A Decision-Making Algorithm for Initiation and Discontinuation of RRT in Severe AKI.

ABSTRACT: AKI is an increasingly common and devastating complication in hospitalized patients. Severe AKI requiring RRT is associated with in-hospital mortality rates exceeding 40%. Clinical decision making related to RRT initiation for patients with AKI in the medical intensive care unit is not standardized.We conducted a 13-month (November of 2013 to December of 2014) prospective cohort study in an academic medical intensive care unit involving the implementation of an AKI Standardized Clinical Assessment and Management Plan, a decision-making algorithm to assist front-line clinicians caring for patients with AKI. The Standardized Clinical Assessment and Management Plan algorithms provided recommendations about optimal indications for initiating and discontinuing RRT on the basis of various clinical parameters; 176 patients managed by nine nephrologists were included in the study. We captured reasons for deviation from the recommended algorithm as well as mortality data.Patients whose clinicians adhered to the Standardized Clinical Assessment and Management Plan recommendation to start RRT had lower in-hospital mortality (42% versus 63%; P<0.01) and 60-day mortality (46% and 68%; P<0.01), findings that were confirmed after multivariable adjustment for age, albumin, and disease severity. There was a differential effect of Standardized Clinical Assessment and Management Plan adherence in low (<50% mortality risk) versus high (?50% mortality risk) disease severity on in-hospital mortality (interaction term P=0.02). In patients with low disease severity, Standardized Clinical Assessment and Management Plan adherence was associated with lower in-hospital mortality (odds ratio, 0.21; 95% confidence interval, 0.08 to 0.54; P=0.001), but no significant association was evident in patients with high disease severity.Physician adherence to an algorithm providing recommendations on RRT initiation was associated with lower in-hospital mortality.

SUBMITTER: Mendu ML 

PROVIDER: S-EPMC5293339 | biostudies-other | 2017 Feb

REPOSITORIES: biostudies-other