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Related Concept Videos

Longitudinal Research02:20

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Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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Cariogram validity in schoolchildren: a two-year follow-up study.

G Campus1, M G Cagetti, S Sale

  • 1Dental Institute, University of Sassari, Sassari, Italy. gcampus@uniss.it

Caries Research
|January 7, 2012
PubMed
Summary

The Cariogram software accurately predicts caries increment in children over two years. This dental caries risk assessment model demonstrates precision, accuracy, and ease of use for predicting future dental caries.

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Area of Science:

  • Dental Public Health
  • Pediatric Dentistry
  • Epidemiology

Background:

  • Dental caries remains a significant public health issue globally.
  • Accurate caries risk assessment is crucial for effective preventive strategies.
  • The Cariogram software offers a computer-based approach to assess caries risk.

Purpose of the Study:

  • To evaluate the validity of the Cariogram software in predicting caries increment over a 2-year period.
  • To assess the performance of Cariogram in identifying children at risk for developing new carious lesions.

Main Methods:

  • A longitudinal study involving 957 Sardinian schoolchildren aged 7-9 years.
  • Caries risk assessment using Cariogram at baseline and a follow-up examination after 2 years on 861 participants.
  • Statistical analyses included Principal Component Analysis (PCA) and Receiver Operating Characteristic (ROC) analysis.

Main Results:

  • 54.4% of participants developed new carious lesions, with a mean caries increment (ΔDFS) of 0.5.
  • PCA indicated that Cariogram, gingival status, and dietary sugar frequency formed a distinct cluster.
  • ROC analysis demonstrated high performance with sensitivity of 0.83, specificity of 0.85, and an area under the curve of 0.93.

Conclusions:

  • The Cariogram software demonstrated strong validity in predicting caries increment over a 2-year period.
  • The software meets criteria for a reliable caries risk assessment model, including precision, accuracy, and ease of use.
  • Findings support the use of Cariogram in pediatric dental care for risk stratification and personalized prevention.