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Published on: August 17, 2017
Prognostic Factors for Functional Recovery at 1-Year Following Fragility Hip Fractures
Nitchanant Kitcharanant1, Pichitchai Atthakomol1, Jiraporn Khorana2,3
1Department of Orthopaedics, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Pre-fracture EQ-VAS scores, Charlson Comorbidity Index (CCI), and surgical treatment predict recovery of daily living activities after hip fractures. These factors can inform clinical prediction models for better patient outcomes.
Area of Science:
- Gerontology
- Orthopedic Surgery
- Rehabilitation Medicine
Background:
- Fragility hip fractures significantly impair patients' ability to perform activities of daily living (ADL).
- Maximizing ADL recovery is a primary treatment goal for hip fracture patients.
- Identifying prognostic factors is crucial for predicting functional recovery after hip fractures.
Purpose of the Study:
- To explore prognostic factors associated with returning to pre-fracture ADL levels at 1 year post-hip fracture.
- To identify key predictors that influence functional recovery in patients with fragility hip fractures.
Main Methods:
- Retrospective study of 405 patients admitted with fragility hip fractures between July 2016 and September 2018.
- Data collected included demographics, pre-fracture health status (CCI, EQ-VAS, Barthel index), ambulatory status, and fracture treatment.
- Multivariable logistic regression analysis was used to assess predictors of returning to pre-fracture ADL status at 1 year.
Main Results:
- 70.1% of patients (284/405) returned to their pre-fracture ADL status at 1 year.
- Pre-fracture EuroQol-Visual Analog Scale (EQ-VAS) scores ≥ 65 showed the strongest association (mOR, 12.90; p=0.03).
- Lower Charlson Comorbidity Index (CCI) scores (<5) (mOR, 1.96; p=0.01) and surgical hip fracture treatment were also significant predictors.
Conclusions:
- Pre-fracture EQ-VAS score, CCI score, and surgical treatment are key prognostic factors for 1-year ADL recovery after hip fracture.
- These identified factors can be utilized to develop a clinical prediction model.
- Such a model could aid in optimizing treatment strategies and managing patient expectations regarding functional outcomes.
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