Predictive Model of Gait Recovery at One Month after Hip Fracture from a National Cohort of 25,607 Patients: The Hip Fracture Prognosis (HF-Prognosis) Tool

The aim of this study was to develop a predictive model of gait recovery after hip fracture. Data was obtained from a sample of 25,607 patients included in the Spanish National Hip Fracture Registry from 2017 to 2019. The primary outcome was recovery of the baseline level of ambulatory capacity. A l...

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Bibliographic Details
Published in:International journal of environmental research and public health 2021-04, Vol.18 (7), p.3809
Main Authors: González de Villaumbrosia, Cristina, Sáez López, Pilar, Martín de Diego, Isaac, Lancho Martín, Carmen, Cuesta Santa Teresa, Marina, Alarcón, Teresa, Ojeda Thies, Cristina, Queipo Matas, Rocío, González-Montalvo, Juan Ignacio, On Behalf Of The Participants In The Spanish National Hip Fracture Registry
Format: Article
Language:English
Subjects:
Anesthesia
Classification
Cognitive ability
Cohort Studies
Data collection
Early Ambulation
Fractures
Gait
Hip Fractures - epidemiology
Hospitalization
Humans
Length of stay
Model accuracy
Mortality
Nursing homes
Prediction models
Pressure ulcers
Prognosis
Statistical analysis
Ulcers
Variables
Walking
Weight-Bearing
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Summary:The aim of this study was to develop a predictive model of gait recovery after hip fracture. Data was obtained from a sample of 25,607 patients included in the Spanish National Hip Fracture Registry from 2017 to 2019. The primary outcome was recovery of the baseline level of ambulatory capacity. A logistic regression model was developed using 40% of the sample and the model was validated in the remaining 60% of the sample. The predictors introduced in the model were: age, prefracture gait independence, cognitive impairment, anesthetic risk, fracture type, operative delay, early postoperative mobilization, weight bearing, presence of pressure ulcers and destination at discharge. Five groups of patients or clusters were identified by their predicted probability of recovery, including the most common features of each. A probability threshold of 0.706 in the training set led to an accuracy of the model of 0.64 in the validation set. We present an acceptably accurate predictive model of gait recovery after hip fracture based on the patients' individual characteristics. This model could aid clinicians to better target programs and interventions in this population.
ISSN:1660-4601
1661-7827
1660-4601
DOI:10.3390/ijerph18073809