Medical decision support system for diagnosing connective tissue dysplasia in children

Background. The difficulty in diagnosing of hereditary connective tissue diseases (HDCTD) in children lies in the variability of signs of individual nosologic forms and lack of experience of physicians due to the low frequency of occurrence of these pathological conditions. Incorrect and untimely diagnosis often leads to negative consequences for the patient, including disability and death. Many pediatricians need consultative support from more experienced colleagues when diagnosing rare diseases.
The aim of this work is to create a system to support medical decision-making in the diagnosis of connective tissue dysplasia in children and its implementation in the form of a web application.
Materials and methods. The article presents the development of a medical decision support system that allows the average specialist to apply in his practice the experience accumulated by experts in the diagnosis of connective tissue dysplasia. The knowledge system was based on international criteria for the diagnosis of Marfan and Ehlers-Danlos syndromes. The database includes multidimensional information about the diseases in question, such as photographs of clinical manifestations and radiographs, which are intended to provide information support to the physician when entering patient data.
Results. With the help of experts, a database of product rules was formed, as well as a list of informative features for diagnosing the above syndromes, and heuristic algorithms for testing diagnostic hypotheses based on the analysis of the knowledge base were proposed. A web application was developed to perform differential diagnosis of Marfan syndrome and Ehlers-Danlo syndrome, including 13 types of this syndrome, and the system was validated on an array of 152 patients. Conclusion. The system developed by the authors helps to identify symptoms during patient examination, assess the degree of phenotypic manifestations, form diagnostic hypotheses, and justify the need for additional studies to confirm the diagnosis

1. Clinical Recommendations of the Russian Scientific Medical Society of Therapists on Diagnostics, Treatment and Rehabilitation of Patients with Connective Tissue Dysplasias. URL: https://www.elibrary.ru/item.asp?id=35040370 (accessed 02.02.2024). (In Russ.)

2. POSSUMweb: Pictures Of Standard Syndromes and Undiagnosed Malformations. URL: https://www.possum.net.au/. (accessed 02.02.2024).

3. London Dysmorphology Database (LDDB). URL: https://www.face2gene.com/lmd-history/. (accessed 02.02.2024).

4. Ayme S, Caraboenf M, Gouvernet J. GENDIAG: A computer assisted syndrome identification system. Clinical Genetics. 1985; 28(5): 410–411.

5. Faviez C, Chen X, Garcelon N, et al. Diagnosis support systems for rare diseases: a scoping review. Orphanet J Rare Dis. 2020; 15: 94. doi: 10.1186/s13023-020-01374-z.

6. Phenomizer. URL: https://compbio.charite.de/phenomizer/ (accessed 02.02.2024).

7. Köhler, et al. The Human Phenotype Ontology in 2017. Nucleic Acids Research. 2017; 45(D1): D865–D876. doi: 10.1093/nar/gkw1039.

8. Rudoj AS, Pashkevich PP, Knyazev IN, Gorustovich AG. Avtomatizirovannaya informacionnaya sistema diagnostiki sindroma Marfana. Voprosy organizacii i informatizacii zdravoohraneniya. 2012; S: 276-278. (In Russ.)

9. Brennan P. Revised diagnostic criteria for Marfan syndrome. L J Med Genet. 2010; 47: 476-485. doi: 10.4997/jrcpe.2011.309.

10. Gribova VV, Kleshchev AS, Moskalenko FM, et al. Oblachnaya platforma IACPAAS dlya razrabotki obolochek intellektual'nykh servisov: sostoyanie i per-spektivy razvitiya. Pro-grammnye produkty i sistemy. 2018; 31(3): 527-536. (In Russ.) doi: 10.15827/0236-235X.123.527-536.

11. Blagosklonov NA, Kobrinskij BA. Razrabotka osnovannoj na znaniyah sistemy diagnostiki orfannyh zabolevanij. Vrach i informacionnye tekhnologii. 2019; 4: 72-78. (In Russ.)

12. Obzor Rossijskih sistem podderzhki prinyatiya vrachebnyh reshenij. URL: https://webiomed.ru/blog/obzor-rossiiskikh-sistem-podderzhki-priniatiia-vrachebnykh-reshenii/. (accessed 02.02.2024). (In Russ.)

13. Rebrova O YU. ZHiznennyj cikl sistem podderzhki prinyatiya vrachebnyh reshenij kak medicinskih tekhnologij. Vrach i informacionnye tekhnologii. 2020; 1: 27-37. (In Russ.)

14. Penpattharakul W, Pithukpakorn M. Revised Ghent Criteria is Comparable to Original Diagnostic Criteria for Marfan Syndrome with Increased Ability to Clinically Diagnose Related Disorders. J Med Assoc Thai. 2016; 99(1): 34-39.

15. Malfait F, et al. The 2017 international classification of the Ehlers-Danlos syndromes. Am. J. Med. Genet. C. Semin. Med. Genet. 2017; 175(1): 8-26.

16. Putintsev A.N., Nikolsky D.A. System of Information Support for Medical Decision Making on the Diagnosis of Connective Tissue Dysplasia in Children. Certificate of registration of a computer program of Rospatent 2024664745. 24.06.2024 (In Russ.)

17. Putintsev AN, Voinova VYu, Shkolnikova MA, et al. Informacionno-analiticheskaya platforma "Cifrovoj fenotip" dlya vyyavleniya vzaimosvyazi fenotipicheskih i geneticheskih dannyh pacientov s nasledstvennymi zabolevaniyami Rossijskij vestnik perinatologii i pediatrii. 2023; 68(3): 92-98. (In Russ.) doi: 10.21508/1027-4065-2023-68-3-92-98.