Creatinine-Based Definitions: From Baseline Creatinine to Serum Creatinine Adjustment in Intensive Care

Rosa, Silvia De; Samoni, Sara; Ronco, Claudio

doi:10.1007/978-3-319-27349-5_8

Cited by 9 publications

(13 citation statements)

References 39 publications

(27 reference statements)

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“…In the critically ill, several confounders affecting Cr‐based AKI definitions have been identified. These include volume overload and subsequent dilution of Cr, malnutrition, and muscle wasting . We did not find difference in cumulative fluid balances among patients with and without AKI in the first 6 hours, and thus, the Cr P value is unlikely to be affected by fluid balance .…”

Section: Discussionmentioning

confidence: 52%

“…The primary outcome was AKI on day 2 based on Cr DAY2 measurement and determined according to the Kidney Disease: Improving Global Outcomes (KDIGO) Cr and RRT criteria . Cr F served as the baseline Cr as no data regarding outpatient Cr values preceding the index hospitalization were available. Data about urine output normalized to patient weight were unavailable which prevented the application of the KDIGO urine output criteria for AKI.…”

Section: Methodsmentioning

confidence: 99%

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Point‐of‐care creatinine measurements to predict acute kidney injury

Vaara

Glassford

Eastwood

et al. 2020

Acta Anaesthesiol Scand

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Background Plasma creatinine (Cr) is a marker of kidney function and typically measured once daily. We hypothesized that Cr measured by point‐of‐care technology early after ICU admission would be a good predictor of acute kidney injury (AKI) the next day in critically ill patients. Methods We conducted a retrospective database audit in a single tertiary ICU database. We included patients with normal first admission Cr (CrF) and identified a Cr value (CrP) obtained within 6‐12 hours from ICU admission. We used their difference converted into percentage (delta‐Cr‐%) to predict subsequent AKI (based on Cr and/or need for renal replacement therapy) the next day. We assessed predictive value by calculating area under the receiver characteristic curve (AUC), logistic regression models for AKI with and without delta‐Cr‐%, and the category‐free net reclassifying index (cfNRI). Results We studied 780 patients. Overall, 70 (9.0%) fulfilled the Cr AKI definition by CrP measurement. On day 2, 148 patients (19.0%) were diagnosed with AKI. AUC (95% CI) for delta‐Cr‐% to predict AKI on day 2 was 0.82 (95% CI 0.78‐0.86), and 0.74 (95% CI 0.69‐0.80) when patients with AKI based on the CrP were excluded. Using a cut‐off of 17% increment, the positive likelihood ratio (95% CI) for delta‐Cr‐% to predict AKI was 3.5 (2.9‐4.2). The cfNRI was 90.0 (74.9‐106.1). Conclusions Among patients admitted with normal Cr, early changes in Cr help predict AKI the following day.

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Section: Discussionmentioning

confidence: 52%

Section: Methodsmentioning

confidence: 99%

Point‐of‐care creatinine measurements to predict acute kidney injury

Vaara

Glassford

Eastwood

et al. 2020

Acta Anaesthesiol Scand

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“…In this study, we found that combination with biomarker NephroCheck and risk factors for risk assessment of AKI has the greatest signi cance to patients with uncertain disease trajectories. Future research needs to clinically or electronically identify patients at high risk of AKI development or progression to CKD or ESRD [1,33]. We plan to develop an electronic alert system including the assessment of NephroCheck and risk factors.…”

Section: Discussionmentioning

confidence: 99%

Combination of biomarker with clinical risk factors for prediction of severe acute kidney injury in critically ill patients

Jia

Sheng

Zamperetti

et al. 2020

Preprint

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Background: Acute kidney injury (AKI) occurs commonly in the intensive care unit (ICU). Insulin-like growth factor-binding protein 7 (IGFBP7) and tissue inhibitor of metalloproteinase-2 (TIMP-2), known as [TIMP-2] x [IGFBP7] (NephroCheck), have been identified as novel biomarkers for the prediction of AKI risk. However, the effective use of disease biomarkers is indispensable from an appropriate clinical context. We conducted a retrospective cohort study to find risk factors and assess the performance of the combination of NephroCheck with risk factors, so as to provide feasible information for AKI prediction.Methods: All patients who were admitted in the ICU ( from June 2016 to July 2017) participated in the study. The primary outcome was the detection of severe AKI within the first seven days after patients being admitted to the ICU. The predictors were separated into three categories: chronic risk factors, acute risk factors and biochemical indicators. Results: The study included 577 patients. 96 patients developed to severe AKI (16.6%) within seven days. In addition to NephroCheck (+) (OR=2.139, 95% CI (1.260-3.630), P =0.005), age >65 years (OR=1.961, 95% CI (1.153-3.336), P=0.013), CKD (OR=2.573, 95% CI (1.319-5.018), P=0.006) and PCT (+)(OR=3.223, 95% CI (1.643-6.321), P=0.001) were also the independent predictors of severe AKI within seven days. Compared to NephroCheck (+) only (AUC=0.66, 95% CI:0.60-0.72), the combination of NephroCheck (+) and risk factors (age>65years, CKD and PCT positive) (AUC=0.75, 95% CI:0.70-0.81) led to a significant increase in the area under ROC curve for severe AKI prediction within seven days.Conclusions: Although NephroCheck is an effective screening tool for recognizing high-risk patients, we found that combination with biomarker and risk factors (age>65years, CKD, procalcitonin positive) for risk assessment of AKI has the greatest significance to patients with uncertain disease trajectories.

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“…AKI was diagnosed as determined by an adjudication committee of 3 expert nephrologists who were blinded to the biomarker results, based on the KDIGO criteria (5) using the peak postoperative sCr within 10 days after surgery and excluding sCr at admission to postoperative ICU. Baseline sCr was defined as the usual value of sCr preceding the admission within at least 7 days (12) or as the nadir sCr after recovery of renal function (13).…”

Section: Methodsmentioning

confidence: 99%

Routine Adoption of TIMP2 and IGFBP7 Biomarkers in Cardiac Surgery for Early Identification of Acute Kidney Injury

et al. 2017

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Background and purposeAcute Kidney Injury (AKI) is a severe complication affecting many hospitalized patients after cardiac surgery, with negative impacts on short- and long-term clinical outcomes and on healthcare costs. Recently, clinical interest has been aimed at defining and classifying AKI, identifying risk factors and developing diagnostic strategies to identify patients at risk early on. Achieving an early and accurate diagnosis of AKI is a crucial issue, because prevention and timely detection may help to prevent negative clinical outcomes and avoid AKI-associated costs. In this retrospective study, we evaluate the NephroCheck Test as a diagnostic tool for early detection of AKI in a high-risk population of patients undergoing cardiac surgery at the San Bortolo Hospital of Vicenza.MethodsWe assessed the ability of the NephroCheck Test to predict the probability of developing CSA-AKI (cardiac surgery-associated AKI) and evaluated its accuracy as a diagnostic test, by building a multivariate logistic regression model for CSA-AKI prediction.ResultsBased on our findings, when the results of the NephroCheck Test are included in a multivariate model its performance is substantially improved, as compared to the benchmark model, which only accounts for the other clinical factors. We also define a rule – in terms of a probability cut-off – for discriminating cases that are at higher risk of developing AKI of any stage versus those in which AKI is less likely.ConclusionsOur study has implications in clinical practice: when a Nephrocheck Test result is >0.3 ng/dL, an automated electronic alert prompts the physician to intervene by following a checklist of preventive measures.

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Creatinine-Based Definitions: From Baseline Creatinine to Serum Creatinine Adjustment in Intensive Care

Abstract: This article is one of ten reviews selected

Cited by 9 publications

References 39 publications

Point‐of‐care creatinine measurements to predict acute kidney injury

Point‐of‐care creatinine measurements to predict acute kidney injury

Combination of biomarker with clinical risk factors for prediction of severe acute kidney injury in critically ill patients

Routine Adoption of TIMP2 and IGFBP7 Biomarkers in Cardiac Surgery for Early Identification of Acute Kidney Injury

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