AIMS: To determine if newer criteria for diagnosing and staging acute kidney injury (AKI) during heart failure (HF) admission are more predictive of clinical outcomes at 30 days and 1 year than the traditional worsening renal function (WRF) definition. METHODS: We analyzed prospectively collected clinical data on 637 HF admissions with 30-day and 1-year follow-up. The incidence, stages, and outcomes of AKI were determined using the following four definitions: KDIGO, RIFLE, AKIN, and WRF (serum creatinine rise ≥0.3 mg/dl). Receiver operating curves were used to compare the predictive ability of each AKI definition for the occurrence of adverse outcomes (death, rehospitalization, dialysis). RESULTS: AKI by any definition occurred in 38.3% (244/637) of cases and was associated with an increased incidence of 30-day (32.3 vs. 6.9%, χ(2) = 70.1; p < 0.001) and 1-year adverse outcomes (67.5 vs. 31.0%, χ(2) = 81.4; p < 0.001). Most importantly, there was a stepwise increase in primary outcome with increasing stages of AKI severity using RIFLE, KDIGO, or AKIN (p < 0.001). In direct comparison, there were only small differences in predictive abilities between RIFLE and KDIGO and WRF concerning clinical outcomes at 30 days (AUC 0.76 and 0.74 vs. 0.72, χ(2) = 5.6; p = 0.02) as well as for KDIGO and WRF at 1 year (AUC 0.67 vs. 0.65, χ(2) = 4.8; p = 0.03). CONCLUSION: During admission for HF, the benefits of using newer AKI classification systems (RIFLE, AKIN, KDIGO) lie with the ability to identify those patients with more severe degrees of AKI who will go on to experience adverse events at 30 days and 1 year. The differences in terms of predictive abilities were only marginal.
AIMS: To determine if newer criteria for diagnosing and staging acute kidney injury (AKI) during heart failure (HF) admission are more predictive of clinical outcomes at 30 days and 1 year than the traditional worsening renal function (WRF) definition. METHODS: We analyzed prospectively collected clinical data on 637 HF admissions with 30-day and 1-year follow-up. The incidence, stages, and outcomes of AKI were determined using the following four definitions: KDIGO, RIFLE, AKIN, and WRF (serum creatinine rise ≥0.3 mg/dl). Receiver operating curves were used to compare the predictive ability of each AKI definition for the occurrence of adverse outcomes (death, rehospitalization, dialysis). RESULTS: AKI by any definition occurred in 38.3% (244/637) of cases and was associated with an increased incidence of 30-day (32.3 vs. 6.9%, χ(2) = 70.1; p < 0.001) and 1-year adverse outcomes (67.5 vs. 31.0%, χ(2) = 81.4; p < 0.001). Most importantly, there was a stepwise increase in primary outcome with increasing stages of AKI severity using RIFLE, KDIGO, or AKIN (p < 0.001). In direct comparison, there were only small differences in predictive abilities between RIFLE and KDIGO and WRF concerning clinical outcomes at 30 days (AUC 0.76 and 0.74 vs. 0.72, χ(2) = 5.6; p = 0.02) as well as for KDIGO and WRF at 1 year (AUC 0.67 vs. 0.65, χ(2) = 4.8; p = 0.03). CONCLUSION: During admission for HF, the benefits of using newer AKI classification systems (RIFLE, AKIN, KDIGO) lie with the ability to identify those patients with more severe degrees of AKI who will go on to experience adverse events at 30 days and 1 year. The differences in terms of predictive abilities were only marginal.
Authors: Robb D Kociol; Melissa A Greiner; Bradley G Hammill; Hemant Phatak; Gregg C Fonarow; Lesley H Curtis; Adrian F Hernandez Journal: Am J Cardiol Date: 2010-04-27 Impact factor: 2.778
Authors: Daniel E Forman; Javed Butler; Yongfei Wang; William T Abraham; Christopher M O'Connor; Stephen S Gottlieb; Evan Loh; Barry M Massie; Michael W Rich; Lynne Warner Stevenson; James B Young; Harlan M Krumholz Journal: J Am Coll Cardiol Date: 2004-01-07 Impact factor: 24.094
Authors: Mohammed W Akhter; Doron Aronson; Fahed Bitar; Salman Khan; Harpreet Singh; Rajinder P Singh; Andrew J Burger; Uri Elkayam Journal: Am J Cardiol Date: 2004-10-01 Impact factor: 2.778
Authors: Kenneth Dickstein; Alain Cohen-Solal; Gerasimos Filippatos; John J V McMurray; Piotr Ponikowski; Philip Alexander Poole-Wilson; Anna Strömberg; Dirk J van Veldhuisen; Dan Atar; Arno W Hoes; Andre Keren; Alexandre Mebazaa; Markku Nieminen; Silvia Giuliana Priori; Karl Swedberg Journal: Eur Heart J Date: 2008-09-17 Impact factor: 29.983
Authors: Ravindra L Mehta; John A Kellum; Sudhir V Shah; Bruce A Molitoris; Claudio Ronco; David G Warnock; Adeera Levin Journal: Crit Care Date: 2007 Impact factor: 9.097
Authors: F Ülger; M Pehlivanlar Küçük; A O Küçük; N K İlkaya; N Murat; B Bilgiç; H Abanoz Journal: Eur J Trauma Emerg Surg Date: 2017-07-17 Impact factor: 3.693
Authors: Scott M Sutherland; John J Byrnes; Manish Kothari; Christopher A Longhurst; Sanjeev Dutta; Pablo Garcia; Stuart L Goldstein Journal: Clin J Am Soc Nephrol Date: 2015-02-03 Impact factor: 8.237
Authors: M Ahmed Ali; E S Mikhael; A Abdelkader; L Mansour; R El Essawy; R El Sayed; A Eladawy; A Mukhtar Journal: Eur J Trauma Emerg Surg Date: 2017-09-15 Impact factor: 3.693
Authors: Morgan B Slater; Andrea Gruneir; Paula A Rochon; Andrew W Howard; Gideon Koren; Christopher S Parshuram Journal: Paediatr Drugs Date: 2017-02 Impact factor: 3.022