A single-centre cohort study of National Early Warning Score (NEWS) and near patient testing in acute medical admissions

Eur J Intern Med. 2016 Nov:35:78-82. doi: 10.1016/j.ejim.2016.06.014. Epub 2016 Jun 23.

Abstract

Introduction: The utility of an early warning score may be improved when used with near patient testing. However, this has not yet been investigated for National Early Warning Score (NEWS). We hypothesised that the combination of NEWS and blood gas variables (lactate, glucose or base-excess) was more strongly associated with clinical outcome compared to NEWS alone.

Methods: This was a prospective cohort study of adult medical admissions to a single-centre over 20days. Blood gas results and physiological observations were recorded at admission. NEWS was calculated retrospectively and combined with the biomarkers in multivariable logistic regression models. The primary outcome was a composite of mortality or critical care escalation within 2days of hospital admission. The secondary outcome was hospital length of stay.

Results: After accounting for missing data, 15 patients out of 322 (4.7%) died or were escalated to the critical care unit. The median length of stay was 4 (IQR 7) days. When combined with lactate or base excess, NEWS was associated with the primary outcome (OR 1.18, p=0.01 and OR 1.13, p=0.03). However, NEWS alone was more strongly associated with the primary outcome measure (OR 1.46, p<0.01). The combination of NEWS with glucose was not associated with the primary outcome. Neither NEWS nor any combination of NEWS and a biomarker were associated with hospital length of stay.

Conclusion: Admission NEWS is more strongly associated with death or critical care unit admission within 2days of hospital admission, compared to combinations of NEWS and blood-gas derived biomarkers.

Keywords: Clinical outcomes; Early warning score; Monitoring; Physiological parameters.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Biomarkers
  • Blood Gas Analysis
  • Female
  • Hospital Mortality*
  • Humans
  • Intensive Care Units*
  • Length of Stay
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Patient Admission / statistics & numerical data*
  • Prospective Studies
  • Risk Assessment
  • Severity of Illness Index
  • Time Factors
  • United Kingdom

Substances

  • Biomarkers