Improving the predictability of ICU illness severity scales
- Resource Type
- Conference
- Authors
- Alqarni, M.; Arabi, Y.; Kakiashvili, T.; Khedr, M.; Koczkodaj, W. W; Leszek, J.; Przelaskowski, A.; Rutkowski, K.
- Source
- 2011 Federated Conference on Computer Science and Information Systems (FedCSIS) Computer Science and Information Systems (FedCSIS), 2011 Federated Conference on. :11-17 Sep, 2011
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Cogeneration
Hospitals
Physiology
Medical diagnostic imaging
Educational institutions
Blood pressure
Computational modeling
medical scales
illness severity
expert system
consistency-driven pairwise comparisons
inconsistency analysis
- Language
This study demonstrates how to improve the predictability of one of the commonly used ICUs severity of illness scales, namely APACHE II, by using the consistency-driven pairwise comparisons (CDPC) method. From a conceptual view, there is little doubt that all items have exactly equal importance or contribution to predicting mortality risk of patients admitted to ICUs. Computing new weights for all individual items is a considerable step forward since it is based on reasonable to assume that not all individual items have equal contribution in predicting mortality risk. The received predictability improvement is 1.6% (from 70.9% to 72.5%) and the standard error decreased from 0.046 to 0.045. This must be taken as an indication of the right way to go.