ArticleFrontiers in artificial intelligence2026
Development and internal validation of machine-learning models for postoperative deep vein thrombosis after hip arthroplasty for femoral neck fracture: evaluation of Traditional Chinese Medicine syndrome features.
Article in Frontiers in artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Postoperative lower-extremity deep vein thrombosis (DVT) remains a clinically important complication after hip arthroplasty for femoral neck fracture. We evaluated whether Traditional Chinese Medicine (TCM) syndrome features add predictive information beyond conventional preoperative variables and examined the association between the triglyceride-glucose (TyG) index and postoperative DVT. Methods: This retrospective single-center study included 380 patients. Group-constrained partitioning and resampling prevented identical prespecified multivariable profiles from crossing evaluation boundaries, yielding a development set ( Results: Postoperative DVT occurred in 105 patients (27.6%). RF achieved a pooled group-aware development out-of-fold AUC of 0.774 (95% CI 0.710-0.837) and a held-out validation AUC of 0.859 (95% CI 0.782-0.935). Across 30 repeated group-constrained partitions, mean validation AUC was 0.792. In the single profile-disjoint held-out validation partition, the development-derived threshold of 0.298 yielded sensitivity of 0.903, specificity of 0.720, positive predictive value of 0.549, and negative predictive value of 0.952; in that same partition, the calibration slope was 1.136 (95% CI 0.753-1.867), the observed-to-expected ratio was 0.846, and the Brier score was 0.132. Adding QSBS and QDBS did not materially improve discrimination (AUC 0.855 vs. 0.859; ΔAUC = 0.003; DeLong Conclusion: RF showed favorable discrimination in the held-out cohort but more modest performance across repeated group-constrained partitions. The two retained TCM syndrome variables did not provide a material increment in AUC, whereas higher TyG remained associated with postoperative DVT after multivariable adjustment. External validation and assessment of recalibration are required before clinical implementation.
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