The Charlson Comorbidity Index (CCI) as a Mortality Predictor after Surgery in Elderly Patients

Am Surg. 2016 Jan;82(1):22-7.

Abstract

The increasing range of surgery in elderly patients reflects the changing demography where in the next 10 years one quarter of the population will be 65 years of age or older. There is presently no consensus concerning the optimal predictive markers for postoperative morbidity and mortality after surgery in older patients with an appreciation that physical frailty is more important than chronological age. In this retrospective analysis, we have compared the impact of age and the calculated preoperative Charlson Comorbidity Index (CCI) on early (30-day) and late (one-year) mortality in a group of patients >75 years of age dividing them into an "older old" cohort (75-84 years of age, Group A) and an "oldest old" group (≥85 years of age, Group B). Increased age was associated with a higher death rate after emergency surgery, with late deaths after elective surgery exceeding those after emergency operations. A higher mean CCI was noted in both age groups in early nonsurvivors after both elective and emergency surgery with a more significant effect of the preoperative CCI than chronological age for the prediction of late postoperative death for both groups after elective and emergency operations. Although the CCI was not designed to predict perioperative mortality in surgical cohorts, it correlates with a greater risk than age for perioperative death in the elderly.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Cause of Death*
  • Chi-Square Distribution
  • Comorbidity*
  • Confidence Intervals
  • Databases, Factual
  • Elective Surgical Procedures / methods
  • Elective Surgical Procedures / mortality
  • Emergencies
  • Female
  • Geriatric Assessment / methods
  • Hospital Mortality*
  • Humans
  • Israel
  • Logistic Models
  • Male
  • Odds Ratio
  • Predictive Value of Tests
  • Retrospective Studies
  • Severity of Illness Index
  • Surgical Procedures, Operative / mortality*
  • Survival Analysis