New scoring system (APACHE-HF) for predicting adverse outcomes in patients with acute heart failure: evaluation of the APACHE II and Modified APACHE II scoring systems

Background: No scoring system for assessing acute heart failure (AHF) has been reported.

Methods and results: Data for 824 AHF patients were analyzed. The subjects were divided into an alive (n=750) and a dead group (n=74). We constructed a predictive scoring system based on eight significant APACHE II factors in the alive group [mean arterial pressure (MAP), pulse, sodium, potassium, hematocrit, creatinine, age, and Glasgow Coma Scale (GCS); giving each one point], defined as the APACHE-HF score. The patients were assigned to five groups by the APACHE-HF score [Group 1: point 0 (n=70), Group 2: points 1 and 2 (n=343), Group 3: points 3 and 4 (n=294), Group 4: points 5 and 6 (n=106), and Group 5: points 7 and 8 (n=11)]. A higher optimal balance was observed in the APACHE-HF between sensitivity and specificity [87.8%, 63.9%; area under the curve (AUC)=0.779] at 2.5 points than in the APACHE II (47.3%, 67.3%; AUC=0.558) at 17.5 points. The multivariate Cox regression model identified belonging to Group 5 [hazard ratio (HR): 7.764, 95% confidence interval (CI) 1.586-38.009], Group 4 (HR: 6.903, 95%CI 1.940-24.568) or Group 3 (HR: 5.335, 95%CI 1.582-17.994) to be an independent predictor of 3-year mortality. The Kaplan-Meier curves revealed a poorer prognosis, including all-cause death and HF events (death, readmission-HF), in Group 5 and Group 4 than in the other groups, in Group 3 than in Group 2 or Group 1, and in Group 2 than in Group 1.

Conclusions: The new scoring system including MAP, pulse, sodium, potassium, hematocrit, creatinine, age, and GCS (APACHE-HF) can be used to predict adverse outcomes of AHF.