DOI:

10.37988/1811-153X_2023_4_6

Caries prediction is a modern direction of development of pediatric preventive dentistry

Authors

  • G.I. Skripkina 1, PhD in Medical Sciences, associate professor and head of the Pediatric dentistry Department
    ORCID ID: 0000-0001-7783-6111
  • E.V. Ekimov 1, PhD in Medical Sciences, associate professor of the Pediatric dentistry Department
    ORCID ID: 0000-0003-4713-2281
  • O.V. Matskieva 1, PhD in Medical Sciences, associate professor of the Pediatric dentistry Department
    ORCID ID: 0000-0001-6737-7564
  • A.Zh. Garifullina 1, PhD in Medical Sciences, associate professor of the Pediatric dentistry Department
    ORCID ID: 0000-0003-2595-5893
  • T.S. Mityaeva 2, pediatric dentist, chief doctor
    ORCID ID: 0000-0003-1792-8086
  • 1 Omsk State Medical University, 644099, Omsk, Russia
  • 2 Professor's Author's Dental Clinic and Co LLC, 119019, Moscow, Russia

Abstract

Modern medicine has accumulated a huge amount of knowledge about the etiology and pathogenesis of the development of many diseases, so the medicine of the present and the future should have a pronounced preventive character. The aim of the study was to determine the most effective integrated approach in predicting dental caries in children at the prenosological stage of the disease development.
Materials and methods.
As a result of the examination, 4 clinical groups (111 people) of caries-resistant children were formed: 5—6 years old, 12 years old, 15 years old, 7—12 years old. A separate group of caries-resistant children with a removable bite (7—12 years old) was identified for a more in-depth study of metabolic processes in the oral cavity during the mineralization of the enamel of the teeth of permanent bite. The clinical part of the study included: anamnesis collection, examination of the oral cavity, determination of indices of the intensity of the carious process; PMA index; Green-Vermillion hygiene index; TER-test, COSRE-test. The laboratory part of the study included the determination of the following parameters of oral fluid: total calcium, phosphorus; active potassium and sodium; viscosity and saliva secretion rate; saliva pH; demineralizing activity and utilization capacity of the oral fluid sediment; specific electrical conductivity, type of microcrystallization of saliva and the mass of the oral fluid sediment; solubility product, the active concentration of calcium and phosphorus ions were calculated.
Results.
Using factor and cluster analysis, it was possible to systematize the obtained correlations between clinical and laboratory parameters in different age groups of children. Age-related factors have been identified that lead to disruption of homeostasis in the oral cavity during various periods of development of the child’s body. The data obtained made it possible to create mathematical models and computer programs for prenosological prediction of the carious process in children of preschool and school age, taking into account all clinical and laboratory parameters of oral cavity homeostasis.
Conclusion.
Preclinical prediction of the risk of developing dental caries in childhood is possible provided knowledge of clinical and laboratory indicators of the age norm. For each age there is a certain set of prognostically significant parameters of metabolic processes in the oral cavity of the child. Preclinical diagnosis of dental caries in children should be based only on prognostic parameters, which increases the prognostic significance of the expected result.

Key words:

prediction of dental caries, children, preventive dentistry

For Citation

[1]
Skripkina G.I., Ekimov E.V., Matskieva O.V., Garifullina A.Zh., Mityaeva T.S. Caries prediction is a modern direction of development of pediatric preventive dentistry. Clinical Dentistry (Russia).  2024; 26 (4): 6—11. DOI: 10.37988/1811-153X_2023_4_6

References

  1. Danilova M.A., Ishmurzin P.V. Prediction of developing temporomandibular joint dysfunction in patients with maxillary dental anomalies. Perm Medical Journal. 2021; 3: 41—47 (In Russian). eLIBRARY ID: 46192176
  2. Ioshchenko E.S. Prediction and individual prevention of dental caries in children: master's thesis. Ekaterinburg, 2010. 22 p. (In Russian). eLIBRARY ID: 19325441
  3. Skrypkina G.I., Mitiaeva T.S., Khvostova K.S. Prenosological problem diagnosis and prognosis of dental caries in children (review). Ural Medical Journal. 2013; 5 (110): 14—21 (In Russian). eLIBRARY ID: 21056955
  4. Terekhova T.N., Chernyavskaya N.D., Naumovich D.N. Physico-chemical properties of the oral fluid of children belonging to different health groups. In: proceedings of the «Actual problems of biochemistry» conference. Grodno, 2019. Pp. 295—298 (In Russian). eLIBRARY ID: 39170057
  5. Skripkina G.I. Prenosological diagnosis and prediction of carious process in children (clinical and laboratory research, mathematical modeling): dissertation abstract. Omsk: Omsk State Medical University, 2012. 33 p. (In Russian). eLIBRARY ID: 30373499
  6. Pitaeva A.N., Korshunov A.P., Suntsov V.G. Physico-chemical methods for studying mixed saliva in clinical and experimental dentistry. Omsk: Omsk State Medical University, 2001. 71 p. (In Russian).
  7. Puzikova O.Yu., Korshunov A.P., Suntsov V.G. Clinical aspects of mathematical modeling of pre-diagnosis of dental caries: a guide for teachers and doctors. Omsk, 2005. 163 p. (In Russian).
  8. Khalafyan A.A., Temerdashev Z.A., Yakuba Yu.F., Guguchkina T.I. The use of multivariate analysis for the final evaluation of the results of expert assessments. Industrial laboratory. Diagnostics of material. 2016; 10: 71—77 (In Russian). eLIBRARY ID: 27187591
  9. Spriestersbach A., Röhrig B., du Prel J.B., Gerhold-Ay A., Blettner M. Descriptive statistics: the specification of statistical measures and their presentation in tables and graphs. Part 7 of a series on evaluation of scientific publications. Dtsch Arztebl Int. 2009; 106 (36): 578—83. PMID: 19890414
  10. Januszyk M., Gurtner G.C. Statistics in medicine. Plast Reconstr Surg. 2011; 127 (1): 437—444. PMID: 21200241
  11. Overholser B.R., Sowinski K.M. Biostatistics primer: part I. Nutr Clin Pract. 2007; 22 (6): 629—35. PMID: 18042950

Received

June 20, 2023

Accepted

November 10, 2023

Published on

January 16, 2024