Acute Kidney Injury Risk Prediction in Patients Undergoing Coronary Angiography in a National Veterans Health Administration Cohort with External Validation

Background: Acute kidney injury (AKI) occurs frequently after cardiac catheterization and percutaneous coronary intervention. Although a clinical risk model exists for percutaneous coronary intervention, no models exist for both procedures, nor do existing models account for risk factors prior to the index admission. We aimed to develop such a model for use in prospective automated surveillance programs in the Veterans Health Administration. Methods and Results: We collected data on all patients undergoing cardiac catheterization or percutaneous coronary intervention in the Veterans Health Administration from January 01, 2009 to September 30, 2013, excluding patients with chronic dialysis, end‐stage renal disease, renal transplant, and missing pre‐ and postprocedural creatinine measurement. We used 4 AKI definitions in model development and included risk factors from up to 1 year prior to the procedure and at presentation. We developed our prediction models for postprocedural AKI using the least absolute shrinkage and selection operator (LASSO) and internally validated using bootstrapping. We developed models using 115 633 angiogram procedures and externally validated using 27 905 procedures from a New England cohort. Models had cross‐validated C‐statistics of 0.74 (95% CI: 0.74–0.75) for AKI, 0.83 (95% CI: 0.82–0.84) for AKIN2, 0.74 (95% CI: 0.74–0.75) for contrast‐induced nephropathy, and 0.89 (95% CI: 0.87–0.90) for dialysis. Conclusions: We developed a robust, externally validated clinical prediction model for AKI following cardiac catheterization or percutaneous coronary intervention to automatically identify high‐risk patients before and immediately after a procedure in the Veterans Health Administration. Work is ongoing to incorporate these models into routine clinical practice

The assessment, serial evaluation, and subsequent sequelae of acute kidney injury (ASSESS-AKI) study: design and methods

<p>Abstract</p> <p>Background</p> <p>The incidence of acute kidney injury (AKI) has been increasing over time and is associated with a high risk of short-term death. Previous studies on hospital-acquired AKI have important methodological limitations, especially their retrospective study designs and limited ability to control for potential confounding factors.</p> <p>Methods</p> <p>The Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury (ASSESS-AKI) Study was established to examine how a hospitalized episode of AKI independently affects the risk of chronic kidney disease development and progression, cardiovascular events, death, and other important patient-centered outcomes. This prospective study will enroll a cohort of 1100 adult participants with a broad range of AKI and matched hospitalized participants without AKI at three Clinical Research Centers, as well as 100 children undergoing cardiac surgery at three Clinical Research Centers. Participants will be followed for up to four years, and will undergo serial evaluation during the index hospitalization, at three months post-hospitalization, and at annual clinic visits, with telephone interviews occurring during the intervening six-month intervals. Biospecimens will be collected at each visit, along with information on lifestyle behaviors, quality of life and functional status, cognitive function, receipt of therapies, interim renal and cardiovascular events, electrocardiography and urinalysis.</p> <p>Conclusions</p> <p>ASSESS-AKI will characterize the short-term and long-term natural history of AKI, evaluate the incremental utility of novel blood and urine biomarkers to refine the diagnosis and prognosis of AKI, and identify a subset of high-risk patients who could be targeted for future clinical trials to improve outcomes after AKI.</p

Predicting Acute Kidney Injury at Hospital Re-entry Using High-dimensional Electronic Health Record Data

Acute Kidney Injury (AKI), a sudden decline in kidney function, is associated with increased mortality, morbidity, length of stay, and hospital cost. Since AKI is sometimes preventable, there is great interest in prediction. Most existing studies consider all patients and therefore restrict to features available in the first hours of hospitalization. Here, the focus is instead on rehospitalized patients, a cohort in which rich longitudinal features from prior hospitalizations can be analyzed. Our objective is to provide a risk score directly at hospital re-entry. Gradient boosting, penalized logistic regression (with and without stability selection), and a recurrent neural network are trained on two years of adult inpatient EHR data (3,387 attributes for 34,505 patients who generated 90,013 training samples with 5,618 cases and 84,395 controls). Predictions are internally evaluated with 50 iterations of 5-fold grouped cross-validation with special emphasis on calibration, an analysis of which is performed at the patient as well as hospitalization level. Error is assessed with respect to diagnosis, race, age, gender, AKI identification method, and hospital utilization. In an additional experiment, the regularization penalty is severely increased to induce parsimony and interpretability. Predictors identified for rehospitalized patients are also reported with a special analysis of medications that might be modifiable risk factors. Insights from this study might be used to construct a predictive tool for AKI in rehospitalized patients. An accurate estimate of AKI risk at hospital entry might serve as a prior for an admitting provider or another predictive algorithm.Comment: In revisio

The Effects of Obesity on the Comparative Effectiveness of Linezolid and Vancomycin in Suspected Methicillin-Resistant \u3cem\u3eStaphylococcus aureus\u3c/em\u3e Pneumonia

Background: Methicillin-Resistant Staphylococcus aureus (MRSA) has become a leading cause of pneumonia in the United States and there is limited data on treatment outcomes in obese patients.We evaluated the effectiveness of linezolid compared to vancomycin for the treatment of MRSA pneumonia in a national cohort of obese Veterans. Methods: This retrospective cohort study included obese patients (body mass index ≥ 30) admitted to Veterans Affairs hospitals with MRSA-positive respiratory cultures and clinical signs of infection between 2002 and 2012. Patients initiating treatment with either vancomycin or linezolid, but not both, were selected for inclusion. Propensity matching and adjustment of Cox proportional hazards regression models quantified the effect of linezolid compared with vancomycin on time to hospital discharge, intensive care unit discharge, 30-day mortality, inpatient mortality, therapy discontinuation, therapy change, 30-day readmission, and 30-day MRSA reinfection. We performed sensitivity analyses by vancomycin Minimum Inhibitory Concentrations (MICs) and true trough levels. Results: We identified 101 linezolid and 2,565 vancomycin patients. Balance in baseline characteristics between the treatment groups was achieved within propensity score quintiles and between propensity matched pairs (76 pairs). No significant differences were observed for the outcomes assessed. Among patients with vancomycin MICs of ≤ 1 μg/mL, the linezolid group had a significantly lower mortality rate, increased length of hospital stay, and longer therapy duration. There were no differences between the linezolid and vancomycin MICs of ≥ 1.5 μg/ mL groups. Clinical outcomes among those with vancomycin trough concentrations of 15-20 mg/L were similar to patients treated with linezolid. Conclusions: In our real-world comparative effectiveness study among obese patients with suspected MRSA pneumonia, linezolid was associated with a significantly lower mortality rate as compared to the vancomycin-treated patients with lower vancomycin MICs. Further studies are needed to determine whether this beneficial effect is observed in other study populations

Addressing the Health Needs of an Aging America: New Opportunities for Evidence-Based Policy Solutions

This report systematically maps research findings to policy proposals intended to improve the health of the elderly. The study identified promising evidence-based policies, like those supporting prevention and care coordination, as well as areas where the research evidence is strong but policy activity is low, such as patient self-management and palliative care. Future work of the Stern Center will focus on these topics as well as long-term care financing, the health care workforce, and the role of family caregivers