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

ABSTRACT: 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.Observational cohort study.3.6 million US veterans followed up from 2004 to 2011 for the receipt of major surgery (cardiac; general; ear, nose, and throat; thoracic; vascular; urologic; and orthopedic) and postoperative outcomes.Demographics, health characteristics, and type of surgery.Postoperative AKI defined by the KDIGO creatinine criteria, postoperative length of stay, end-stage renal disease, and mortality.Postoperative AKI occurred in 11.8% of the 161,185 major surgery hospitalizations (stage 1, 76%; stage 2, 15%, stage 3 [without dialysis], 7%; and AKI requiring dialysis, 2%). Cardiac surgery had the highest postoperative 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 ear, nose, and throat (RR, 0.32; 95% CI, 0.28-0.37) surgery. Risk factors for postoperative AKI included older age, African American race, hypertension, diabetes mellitus, and, for estimated glomerular filtration rate < 90mL/min/1.73m(2), lower estimated glomerular filtration rate. Participants with postoperative AKI had longer lengths of stay (15.8 vs 8.6 days) and higher rates of 30-day hospital readmission (21% vs 13%), 1-year end-stage renal disease (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.Urine output was not available to classify AKI; cohort included mostly men.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 postoperative AKI to the noncardiac surgery setting.

SUBMITTER: Grams ME

PROVIDER: S-EPMC4775458 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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

Grams Morgan E ME Sang Yingying Y Coresh Josef J Ballew Shoshana S Matsushita Kunihiro K Molnar Miklos Z MZ Szabo Zoltan Z Szabo Zoltan Z Kalantar-Zadeh Kamyar K Kovesdy Csaba P CP

American journal of kidney diseases : the official journal of the National Kidney Foundation 20150901 6

<h4>Background</h4>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.<h4>Study design</h4>Observational cohort study.<h4>Setting & participants</h4>3.6 million US veterans followed up from 2004 to 2011 f ...[more]

PMID: 26337133

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Project description:BackgroundStudies suggest an association between acute kidney injury (AKI) and long-term risk for chronic kidney disease (CKD), even following apparent renal recovery. Whether the pattern of renal recovery predicts kidney risk following AKI is unknown.Study designRetrospective cohort.Setting & participantsPatients in the Veterans Health Administration in 2011 hospitalized (> 24 hours) with at least 2 inpatient serum creatinine measurements, baseline estimated glomerular filtration rate > 60 mL/min/1.73 m², and no diagnosis of end-stage renal disease or non-dialysis-dependent CKD: 17,049 (16.3%) with and 87,715 without AKI.PredictorPattern of recovery to creatinine level within 0.3 mg/dL of baseline after AKI: within 2 days (fast), in 3 to 10 days (intermediate), and no recovery by 10 days (slow or unknown).OutcomeCKD stage 3 or higher, defined as 2 outpatient estimated glomerular filtration rates < 60 mL/min/1.73m² at least 90 days apart or CKD diagnosis, dialysis therapy, or transplantation.MeasurementsRisk for CKD was modeled using modified Poisson regression and time to death-censored CKD was modeled using Cox proportional hazards regression, both stratified by AKI stage.ResultsMost patients' AKI episodes were stage 1 (91%) and 71% recovered within 2 days. At 1 year, 18.2% had developed CKD (AKI, 31.8%; non-AKI, 15.5%; P < 0.001). In stage 1, the adjusted relative risk ratios for CKD stage 3 or higher were 1.43 (95% CI, 1.39-1.48), 2.00 (95% CI, 1.88-2.12), and 2.65 (95% CI, 2.51-2.80) for fast, intermediate, and slow/unknown recovery. A similar pattern was observed in subgroup analyses incorporating albuminuria and sensitivity analysis of death-censored time to CKD.LimitationsVariable timing of follow-up and mostly male veteran cohort may limit generalizability.ConclusionsPatients who develop AKI during a hospitalization are at substantial risk for the development of CKD by 1 year following hospitalization and timing of AKI recovery is a strong predictor, even for the mildest forms of AKI.

Project description:Importance:Acute kidney injury (AKI) is one of the most common complications after noncardiac surgery. Yet current postoperative AKI risk stratification models have substantial limitations, such as limited use of perioperative data. Objective:To examine whether adding preoperative and intraoperative data is associated with improved prediction of noncardiac postoperative AKI. Design, Setting, and Participants:A prognostic study using logistic regression with elastic net selection, gradient boosting machine (GBM), and random forest approaches was conducted at 4 tertiary academic hospitals in the United States. A total of 42 615 hospitalized adults with serum creatinine measurements who underwent major noncardiac surgery between January 1, 2014, and April 30, 2018, were included in the study. Serum creatinine measurements from 365 days before and 7 days after surgery were used in this study. Main Outcomes and Measures:Postoperative AKI (defined by the Kidney Disease Improving Global Outcomes within 7 days after surgery) was the primary outcome. The area under the receiver operating characteristic curve (AUC) was used to assess discrimination. Results:Among 42 615 patients who underwent noncardiac surgery, the mean (SD) age was 57.9 (15.7) years, 23 943 (56.2%) were women, 27 857 (65.4%) were white, and the most frequent surgery types were orthopedic (15 718 [36.9%]), general (8808 [20.7%]), and neurologic (6564 [15.4%]). The rate of postoperative AKI was 10.1% (n = 4318). The progressive addition of clinical data improved model performance across all modeling approaches, with GBM providing the highest discrimination by AUC. In GBM models, the AUC increased from 0.712 (95% CI, 0.694-0.731) using prehospitalization variables to 0.804 (95% CI, 0.788-0.819) using preoperative variables (inclusive of prehospitalization variables) (P < .001 for AUC comparison). The AUC further increased to 0.817 (95% CI, 0.802-0.832) when adding intraoperative variables (P < .001 for comparison vs model using preoperative variables). However, the statistically significant improvements in discrimination did not appear to be clinically significant. In particular, the AKI rate among patients classified as high risk improved from 29.1% to 30.0%, a net of 15 patients were appropriately reclassified as high risk, and an additional 15 patients were appropriately reclassified as low risk. Conclusions and Relevance:The findings of the study suggest that electronic health record data may be used to accurately stratify patients at risk of perioperative AKI, but the modest improvements from adding intraoperative data should be weighed against challenges in using intraoperative data.

Project description:BackgroundPostoperative acute kidney injury is common after major vascular surgery and is associated with increased morbidity, mortality, and cost. High-performance risk stratification using a machine learning model can inform strategies that mitigate harm and optimize resource use. It is hypothesized that incorporating intraoperative data would improve machine learning model accuracy, discrimination, and precision in predicting acute kidney injury among patients undergoing major vascular surgery.MethodsA single-center retrospective cohort of 1,531 adult patients who underwent nonemergency major vascular surgery, including open aortic, endovascular aortic, and lower extremity bypass procedures, was evaluated. The validated, automated MySurgeryRisk analytics platform used electronic health record data to forecast patient-level probabilistic risk scores for postoperative acute kidney injury using random forest models with preoperative data alone and perioperative data (preoperative plus intraoperative). The MySurgeryRisk predictions were compared with each other as well as with the American Society of Anesthesiologists physical status classification.ResultsMachine learning models using perioperative data had greater accuracy, discrimination, and precision than models using either preoperative data alone or the American Society of Anesthesiologists physical status classification (accuracy: 0.70 vs 0.64 vs 0.62, area under the receiver operating characteristics curve: 0.77 vs 0.68 vs 0.61, area under the precision-recall curve: 0.70 vs 0.58 vs 0.48).ConclusionIn predicting acute kidney injury after major vascular surgery, machine learning approaches that incorporate dynamic intraoperative data had greater accuracy, discrimination, and precision than models using either preoperative data alone or the American Society of Anesthesiologists physical status classification. Machine learning methods have the potential for real-time identification of high-risk patients who may benefit from personalized risk-reduction strategies.

Dataset Information

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

Publications

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

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