Discriminative Ability for Adverse Outcomes After Hip Fracture Surgery: A Comparison of Three Commonly Used
Junfei Guo1,2, Jun Di1, Xian Gao3
1Department of Orthopaedic Surgery, Third Hospital of Hebei Medical University, Shijiazhuang, China.
Insights
The modified Elixhauser
Area of Science:
- Orthopedic Surgery
- Geriatric Medicine
- Health Services Research
Background:
- Preoperative risk assessment is crucial for predicting adverse outcomes in hip fracture surgery.
- Existing models like Charlson Comorbidity Index (CCI), modified Elixhauser's Comorbidity Measure (mECM), and modified frailty index (mFI-5) have limitations and no consensus on optimal use.
- Accurate risk stratification aids in surgical decision-making and patient management strategies.
Purpose of the Study:
- To identify risk factors and patient characteristics for predicting mortality, perioperative complications, and extended length of stay (LOS) after hip fracture surgery.
- To compare the predictive performance of CCI, mECM, and mFI-5 when combined with a base model.
- To determine the optimal risk adjustment model for adverse outcomes in hip fracture patients.
Main Methods:
- Retrospective review of 2,241 hip fracture patients (age ≥65) undergoing surgery (PFNA) from 2013-2018.
- Development and comparison of multivariate logistic regression and Cox proportional hazards models.
- Inclusion of a base model with patient characteristics (age, BMI, ASA grade, etc.) and comorbidity indices (CCI, mECM, mFI-5).
Main Results:
- The base model combined with mECM demonstrated superior prediction for major complications (AUCs ranging from 0.637 to 0.679).
- Base model + CCI showed better prediction for minor neurological and hematological complications (AUCs ~0.659).
- Age was the strongest predictor of all-cause mortality (HR 1.35), while BMI, surgical delay, anesthesia type, and ASA grade predicted extended LOS.
Conclusions:
- The modified Elixhauser's Comorbidity Measure (mECM), when combined with a base model, appears to be the most effective index for predicting major complications in hip fracture surgery.
- The base model alone provides good discrimination for mortality and extended LOS, with limited improvement from adding comorbidity indices.
- Further research may refine risk assessment for optimizing patient outcomes after hip fracture surgery.
Introduction:
Preoperative risk assessment can predict adverse outcomes following hip fracture surgery, helping with decision-making and management strategies. Several risk adjustment models based on coded comorbidities such as Charlson Comorbidity Index (CCI), modified Elixhauser's Comorbidity Measure (mECM), and modified frailty index (mFI-5) are currently prevalent for orthopedic patients, but there is no consensus regarding which is optimal. The primary purpose was to identify the risk factors of CCI, mECM, and mFI-5, as well as patient characteristics for predicting (1) 1-month, 3-month, 1-year, and 2-year mortality, (2) perioperative complications, and (3) extended length of stay (LOS) following hip fractured surgery. The secondary aim was to compare the best-performing comorbidity index combined with characteristics identified in terms of their discriminative ability for adverse outcomes.
Methods:
We retrospectively reviewed 3,379 consecutive patients presenting with intertrochanteric fractures at our Level I trauma center from 2013 to 2018. After eliminated by exclusion criteria, 2,241 patients undergoing hip fracture surgery by PFNA, with age ≥65 years, were included. Three main multivariate logistic regression models were constructed. Cox proportional hazards models were used to calculate hazard ratios for mortality. A base model included age, BMI, surgical delay, anesthesia type, hemoglobin record at admission, and American Society of Anesthesiologists grade (ASA) also was constructed and assessed.
Results:
Base model + mECM outperformed other models for the occurrence of major complications including severe complications, cardiac complications, and pulmonary complications [the area under the receiver operating characteristic curve (AUC), 0.647; 95% CI, 0.616-0.677; AUC, 0.637; 95% CI, 0.610-0.664; AUC, 0.679; 95% CI, 0.642-0.715, respectively], while base model + CCI provided better prediction of minor complications of neurological complications and hematological complications (AUC, 0.659; 95% CI, 0.609, 0.709; AUC, 0.658; 95% CI, 0.635, 0.680). In addition, BMI, surgical delay, anesthesia type, and ASA were found highly relevant to extended LOS. Age-group (with a 10-year interval) was indicated to be mostly associated with all-cause mortality with fully adjusted hazard ratio of 1.35 and 95% CI range 1.20-1.51.
Conclusions:
In comparison with mFI-5 and CCI, mECM so far may be the best comorbidity index combined with the base model for predicting major complications following hip fracture. The base model already achieved good discrimination for all-cause mortality and extended LOS, further addition of risk adjustment indices led to only 1% increase in the amount of variation explained.
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