Randomized controlled trial comparing AI-assisted digital and conventional orthodontics: Superior PAR reduction and occlusal outcomes

Xie Xiaoting, Nurul Azira Ismail, Mohammed Abdelfatah Alhoot, Liu Ying, Rabab Alayham Abbas Helmi, Qing Song and Li Ruiting

PLOS ONE, 2026, vol. 21, issue 5, 1-18

Abstract: 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

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0347499

DOI: 10.1371/journal.pone.0347499

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