The 5 and 11 Factor Modified Frailty Indices are Equally Effective at Outcome Prediction Using TQIP

The 5-factor modified frailty index (mFI-5) and the 11-factor modified frailty index (mFI-11) are equally effective in predicting adverse outcomes in the American College of Surgeons National Surgical Quality Improvement Program database. The similarly structured American College of Surgeons Trauma Quality Improvement Program (TQIP) database has not been studied with these two frailty indices. We hypothesized that the mFI-5 and mFI-11 could similarly predict adverse outcomes with TQIP data.

The mFI-5 and mFI-11 were calculated for each patient comprising our institutional TQIP registry (2016-2018). Spearman ρ was calculated to assess correlations between the two indices across multiple predefined TQIP patient cohorts. Complications were stratified by frailty score for each index. Multivariable logistic regression models adjusting for age, Glasgow Coma Scale score, and Injury Severity Score were created to assess each mFI's association with any complication and discharge dispositions (home, facility, and expired).

There were 8467 patients. Spearman ρ was >0.9 (P < 0.0001) for all patient cohorts except elderly, elderly blunt multisystem, and isolated hip fractures. Increasing frailty scores for both mFIs were associated with greater rates of acute kidney injury (P < 0.0001), myocardial infarction (P < 0.001), severe sepsis (P < 0.05), unplanned return to the intensive care unit (P < 0.0001), and unplanned intubation (P < 0.0001). On separate multivariable logistic regressions, the mFI-5 and mFI-11 were each predictive of any complication (P < 0.0001) and a facility discharge (P < 0.001). Neither the mFI-5 nor the mFI-11 were associated with mortality (P > 0.05).

The mFI-5 and mFI-11 are highly correlated across several TQIP patient cohorts. They also are both predictive of complications and discharge dispositions; however, neither index can predict mortality. Given its ease of use, the mFI-5 may be a better option for identifying frail patients and predicting adverse outcomes at the point of care in trauma.