Enhancing Braden pressure ulcer risk assessment in acutely ill adult veterans

Wound Repair Regen. 2012 Mar-Apr;20(2):137-48. doi: 10.1111/j.1524-475X.2011.00761.x. Epub 2012 Feb 3.


This study sought to determine if a parsimonious pressure ulcer (PU) predictive model could be identified specific to acute care to enhance the current PU risk assessment tool (Braden Scale) utilized within veteran facilities. Factors investigated include: diagnosis of gangrene, anemia, diabetes, malnutrition, osteomyelitis, pneumonia/pneumonitis, septicemia, candidiasis, bacterial skin infection, device/implant/graft complications, urinary tract infection, paralysis, senility, respiratory failure, acute renal failure, cerebrovascular accident, or congestive heart failure during hospitalization; patient's age, race, smoking status, history of previous PU, surgery, hours in surgery; length of hospitalization, and intensive care unit days. Retrospective chart review and logistic regression analyses were used to examine Braden scores and other risk factors in 213 acutely ill veterans in North Florida with (n = 100) and without (n = 113) incident PU from January-July 2008. Findings indicate four medical factors (malnutrition, pneumonia/pneumonitis, candidiasis, and surgery) have stronger predictive value (sensitivity 83%, specificity 72%, area under receiver operating characteristic [ROC] curve 0.82) for predicting PUs in acutely ill veterans than Braden Scale total scores alone (sensitivity 65%, specificity 70%, area under ROC curve 0.70). In addition, accounting for four medical factors plus two Braden subscores (activity and friction) demonstrates better overall model performance (sensitivity 80%, specificity 76%, area under ROC curve 0.88).

MeSH terms

  • Acute Disease
  • Aged
  • Case-Control Studies
  • Female
  • Florida / epidemiology
  • Humans
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Pressure Ulcer / epidemiology
  • Pressure Ulcer / etiology*
  • Pressure Ulcer / prevention & control*
  • Retrospective Studies
  • Risk Assessment
  • Risk Factors
  • Veterans* / statistics & numerical data