Machine learning methods are comparable to logistic regression techniques in predicting severe walking limitation following total knee arthroplasty.
Knee Surg Sports Traumatol Arthrosc
; 28(10): 3207-3216, 2020 Oct.
Article
em En
| MEDLINE
| ID: mdl-31832697
ABSTRACT
PURPOSE:
Machine-learning methods are flexible prediction algorithms with potential advantages over conventional regression. This study aimed to use machine learning methods to predict post-total knee arthroplasty (TKA) walking limitation, and to compare their performance with that of logistic regression.METHODS:
From the department's clinical registry, a cohort of 4026 patients who underwent elective, primary TKA between July 2013 and July 2017 was identified. Candidate predictors included demographics and preoperative clinical, psychosocial, and outcome measures. The primary outcome was severe walking limitation at 6 months post-TKA, defined as a maximum walk time ≤ 15 min. Eight common regression (logistic, penalized logistic, and ordinal logistic with natural splines) and ensemble machine learning (random forest, extreme gradient boosting, and SuperLearner) methods were implemented to predict the probability of severe walking limitation. Models were compared on discrimination and calibration metrics.RESULTS:
At 6 months post-TKA, 13% of patients had severe walking limitation. Machine learning and logistic regression models performed moderately [mean area under the ROC curves (AUC) 0.73-0.75]. Overall, the ordinal logistic regression model performed best while the SuperLearner performed best among machine learning methods, with negligible differences between them (Brier score difference, < 0.001; 95% CI [- 0.0025, 0.002]).CONCLUSIONS:
When predicting post-TKA physical function, several machine learning methods did not outperform logistic regression-in particular, ordinal logistic regression that does not assume linearity in its predictors. LEVEL OF EVIDENCE Prognostic level II.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Caminhada
/
Artroplastia do Joelho
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Limitação da Mobilidade
/
Aprendizado de Máquina
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Aged
/
Female
/
Humans
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Male
/
Middle aged
Idioma:
En
Revista:
Knee Surg Sports Traumatol Arthrosc
Ano de publicação:
2020
Tipo de documento:
Article