Predictors of Failure After Two-Stage Revision for Periprosthetic Joint Infections of the Knee.

BACKGROUND

Prosthetic joint infection (PJI) following total knee arthroplasty remains a serious complication. Although two-stage revision is considered the gold standard, predictors of failure remain unclear. This study aimed to identify factors associated with failure after two-stage revision for knee PJI using conventional statistics with exploratory machine-learning validation.

METHODS

A retrospective review was conducted on 154 patients who underwent two-stage revision for knee PJI between 2018 and 2022 at a high-volume arthroplasty center. All patients completed a minimum 24-month follow-up (mean 36.3 ± 20.3 months). Treatment success and failure were defined using MSIS Tier-1 criteria. Independent predictors of failure were identified using multivariate logistic regression and Random Forest classification model.

RESULTS

Most infections were late in onset (91.6%), and 68.2% were culture-positive. Difficult-to-treat (DTT) organisms were identified in 22.1% of cases and were associated with significantly worse postoperative WOMAC, KSS, and OKS outcomes (all P < .001). Multivariate analysis identified DTT organisms (odds ratio 0.035, P < .001) and shorter time from index surgery to infection (odds ratio 1.033, P = .016) as independent predictors of failure. The random Forest model demonstrated an overall accuracy of 84.2% and identified DTT organisms, pre-revision C-reactive protein levels, and time from index surgery as the most influential variables contributing to classification performance. Most failures occurred within 30 months of reimplantation.

CONCLUSIONS

DTT organisms and shorter time from index surgery to infection were independent predictors of failure following two-stage revision for knee PJI. Exploratory machine-learning analysis identified similar predictor patterns and supports the importance of microbiological factors in determining outcomes.