The modified-KLICC score: a novel tool to predict outcomes following debridement, antibiotics, and implant retention after early acute periprosthetic hip infection.

Aims: Two preoperative risk models have been designed to predict debridement, antibiotics, and implant retention (DAIR) failure: KLICC and CRIME-80 scores. However, external validation of both scores is scarce. We aimed to validate these scores in an external cohort and to create a new model with additional risk factors. Methods: We retrospectively evaluated 96 patients with early acute periprosthetic hip infection treated with DAIR. At a two-year cut-off, failure was defined as the need for second DAIR, implant removal, or 90-day infection-related death. Association between demographic variables and failures was tested. The model discriminatory performance was measured using the time-dependent receiver operating characteristic (ROC) curve and Harrell concordance index (C-index). The 'calibration in the large' (CITL) was calculated as the logistic regression model intercept. A modified KLICC score was created by adding the variable time from onset of symptoms to DAIR. Results: The 24-month cumulative incidence of failure was 23.96% (95% CI 15.9 to 32.8). KLICC's area under receiver operating characteristic (AUROC) was 0.79 (95% CI 0.67 to 0.90), with a CITL of -0.57 (95% CI -1.16 to -0.01) and a slope of 0.68 (95% CI 0.35 to 1.02). CRIME-80's AUROC was 0.63 (95% CI 0.51 to 0.76), with a CITL of -1.66 (95% CI -2.13 to -1.19) and a slope of 0.35 (95% CI -0.14 to 0.85). The difference between both AUROCs was statistically significant (p = 0.0138), with the KLICC score performing better. As compared with the original KLICC score, the modified-KLICC improved the AUROC to 0.85 and the beta-slope and α intercept to 1.24 and -0.07, respectively (p = 0.020). Conclusion: KLICC was superior to CRIME-80 in predicting DAIR failure. The modified-KLICC score improved the model prediction and could be useful to help indicate alternatives to DAIR when the predictive failure is high.