Taku Inohara1, Shun Kohsaka2, Hiroaki Miyata3, Ikuko Ueda4, Yuichiro Maekawa4, Keiichi Fukuda4, David J Cohen5, Kevin F Kennedy5, John S Rumsfeld6, John A Spertus5. 1. Department of Cardiology, Keio University School of Medicine, Tokyo, Japan; Department of Cardiology, Hiratsuka City Hospital, Hiratsuka, Japan. 2. Department of Cardiology, Keio University School of Medicine, Tokyo, Japan. Electronic address: kohsaka@cpnet.med.keio.ac.jp. 3. Department Health Policy and Management, Keio University School of Medicine, Tokyo, Japan. 4. Department of Cardiology, Keio University School of Medicine, Tokyo, Japan. 5. Saint Luke's Mid America Heart Institute, University of Missouri-Kansas City School of Medicine, Kansas City, Missouri. 6. Denver VA Medical Center, Denver, Colorado.
Abstract
BACKGROUND: Stratifying patient risk for acute kidney injury (AKI) prior to percutaneous coronary intervention (PCI) can enable clinicians to tailor their approach to minimize AKI. The National Cardiovascular Data Registry (NCDR) CathPCI Registry recently developed 2 prediction models: for AKI and AKI requiring dialysis (AKI-D). OBJECTIVES: This study sought to externally validate the NCDR AKI and AKI-D models in a Japanese population. Determining the generalizability of the U.S. model could support quality improvement efforts in Japan. METHODS: The NCDR prediction models were applied to 11,041 consecutive patients in the Japanese multicenter PCI registry. AKI was defined as an absolute increase ≥ 0.3 mg/dl or a relative increase of 50% in serum creatinine, in accordance with the definition of AKI Network criteria; AKI-D was defined as initiation of dialysis after PCI. Discrimination and calibration of the NCDR models were tested in the Japanese cohort. If the model was perfectly calibrated, the slope and intercept would equal 1.0 and 0.0, respectively. RESULTS: In the Japanese PCI cohort, AKI and AKI-D occurred in 10.5% and 1.5% of patients, respectively. The NCDR AKI prediction model showed good discrimination (c-statistic = 0.76) and calibration (slope = 0.93 and intercept = -0.10) in both acute and nonacute PCI. The AKI-D prediction model had good discrimination (c-statistic = 0.92), but while the calibration slope was good (1.04), the intercept was significantly underestimated (0.96). However, this was corrected with recalibration (slope = 1.04 and intercept = -0.087). CONCLUSIONS: In a Japanese population, the NCDR AKI models validly predict post-procedural AKI and, with recalibration, AKI-D. Prospective use of these models to inform clinical decision making should be tested as a means of reducing AKI after PCI in Japan. (Japan Cardiovascular Database, Percutaneous Coronary Intervention Registry; UMIN R000004736).
BACKGROUND: Stratifying patient risk for acute kidney injury (AKI) prior to percutaneous coronary intervention (PCI) can enable clinicians to tailor their approach to minimize AKI. The National Cardiovascular Data Registry (NCDR) CathPCI Registry recently developed 2 prediction models: for AKI and AKI requiring dialysis (AKI-D). OBJECTIVES: This study sought to externally validate the NCDR AKI and AKI-D models in a Japanese population. Determining the generalizability of the U.S. model could support quality improvement efforts in Japan. METHODS: The NCDR prediction models were applied to 11,041 consecutive patients in the Japanese multicenter PCI registry. AKI was defined as an absolute increase ≥ 0.3 mg/dl or a relative increase of 50% in serum creatinine, in accordance with the definition of AKI Network criteria; AKI-D was defined as initiation of dialysis after PCI. Discrimination and calibration of the NCDR models were tested in the Japanese cohort. If the model was perfectly calibrated, the slope and intercept would equal 1.0 and 0.0, respectively. RESULTS: In the Japanese PCI cohort, AKI and AKI-D occurred in 10.5% and 1.5% of patients, respectively. The NCDR AKI prediction model showed good discrimination (c-statistic = 0.76) and calibration (slope = 0.93 and intercept = -0.10) in both acute and nonacute PCI. The AKI-D prediction model had good discrimination (c-statistic = 0.92), but while the calibration slope was good (1.04), the intercept was significantly underestimated (0.96). However, this was corrected with recalibration (slope = 1.04 and intercept = -0.087). CONCLUSIONS: In a Japanese population, the NCDR AKI models validly predict post-procedural AKI and, with recalibration, AKI-D. Prospective use of these models to inform clinical decision making should be tested as a means of reducing AKI after PCI in Japan. (Japan Cardiovascular Database, Percutaneous Coronary Intervention Registry; UMIN R000004736).
Authors: Jonathan C Hsu; Masaharu Akao; Mitsuru Abe; Karen L Anderson; Alvaro Avezum; Nathan Glusenkamp; Shun Kohsaka; Deirdre A Lane; Gregory Y H Lip; Chang-Sheng Ma; Frederick A Masoudi; Tatjana S Potpara; Teo Wee Siong; Mintu P Turakhia; Hung-Fat Tse; John S Rumsfeld; Thomas M Maddox Journal: J Am Heart Assoc Date: 2016-11-02 Impact factor: 5.501
Authors: Taku Inohara; Shun Kohsaka; Hiroaki Miyata; Mitsuaki Sawano; Ikuko Ueda; Yuichiro Maekawa; Keiichi Fukuda; Philip G Jones; David J Cohen; Zhenxiang Zhao; John A Spertus; Kim G Smolderen Journal: J Am Heart Assoc Date: 2017-10-27 Impact factor: 5.501