Should age be included as a component of track and trigger systems used to identify sick adult patients?

Resuscitation. 2008 Aug;78(2):109-15. doi: 10.1016/j.resuscitation.2008.03.004. Epub 2008 May 27.

Abstract

Aim of study: Few published "track and trigger systems" used to identify sick adult patients incorporate patient age as a variable. We investigated the relationship between vital signs, patient age and in-hospital mortality and investigated the impact of patient age on the function as predictors of in-hospital mortality of the two most commonly used track and trigger systems.

Materials and methods: Using a database of 9987 vital signs datasets, we studied the relationship between admission vital signs and in-hospital mortality for a range of selected vital signs, grouped by patient age. We also used the vital signs data set to study the impact of patient age on the relationship between patient triggers using the "MET criteria" and "MEWS", and in-hospital mortality.

Results: At hospital discharge, there were 9152 (91.6%) survivors and 835 (8.4%) non-survivors. As admission vital signs worsened, mortality increased for each age range. Where groups of patients had triggered a certain MET criterion, mortality was higher as patient age increased. Mortality varied significantly with age (p<0.05; Fishers exact test) for breathing rate >36breathsmin(-1), systolic BP<90mmHg and decreased conscious level. For each age group, mortality also increased as total MEWS score increased. As the number of simultaneously occurring MEWS abnormalities, or simultaneously occurring MET criteria, increased, mortality increased for each age range.

Conclusions: Age has a significant impact on in-hospital mortality. Our data suggest that the inclusion of age as a component of these systems could be advantageous in improving their function.

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Analysis of Variance
  • Critical Care / methods*
  • Health Status Indicators*
  • Hospital Mortality
  • Humans
  • Male
  • Middle Aged
  • Monitoring, Physiologic / methods*
  • Predictive Value of Tests
  • Risk Assessment / methods*