Background: Metallic orthopedic implants face persistent clinical challenges that have proved resistant to incremental conventional development. Machine learning and artificial intelligence offer a complementary paradigm for navigating the high-dimensional design spaces governing implant performance, yet the literature remains fragmented across disciplinary silos with no comprehensive synthesis spanning the full development pipeline. Methods: A structured database search of PubMed/MEDLINE, Embase, and Cochrane (executed May 2026), supplemented by hand-searching of reference lists, identified 33 primary studies organized across five sequential domains: alloy composition discovery, additive manufacturing process–property optimization, lattice and porous structure design, surface engineering and coatings, and corrosion and wear prediction. Results: Across all five domains, machine learning approaches, including random forests, convolutional neural networks, Bayesian optimization, generative adversarial networks, physics-informed neural networks, and autonomous multi-agent platforms, have accelerated property prediction and design space exploration beyond experimental or simulation-based methods. Shared barriers to translation include small, heterogeneous datasets, reliance on internal rather than external validation, limited interpretability, and the absence of regulatory frameworks for AI-assisted device design. Representative performance included modulus predictions within ~4 GPa of first-principles values, ML-designed alloys reaching ~42.7 GPa (versus 103–120 GPa for Ti-6Al-4V), property prediction R² often above 0.90 (up to 0.96–0.9991), 98.3% corrosion severity classification accuracy, and acceleration from a roughly fivefold reduction in finite element simulations to surrogates compressing days into minutes. Conclusions: Addressing these limitations will require open standardized databases linking materials parameters to registry-level clinical outcomes, prospective clinical validation studies, and coordinated engagement between researchers, industry, and regulatory agencies.

Background: Non-tobacco nicotine (NTN) products including e-cigarettes, nicotine pouches, and synthetic nicotine devices have become increasingly popular. Although the adverse effects of tobacco-derived nicotine on other surgical outcomes are well established, the impact of NTN use on orthopaedic procedures such as total ankle arthroplasty (TAA) remains unclear. Given nicotine’s known effects on vascularity and wound repair, understanding NTN-related perioperative risks is clinically important. Methods: A retrospective cohort study was conducted using the TriNetX Research Network. Adults (≥18 years) who underwent primary TAA between January 1, 2004, and December 31, 2024, were identified. Two matched cohorts were constructed: NTN-dependent users and non–nicotine-dependent controls. Outcomes were assessed at 6 months and 1 year included surgical site complications, implant/prosthesis complications, health care use, and nicotine-specific healing outcomes. Implant/prosthesis complications and health care use were also examined at 3 years and 5 years. Results: After matching, 401 patients were included in each cohort (mean age 58.2 years; 34.7% female). At 6 months and 1 year, surgical site complications were significantly higher among NTN users (6 months: P = .017, OR 1.909, 95% CI 1.113-3.275; 1 year: P = .039, OR 1.662, 95% CI 1.021-2.705). With the numbers available, no significant differences were observed for implant/prosthesis complications, health care use, or nicotine-specific healing outcomes at any time point. At 3 years and 5 years, implant and health care-related outcomes were not significantly different between groups. Conclusion: NTN use is primarily associated with early wound-healing complications, specifically surgical site issues, whereas no significant difference was detected for implant-related outcomes. Consequently, including NTN products in routine preoperative screening could facilitate risk stratification and inform patient counseling.