Evaluating the Clinical Characteristics of Acute Kidney Injury in the ICU Setting

Author(s)

Brothers T1, Strock J1, Al-Mamun M2
1University of Rhode Island, Kingston, RI, USA, 2University of West Virginia, Morgantown, WV, USA

OBJECTIVES: This study evaluates the clinical characteristics and potential correlates associated with AKI in critically ill adults.

METHODS: A retrospective cohort study of 322 patients was performed in adult critically ill patients from February 1 to August 30, 2020. Patients excluded were long-term care patients, extreme outliers (> 4 standard deviations of ICU length of stay), a history of renal replacement therapy or kidney transplantation. AKI status was determined by both SCr- and UO-based methods based upon The Kidney Disease Improving Global Outcomes (KDIGO) classification system.

Our aim was to evaluate the correlates and incidence of AKI. Multivariable Logistic regression models were utilized to examine risk factors for AKI incidence.

RESULTS: Overall, 322 patients were evaluated, of which 155 (48.1%) experienced AKI. The AKI cohort had significantly lower eGFR, 59.4 (22.4-89.8, p < 0.05) when compared to non-AKI patients. Hispanic ethnicity had higher rates of AKI 24, (15%) when compared to non-AKI patients. In the AKI cohorts, the most commonly prescribed medication classes were analgesics/sedatives, anti-infectives, and intravenous fluids. Medication classes such as anti-infectives and diuretics were significantly associated with AKI incidence on day 2 of ICU admission (OR’s): 2.54 (1.27-5.20, p-value < 0.05) and 0.30 (0.11-0.77, p-value < 0.05), respectively. Charlson Comorbidity Index, age, and BMI were significantly associated with AKI incidence on day 2 of ICU admission (OR’s): 1.25 (1.05-1.49, p-value < 0.01) and 1.01 (1.00-1.02, p-value < 0.05), and 1.03 (1.00-1.07, p-value < 0.05) respectively.

CONCLUSIONS: Incorporating medication use data with clinical information improves AKI risk stratification. Medication classes further impact the risk of developing AKI, necessitating the need for early recognition of high-risk pharmacotherapies to mitigate potential risk.

Conference/Value in Health Info

2022-05, ISPOR 2022, Washington, DC, USA

Value in Health, Volume 25, Issue 6, S1 (June 2022)

Code

CO62

Topic

Clinical Outcomes, Methodological & Statistical Research

Topic Subcategory

Artificial Intelligence, Machine Learning, Predictive Analytics, Clinical Outcomes Assessment, Performance-based Outcomes

Disease

Urinary/Kidney Disorders

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