Predictors of Renal Replacement Therapy in Acute Kidney Injury

Koziolek, Michael; Datta, Rabi R.; Mattes, Harry; Jung, Klaus; Heise, Daniel; Streich, Jan H.; Mühlhausen, Johannes; Muêller, G.; Dihazi, Hassan

doi:10.1159/000342257

Cited by 3 publications

(9 citation statements)

References 43 publications

(33 reference statements)

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“…The prediction value of FABP1 and FABP3 is significantly better than the rate we reported recently (88% accuracy in predicting RRT for AKI patients) and better than the best single parameter, cystatin C (correct classification rate 74%) [32] . Despite plasma creatinine and urine output differed between the dialysis and non-dialysis group even at baseline, the AUC of each of these parameters were with 70 and 73% [32] , respectively, clearly below the predictive value of FABP1 and FABP3. This reflects that indication for RRT is complex and actually cannot be based solely on one clinical or laboratory parameter.…”

Section: Discussioncontrasting

confidence: 79%

FABP1 and FABP3 Have High Predictive Values for Renal Replacement Therapy in Patients with Acute Kidney Injury

Dihazi

Koziolek²,

Datta³

et al. 2016

Blood Purif

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Background/Aims: Early initiation of renal replacement therapy (RRT) is recommended in order to improve the clinical outcome of patients who develop an acute kidney injury (AKI). However, markers that guide an early RRT initiation do not really exist currently. Methods: Urine and serum samples were prospectively collected from 120 AKI patients. Depending on the necessity of initiating RRT, patients were divided into 2 different groups: dialysis (n = 52) and non-dialysis (n = 68). Results: Comparative urinary proteomic analyses identified 4 different proteins (fatty acid binding proteins 1 and 3 (FABP1 and FABP3), β-2-microglobulin (B2M), cystatin-M (CST6)) that discriminate AKI patients with high risk for RRT. Western blot analysis confirmed the proteomics data for FABP1 and FABP3 but not for B2M and CST6. Validation analysis confirmed that the FABP1 and FABP3 fulfilled the requirement of functioning as markers for AKI patients with risk to dialysis (p < 0.001). Conclusion: The release of high amounts of FABP1 and FABP3 in urine of AKI patients could serve as a diagnostic/prognosis marker for RRT initiation in these patients.

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Section: Discussioncontrasting

confidence: 79%

FABP1 and FABP3 Have High Predictive Values for Renal Replacement Therapy in Patients with Acute Kidney Injury

Dihazi

Koziolek²,

Datta³

et al. 2016

Blood Purif

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“…Other etiologies of AKI investigated only by a single trial were contrast-associated AKI [ 77 ], Shiga toxin-mediated hemolytic uremic syndrome [ 78 ], burns [ 79 ], and crush syndrome [ 80 ]. Of included studies, only 9 (14.28%) had the primary aim focused on the prediction of RRT [ 18 , 32 , 41 , 45 , 50 , 56 , 72 , 75 , 78 ]. A total of 41 studies, including a total of 13 biomarkers, were included in the quantitative synthesis (meta-analysis).…”

Section: Resultsmentioning

confidence: 99%

“…2). While sample collection and biomarker analysis were quite similar throughout all studies, only 15 studies [ 18 , 27 , 32 , 37 , 41 , 50 , 52 , 56 , 57 , 61 , 64 , 68 , 71 , 75 , 76 ] specified the clinical indications for initiation of RRT. Of these studies, seven [ 19 , 27 , 50 , 56 , 61 , 64 , 76 ] were rated as having set predefined criteria for RRT initiation.…”

Section: Resultsmentioning

confidence: 99%

“…Urine output (UO), analyzed in two studies [ 41 , 49 ] including 604 patients, showed the lowest predictive ability with a pooled AUC of 0.614 (0.389–0.840) (ESM_1_Fig. 13a).…”

Section: Resultsmentioning

confidence: 99%

“…Plasma and serum cystatin C was investigated in eight studies [ 23 , 32 , 37 , 41 , 44 , 50 , 53 , 57 ]; one was excluded for duplicate publication [ 32 ], and the remaining seven showed a pooled AUC of 0.768 (0.729–0.807) derived from 1079 patients (Fig. 5 ).…”

Section: Resultsmentioning

confidence: 99%

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Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis

et al. 2018

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PurposeAcute kidney injury (AKI) frequently occurs in critically ill patients and often precipitates use of renal replacement therapy (RRT). However, the ideal circumstances for whether and when to start RRT remain unclear. We performed evidence synthesis of the available literature to evaluate the value of biomarkers to predict receipt of RRT for AKI.MethodsWe conducted a PRISMA-guided systematic review and meta-analysis including all trials evaluating biomarker performance for prediction of RRT in AKI. A systematic search was applied in MEDLINE, Embase, and CENTRAL databases from inception to September 2017. All studies reporting an area under the curve (AUC) for a biomarker to predict initiation of RRT were included.ResultsSixty-three studies comprising 15,928 critically ill patients (median per study 122.5 [31–1439]) met eligibility. Forty-one studies evaluating 13 different biomarkers were included. Of these biomarkers, neutrophil gelatinase-associated lipocalin (NGAL) had the largest body of evidence. The pooled AUCs for urine and blood NGAL were 0.720 (95% CI 0.638–0.803) and 0.755 (0.706–0.803), respectively. Blood creatinine and cystatin C had pooled AUCs of 0.764 (0.732–0.796) and 0.768 (0.729–0.807), respectively. For urine biomarkers, interleukin-18, cystatin C, and the product of tissue inhibitor of metalloproteinase-2 and insulin growth factor binding protein-7 showed pooled AUCs of 0.668 (0.606–0.729), 0.722 (0.575–0.868), and 0.857 (0.789–0.925), respectively.ConclusionThough several biomarkers showed promise and reasonable prediction of RRT use for critically ill patients with AKI, the strength of evidence currently precludes their routine use to guide decision-making on when to initiate RRT.Electronic supplementary materialThe online version of this article (10.1007/s00134-018-5126-8) contains supplementary material, which is available to authorized users.

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Electronic health records accurately predict renal replacement therapy in acute kidney injury

et al. 2019

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BackgroundElectronic health records (EHR) detect the onset of acute kidney injury (AKI) in hospitalized patients, and may identify those at highest risk of mortality and renal replacement therapy (RRT), for earlier targeted intervention.MethodsProspective observational study to derive prediction models for hospital mortality and RRT, in inpatients aged ≥18 years with AKI detected by EHR over 1 year in a tertiary institution, fulfilling modified KDIGO criterion based on serial serum creatinine (sCr) measures.ResultsWe studied 3333 patients with AKI, of 77,873 unique patient admissions, giving an AKI incidence of 4%. KDIGO AKI stages at detection were 1(74%), 2(15%), 3(10%); corresponding peak AKI staging in hospital were 61, 20, 19%. 392 patients (12%) died, and 174 (5%) received RRT. Multivariate logistic regression identified AKI onset in ICU, haematological malignancy, higher delta sCr (sCr rise from AKI detection till peak), higher serum potassium and baseline eGFR, as independent predictors of both mortality and RRT. Additionally, older age, higher serum urea, pneumonia and intraabdominal infections, acute cardiac diseases, solid organ malignancy, cerebrovascular disease, current need for RRT and admission under a medical specialty predicted mortality. The AUROC for RRT prediction was 0.94, averaging 0.93 after 10-fold cross-validation. Corresponding AUROC for mortality prediction was 0.9 and 0.9 after validation. Decision tree analysis for RRT prediction achieved a balanced accuracy of 70.4%, and identified delta-sCr ≥ 148 μmol/L as the key factor that predicted RRT.ConclusionCase fatality was high with significant renal deterioration following hospital-wide AKI. EHR clinical model was highly accurate for both RRT prediction and for mortality; allowing excellent risk-stratification with potential for real-time deployment.Electronic supplementary materialThe online version of this article (10.1186/s12882-019-1206-4) contains supplementary material, which is available to authorized users.

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Predictors of Renal Replacement Therapy in Acute Kidney Injury

Cited by 3 publications

References 43 publications

FABP1 and FABP3 Have High Predictive Values for Renal Replacement Therapy in Patients with Acute Kidney Injury

FABP1 and FABP3 Have High Predictive Values for Renal Replacement Therapy in Patients with Acute Kidney Injury

Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis

Electronic health records accurately predict renal replacement therapy in acute kidney injury

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