351, 2019 06.
Article in English | MEDLINE | ID: mdl-30941671

ABSTRACT

Early detection of graft injury after kidney transplantation is key to maintaining long-term good graft function. Graft injury could be due to a multitude of factors including ischaemia reperfusion injury, cell or antibody-mediated rejection, progressive interstitial fibrosis and tubular atrophy, infections and toxicity from the immunosuppressive drugs themselves. The current gold standard for assessing renal graft dysfunction is renal biopsy. However, biopsy is usually late when triggered by a change in serum creatinine and of limited utility in diagnosis of early injury when histological changes are equivocal. Therefore, there is a need for timely, objective and non-invasive diagnostic techniques with good early predictive value to determine graft injury and provide precision in titrating immunosuppression. We review potential novel plasma and urine biomarkers that offer sensitive new strategies for early detection and provide major insights into mechanisms of graft injury. This is a rapidly expanding field, but it is likely that a combination of biomarkers will be required to provide adequate sensitivity and specificity for detecting graft injury.


Subject(s)
Graft Rejection/diagnosis , Graft Rejection/etiology , Graft Survival , Kidney Transplantation/adverse effects , Cytokines/metabolism , Gene Expression Profiling , Graft Rejection/metabolism , Humans , Metabolomics/methods , MicroRNAs/genetics , Proteomics/methods , RNA, Messenger/genetics , Transcriptome
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