Proteinuria and reduced glomerular filtration rate as risk factors for acute kidney injury.
ABSTRACT Acute kidney injury (AKI) is a major public health concern, and preexisting kidney disease may be one of the most important risk factors. We review recent epidemiologic evidence supporting baseline proteinuria and reduced glomerular filtration rate as risk factors for AKI.
In 2008, a case-control study of over 600 000 patients in an integrated healthcare system in California first quantified a graded association between reduced baseline estimated glomerular filtration rate (eGFR) and risk of dialysis-requiring AKI; it also showed proteinuria as an independent predictor for AKI. In 2010, a cohort study consisting of 1235 adults undergoing coronary artery bypass graft in Taiwan demonstrated that mild and heavy degrees of proteinuria detected by dipstick were associated with increasingly higher odds ratio of postoperative AKI, independent of chronic kidney disease stage. A US cohort study in 2010 of over 11 000 patients determined that elevated urine albumin-to-creatinine ratio (UACR) was an independent risk factor for hospitalizations with AKI; this association started with the submicroalbuminuric range (UACR 11-29 mg/g) and increased stepwise along severity of albuminuria, after adjustment for eGFR. A cohort study in 2010 of over 900 000 adults in Alberta demonstrated increased rates of hospital admissions with AKI for patients with mild and moderate dipstick proteinuria across all values of eGFR.
The presence of baseline proteinuria and reduced baseline eGFR are powerful independent predictors for AKI and should be taken into account in clinical practice to identify high-risk patients for receipt of aggressive preventive measures to reduce risk of AKI.
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ABSTRACT: Administrative and claims databases may be useful for the study of acute renal failure (ARF) and ARF that requires dialysis (ARF-D), but the validity of the corresponding diagnosis and procedure codes is unknown. The performance characteristics of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes for ARF were assessed against serum creatinine-based definitions of ARF in 97,705 adult discharges from three Boston hospitals in 2004. For ARF-D, ICD-9-CM codes were compared with review of medical records in 150 patients with ARF-D and 150 control patients. As compared with a diagnostic standard of a 100% change in serum creatinine, ICD-9-CM codes for ARF had a sensitivity of 35.4%, specificity of 97.7%, positive predictive value of 47.9%, and negative predictive value of 96.1%. As compared with review of medical records, ICD-9-CM codes for ARF-D had positive predictive value of 94.0% and negative predictive value of 90.0%. It is concluded that administrative databases may be a powerful tool for the study of ARF, although the low sensitivity of ARF codes is an important caveat. The excellent performance characteristics of ICD-9-CM codes for ARF-D suggest that administrative data sets may be particularly well suited for research endeavors that involve patients with ARF-D.Journal of the American Society of Nephrology 07/2006; 17(6):1688-94. · 8.99 Impact Factor
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ABSTRACT: To determine the relationship between long-term mortality and acute kidney injury (AKI) during hospitalization after major surgery. AKI is associated with a risk of short-term mortality that is proportional to its severity; however the long-term survival of patients with AKI is poorly studied. This is a retrospective cohort study of 10,518 patients with no history of chronic kidney disease who were discharged after a major surgery between 1992 and 2002. AKI was defined by the RIFLE (Risk, Injury, Failure, Loss, and End-stage Kidney) classification, which requires at least a 50% increase in serum creatinine (sCr) and stratifies patients into 3 severity stages: risk, injury, and failure. Patient survival was determined through the National Social Security Death Index. Long-term survival was analyzed using a risk-adjusted Cox proportional hazards regression model. In the risk-adjusted model, survival was worse among patients with AKI and was proportional to its severity with an adjusted hazard ratio of 1.18 (95% confidence interval [CI], 1.08-1.29) for the RIFLE-Risk class and 1.57 (95% CI, 1.40-1.75) for the RIFLE-Failure class, compared with patients without AKI (P < 0.001). Patients with complete renal recovery after AKI still had an increased adjusted hazard ratio for death of 1.20 (95% CI, 1.10-1.31) compared with patients without AKI (P < 0.001). In a large single-center cohort of patients discharged after major surgery, AKI with even small changes in sCr level during hospitalization was associated with an independent long-term risk of death.Annals of surgery 05/2009; 249(5):851-8. · 7.90 Impact Factor
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ABSTRACT: We sought to develop a simple risk score of contrast-induced nephropathy (CIN) after percutaneous coronary intervention (PCI). Although several risk factors for CIN have been identified, the cumulative risk rendered by their combination is unknown. A total of 8,357 patients were randomly assigned to a development and a validation dataset. The baseline clinical and procedural characteristics of the 5,571 patients in the development dataset were considered as candidate univariate predictors of CIN (increase >or=25% and/or >or=0.5 mg/dl in serum creatinine at 48 h after PCI vs. baseline). Multivariate logistic regression was then used to identify independent predictors of CIN with a p value <0.0001. Based on the odds ratio, eight identified variables (hypotension, intra-aortic balloon pump, congestive heart failure, chronic kidney disease, diabetes, age >75 years, anemia, and volume of contrast) were assigned a weighted integer; the sum of the integers was a total risk score for each patient. The overall occurrence of CIN in the development set was 13.1% (range 7.5% to 57.3% for a low [<or=5] and high [>or=16] risk score, respectively); the rate of CIN increased exponentially with increasing risk score (Cochran Armitage chi-square, p < 0.0001). In the 2,786 patients of the validation dataset, the model demonstrated good discriminative power (c statistic = 0.67); the increasing risk score was again strongly associated with CIN (range 8.4% to 55.9% for a low and high risk score, respectively). The risk of CIN after PCI can be simply assessed using readily available information. This risk score can be used for both clinical and investigational purposes.Journal of the American College of Cardiology 10/2004; 44(7):1393-9. · 14.09 Impact Factor