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1.
J Dent Res ; 99(7): 787-796, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32311276

RESUMO

Despite development of new technologies for caries control, tooth decay in primary teeth remains a major global health problem. Caries risk assessment (CRA) models for toddlers and preschoolers are rare. Among them, almost all models use dental factors (e.g., past caries experience) to predict future caries risk, with limited clinical/community applicability owing to relatively uncommon dental visits compared to frequent medical visits during the first year of life. The objective of this study was to construct and evaluate risk prediction models using information easily accessible to medical practitioners to forecast caries at 2 and 3 y of age. Data were obtained from the Growing Up in Singapore Towards Healthy Outcomes (GUSTO) mother-offspring cohort. Caries was diagnosed using modified International Caries Detection and Assessment System criteria. Risk prediction models were constructed using multivariable logistic regression coupled with receiver operating characteristic analyses. Imputation was performed using multiple imputation by chained equations to assess effect of missing data. Caries rates at ages 2 y (n = 535) and 3 y (n = 721) were 17.8% and 42.9%, respectively. Risk prediction models predicting overall caries risk at 2 and 3 y demonstrated area under the curve (AUC) (95% confidence interval) of 0.81 (0.75-0.87) and 0.79 (0.74-0.84), respectively, while those predicting moderate to extensive lesions showed 0.91 (0.85-0.97) and 0.79 (0.73-0.85), respectively. Postimputation results showed reduced AUC of 0.75 (0.74-0.81) and 0.71 (0.67-0.75) at years 2 and 3, respectively, for overall caries risk, while AUC was 0.84 (0.76-0.92) and 0.75 (0.70-0.80), respectively, for moderate to extensive caries. Addition of anterior caries significantly increased AUC in all year 3 models with or without imputation (all P < 0.05). Significant predictors/protectors were identified, including ethnicity, prenatal tobacco smoke exposure, history of allergies before 12 mo, history of chronic maternal illness, maternal brushing frequency, childbearing age, and so on. Integrating oral-general health care using medical CRA models may be promising in screening caries-susceptible infants/toddlers, especially when medical professionals are trained to "lift the lip" to identify anterior caries lesions.


Assuntos
Atenção à Saúde , Cárie Dentária , Estudos de Coortes , Cárie Dentária/epidemiologia , Humanos , Modelos Logísticos , Fatores de Risco , Dente Decíduo
2.
J Oral Rehabil ; 29(7): 682-8, 2002 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-12153459

RESUMO

This study investigated the mechanical properties (hardness, compressive and diametral tensile strength) of two restorative reinforced glass-ionomer cements (GC Fuji IX GP and Miracle Mix). The mechanical properties of the two cements were compared after 1 day, 1 week and 1 month storage in distilled water at 37 degrees C. Hardness testing (VHN) was carried out with a digital microhardness tester (load = 50 g, dwell time = 30 s) and compressive/diametral tensile strength testing (MPa) was conducted based upon British Standard Specification for Glass-Ionomer Cements (BS 6039: 1981). Results were analysed using analysis of variance (ANOVA)/Scheffe's test and independent samples t-test (P < 0.05). Mechanical properties generally increased with time for both cements. Hardness at 1 day was significantly lower than that at 1 week and 1 month. No significance difference in compressive and diametral tensile strengths was observed between the different time intervals. After 1 month storage in water, no significant difference in hardness and compressive strength was observed between Fuji IX and Miracle. The diametral tensile strength of Fuji IX was, however, significantly greater than that of Miracle Mix at all time intervals. Fuji IX GP may serve as a potential substitute for Miracle Mix.


Assuntos
Cimentos de Ionômeros de Vidro/química , Análise de Variância , Força Compressiva , Ligas Dentárias/química , Dureza , Humanos , Teste de Materiais , Prata/química , Estatística como Assunto , Estresse Mecânico , Temperatura , Resistência à Tração , Fatores de Tempo , Água/química
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