Preventing Acute Kidney Injury and Improving Outcome in Critically Ill Patients Utilising Risk Prediction Score

Background and rationale AKI is common in the intensive care unit .It contributes significantly to mortality and morbidity .the estimated incidence or AKI among critically ill patients is 30-40% and morality is high.

There is a well recognized gap between the optimal care and the delivered care regarding prevention and management of AKI.

The focus over the last few years has been on early detection. A panel of urinary biomarkers have proved helpful for early detection of AKI. However the cost and low specificity make no single one of them solely reliable .using a panel of bio-markers increases their specificity.

The concept of electronic alerts has been recently introduced. Some trials have been testing its impact on the outcome of AKI. The benefit of electronic alerts is still uncertain .A meta-analysis is currently underway to synthesize stronger evidence of electronic alerts benefit.

Another evolving area, is the development of risk score to predict AKI and and hence applying timely preventive measures.

KDIGO recommends applying preventive measures to high risk patients. However no study to date has tested risk scores based interventions

Hypothesis:

We will use the recently validated score to predict AKI in ICU patients. We will then apply preventive measures. To patients at risk .To our knowledge this is the first study to apply preventive interventions based on AKI risk score assessment

Inclusion criteria

All adult patients (≥18 year old) admitted to the intensive care unit and do not fulfill the criteria for the diagnosis of AKI by Kidney Disease Improving Global Outcome (KDIGO) definition

Exclusion criteria

• Patients who have already developed AKI at the time of intensive care unit ICU admission.
• Patients with insufficient medical records to obtain previous medical history
• Patients who lack mental capacity