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A combined cardiorenal assessment for the prediction of acute kidney injury in lower respiratory tract infections.

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Author Breidthardt Tobias, Christ-Crain Mirjam, Stolz Daiana, Bingisser Roland, Drexler Beatrice, Klima Theresia, Balmelli Catharina, Schuetz Philipp, Haaf Philip, Schärer Michael, Tamm Michael, Müller Beat, Müller Christian,
Project Preventing viral exacerbation of chronic obstructive pulmonary disease in upper respiratory tract infection - The PREVENT study
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Original article (peer-reviewed)

Journal The American journal of medicine
Volume (Issue) 125(2)
Page(s) 168 - 75
Title of proceedings The American journal of medicine
DOI 10.1016/j.amjmed.2011.07.010

Abstract

BACKGROUND The accurate prediction of acute kidney injury (AKI) is an unmet clinical need. A combined assessment of cardiac stress and renal tubular damage might improve early AKI detection. METHODS A total of 372 consecutive patients presenting to the Emergency Department with lower respiratory tract infections were enrolled. Plasma B-type natriuretic peptide (BNP) and neutrophil gelatinase-associated lipocalin (NGAL) levels were measured in a blinded fashion at presentation. The potential of these biomarkers to predict AKI was assessed as the primary endpoint. AKI was defined according to the AKI Network classification. RESULTS Overall, 16 patients (4%) experienced early AKI. These patients were more likely to suffer from preexisting chronic cardiac disease or diabetes mellitus. At presentation, BNP (334 pg/mL [130-1119] vs 113 pg/mL [52-328], P <.01) and NGAL (269 ng/mL [119-398] vs 96 ng/mL [60-199], P <.01) levels were significantly higher in AKI patients. The predictive accuracy of presentation BNP and NGAL levels was comparable (BNP 0.74; 95% confidence interval [CI], 0.64-0.84 vs NGAL 0.74; 95% CI, 0.61-0.87). In a combined logistic model, a joint BNP/NGAL approach improved the predictive accuracy for early AKI over either biomarker alone (area under the receiver operating characteristic curve: 0.82; 95% CI, 0.74-0.89). The combined categorical cut point defined by BNP >267 pg/mL or NGAL >231 ng/mL correctly identified 15 of 16 early AKI patients (sensitivity 94%, specificity 61%). During multivariable regression analysis, the combined BNP/NGAL cutoff remained the independent predictor of early AKI (hazard ratio 10.82; 95% CI, 1.22-96.23; P = .03). CONCLUSION A model combining the markers BNP and NGAL is a powerful predictor of early AKI in patients with lower respiratory tract infection.
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