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Integration of APACHE II and III scoring systems in extremely high risk patients with acute renal failure treated by
Yung-Chang Chen1, Hsiang-Hao Hsu, Chen-Yin Chen
1Department of Medicine, Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, Taiwan.
Objective:
Acute physiology, age, chronic health evaluation II and III (APACHE II and III) scoring systems obtained on the day of the initiation of dialysis were compared the mortality rate among in critically ill patients with acute renal failure requiring dialysis.
Design:
Retrospective study.
Setting:
Intensive care units in a tertiary care university hospital in Taiwan.
Patients:
100 patients diagnosed with acute renal failure and requiring dialysis were admitted to intensive care units from January 1997 through December 1998.
Interventions:
Information deemed necessary to compute the APACHE II and APACHE III score on the day of dialysis initiation was collected.
Measurements And Results:
The overall hospital mortality rate was 71%. The relationship between APACHE II and APACHE III scores for patients was linear and correlated significantly in all subgroups. Goodness-of-fit was good for APACHE II and APACHE III models. Both reported good areas under receiver operating characteristic curve. Death in most patients was related to a higher APACHE II or APACHE III score during the 24 h immediately preceding the initiation of acute hemodialysis. Our results indicated a significant rise in mortality rates associated with higher APACHE II or III scores among all patients. Although less than 60%, the mortality rates markedly increased extent when APACHE II score of 24 or higher or APACHE III score above 90 had mortality rates exceeding 85%.
Conclusion:
Both predictive models demonstrated a similar degree of overall goodness-of-fit. Although APACHE II showed better calibration, APACHE III was better in terms of discrimination. The prediction accuracy of the APACHE II score for extremely high-risk patients is further enhanced by specific utility of APACHE III scoring as a second prediction model when the AII score is 24 or higher.