Effect of age and comorbidity on the ability of quick-Sequential Organ Failure Assessment score to predict outcome in emergency department patients with suspected infection

Objective: To determine if a combination of the Charlson Comorbidity Index (CCI) and quick-Sequential Organ Failure Assessment (qSOFA) score is superior to qSOFA alone for predicting the outcome of ED patients with suspected infection. Methods: A prospective, observational single-centre study recruited consecutive adult patients who underwent blood culture collection in the ED and were admitted to hospital. The primary outcome was 28-day in-hospital mortality, and the secondary outcome a composite of mortality and/or ICU admission >= 72 h duration. The qSOFA and CCI were combined using logistic regression models, and the resulting area under the receiver operating characteristic curve (AUROC) compared to that for qSOFA alone. Results: Of 551 patients recruited, 18 (3%) died and 27 (5%) attained the composite outcome. The AUROC for qSOFA/CCI versus qSOFA for the primary outcome is 0.79 versus 0.72 (95% confidence interval 0.71-0.88 vs 0.62-0.82, P = 0.055) and 0.80 versus 0.76 (95% confidence interval 0.73-0.86 vs 0.68-0.84, P = 0.048). Deaths among patients not admitted to ICU (12/495) accounted for most of the overall differences in AUROC. Conclusions: This generates the hypothesis that age and comorbid disease status augment the qSOFA score for predicting adverse outcome among patients with suspected infection in the ED. The resultsmay reflect the predominance of these factors in determining suitability for admission to ICU. Reported limitations of qSOFA to detect the risk of adverse outcome may reflect the influence of unmeasured patient factors.

Automated summary

The combination of CCI and qSOFA score was found to be superior to qSOFA alone in predicting outcomes for ED patients with suspected infection. Age and comorbid disease status were shown to enhance the predictive value of qSOFA for adverse outcomes. The limitations of qSOFA in detecting adverse outcome risk may be influenced by unmeasured patient factors according to the results.