A Meta-analysis of the Association of Estimated GFR, Albuminuria, Age, Race, and Sex With Acute Kidney Injury

Tonelli, Marcello; Hemmelgarn, Brenda R.; James, Matthew T.; Turin, Tanvir Chowdhury; Shlipak, Michael G.; Katz, Ronit; Wheeler, David C.; Emberson, Jonathan; Landray, Martin J; Townend, Jonathan; Green, Jamie; Kirchner, Henriette; Perkins, Robert M.; Chang, Alex R.; Romundstad, Solfrid; Aasarød, Knut; Øien, Cecilia Montgomery; Hallan, Stein; Smith, David H.; Thorp, Micah L.; Johnson, Eric S.; Chodick, Gabriel; Herzel, Esma; Katz, Rachel; Shalev, Varda; Bakker, Stephan J. L.; Heerspink, Hiddo J L; Harst, Pim van der; Jee, Sun Ha; Kim, Heejin; Mok, Yejin; Tangri, Navdeep; Naimark, David; Ärnlöv, Johan; Larsson, Anders; Lannfelt, Lars; Kövesdy, Csaba P.; Kalantar‐Zadeh, Kamyar; Gansevoort, Ron T.; Jong, Paul E. de; Iseki, Kunitoshi; Levey, Andrew S.; Sarnak, Mark J.; Stengel, Bénédicte; Warnock, David G.; Ballew, Shoshana H.; Coresh, Josef; Grams, Morgan E.; Matsushita, Kunihiro; Sang, Yingying; Woodward, Mark

doi:10.1053/j.ajkd.2015.02.337

Cited by 145 publications

(102 citation statements)

References 41 publications

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“…Consistent with large meta-analyses of hospitalized AKI, older age, male sex, African American race, diabetes, and hypertension were associated with AKI overall and in most surgery types. 33, 34 In contrast, the relationship between eGFR and AKI was slightly different than previous work. 33-35 In our study, eGFR had a U-shaped association with post-operative AKI, with lower levels below 90 ml/min/1.73 m 2 and higher levels at or above 90 ml/min/1.73 m 2 associated with higher AKI risk.…”

Section: Discussioncontrasting

confidence: 69%

Acute Kidney Injury After Major Surgery: A Retrospective Analysis of Veterans Health Administration Data

Grams

Sang

Ballew

et al. 2016

American Journal of Kidney Diseases

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242

215

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Background Few trials of acute kidney injury (AKI) prevention after surgery have been conducted and most observational studies focus on AKI following cardiac surgery. The frequency of, risk factors for, and outcomes after AKI following other types of major surgery have not been well characterized, and may present additional opportunities for trials in AKI. Study Design Observational cohort study. Setting & Participants 3.6 million US veterans followed up from 2004-2011 for the receipt of major surgery (cardiac; general; ear, nose, and throat [ENT], thoracic, vascular, urologic, orthopedic) and post-operative outcomes. Factors Demographics, health characteristics, and type of surgery. Outcomes Post-operative AKI defined by the KDIGO creatinine criteria, post-operative length of stay, end-stage renal disease (ESRD), and mortality. Results Post-operative AKI occurred in 11.8% of the 161,185 major surgery hospitalizations (stage 1, 76%; stage 2, 15%, stage 3 [without dialysis], 7%; AKI requiring dialysis, 2%). Cardiac surgery had the highest post-operative AKI risk (relative risk [RR], 1.22; 95% CI, 1.17-1.27), followed by general (reference), thoracic (RR, 0.92; 95% CI, 0.87-0.98), orthopedic (RR, 0.70; 95% CI, 0.67-0.73), vascular (RR, 0.68; 95% CI, 0.64-0.71), urologic (RR, 0.65; 95% CI, 0.61-0.69), and ENT (RR, 0.32; 95% CI, 0.28-0.37) surgery. Risk factors for post-operative AKI included older age, African-American race, hypertension, diabetes mellitus, and, when eGFR < 90 ml/min/1.73 m2, lower eGFR. Participants with post-operative AKI had longer length of stay (15.8 vs. 8.6 days) and higher rates of 30-day hospital readmission (21% vs. 13%), 1-year ESRD (0.94% vs. 0.05%) and mortality (19% vs. 8%), with similar associations by type of surgery and more severe stage of AKI relating to poorer outcomes. Limitations Urine output was not available to classify AKI; cohort included mostly men. Conclusions AKI was common after major surgery, with similar risk factor and outcome associations across surgery type. These results can inform the design of clinical trials in post-operative AKI to the non-cardiac surgery setting.

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Section: Discussioncontrasting

confidence: 69%

Acute Kidney Injury After Major Surgery: A Retrospective Analysis of Veterans Health Administration Data

Grams

Sang

Ballew

et al. 2016

American Journal of Kidney Diseases

Self Cite

242

215

View full text Add to dashboard Cite

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“…Preexisting proteinuria is a risk factor for AKI in various clinical situations [59] . Only few studies have examined the significance of de novo proteinuria during AKI.…”

Section: Discussionmentioning

confidence: 99%

Glomerular Proteinuria Predicts the Severity of Acute Kidney Injury in Puumala Hantavirus-Induced Tubulointerstitial Nephritis

Mantula

Outinen

Clément

et al. 2017

Nephron

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Background:Puumala virus (PUUV)-induced hemorrhagic fever with renal syndrome is common in many European countries. The typical renal histologic lesion is acute tubulointerstitial nephritis. We examined the type and kinetics of urine protein excretion and prognostic significance of proteinuria for the severity of acute kidney injury (AKI) in acute PUUV infection. Methods: The amount of dipstick albuminuria at hospital admission was analyzed in 205 patients with acute PUUV infection. Dipstick albuminuria at admission was graded into 3 categories: 0-1+, 2+, and 3+. In 70 patients, 24-h urinary excretion of protein, overnight urinary excretion of albumin, immunoglobulin (Ig) G, and α1-microglobulin also were measured over 3 consecutive days during the hospital stay. Results: Maximum median daily proteinuria, overnight albuminuria, and IgG excretion were observed over 5 days, while that of creatinine values was observed 9 days after the onset of the disease. The medians of maximum plasma creatinine levels during hospital stay were different in the 3 categories of dipstick albuminuria: 0-1+: 98 µmol/L (58-1,499), 2+: 139 µmol/L (71-829), and 3+: 363 µmol/L (51-1,285; p < 0.001). Dipstick albuminuria ≥2+ at admission could be detected in 89% of the patients who subsequently developed severe AKI. Glomerular proteinuria, but not tubular proteinuria (α1-microglobulin), correlated with the severity of the emerging AKI. Conclusion: In acute PUUV infection, maximum median proteinuria values preceded the most severe phase of AKI by a few days. A highly useful finding for clinical work was that a quick and simple albuminuria dipstick test at hospital admission predicted the severity of the upcoming AKI.

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“…Many recent efforts have been made to identify the clinical variables, such as estimated glomerular filtration rate (eGFR), albumin, urinary neutrophil gelatinaseassociated lipocalin (uNGAL) and urinary angiotensionogen (uAGT) for the early diagnosis of CRS1 [9][10][11][12][13][14]. However, their effectiveness for predicting CRS1 is still controversial.…”

Section: Introductionmentioning

confidence: 99%

Nomogram Model to Predict Cardiorenal Syndrome Type 1 in Patients with Acute Heart Failure

Fan

Yang

et al. 2018

Kidney Blood Press Res

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Background/Aims: Cardiorenal syndrome type 1(CRS1) is a serious clinical condition in patients with acute heart failure (AHF) associated with adverse clinical outcomes. Although several biomarkers for identifying CRS1 have been reported, early and accurate predicting CRS1 still remains a challenge. This study was aimed to develop and validate an individualized predictive nomogram for the risk of CRS1 in patients with AHF. Methods: A total of 1235 AHF patients between 2013 and 2018 were included in this study. The patients were randomly classified into training set (n=823) and validation set (n=412). All data of the training set were used to screen the predictors of CRS1 via univariate and multivariate analyses. A nomogram was developed based on these predictors and validated by internal and external validation. The nomogram validation comprised discriminative ability determined by the area under the curve (AUC) of receiver-operating characteristic (ROC) curve and the predictive accuracy by calibration plots. Results: The overall incidence of CRS1 was 31.7%. Multivariate logistic regression revealed that age, diabetes, NYHA class, eGFR, hs-CRP and uAGT were independently associated with CRS1. A nomogram developed based on the six variables was with the AUC 0.885 and 0.823 on internal and external validation, respectively. Calibration plots showed that the predicted and actual CRS1 probabilities were fitted well on both internal and external validation. Conclusion: The proposed nomogram could predict the individualized risk of CRS1 with good accuracy, high discrimination, and potential clinical applicability in patients with AHF.

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A Meta-analysis of the Association of Estimated GFR, Albuminuria, Age, Race, and Sex With Acute Kidney Injury

Cited by 145 publications

References 41 publications

Acute Kidney Injury After Major Surgery: A Retrospective Analysis of Veterans Health Administration Data

Acute Kidney Injury After Major Surgery: A Retrospective Analysis of Veterans Health Administration Data

Glomerular Proteinuria Predicts the Severity of Acute Kidney Injury in Puumala Hantavirus-Induced Tubulointerstitial Nephritis

Nomogram Model to Predict Cardiorenal Syndrome Type 1 in Patients with Acute Heart Failure

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