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HOW WELL DO PHYSICIANS ESTIMATE MORTALITY AT DISCHARGE FROM ICU?. Dr Sam Ley CT2 ICM Dr Radha Sundaram Consultant ICM Royal Alexandra Hospital, Paisley, Scotland. INTRODUCTION.
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HOW WELL DO PHYSICIANS ESTIMATE MORTALITY AT DISCHARGE FROM ICU? Dr Sam Ley CT2 ICM Dr Radha Sundaram Consultant ICM Royal Alexandra Hospital, Paisley, Scotland
INTRODUCTION There are a variety of prognostic scoring systems used within ICM, however studies have shown clinician’s prediction of outcome is more powerful than a single APACHE II score at admission [1] [2]. This study asks the question: Does physician’s prediction of patient outcome at ICU discharge correlate with the 30 day mortality in all patients discharged from a seven bedded ICU (400 admissions a year) in a UK District General Hospital? • Rocker GM, Cook D Et al. Clinicians prediction of ICU mortality. Critical Care Medicine.2004;32;5; 1149 -1154. • Scholz N, Basler K et al. Outcome prediction in critical care: physicians prognoses versus scoring systems. EJA. 2004.21(8) ;606-611.
METHOD A retrospective database study was conducted of all patients discharged in a one year period (2011) from the ICU. Date was collected on: • Age, gender, admitting specialty. • APACHE II, physician prediction of outcome. • Survival at discharge and at 30 days.
RESULTS • Prediction of “Survivor/Non-Survivor” showed: • Statistical significance with 30 day mortality (p<0.0001). • PPV 98.3%, NPV 100%. • Patients given an “Uncertain” outcome had a 30 day survival of 82%. • The was a statistically significant relationship between 30 day mortality and APACHE II (p<0.0001).
CONCLUSION • The physician’s opinion with regards to whether a patient would be a “Survivor” or a “Non Survivor” at discharge was a statistically significant predictor of 30 day mortality post discharge within this ICU. • Patients with a “Uncertain” outcome tended towards 30 day survival.
LIMITATIONS & DEVELOPMENT • Limitations included the studies retrospective nature, the reliance on data sources and that the primary outcome was mortality and not quality of life. • Further studies are needed to evaluate quality of life predictions, as this would alter clinical decision making to a greater extent than mortality predictions.