Discriminative Ability for Adverse Outcomes in Traumatic Ankle Fracture: A Comparison of the Modified Charlson Comorbidity Index, Elixhauser Comorbidity Measure, and Modified Frailty Index. Issue 4 (November 2022)

• Record Type: Journal Article
• Authors: Mehta, Sanket; Danford, Nicholas C.; Boddapati, Venkat; Chien, Bonnie Y.; Greisberg, Justin K.
• Is Part Of: Foot & ankle orthopaedics. Volume 7:Issue 4(2022)
• Publication Date: 2022-11
• Subjects: Ankle Fracture -- Trauma -- Clinical Outcomes; Foot -- Surgery -- Periodicals; Ankle -- Surgery -- Periodicals; Orthopedics -- Periodicals; 617.584
• DOI: 10.1177/2473011421S00803
• Languages: English
• ISSNs: 2473-0114

Abstract

Category: Trauma; Ankle Introduction/Purpose: The modified Charlson Comorbidity Index (mCCI), Elixhauser comorbidity measure (ECM), and 5- factor modified Frailty Index (mFI-5) have been validated for the purpose of outcome prediction in foot and ankle orthopedic care. However, from the perspective of clinical utility, no study has sought to compare the predictive performance of these measures specifically following traumatic ankle fracture. The present study compares the discriminative ability of the mCCI, ECM, and mFI-5, as well as various demographic characteristics, such as age, gender, and race, to predict in-hospital mortality and complications after the surgical management of traumatic ankle fracture. Methods: We performed a retrospective cohort study of adult patients registered in the National Trauma Data Bank (NTDB) 2011-2016 experiencing ankle trauma as malleolar fracture and undergoing surgical management. Patients missing baseline or comorbidity information, dead on arrival, or with a pilon fracture or stress fracture were excluded. Enhanced ICD-9 algorithms were used to calculate mCCI, ECM, and mFI-5 as has been done in prior orthopedic literature. The discriminative ability of the indices for adverse outcomes was assessed using area under the curve analysis from receiver operating characteristic curves. Outcomes included death, severe adverse events (death, deep surgical site infection (SSI), myocardial infarction (MI), cardiac arrest, deep vein thrombosis (DVT), pulmonary embolism (PE), sepsis, stroke, compartment syndrome), minor adverse events (acute kidney injury (AKI), pneumonia, superficial SSI, urinary tract infection (UTI)), infectious events (deep SSI, organ/space SSI, superficial SSI, pneumonia, UTI, catheter-related bloodstream infection, osteomyelitis, sepsis), and any adverse event. Results: In total, 171, 097 patients met inclusion criteria. The median age was 50 years and 49% of patients were male. Compared to ECM and mFI-5, mCCI had the largest discriminative ability for the outcome of in-hospital mortality (P=0.02 versus ECM, P<0.001 versus mFI-5, Table I). ECM, however, had a larger discriminative ability for major adverse event, minor adverse event, infectious event, and any complication during the hospitalization (P<0.001, all comparisons). In an analysis of demographic factors, age demonstrated higher discriminative ability for in-hospital mortality compared to gender (P<0.001) and race (P<0.001). Race had sole or shared inferior discriminative ability for all outcomes. The most discriminative comorbidity index (ECM) outperformed the most discriminative demographic factor (age, gender) for any complication, minor adverse event, and infectious events. A combination analysis of the most predictive comorbidity index and the most predictive demographic factor resulted in discriminative improvements in all five outcome variables. Conclusion: Among comorbidity indices, the mCCI demonstrated significantly greater discriminative ability for mortality and the ECM demonstrated significantly greater discriminative ability for multiple adverse events during hospitalization. The use of these indices in conjunction with easily accessible demographic factors, such as age, resulted in further improvements in discrimination ability. These findings suggest that increased use of the mCCI and ECM may assist in the identification and management of patients at risk of death and postoperative complications, respectively, and thereby help optimize risk stratification, inform patient expectations, and guide outcomes-based reimbursements in the management of traumatic ankle fracture.