Risk assessment models to predict caries recurrence after oral rehabilitation under general anaesthesia: a pilot study. (8th May 2018)

• Record Type: Journal Article
• Authors: Lin, Yai‐Tin; Kalhan, Ashish Chetan; Lin, Yng‐Tzer Joseph; Kalhan, Tosha Ashish; Chou, Chein‐Chin; Gao, Xiao Li; Hsu, Chin‐Ying Stephen
• Is Part Of: International dental journal. Volume 68:Number 6(2018)
• Page Start: 378
• Page End: 385
• Publication Date: 2018-05-08
• Subjects: Caries risk assessment -- caries recurrence -- general anaesthesia; Dentistry -- Periodicals; Dentistry -- Periodicals; 617.6005
• DOI: 10.1111/idj.12396
• Languages: English
• ISSNs: 0020-6539

Abstract

Abstract : Objectives: Oral rehabilitation under general anaesthesia (GA), commonly employed to treat high caries‐risk children, has been associated with high economic and individual/family burden, besides high post‐GA caries recurrence rates. As there is no caries prediction model available for paediatric GA patients, this study was performed to build caries risk assessment/prediction models using pre‐GA data and to explore mid‐term prognostic factors for early identification of high‐risk children prone to caries relapse post‐GA oral rehabilitation. Methods: Ninety‐two children were identified and recruited with parental consent before oral rehabilitation under GA. Biopsychosocial data collection at baseline and the 6‐month follow‐up were conducted using questionnaire (Q), microbiological assessment (M) and clinical examination (C). Results: The prediction models constructed using data collected from Q, Q + M and Q + M + C demonstrated an accuracy of 72%, 78% and 82%, respectively. Furthermore, of the 83 (90.2%) patients recalled 6 months after GA intervention, recurrent caries was identified in 54.2%, together with reduced bacterial counts, lower plaque index and increased percentage of children toothbrushing for themselves (all P < 0.05). Additionally, meal‐time and toothbrushing duration were shown, through bivariate analyses, to be significant prognostic determinants for caries recurrence (both P < 0.05). Conclusions: Risk assessment/prediction models built using pre‐GA data may be promising in identifying high‐risk children prone to post‐GA caries recurrence, although future internal and external validation of predictive models is warranted.