Related Experiment Video
Updated: Feb 4, 2026

Measuring Frailty in HIV-infected Individuals. Identification of Frail Patients is the First Step to Amelioration and Reversal of Frailty
Published on: July 24, 2013
Frailty predicts mortality and complications in chronologically young patients with traumatic orthopaedic injuries
Rahul M Rege1, Robert P Runner2, Christopher A Staley2
1Emory University, School of Medicine, 1648 Pierce Dr. NE, Atlanta, GA 30307, United States.
Insights
The modified frailty index (mFI) effectively predicts mortality and complications in younger patients with orthopaedic trauma. This tool aids in individualized risk assessment for better patient outcomes.
Area of Science:
- Orthopaedic Surgery
- Trauma Care
- Geriatric Medicine
Background:
- Rising morbidity and mortality in traumatic orthopaedic injuries necessitates improved complication prediction.
- Frailty indices are validated predictors in various surgical fields, primarily in geriatric populations.
- Limited evidence exists on frailty in younger, non-geriatric trauma patients.
Purpose of the Study:
- To evaluate the modified frailty index (mFI) as a predictor of mortality and complications.
- To assess the mFI's role in patients of all ages undergoing surgery for pelvic, acetabular, and lower extremity trauma.
Main Methods:
- Utilized the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database (2005-2014).
- Analyzed 56,241 patients, divided into geriatric (≥60 years) and young (<60 years) cohorts.
- Calculated mFI, performing bivariate and multivariate analyses with logistic regression and chi-square tests.
Main Results:
- The mFI strongly predicted 30-day mortality in the young cohort (OR 11.02, p<0.001).
- mFI was also a significant predictor of Clavien-Dindo grade IV complications in younger patients (OR 28.82, p<0.001).
Conclusions:
- The mFI is a significant predictor of morbidity and mortality in chronologically young orthopaedic trauma patients.
- mFI facilitates individualized risk assessment for perioperative counseling and outcome improvement.
Background:
As morbidity and mortality from traumatic orthopaedic injuries continues to rise, increased research is being conducted on how to best predict complications in at risk patients. Recently, frailty indices have been validated in a variety of surgical subspecialties as predictors of morbidity and mortality. However, the vast majority of research has been conducted on geriatric patient populations, with little evidence on patients who are chronologically young. The purpose of this study was to evaluate the role of a modified frailty index (mFI) in predicting mortality and complications after pelvis, acetabulum, and lower extremity trauma in patients of all ages.
Methods:
The American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database was queried from 2005 to 2014 for all patients who underwent surgery for pelvis, acetabulum, and lower extremity trauma. The sample size was divided into geriatric (age ≥ 60) and young (age < 60) cohorts. The mFI score was calculated for each patient. Bivariate analysis was performed using logistic regression and a chi-square test to determine the relationship between mFI and both primary and secondary outcomes while adjusting for age. Univariate analysis and multivariate analyses were performed. All analyses were done using SAS 9.4 (Cary, NC) and a p < 0.05 was considered significant.
Results:
56,241 patients were identified to have undergone surgery for pelvis, acetabulum, or lower extremity trauma. 28% of patients were identified under the age of 60. In the young cohort, mFI was a strong predictor of thirty-day mortality (OR 11.02, 95% CI 6.26-19.39, p < 0.001). With regards to Clavien-Dindo grade IV complications, MFI is also a strong predictor in the young cohort (OR 28.82, 95% CI 16.05-51.77, p < 0.001).
Conclusion And Relevance:
The mFI score was a significant predictor of morbidity and mortality in chronologically young orthopaedic trauma patients. The use of the mFI score can provide an individualized risk assessment to interdisciplinary teams for perioperative counseling and to improve outcomes.
Related Concept Videos
Predicting Molecular Geometry
Hemodialysis II: Procedure and Complications
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Pneumonia III: Complications and Assessment
Diabetes: Symptoms, Diagnosis, and Complications
Traumatic Memory

