Review and performance evaluation of aggregate weighted 'track and trigger' systems.
OBJECTIVE
There is no up-to-date literature review of physiologically based, aggregate weighted 'track and trigger' systems (AWTTS) and few data on their predictive ability for serious adverse outcomes. The aim of this study was to describe the AWTTS in clinical use and assess their ability to discriminate between survivors and non-survivors of hospital admission, based on an initial set of vital signs.


METHODS
A systematic review of the literature was performed, to describe the AWTTS, their components and their differences. Their ability to discriminate between survivors and non-survivors was evaluated using the area under the receiver-operating characteristics (AUROC) curve, and a database of 9987 vital signs datasets.


RESULTS
A total of 33 unique AWTTS were identified with AUROC (+/-95% CI) ranging from 0.657 (0.636-0.678) to 0.782 (0.767-0.797). 12 AWTTS (36%) discriminated reasonably well between survivors and non-survivors, the top four performing AWTTS incorporated age as a component (AUROCs ranging from 0.722 to 0.782). The top two systems also incorporated temperature.


CONCLUSIONS
There is a wide range of unique, but very similar, AWTTS in clinical use. There is no consistency regarding their physiological components, but the majority differ only in minor variations in the weightings for physiological derangement and/or the cut-off points between physiological weighting bands. The performance of most systems tested was poor when used to discriminate between survivors and non-survivors, although 36% discriminated reasonably well. Our results suggest that physiology can be used to predict outcome, but that further work is required to improve the AWTTS models.
Smith
Gary B
GB
Portsmouth Hospitals NHS Trust and University of Bournemouth, UK. gary.smith@porthosp.nhs.uk
Prytherch
David R
DR
Schmidt
Paul E
PE
Featherstone
Peter I
PI
D003422:Critical Care / Q000379:methods*; D016208:Databases, Factual; D006305:Health Status Indicators; D017052:Hospital Mortality; D006760:Hospitalization; D006801:Humans; D007362:Intensive Care Units; D008991:Monitoring, Physiologic / Q000379:methods*; D011237:Predictive Value of Tests; D012372:ROC Curve; D018570:Risk Assessment / Q000379:methods*