Enhanced control of periodontitis by an artificial intelligence-enabled multimodal-sensing toothbrush and targeted mHealth micromessages: A randomized trial

Abstract

Aim: Treatment of periodontitis, a chronic inflammatory disease driven by biofilm dysbiosis, remains challenging due to patients' poor performance and adherence to the necessary oral hygiene procedures. Novel, artificial intelligence-enabled multimodal-sensing toothbrushes (AI-MST) can guide patients' oral hygiene practices in real-time and transmit valuable data to clinicians, thus enabling effective remote monitoring and guidance. The aim of this trial was to assess the effect of such a system as an adjunct to clinical practice guideline-conform treatment. Materials and Methods: This was a single-centre, double-blind, standard-of-care controlled, randomized, parallel-group, superiority trial. Male and female adults with generalized Stage II/III periodontitis were recruited at the Shanghai Ninth People's Hospital, China. Subjects received a standard-of-care oral hygiene regimen or a technology-enabled, theory-based digital intervention consisting of an AI-MST and targeted doctor's guidance by remote micromessaging. Additionally, both groups received guideline-conform periodontal treatment. The primary outcome was the resolution of inflamed periodontal pockets (≥4 mm with bleeding on probing) at 6 months. The intention-to-treat (ITT) analysis included all subjects who received the allocated treatment and at least one follow-up. Results: One hundred patients were randomized and treated (50 tests/controls) between 1 February and 30 November 2022. Forty-eight tests (19 females) and 47 controls (16 females) were analysed in the ITT population. At 6 months, the proportion of inflamed periodontal pockets decreased from 80.7% (95% confidence interval [CI] 76.5–84.8) to 52.3% (47.7–57.0) in the control group, and from 81.4% (77.1–85.6) to 44.4% (39.9–48.9) in the test group. The inter-group difference was 7.9% (1.6–14.6, p