Improvement of the performance of survival prediction in the ageing blunt trauma population: A cohort study

PLoS One. 2018 Dec 18;13(12):e0209099. doi: 10.1371/journal.pone.0209099. eCollection 2018.

Abstract

Introduction: The overestimation of survival predictions in the ageing trauma population results in negative benchmark numbers in hospitals that mainly treat elderly patients. The aim of this study was to develop and validate a modified Trauma and Injury Severity Score (TRISS) for accurate survival prediction in the ageing blunt trauma population.

Methods: This retrospective study was conducted with data from two Dutch Trauma regions. Missing values were imputed. New prediction models were created in the development set, including age (continuous or categorical) and Anesthesiologists Physical Status (ASA). The models were externally validated. Subsets were created based on age (≥75 years) and the presence of hip fracture. Model performance was assessed by proportion explained variance (Nagelkerke R2), discrimination (Area Under the curve of the Receiver Operating Characteristic, AUROC) and visually with calibration plots. A final model was created based on both datasets.

Results: No differences were found between the baseline characteristics of the development dataset (n = 15,530) and the validation set (n = 15,504). The inclusion of ASA in the prediction models showed significant improved discriminative abilities in the two subsets (e.g. AUROC of 0.52 [95% CI: 0.46, 0.58] vs. 0.74 [95% CI: 0.69, 0.78] for elderly patients with hip fracture) and an increase in the proportion explained variance (R2 = 0.32 to R2 = 0.35 in the total cohort). The final model showed high agreement between observed and predicted survival in the calibration plot, also in the subsets.

Conclusions: Including ASA and age (continuous) in survival prediction is a simple adjustment of the TRISS methodology to improve survival predictions in the ageing blunt trauma population. A new model is presented, through which even patients with isolated hip fractures could be included in the evaluation of trauma care.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • Aging*
  • Area Under Curve
  • Female
  • Hip Fractures / diagnosis
  • Hip Fractures / epidemiology
  • Humans
  • Male
  • Middle Aged
  • Prognosis
  • ROC Curve
  • Retrospective Studies
  • Survival Analysis
  • Trauma Severity Indices*
  • Wounds, Nonpenetrating / diagnosis*
  • Wounds, Nonpenetrating / mortality*

Grants and funding

This work was supported by a grant of the Dutch organization for health research and care innovation (ZonMW) section TopCare projects (grantnumber: 80-84200-98-14226) (https://www.zonmw.nl/nl/onderzoek-resultaten/kwaliteit-van-zorg/programmas/project-detail/topzorg/models-of-fatal-and-non-fatal-outcome-measurement-in-the-trauma-population/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.