MATERIALS AND METHODS: An electronic search was carried out using databases such as PubMed, Scopus, and the Web of Science Core Collection. Two reviewers searched the databases separately and concurrently. The initial search was conducted on 6 July 2021. The publishing period was unrestricted; however, the search was limited to articles involving human participants and published in English. Combinations of Medical Subject Headings (MeSH) phrases and free text terms were used as search keywords in each database. The following data was taken from the methods and results sections of the selected papers: The amount of AI training datasets utilized to train the intelligent system, as well as their conditional properties; Unilateral CLP, Bilateral CLP, Unilateral Cleft lip and alveolus, Unilateral cleft lip, Hypernasality, Dental characteristics, and sagittal jaw relationship in children with CLP are among the problems studied.
RESULTS: Based on the predefined search strings with accompanying database keywords, a total of 44 articles were found in Scopus, PubMed, and Web of Science search results. After reading the full articles, 12 papers were included for systematic analysis.
CONCLUSIONS: Artificial intelligence provides an advanced technology that can be employed in AI-enabled computerized programming software for accurate landmark detection, rapid digital cephalometric analysis, clinical decision-making, and treatment prediction. In children with corrected unilateral cleft lip and palate, ML can help detect cephalometric predictors of future need for orthognathic surgery.
STUDY DESIGN: The study is a systematic review regarding the evaluation of the existing questionnaire and a cohort study regarding the validation of our new MSGS questionnaire.
MATERIALS AND METHODS: A Multidisciplinary Salivary Gland Society (MSGS) questionnaire consisting of 20 questions and two scoring systems was developed to quantify symptoms of dry mouth and sialadenitis. Validation of the questionnaire was carried out on 199 patients with salivary pathologies (digestive, nasal, or age-related xerostomia, post radiation therapy, post radioiodine therapy, Sjögren's syndrome, IgG4 disease, recurrent juvenile parotitis, stones, and strictures) and a control group of 66 healthy volunteers. The coherence of the questionnaire's items, its reliability to distinguish patients from healthy volunteers, its comparison with unstimulated sialometry, and the time to fill both versions were assessed.
RESULTS: The novel MSGS questionnaire showed good internal coherence of the items, indicating its pertinence: the scale reliability coefficients amounted to a Cronbach's alpha of 0.92 for Q10 and 0.90 for Q3. The time to complete Q3 and Q10 amounted, respectively, to 5.23 min (±2.3 min) and 5.65 min (±2.64 min) for patients and to 3.94 min (±3.94 min) and 3.75 min (±2.11 min) for healthy volunteers. The difference between Q3 and Q10 was not significant.
CONCLUSION: We present a novel self-administered questionnaire quantifying xerostomia and non-tumoral salivary gland pathologies. We recommend the use of the Q10 version, as its scale type is well known in the literature and it translation for international use will be more accurate. Laryngoscope, 132:322-331, 2022.