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Randomized controlled trial comparing AI-assisted digital and conventional orthodontics: Superior PAR reduction and
Xie Xiaoting1,2,3, Nurul Azira Ismail3,4, Mohammed Abdelfatah Alhoot3,5
1School of Stomatology, North Sichuan Medical College, Nanchong, Sichuan, China.
Background:
Advances in digital orthodontics and artificial intelligence (AI) planning have the potential to enhance treatment precision, but randomized evidence based on the Peer Assessment Rating (PAR) index remains limited.
Methods:
In this single-center, parallel-group randomized controlled trial registered retrospectively in the Chinese Clinical Trial Registry (ChiCTR2500108499), 140 patients aged 12-35 years with Angle Class I malocclusion were randomized to receive an AI-assisted digital workflow (Digital and AI group) or conventional fixed appliances (Conventional group). PAR scores were assessed at baseline (T0), 6-month intervals (T1), and immediately after treatment completion (T2) by calibrated, blinded examiners following British Standards Institute criteria. Analyses followed the intention-to-treat principle, applying independent t-tests, χ²/Fisher's exact tests, repeated-measures mixed-effects models, and multivariable linear regression. Effect sizes were expressed as mean difference (MD) or relative risk (RR) with 95% confidence intervals (CI).
Results:
Baseline PAR scores did not differ significantly between groups (MD = 0.63, 95% CI: -0.13 to 1.40; p = 0.105). At T2, the Digital and AI group had lower mean PAR scores (4.88 ± 0.45) than the Conventional group (7.81 ± 0.70; MD = 2.93, 95% CI: 2.73-3.13; p < 0.001). A higher proportion of patients in the Digital and AI group achieved ≥70% PAR reduction (82.9% vs 50.0%; RR = 1.66, 95% CI: 1.27-2.17; p < 0.001). Repeated-measures mixed-effects analysis showed significant effects of intervention, time, and their interaction (all p < 0.001), indicating different improvement trajectories between groups. Multivariable regression identified allocation to the Digital and AI group, higher baseline PAR, and younger age as independent predictors of greater PAR reduction. No severe adverse events occurred, and no participants were lost to follow-up between T0 and T2.
Conclusions:
Under controlled trial conditions, the AI-assisted digital workflow produced greater short-term improvements in PAR-based occlusal outcomes than conventional fixed appliances. These findings suggest a potential benefit of integrating an AI-assisted digital system into orthodontic practice; however, conclusions are limited to short-term occlusal changes, and further multicenter studies with longer follow-up, patient-reported outcomes, and economic evaluation are warranted.
