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The role of the lower extremity functional scale in predicting surgical outcomes for total joint arthroplasty patients

The purpose of this study was to evaluate the relationship between lower extremity functional scale (LEFS) scores with postoperative functional outcomes for total joint arthroplasty (TJA) patients and to investigate the utility of this tool to create an individualized plan of care perioperatively. P...

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Bibliographic Details
Published in:Arthroplasty 2022-02, Vol.4 (1), p.3-3, Article 3
Main Authors: Turcotte, Justin J, Kelly, McKayla E, Fenn, Alyssa B, Grover, Jennifer J, Wu, Christina A, MacDonald, James H
Format: Article
Language:English
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Summary:The purpose of this study was to evaluate the relationship between lower extremity functional scale (LEFS) scores with postoperative functional outcomes for total joint arthroplasty (TJA) patients and to investigate the utility of this tool to create an individualized plan of care perioperatively. Patients undergoing primary TJA at a single institution from 2016 to 2019 was retrospectively reviewed by a univariate analysis in terms of patient characteristics and outcomes across LEFS quartiles. Multivariate regression models were constructed to evaluate the association between the LEFS quartile and outcomes after controlling for confounding factors. A total of 1389 patients were included. All patients had a documented LEFS pre- and postoperatively with the last value documented at least 60 days to a maximum of 1 year after surgery. The following cutoffs for LEFS quartiles were observed: quartile 1 preoperative LEFS ≤27, quartile 2 ranges from 28 to 35, quartile 3 ranges from 36 to 43, and quartile 4 ≥ 44. Patients with a higher comorbidity burden and ASA score were more likely to have a lower LEFS. Higher levels of preoperative function were significantly associated with shorter LOS and higher rates of same day discharge, independent ambulation, mobility and activity scores, and rates of discharge home. These findings suggest that LEFS is a useful tool for aiding clinical resource allocation decisions, and incorporation of the measure into existing predictive models may improve their accuracy.
ISSN:2524-7948
2524-7948
DOI:10.1186/s42836-021-00106-3