18 research outputs found

    Caries risk assessment in school children using a reduced Cariogram model without saliva tests

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    <p>Abstract</p> <p>Background</p> <p>To investigate the caries predictive ability of a reduced Cariogram model without salivary tests in schoolchildren.</p> <p>Methods</p> <p>The study group consisted of 392 school children, 10-11 years of age, who volunteered after informed consent. A caries risk assessment was made at baseline with aid of the computer-based Cariogram model and expressed as "the chance of avoiding caries" and the children were divided into five risk groups. The caries increment (ΔDMFS) was extracted from the dental records and bitewing radiographs after 2 years. The reduced Cariogram was processed by omitting the variables "salivary mutans streptococci", "secretion rate" and "buffer capacity" one by one and finally all three. Differences between the total and reduced models were expressed as area under the ROC-curve.</p> <p>Results</p> <p>The baseline caries prevalence in the study population was 40% (mean DMFS 0.87 ± 1.35) and the mean 2-year caries increment was 0.51 ± 1.06. Both Cariogram models displayed a statistically relationship with caries development (p < 0.05); more caries was found among those assessed with high risk compared to those with low risk. The combined sensitivity and specificity decreased after exclusion of the salivary tests and a statistically significant reduction of the area under the ROC-curve was displayed compared with the total Cariogram (p < 0.05). Among the salivary variables, omission of the mutans streptococci enumeration impaired the predictive ability the most.</p> <p>Conclusions</p> <p>The accuracy of caries prediction in school children was significantly impaired when the Cariogram model was applied without enumeration of salivary tests.</p

    Improved ability of biological and previous caries multimarkers to predict caries disease as revealed by multivariate PLS modelling

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    <p>Abstract</p> <p>Background</p> <p>Dental caries is a chronic disease with plaque bacteria, diet and saliva modifying disease activity. Here we have used the PLS method to evaluate a multiplicity of such biological variables (n = 88) for ability to predict caries in a cross-sectional (baseline caries) and prospective (2-year caries development) setting.</p> <p>Methods</p> <p>Multivariate PLS modelling was used to associate the many biological variables with caries recorded in thirty 14-year-old children by measuring the numbers of incipient and manifest caries lesions at all surfaces.</p> <p>Results</p> <p>A wide but shallow gliding scale of one fifth caries promoting or protecting, and four fifths non-influential, variables occurred. The influential markers behaved in the order of plaque bacteria > diet > saliva, with previously known plaque bacteria/diet markers and a set of new protective diet markers. A differential variable patterning appeared for new versus progressing lesions. The influential biological multimarkers (n = 18) predicted baseline caries better (ROC area 0.96) than five markers (0.92) and a single lactobacilli marker (0.7) with sensitivity/specificity of 1.87, 1.78 and 1.13 at 1/3 of the subjects diagnosed sick, respectively. Moreover, biological multimarkers (n = 18) explained 2-year caries increment slightly better than reported before but predicted it poorly (ROC area 0.76). By contrast, multimarkers based on previous caries predicted alone (ROC area 0.88), or together with biological multimarkers (0.94), increment well with a sensitivity/specificity of 1.74 at 1/3 of the subjects diagnosed sick.</p> <p>Conclusion</p> <p>Multimarkers behave better than single-to-five markers but future multimarker strategies will require systematic searches for improved saliva and plaque bacteria markers.</p

    Risk, riskbedömning och prevention

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    Biologiska markörer som baserar sig pÄ egenskaper och aktivitet hos bakterier i dentala biofilmer skulle kunna anvÀndas för att identifiera patienter med hög risk för karies och parodontit. Genom att studera hur tandlÀkare gör riskbedömningar och tar beslut om ÄtgÀrder kan man fÄ ett bra underlag för att förbÀttra praxis
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