Impact of Frailty and Malnutrition on Outcomes After Surgical Fixation of Lower Extremity Fractures in Young Patients

Abstract

Objectives: Evaluate the relationship of nutrition parameters and the modified frailty index (mFI) on postsurgical complications within a young patient population sustaining lower extremity orthopaedic trauma. Design: Retrospective observational cohort study. Setting: Urban, American College of Surgeons-Verified, Level-1, Trauma Center. Patients/Participants: Seventeen-thousand one hundred nine adult patients under the age of 65 sustaining lower extremity fractures undergoing operative intervention from 2006 to 2018. Main Outcome Measures: On admission, mFI and albumin levels were obtained, as well as complication data. Statistical analysis was used to analyze the association between frailty, malnutrition, and postoperative complications. Patients were stratified, healthy (mFI ≤1, albumin ≥3.5 g/dL), malnourished (mFI ≤1, albumin <3.5 g/dL), frail (mFI ≥2, albumin ≥3.5 g/dL), and frail and malnourished (mFI ≥2, albumin <3.5 g/dL). Results: 60.4% of patients were healthy, 18.8% were malnourished, 11.7% were frail, and 9.0% were frail and malnourished. Frailty and/or malnourishment on admission predicted significantly higher odds of postoperative complications and mortality when compared with healthy patients. Frailty and malnourishment in conjunction predicted a significantly higher odds ratio of 1.46 (1.22–1.75) for developing postoperative complications when compared with the only malnourished. This was also observed when compared with the only frail (odd ratio: 1.61, P < 0.001); however, there was also a 2.72 (P < 0.001) increased odds of mortality. Conclusions: Frailty and malnutrition in conjunction predicts a subset of patients with a higher risk of postoperative complications beyond that of frailty or malnutrition in isolation. Identification of these physiological states on admission allows for interventional opportunities during hospitalization. Level of Evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Use of a Six-Item Modified Frailty Index to Predict 30-day Adverse Events, Readmission, and Mortality in Older Patients Undergoing Surgical Fixation of Lower Extremity, Pelvic, and Acetabular Fractures

“… 13 In addition to these variables, hypoalbuminemia is an important predictor of outcomes after orthopaedic surgery, although it is not routinely measured in clinical care nor included in frailty indices. 27 28 29 30 31 In this study, hypoalbuminemia was considered in addition to the five items of the MF-5 to create a six-item modified frailty index (MF-6). The purpose of this study was to assess the use of the MF-6 in predicting short-term (≤30 days) adverse outcomes among patients older than 65 years undergoing open reduction and internal fixation for lower extremity, pelvic, and acetabular fractures in the inpatient setting.…”

Visualizing Frailty: Exploring Radiographical Measures of Frailty in Trauma Patients

“…In the last few years, several studies have demonstrated the capacity of frailty scores and markers to predict postoperative outcomes [37,38]. Frailty and malnourishment have demonstrated a synergistic effect when compared with malnourishment alone in predicting the potential for postoperative complications [38].…”

“…In the last few years, several studies have demonstrated the capacity of frailty scores and markers to predict postoperative outcomes [37,38]. Frailty and malnourishment have demonstrated a synergistic effect when compared with malnourishment alone in predicting the potential for postoperative complications [38]. Frailty has also been shown to increase the risk of postoperative morbidity, even when controlling for other comorbidities, and demographic factors [37].…”

Does a Modified Frailty Index Predict 30-day Complications After Long-Bone Nonunion or Malunion Surgery?

“…The anatomic locations were grouped by CPT code into procedures of the femur (27470 and 27472) or tibia and fibula (27720, 27722, 27724, 27725, and 27726), as is consistent with previous studies. 28–30…”

“…The anatomic locations were grouped by CPT code into procedures of the femur (27470 and 27472) or tibia and fibula (27720, 27722, 27724, 27725, and 27726), as is consistent with previous studies. [28][29][30] Preoperative Variables Demographic data collected included age, sex, race, and ASA class, as well as comorbidities including smoking, dialysis, bleeding disorders, obesity, and chronic steroid use. To allow for multivariate regression analysis of postoperative outcomes, patients were excluded if they were missing any of the demographic variables which were entered as inputs in the regression model.…”