Aim: To assess the beneficial and adverse effects on the dental and periodontal issues of periodontal–orthodontic treatment of teeth with pathological tooth flaring, drifting, and elongation in patients with severe periodontitis.Materials and methods: Nine databases were searched in April 2020 for randomized/non‐randomized clinical studies. After duplicate study selection, data extraction, and risk‐of‐bias assessment, random‐effect meta‐analyses of mean differences (MDs) and their 95% confidence intervals (CIs) were performed, followed by subgroup/meta‐regression analyses.Results: A total of 30 randomized and non‐randomized clinical studies including 914 patients (29.7% male; mean age 43.4 years) were identified. Orthodontic treatment of pathologically migrated teeth was associated with clinical attachment gain (−0.24 mm; seven studies), pocket probing depth reduction (−0.23 mm; seven studies), marginal bone gain (−0.36 mm; seven studies), and papilla height gain (−1.42 mm; two studies) without considerable adverse effects, while patient sex, gingival phenotype, baseline disease severity, interval between periodontal and orthodontic treatment, and orthodontic treatment duration affected the results. Greater marginal bone level gains were seen by additional circumferential fiberotomy (two studies; MD = –0.98 mm; 95% CI = –1.87 to −0.10 mm; p = .03), but the quality of evidence was low.Conclusions: Limited evidence of poor quality indicates that orthodontic treatment might be associated with small improvements of periodontal parameters, which do not seem to affect prognosis, but more research is needed.

Background: The accuracy of artificial intelligence (AI) in treatment planning and outcome prediction in orthognathic treatment (OGT) has not been systematically reviewed. Objectives: To determine the accuracy of AI in treatment planning and soft tissue outcome prediction in OGT. Design: Systematic review. Data sources: Unrestricted search of indexed databases and reference lists of included studies. Data selection: Clinical studies that addressed the focused question ‘Is AI useful for treatment planning and soft tissue outcome prediction in OGT?’ were included. Data extraction: Study screening, selection and data extraction were performed independently by two authors. The risk of bias (RoB) was assessed using the Cochrane Collaboration’s RoB and ROBINS-I tools for randomised and non-randomised clinical studies, respectively. Data synthesis: Eight clinical studies (seven retrospective cohort studies and one randomised controlled study) were included. Four studies assessed the role of AI for treatment decision making; and four studies assessed the accuracy of AI in soft tissue outcome prediction after OGT. In four studies, the level of agreement between AI and non-AI decision making was found to be clinically acceptable (at least 90%). In four studies, it was shown that AI can be used for soft tissue outcome prediction after OGT; however, predictions were not clinically acceptable for the lip and chin areas. All studies had a low to moderate RoB. Limitations: Due to high methodological inconsistencies among the included studies, it was not possible to conduct a meta-analysis and reporting biases assessment. Conclusion: AI can be a useful aid to traditional treatment planning by facilitating clinical treatment decision making and providing a visualisation tool for soft tissue outcome prediction in OGT. Registration: PROSPERO CRD42022366864.