A Prediction Model for Instability in Adult Distal Radius Fractures: Integrating Post-Reduction and Follow-Up...

Area of Science:

• Orthopedic Surgery
• Radiology
• Biostatistics

Background:

• Lafontaine criteria have limited predictive performance for distal radius fracture (DRF) instability.
• Accurate prediction of DRF instability is crucial for guiding treatment and preventing complications.

Purpose of the Study:

• To develop and validate an enhanced predictive model for DRF instability.
• To incorporate post-reduction and one-week follow-up radiographic findings for improved accuracy.

Main Methods:

• Retrospective study of adult DRF patients treated with closed reduction and casting.
• Development of a logistic regression model using pre- and post-reduction radiographs.
• Creation of simplified risk scores and a one-week follow-up model for moderate-risk cases.

Main Results:

• The developed model demonstrated good performance (AUC = 0.86) and outperformed Lafontaine criteria (AUC = 0.75 vs. 0.68).
• Key predictors included dorsal angulation, intra-articular involvement, ulnar variance, and post-reduction volar angulation.
• Risk stratification identified 39% of patients as moderate risk, necessitating further evaluation.

Conclusions:

• The proposed model offers superior accuracy in stratifying DRF instability risk compared to existing criteria.
• Integration of post-reduction and one-week radiographic parameters enhances clinical decision-making for DRF management.