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Prognostic utilization of models based on the APACHE II, APACHE IV, and SAPS II scores for predicting in-hospital
Zahra Rahmatinejad1, Fariba Tohidinezhad1, Hamidreza Reihani2
1Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Background:
This study was designed to evaluate and compare the prognostic value of the APACHE II, APACHE IV, and SAPSII scores for predicting in-hospital mortality in the ED on a large sample of patients. Earlier studies in the ED setting have either used a small sample or focused on specific diagnoses.
Methods:
A prospective study was conducted to include patients with higher risk of mortality from March 2016 to March 2017 in the ED of Emam Reza Hospital, northeast of Iran. Logistic regression was used to develop three models. Evaluation was performed in terms of the overall performance (Brier Score, BS, and Brier Skill Score, BSS), discrimination (Area Under the Curve, AUC), and calibration (calibration graph).
Results:
A total of 2205 patients met the study criteria (53% male and median age of 64, IQR: 50-77). In-hospital mortality amounted to 19%. For APACHE II, APACHE IV, and SAPS II the BS was 0.132, 0.125 and 0.133 and the BSS was 0.156, 0.2, and 0.144, respectively. The AUC was 0.755 (0.74 to 0.779) for APACHE II, 0.794 (0.775 to 0.818) for APACHE IV, and 0.751 (0.727 to 0.776) for SAPS II. The APACHE IV showed significantly greater AUC in comparison to the APACHE II and SAPS II. The graphical evaluation revealed good calibration of the APACHE IV model.
Conclusion:
APACHEIV outperformed APACHEII and SAPSII in terms of discrimination and calibration. More validation is needed for using these models for decision-making about individual patients, although they would perform best at a cohort level.
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