What question did this study set out to answer?

The research aims to classify postoperative pain archetypes and develop a predictive model to identify high-risk patients after total knee arthroplasty.

April 18, 2026Regional Anesthesia & Pain Medicine

Classification and stratification of patient pain archetypes following total knee arthroplasty: a machine learning approach

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Authors

JCJustin ChewHospital for Special Surgery JWJunying WangHospital for Special Surgery RRRenee RenHospital for Special Surgery

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Implication

Exploratory study identifies distinct pain profiles in TKA patients, suggesting tailored pain management is necessary.

Key Points

The research aims to classify postoperative pain archetypes and develop a predictive model to identify high-risk patients after total knee arthroplasty.
Analyzed 17,200 primary unilateral TKAs from 2021 to 2024
Used long short-term memory and K-means clustering for modeling pain scores
Applied least absolute shrinkage and selection operator for feature selection
Trained an eXtreme Gradient Boosting model to predict pain archetypes
Assessed model performance using accuracy and ROC-AUC
Identified two pain archetypes: low pain (n=7,082) and high pain (n=6,678)
High pain cluster exhibited higher mean NRS scores and opioid consumption
XGBoost predicted high-pain membership with 64% accuracy and ROC-AUC of 0.68
Younger age and higher tolerable NRS scores were key predictors of high pain
Moderate concordance found when clustering pain data from the first 12 or 24 hours postoperatively

Cite This Study

Chew et al. (2026) studied this question.

synapsesocial.com/papers/69e3209340886becb653fb1d https://doi.org/10.1136/rapm-2026-107626

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Classification and stratification of patient pain archetypes following total knee arthroplasty: a machine learning approach

Discussion

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Implication

Key Points

Cite This Study

Classification and stratification of patient pain archetypes following total knee arthroplasty: a machine learning approach

Discussion

Member takes

Implication

Key Points

Cite This Study

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