Early prediction of acute kidney injury after transapical and transaortic aortic valve implantation with urinary G1 cell cycle arrest biomarkers

Dusse, Fabian; Edayadiyil-Dudásova, Michaela; Thielmann, Matthias; Wendt, Daniel; Kahlert, Philipp; Demircioğlu, Ender; Jakob, Heinz; Schaefer, Simon; Pilarczyk, Kevin

doi:10.1186/s12871-016-0244-8

Cited by 51 publications

(46 citation statements)

References 26 publications

(40 reference statements)

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“…“?” in yellow means unclear risk. In the index test part, some studies [13–15, 17–18] were valued as high risk, because these studies had not used setting threshold. Two studies [13–14] did not mentioned blind or not so we valued them unclear risk in the reference standard part.…”

Section: Resultsmentioning

confidence: 99%

Diagnostic Value of Urine Tissue Inhibitor of Metalloproteinase-2 and Insulin-Like Growth Factor-Binding Protein 7 for Acute Kidney Injury: A Meta-Analysis

Gong

et al. 2017

PLoS ONE

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BackgroundTissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein-7 (IGFBP7) are both involved in renal tubular epithelial cell cycle arrest in acute kidney injury (AKI). Several recent studies showed that urine TIMP-2 times IGFBP7 ([TIMP-2]*[IGFBP7]) is a promising biomarker to predict AKI.MethodsThe aim of this meta-analysis was to assess the diagnostic value of urine [TIMP-2]*[IGFBP7] for early diagnosis of AKI. Relevant studies were retrieved from the PubMed, EMBASE, and Cochrane Library databases. The sensitivity and specificity were determined, and summary receiver operating characteristic (SROC) curves were constructed.ResultsTen full-text prospective studies were included in this meta-analysis. The estimated sensitivity of urine [TIMP-2]*[IGFBP7] for the early diagnosis of AKI was 0.84 (95% CI = 0.80–0.88) and the specificity was 0.57 (95%CI = 0.55–0.60). The SROC analysis showed an area under the curve of 0.8813.LimitationThe limited number of included studies, small sample size, unpublished negative results and language limitation might have affected the evaluation.ConclusionUrine [TIMP-2]*[IGFBP7] is a promising candidate for early detection of AKI, especially in ruling-out AKI. However, the potential of this biomarker should be validated in larger studies with a broader spectrum of clinical settings.

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Section: Resultsmentioning

confidence: 99%

Diagnostic Value of Urine Tissue Inhibitor of Metalloproteinase-2 and Insulin-Like Growth Factor-Binding Protein 7 for Acute Kidney Injury: A Meta-Analysis

Gong

et al. 2017

PLoS ONE

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“…After removing duplicates, 52 articles were screened by title and abstract, 24 were subsequently rescreened by full text, with 28 articles excluded. Finally, four eligible studies with 277 patients were included in this study . These four studies, published between 2015 and 2016, were all prospective cohort studies.…”

Section: Resultsmentioning

confidence: 99%

“…About 15.8–34.8% of AKI patients require RRT . Critically ill patients with AKI who require RRT show higher potential risk of death than non‐RRT patients .…”

Section: Discussionmentioning

confidence: 99%

“…About 15.8-34.8% of AKI patients require RRT. [17][18][19][20] Critically ill patients with AKI who require RRT show higher potential risk of death than non-RRT patients. 20,23,24 By predicting the need for RRT, clinicians can initiate the implementation of supportive measures (volume management, maintenance of adequate blood pressure, and avoidance of nephrotoxins) earlier, which may decrease the need for RRT as well as mortality.…”

Section: Discussionmentioning

confidence: 99%

“…Finally, four eligible studies with 277 patients were included in this study. [17][18][19][20] These four studies, published between 2015 and 2016, were all prospective cohort studies. Among them, the definitions of high risk for AKI were different: one study defined it as major surgery with an additional risk factor (critical illness, sepsis, major trauma, chronic renal disease or use of radiocontrast agent), one study as cardiac surgery, and the remaining two studies as critical illness in the ICU.…”

Section: Study Selection and Characteristicsmentioning

confidence: 99%

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Prognostic value of cell cycle arrest biomarkers in patients at high risk for acute kidney injury: A systematic review and meta‐analysis

et al. 2017

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Urinary tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7) are G1 cell cycle arrest biomarkers. This systematic review aimed to evaluate the prognostic value of urinary [TIMP-2]·[IGFBP7] in patients at high risk for AKI. The MEDLINE (via PubMed), Ovid, EMBASE and Cochrane Library databases were systematically searched from inception to December 25, 2016. Original clinical studies which met the eligibility criteria were included in this study. The prognostic accuracy of urinary [TIMP-2]·[IGFBP7] for assessing the need for renal replacement therapy (RRT) and mortality was evaluated by pooled sensitivity, specificity, diagnostic odds ratio, and summary receiver operating characteristic curves. A total of four prospective cohort studies evaluating 277 patients were included. The estimated area under the receiver operating characteristic curve (AUC) of urinary [TIMP-2]·[IGFBP7] for predicting the need for RRT in patients at high risk for AKI was 0.915 (standard error [SE] = 0.040). Pooled sensitivity and specificity with corresponding 95% confidence intervals (CI) were 0.69 (95% CI 0.53-0.82) and 0.81 (95% CI 0.75-0.86), respectively. Urinary [TIMP-2]·[IGFBP7] for mortality prediction in patients at high risk for AKI was assessed by qualitative description. Based on the above data, urinary [TIMP-2]·[IGFBP7] performs well in predicting the need for RRT and mortality in patients at high risk for AKI. However, further meta-analyses are warranted as more data become available.

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Predictive Accuracy of a Perioperative Laboratory Test–Based Prediction Model for Moderate to Severe Acute Kidney Injury After Cardiac Surgery

Demirjian

Bashour

Shaw

et al. 2022

JAMA

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IMPORTANCEEffective treatment of acute kidney injury (AKI) is predicated on timely diagnosis; however, the lag in the increase in serum creatinine levels after kidney injury may delay therapy initiation.OBJECTIVE To determine the derivation and validation of predictive models for AKI after cardiac surgery.DESIGN, SETTING, AND PARTICIPANTS Multivariable prediction models were derived based on a retrospective observational cohort of adult patients undergoing cardiac surgery between January 2000 and December 2019 from a US academic medical center (n = 58 526) and subsequently validated on an external cohort from 3 US community hospitals (n = 4734). The date of final follow-up was January 15, 2020.EXPOSURES Perioperative change in serum creatinine and postoperative blood urea nitrogen, serum sodium, potassium, bicarbonate, and albumin from the first metabolic panel after cardiac surgery. MAIN OUTCOMES AND MEASURESArea under the receiver-operating characteristic curve (AUC) and calibration measures for moderate to severe AKI, per Kidney Disease: Improving Global Outcomes (KDIGO), and AKI requiring dialysis prediction models within 72 hours and 14 days following surgery. RESULTSIn a derivation cohort of 58 526 patients (median [IQR] age, 66 [56-74] years; 39 173 [67%] men; 51 503 [91%] White participants), the rates of moderate to severe AKI and AKI requiring dialysis were 2674 (4.6%) and 868 (1.48%) within 72 hours and 3156 (5.4%) and 1018 (1.74%) within 14 days after surgery. The median (IQR) interval to first metabolic panel from conclusion of the surgical procedure was 10 (7-12) hours. In the derivation cohort, the metabolic panel-based models had excellent predictive discrimination for moderate to severe AKI within 72 hours (AUC, 0.876 [95% CI, 0.869-0.883]) and 14 days (AUC, 0.854 [95% CI, 0.850-0.861]) after the surgical procedure and for AKI requiring dialysis within 72 hours (AUC, 0.916 [95% CI, 0.907-0.926]) and 14 days (AUC, 0.900 [95% CI, 0.889-0.909]) after the surgical procedure. In the validation cohort of 4734 patients (median [IQR] age, 67 (60-74) years; 3361 [71%] men; 3977 [87%] White participants), the models for moderate to severe AKI after the surgical procedure showed AUCs of 0.860 (95% CI, 0.838-0.882) within 72 hours and 0.842 (95% CI, 0.820-0.865) within 14 days and the models for AKI requiring dialysis and 14 days had an AUC of 0.879 (95% CI, 0.840-0.918) within 72 hours and 0.873 (95% CI, 0.836-0.910) within 14 days after the surgical procedure. Calibration assessed by Spiegelhalter z test showed P >.05 indicating adequate calibration for both validation and derivation models.CONCLUSIONS AND RELEVANCE Among patients undergoing cardiac surgery, a prediction model based on perioperative basic metabolic panel laboratory values demonstrated good predictive accuracy for moderate to severe acute kidney injury within 72 hours and 14 days after the surgical procedure. Further research is needed to determine whether use of the risk prediction tool improves clinical outcomes.

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Early prediction of acute kidney injury after transapical and transaortic aortic valve implantation with urinary G1 cell cycle arrest biomarkers

Cited by 51 publications

References 26 publications

Diagnostic Value of Urine Tissue Inhibitor of Metalloproteinase-2 and Insulin-Like Growth Factor-Binding Protein 7 for Acute Kidney Injury: A Meta-Analysis

Diagnostic Value of Urine Tissue Inhibitor of Metalloproteinase-2 and Insulin-Like Growth Factor-Binding Protein 7 for Acute Kidney Injury: A Meta-Analysis

Prognostic value of cell cycle arrest biomarkers in patients at high risk for acute kidney injury: A systematic review and meta‐analysis

Predictive Accuracy of a Perioperative Laboratory Test–Based Prediction Model for Moderate to Severe Acute Kidney Injury After Cardiac Surgery

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