RESUMO
SIGNIFICANCE: FT-IR is an important and emerging tool, providing information related to the biochemical composition of biofluids. It is important to demonstrate that there is an efficacy in separating healthy and diseased groups, helping to establish FT-IR uses as fast screening tool. AIM: Via saliva diagnosis evaluate the accuracy of FT-IR associate with machine learning model for classification among healthy (control group), diabetic (D) and periodontitis (P) patients and the association of both diseases (DP). APPROACH: Eighty patients diagnosed with diabetes and periodontitis through conventional methods were recruited and allocated in one of the four groups. Saliva samples were collected from participants of each group (n = 20) and were processed using Bruker Alpha II spectrometer in a FT-IR spectral fingerprint region between 600 and-1800 cm-1, followed by data preprocessing and analysis using machine learning tools. RESULTS: Various FTI-R peaks were detectable and attributed to specific vibrational modes, which were classified based on confusion matrices showed in paired groups. The highest true positive rates (TPR) appeared between groups C vs D (93.5 % ± 2.7 %), groups C vs. DP (89.2 % ± 4.1 %), and groups D and P (90.4 % ± 3.2 %). However, P vs DP presented higher TPR for DP (84.1 % ±3.1 %) while D vs. DP the highest rate for DP was 81.7 % ± 4.3 %. Analyzing all groups together, the TPR decreased. CONCLUSION: The system used is portable and robust and can be widely used in clinical environments and hospitals as a new diagnostic technique. Studies in our groups are being conducted to solidify and expand data analysis methods with friendly language for healthcare professionals. It was possible to classify healthy patients in a range of 78-93 % of accuracy. Range over 80 % of accuracy between periodontitis and diabetes were observed. A general classification model with lower TPR instead of a pairwise classification would only have advantages in scenarios where no prior patient information is available regarding diabetes and periodontitis status.
Assuntos
Periodontite , Saliva , Humanos , Periodontite/diagnóstico , Feminino , Masculino , Saliva/química , Pessoa de Meia-Idade , Adulto , Espectroscopia de Infravermelho com Transformada de Fourier/métodos , Diabetes Mellitus/diagnóstico , Aprendizado de Máquina , Estudos de Casos e ControlesRESUMO
This review aimed to assess the impact of dietary omega-3 fatty acids as an adjunct to non-surgical periodontal treatment when compared with periodontal treatment alone on periodontal clinical parameters of periodontitis patients. We included only randomized clinical trials (RCTs) with at least 3-months follow-up of non-surgical periodontal therapy, in combination with dietary omega-3 fatty acids. The MEDLINE, EMBASE, and LILACS databases were searched for articles published up to October 2021. Random-effects meta-analyses were conducted to determine the change in clinical attachment level (CAL), probing pocket depth (PPD), bleeding on probing (BOP), and gingival index (GI) after therapy. Of the eight hundred eighty-four potentially relevant papers retrieved from the electronic databases, 10 RCTs were selected for qualitative analysis, and of these, 8 RCTs were included in meta-analysis. RCTs showed a significant PPD reduction/CAL gain associated with the use of omega-3 fatty acids. The pooled estimates revealed significant overall PPD reduction of 0.42 mm (95% CI 0.15, 0.68) and CAL gain 0.58 mm (95% CI 0.24, 0.92). In individuals with periodontitis, the use of omega-3 fatty acid dietary supplementation as an adjunct to non-surgical periodontal treatment can provide additional benefits in CAL gain and PPD reduction, compared with non-surgical periodontal treatment alone.