A Retrospective Cohort Study Examining the Validation of the Modified Duke Activity Status Index in the Non-cardiac

Michael Hua-Gen Li1, Morgan Rosser1, Jeanna Blitz1

  • 1Department of Anesthesiology, Duke University Hospital, Durham, NC.

Insights

The Duke Activity Status Index (DASI) reliably predicts long-term outcomes after major non-cardiac surgery. Simplified DASI versions also show predictive power for mortality and myocardial injury in at-risk patients.

Area of Science:

  • Cardiology
  • Anesthesiology
  • Public Health

Background:

  • Assessing preoperative risk is crucial for major non-cardiac surgery.
  • The Duke Activity Status Index (DASI) measures functional capacity.
  • Predictive tools for postoperative outcomes in at-risk patients are needed.

Purpose of the Study:

  • To evaluate the Duke Activity Status Index (DASI) and its simplified versions for predicting 30-day mortality and myocardial injury.
  • To validate DASI's predictive capability in patients with coronary artery disease risk factors undergoing major non-cardiac surgery.
  • To investigate the impact of the Area Deprivation Index (ADI) on DASI scores and outcomes.

Main Methods:

  • Retrospective cohort study including 4,199 patients.
  • Validated DASI and its variants for predicting composite outcomes (30-day mortality/myocardial injury).
  • Assessed 30-day severe complications, 1-year survival, and the influence of Area Deprivation Index (ADI).

Main Results:

  • Original and 4-question DASI accurately predicted 30-day composite outcomes (AUC 0.82).
  • Both DASI versions predicted 1-year composite outcomes, but not severe complications.
  • Higher Area Deprivation Index (ADI) correlated with lower DASI scores, indicating socioeconomic disparities.

Conclusions:

  • The Duke Activity Status Index (DASI) is a dependable predictor of long-term postoperative outcomes.
  • Simplified DASI versions maintain significant predictive value.
  • Socioeconomic factors, measured by ADI, influence functional capacity assessments like DASI.
Abstract