N Flynn1, A Dawnay2. 1. Department of Clinical Biochemistry, University College London Hospitals NHS Foundation Trust, London. 2. Department of Clinical Biochemistry, University College London Hospitals NHS Foundation Trust, London anne.dawnay@uclh.nhs.uk.
Abstract
BACKGROUND: Acute kidney injury (AKI) is frequently under-recognized and contributes to poor outcomes. Electronic alerts (e-alerts) to highlight AKI based on changes in serum creatinine may facilitate earlier recognition and treatment, and sophisticated algorithms for AKI detection have been proposed or implemented elsewhere. However, many laboratories currently lack the resources or capability to replicate these systems. METHODS: A real-time automated delta check e-alert flags a 50% increase in creatinine to a concentration of >50 µmol/L from the most recent result within a 90-day period and automatically adds the comment '?AKI - creatinine increase >50% from previous' with a link to local AKI guidelines. In addition, creatinine results >300 µmol/L are retrospectively reviewed and phoned if AKI is suspected. For each alert over a 12-day period we manually reviewed previous and subsequent creatinine results to determine baseline creatinine and stage AKI according to Acute Kidney Injury Network (AKIN) criteria. RESULTS: From 11,930 creatinine requests, 63 of 90 (70%) delta check e-alerts were due to AKI, identifying 61 episodes of AKI. Thirty four of 54 (63%) creatinine results >300 µmol/L were due to AKI, identifying a further 10 episodes of AKI. The positive predictive value (PPV) for AKI of a delta check e-alert was greater when the trigger creatinine was >100 µmol/L (PPV 89%) or when the absolute change in creatinine was >50 µmol/L (PPV 93%). CONCLUSION: This study demonstrates that a simple automated delta check can detect and flag AKI in real time, continuously, at little extra cost and without manual input.
BACKGROUND:Acute kidney injury (AKI) is frequently under-recognized and contributes to poor outcomes. Electronic alerts (e-alerts) to highlight AKI based on changes in serum creatinine may facilitate earlier recognition and treatment, and sophisticated algorithms for AKI detection have been proposed or implemented elsewhere. However, many laboratories currently lack the resources or capability to replicate these systems. METHODS: A real-time automated delta check e-alert flags a 50% increase in creatinine to a concentration of >50 µmol/L from the most recent result within a 90-day period and automatically adds the comment '?AKI - creatinine increase >50% from previous' with a link to local AKI guidelines. In addition, creatinine results >300 µmol/L are retrospectively reviewed and phoned if AKI is suspected. For each alert over a 12-day period we manually reviewed previous and subsequent creatinine results to determine baseline creatinine and stage AKI according to Acute Kidney Injury Network (AKIN) criteria. RESULTS: From 11,930 creatinine requests, 63 of 90 (70%) delta check e-alerts were due to AKI, identifying 61 episodes of AKI. Thirty four of 54 (63%) creatinine results >300 µmol/L were due to AKI, identifying a further 10 episodes of AKI. The positive predictive value (PPV) for AKI of a delta check e-alert was greater when the trigger creatinine was >100 µmol/L (PPV 89%) or when the absolute change in creatinine was >50 µmol/L (PPV 93%). CONCLUSION: This study demonstrates that a simple automated delta check can detect and flag AKI in real time, continuously, at little extra cost and without manual input.
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