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.
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.
Authors: Robert M Cronin; Jacob P VanHouten; Edward D Siew; Svetlana K Eden; Stephan D Fihn; Christopher D Nielson; Josh F Peterson; Clifton R Baker; T Alp Ikizler; Theodore Speroff; Michael E Matheny Journal: J Am Med Inform Assoc Date: 2015-06-23 Impact factor: 4.497
Authors: Mostafa S K Tawfeek; Doaa M Raafat; Khaled Saad; Naglaa K Idriss; Sherif Sayed; Doaa A Fouad; Amira A El-Houfey Journal: Ther Adv Cardiovasc Dis Date: 2015-11-30
Authors: Sharon E Davis; Thomas A Lasko; Guanhua Chen; Edward D Siew; Michael E Matheny Journal: J Am Med Inform Assoc Date: 2017-11-01 Impact factor: 4.497
Authors: Salvatore Di Somma; Laura Magrini; Benedetta De Berardinis; Rossella Marino; Enrico Ferri; Paolo Moscatelli; Paola Ballarino; Giuseppe Carpinteri; Paola Noto; Biancamaria Gliozzo; Lorenzo Paladino; Enrico Di Stasio Journal: Crit Care Date: 2013-02-12 Impact factor: 9.097