A Roadmap towards Precision Periodontics.
algorithms
biomarkers
diagnosis
machine learning
periodontitis
precision medicine
Journal
Medicina (Kaunas, Lithuania)
ISSN: 1648-9144
Titre abrégé: Medicina (Kaunas)
Pays: Switzerland
ID NLM: 9425208
Informations de publication
Date de publication:
03 Mar 2021
03 Mar 2021
Historique:
received:
31
01
2021
revised:
24
02
2021
accepted:
26
02
2021
entrez:
3
4
2021
pubmed:
4
4
2021
medline:
15
5
2021
Statut:
epublish
Résumé
Periodontitis is among the most common health conditions and represents a major public health issue related to increasing prevalence and seriously negative socioeconomic impacts. Periodontitis-associated low-grade systemic inflammation and its pathological interplay with systemic conditions additionally raises awareness on the necessity for highly performant strategies for the prevention and management of periodontitis. Periodontal diagnosis is the backbone of a successful periodontal strategy, since prevention and treatment plans depend on the accuracy and precision of the respective diagnostics. Periodontal diagnostics is still founded on clinical and radiological parameters that provide limited therapeutic guidance due to the multifactorial complexity of periodontal pathology, which is why biomarkers have been introduced for the first time in the new classification of periodontal and peri-implant conditions as a first step towards precision periodontics. Since the driving forces of precision medicine are represented by biomarkers and machine learning algorithms, with the lack of periodontal markers validated for diagnostic use, the implementation of a precision medicine approach in periodontology remains in the very initial stage. This narrative review elaborates the unmet diagnostic needs in periodontal diagnostics, the concept of precision periodontics, periodontal biomarkers, and a roadmap toward the implementation of a precision medicine approach in periodontal practice.
Identifiants
pubmed: 33802358
pii: medicina57030233
doi: 10.3390/medicina57030233
pmc: PMC7999128
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
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