PREDICTING AKI IS MORE CHALLENGING AS AGE PROGRESSES Sandra Kane-Gill, PharmD, MSc Associate Professor, School of Pharmacy

Co-Investigators Florentina Sileanu, BS, PhD candidate Greg Trieteley, PharmD candidate Ragi Marugan, MD Steven Handler, MD John Kellum, MD

Putting the Problem in Context Acute kidney injury (AKI) Develops over hours to days in either community or hospitalized patients Incidence of AKI doubled from 2000 to 2009 Outcomes: Length of stay 2.4 times longer Hospital mortality rates as high as 60% in ICU patients and over 80% in patients requiring renal replacement therapies AKI predisposes patients to progression of chronic kidney disease and end-stage renal disease Risk factors: Advanced age (>65 y.o.) Organ failure Sepsis and infection Cardiac shock Pre-existing chronic medical conditions Nephrotoxic drugs Obesity Surgery Transplantation Recent rise in AKI contributed to the growing elderly population Himmerlfarb J. Semin Nephrol 2009;29: Wang WE et al. Am J Nephrol 2012;35: Coca SG et al. Nephron Clin Prac 2011;119:suppl 1:c19-24

RESEARCH QUESTION Will the risk factors or model of prediction be upheld in the elderly population?

Study Design and Sample: Retrospective cohort study from July 2000-June ,655 7 ICUs with greater than 120 beds 3,762 Receiving hemodialysis or rental transplant prior to hospitalization 105 Baseline serum creatinine ≥ 4 1,340 Underwent liver transplantation prior to hospitalization 494 Inadequate information to determine AKI status 16 Unknown age 39,938 Included in analysis

Methods Data were obtained from the Medical Archival Repository System (MARS) International Classification Diseases, 9 th edition (ICD9) Diagnosis related group (DRG) Severity of illness (APCHE III) Sepsis (blood culture and antibiotic in 24h of each other) Hypotensive index Baseline serum creatinine Admission creatinine Reference creatinine GFR (mL/min/1.73 m2) = 175 × (Scr) × (Age) × (0.742 if female) × (1.212 if African American) (conventional units) eGFR of 75ml/min/1.73m 2 when baseline creatinine missing

Methods Categorized by age (≥ 65 y.o.) Cohort evaluated for patients who developed AKI AKI classification according to KDIGO

Analysis Prevalence compared by group and then by year Outcome comparison Mortality Recovery from renal replacement therapy (RRT) 90 and 365 days after first RRT and alive but not in United States Renal Data System Risk factor assessment completed using a multivariate logistic regression model Impact of age Separate assessment by age group

Results

Comparison of Outcomes by Age for Patients with Acute Kidney Injury

Multivariable regression analysis of risk factors for AKI patients compared to non-AKI patients

Multivariable regression analysis of risk factors for AKI patients compared to non-AKI patients (≥ 65 and <65) Age ≥65; N = 15,542; AKI developed on or afterAge < 65; N = 19,812; AKI developed on or ICU admission; AUC after ICU admission; AUC Outcome: AKIOR95% C.I.for ORp-valueOR95% C.I.for ORp-value Age < Race.002 <0.001 Black vs. White Other vs. White < <0.001 Diabetes Cardiac Disease <0.001 Surgical Sepsis (24hrs from ICU day 1) < <0.001 Vasopressors (24hrs from ICU day 1) < <0.001 Mechanical Ventilation (24hrs from ICU day 1) < <0.001 eGFR < < <0.001 [30-60] vs > < <0.001 Hypotensive Index (24hrs from ICU admission) < <0.001 History of hypertension <0.001

Comparison of AUC for Elderly vs Younger

Conclusion From previous studies, we know age is an independent risk factor for AKI and this study provides confirmation Younger patients are less likely to develop AKI compared to elderly patients, but their in-hospital outcomes are similar, though their prolonged recovery is slightly improved Likelihood of developing AKI increases with age; but the ability to predict patients at risk for AKI declines with age using an established set of risk factors Automation may assist with identification of patients at risk for AKI, especially considering the current challenges