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Derivation and validation of a risk score for predicting mortality among inpatients following rapid response team activation
  1. Kyle White1,
  2. Anne Bernard2,
  3. Ian Scott3,4
  1. 1 Department of Internal Medicine and Clinical Epidemiology, Princess Alexandra Hospital, Brisbane, Queensland, Australia
  2. 2 Queensland Facility for Advanced Bioinformatics, Brisbane, Queensland, Australia
  3. 3 School of Clinical Medicine, University of Queensland Faculty of Health and Behavioural Sciences, Herston, Queensland, Australia
  4. 4 Department of Internal Medicine and Clinical Epidemiology, Princess Alexandra Hospital, Woolloongabba, Queensland, Australia
  1. Correspondence to Dr Ian Scott, Director of Internal Medicine and Clinical Epidemiology, Princess Alexandra Hospital, Brisbane, QLD 4102, Australia; Ian.Scott{at}


Purpose of the study Despite mature rapid response systems (RRS) for clinical deterioration, individuals activating RRS have poor outcomes, with up to one in four dying in hospital. We aimed to derive and validate a risk prediction tool for estimating risk of 28-day mortality among hospitalised patients following rapid response team (RRT) activation.

Study design Analysis of prospectively collected data on 1151 consecutive RRT activations involving 800 inpatients at a tertiary adult hospital. Patient characteristics, RRT triggers and actions, and mortality were ascertained from medical records and death registries. A multivariable risk prediction regression model, derived from 600 randomly selected patients, was validated in the remaining 200 patients. Main outcome was accuracy of weighted risk score (measured by area under receiver operator curve (AUC)) and performance characteristics for various cut-off scores.

Results At 28 days, 150 (18.8%) patients had died. Increasing age, emergency admission, chronic liver disease, chronic kidney disease, malignancy, after-hours RRT activation, increasing National Early Warning Score, major/intense RRT intervention and multiple RRT activations were predictors of mortality. The risk score (0–105) in derivation and validation cohorts had AUCs 0.86 (95% CI 0.82 to 0.89) and 0.82 (95% CI 0.75 to 0.90), respectively. In the validation cohort, cut-off score of 32.5 or higher maximised sensitivity: 81.6% (95% CI 68.4% to 92.1%), specificity: 56.2% (95% CI 49.4% to 63.6%), positive likelihood ratio (LR): 1.9 (95% CI 1.5 to 2.3) and negative LR: 0.3 (95% CI 0.2 to 0.6).

Conclusion A validated risk score predicted risk of post-RRT death with more than 80% accuracy, helping to identify patients for whom targeted rescue care may improve survival.

  • rapid response teams
  • tertiary hospital
  • prospective study
  • patient characteristics
  • outcomes

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  • Contributors KW planned the study, undertook all data collection and assisted in data analyses and drafting the manuscript. AB undertook all statistical analyses and assisted in drafting and revising the manuscript. IS conceived the study, assisted in data analysis and wrote the draft manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Ethics approval The study protocol was approved by the Metro South Health Research Ethics Committee, Brisbane, Queensland.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information.

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