Non-invasive assessment of periodontal inflammation by continuum-removal hemodynamic spectral indices.

BACKGROUND: Hyperspectral techniques have aroused great interest in non-invasively measuring periodontal tissue hemodynamics. However, current studies mainly focused on three typical inflammation stages (healthy, gingivitis and periodontitis) and practical approaches for using optical spectroscopy for early and precisely detection of periodontal inflammation at finer disease stages have not been well studied. METHODS: This study provided novel spectroscopic insights into periodontitis at different stages of disease, and developed six simple but physically meaning hemodynamic spectral indices (HSIs) including four spectral absorption depths of oxyhemoglobin ( D HbO 2 ), deoxyhemoglobin ( D Hb ), total hemoglobin ( t Hb ) and tissue water ( D water ), and two normalized difference indices of oxyhemoglobin( N D HbO 2 I ) and deoxyhemoglobin ( N D Hb I ) from continuum-removal spectra (400-1700 nm) of periodontal tissue collected from 47 systemically healthy subjects over different severities from healthy, gingivitis, slight, moderate to severe periodontitis for early and precision diagnostics of periodontitis. Typical statistical analyses were conducted to explore the effectiveness of the proposed HSIs. RESULTS: D Hb and t Hb exerted significant increasing trends as inflammation progressed, whereas D HbO 2 exhibited significant difference (P < 0.05) from the healthy sites only at moderate and severe periodontitis and D water presented unstable sensitives to disease severity. By contrast, N D HbO 2 I and N D Hb I showed more steadily downward trends as severity increased, and demonstrated the highest correlations with clinical gold standard parameters. Particularly, the proposed normalized HSIs ( N D HbO 2 I and N D Hb I ) yielded high correlations of - 0.49 and - 0.44 with probing depth, respectively, far outperforming results achieved by previous studies. The performances of the HSIs were also confirmed using the periodontal therapy group. CONCLUSIONS: These results indicated great potentials of combination optical spectroscopy and smart devices to non-invasively probe periodontitis at earlier stages using the simple and practical HSIs. Trial registration This study was retrospectively registered in the Chinese Clinical Trial Registry on October 24, 2021, and the clinical registration number is ChiCTR2100052306.

Anti-melanoma Differentiation-associated Gene 5 Antibody-positive Dermatomyositis Presenting as Refractory Gingivitis at the First Clinical Manifestation.

We herein report a case of melanoma differentiation-associated gene 5 (MDA5) antibody-positive dermatomyositis that developed in a patient with refractory gingivitis. The diagnosis of anti-MDA5 antibody-positive dermatomyositis was made based on a characteristic skin rash, weakness of proximal muscles, interstitial pneumonia, and positivity for anti-MDA5 antibody. The patient was started on triple therapy with high-dose prednisolone, tacrolimus, and intravenous cyclophosphamide. After treatment, the refractory gingivitis disappeared, and the other skin rash and interstitial lung disease also improved. In the diagnosis and treatment of anti-MDA5 antibody-positive dermatomyositis, it is necessary to pay attention to the intraoral findings, including the gingiva.

The evaluation of salivary leucine-rich alpha-2 glycoprotein (LRG) and C-reactive protein (CRP) in humans with periodontal health or periodontal disease.

OBJECTIVE: The purpose of the present research is to evaluate the salivary levels of leucine-rich alpha-2 glycoprotein (LRG) and C-reactive protein (CRP) in periodontal health and disease (gingivitis and stage III periodontitis) and also to compare the discriminative efficiencies of both biomarkers in periodontal disease. BACKGROUND: LRG is a new acute-phase protein whose functions are still being investigated. LRG and CRP are both biomarkers that are increased by inflammation. No clinical study has yet investigated the comparison of the level of LRG and CRP in periodontal health, gingivitis and periodontitis in saliva samples. METHODS: A total of 60 individuals, including 20 periodontally healthy (control group/group C), 20 with gingivitis (group G), and 20 with Stage III periodontitis (group P), who were systemically healthy and non-smokers, participated in this study. Periodontal charts were used for recording clinical periodontal parameters and saliva LRG and CRP levels were measured by ELISA. Analyzing the area under the curve (AUC) was performed by the receiver-operating characteristics curve. RESULTS: Salivary levels of LRG and CRP were significantly higher in disease groups than in group C (p < .05). Positive statistically significant correlations were observed between both biomarkers and clinical parameters (p < .05). There was also a strong positive correlation between two biomarkers (p < .05). In distinguishing periodontal disease from periodontal health, LRG (AUC = 0.833) and CRP (AUC = 0.826) were found to have similar accuracy (p = .923). CONCLUSION: LRG and CRP may be useful and similarly effective biomarkers in the diagnosis of periodontal diseases based on the findings of this study.

Gingival crevicular fluid levels of apelin correlates with clinical periodontal diagnosis.

OBJECTIVES: Limitations of clinical periodontal measurements have led to the search for reliable biomarkers that can be used in diagnosis and monitoring of periodontal diseases. Considering the relationship of adipokines with periodontal disease, diabetes, and obesity, apelin may be a biomarker for periodontal diseases due to its modulating effects on inflammation. The present study was conducted to determine gingival crevicular fluid (GCF) apelin levels in systemically healthy individuals and to evaluate the potential of apelin as a biomarker for periodontal diagnosis. MATERIALS AND METHODS: Ten individuals with clinically healthy periodontal tissues, 10 patients diagnosed with gingivitis, and 10 patients with periodontitis were included in the present study. Whole mouth clinical periodontal measurements were recorded and GCF samples were obtained from the buccal approximal regions of single-rooted teeth with features that would represent clinical periodontal diagnosis. Apelin level in the samples was determined by ELISA. Clinical and biochemical findings were statistically analyzed. Possible relationship between the variables was evaluated with Pearson correlation analysis. RESULTS: Apelin level in the gingivitis group was higher than that in the clinically healthy group (p = 0.000) and lower than that in the periodontitis group (p = 0.000). A positive correlation was found between GCF apelin concentration and plaque score, bleeding on probing, and probing depth (p = 0.000). CONCLUSIONS: Within the limits of this study, it can be suggested that GCF apelin concentration may be a biomarker that can distinguish between healthy periodontal tissues, gingivitis, and periodontitis patients. CLINICAL RELEVANCE: Apelin concentration in the gingival crevicular fluid may aid in the diagnosis of periodontal disease.

Comparing gingivitis diagnoses by bleeding on probing (BOP) exclusively versus BOP combined with visual signs using large electronic dental records.

The major significance of the 2018 gingivitis classification criteria is utilizing a simple, objective, and reliable clinical sign, bleeding on probing score (BOP%), to diagnose gingivitis. However, studies report variations in gingivitis diagnoses with the potential to under- or over-estimating disease occurrence. This study determined the agreement between gingivitis diagnoses generated using the 2018 criteria (BOP%) versus diagnoses using BOP% and other gingival visual assessments. We conducted a retrospective study of 28,908 patients' electronic dental records (EDR) from January-2009 to December-2014, at the Indiana University School of Dentistry. Computational and natural language processing (NLP) approaches were developed to diagnose gingivitis cases from BOP% and retrieve diagnoses from clinical notes. Subsequently, we determined the agreement between BOP%-generated diagnoses and clinician-recorded diagnoses. A thirty-four percent agreement was present between BOP%-generated diagnoses and clinician-recorded diagnoses for disease status (no gingivitis/gingivitis) and a 9% agreement for the disease extent (localized/generalized gingivitis). The computational program and NLP performed excellently with 99.5% and 98% f-1 measures, respectively. Sixty-six percent of patients diagnosed with gingivitis were reclassified as having healthy gingiva based on the 2018 diagnostic classification. The results indicate potential challenges with clinicians adopting the new diagnostic criterion as they transition to using the BOP% alone and not considering the visual signs of inflammation. Periodic training and calibration could facilitate clinicians' and researchers' adoption of the 2018 diagnostic system. The informatics approaches developed could be utilized to automate diagnostic findings from EDR charting and clinical notes.

Evaluation of perfusion parameters of gingival inflammation using laser Doppler flowmetry and tissue spectrophotometry- a prospective comparative clinical study.

BACKGROUND: The aim of this study was to determine the values of different perfusion parameters- such as oxygen saturation, the relative amount of hemoglobin, and blood flow- in healthy subjects compared to patients with gingivitis as a non-invasive measurement method. METHODS: A total of 114 subjects were enrolled in this study and separated into subjects with gingivitis (50) and without gingivitis (64) based on clinical examination. Gingival perfusion was measured at 22 points in the maxilla and mandible using laser Doppler flowmetry and tissue spectrophotometry (LDF-TS) with the "oxygen to see" device. All patients underwent measurement of gingival perfusion, followed by the clinical evaluation (measurement of probing depths, evaluation of bleeding on probing, plaque level, and biotype). Perfusion parameters were compared between the groups, associations between the non-invasive and clinical measurements were analyzed, and theoretical optimal cut-off values for predicting gingivitis were calculated with receiver operating characteristics. RESULTS: The mean oxygen saturation, mean relative amount of hemoglobin, and mean blood flow all significantly differed between the groups with and without gingivitis (p = 0.005, p < 0.001, and p < 0.001, respectively). The cut-off value for predicting gingivitis was > 40 AU (p < 0.001; sensitivity 0.90, specificity 0.67). CONCLUSIONS: As a non-invasive method, LDF-TS can help determine gingival hyperemia. Flow values above 40 AU indicate a higher risk of hyperemia, which can be associated with inflammation. The LDF-TS method can be used for the objective evaluation of perfusion parameters during routine examinations and can signal the progression of hyperperfusion before any change in clinical parameters is observed. TRIAL REGISTRATION: All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the institutional Clinical Research Ethics Committee (Ethik-Kommission der Medizinischen Fakultät der RWTH Aachen, Decision Number 286/20) and retrospectively registered by the German Clinical Trials Register (File Number DRKS00024048, registered on the 15th of October 2021).

Developing diagnostic tools for canine periodontitis: combining molecular techniques and machine learning models.

BACKGROUND: Dental plaque microbes play a key role in the development of periodontal disease. Numerous high-throughput sequencing studies have generated understanding of the bacterial species associated with both canine periodontal health and disease. Opportunities therefore exist to utilise these bacterial biomarkers to improve disease diagnosis in conscious-based veterinary oral health checks. Here, we demonstrate that molecular techniques, specifically quantitative polymerase chain reaction (qPCR) can be utilised for the detection of microbial biomarkers associated with canine periodontal health and disease. RESULTS: Over 40 qPCR assays targeting single microbial species associated with canine periodontal health, gingivitis and early periodontitis were developed and validated. These were used to quantify levels of the respective taxa in canine subgingival plaque samples collected across periodontal health (PD0), gingivitis (PD1) and early periodontitis (PD2). When qPCR outputs were compared to the corresponding high-throughput sequencing data there were strong correlations, including a periodontal health associated taxa, Capnocytophaga sp. COT-339 (rs =0.805), and two periodontal disease associated taxa, Peptostreptococcaceae XI [G-4] sp. COT-019 (rs=0.902) and Clostridiales sp. COT-028 (rs=0.802). The best performing models, from five machine learning approaches applied to the qPCR data for these taxa, estimated 85.7% sensitivity and 27.5% specificity for Capnocytophaga sp. COT-339, 74.3% sensitivity and 67.5% specificity for Peptostreptococcaceae XI [G-4] sp. COT-019, and 60.0% sensitivity and 80.0% specificity for Clostridiales sp. COT-028. CONCLUSIONS: A qPCR-based approach is an accurate, sensitive, and cost-effective method for detection of microbial biomarkers associated with periodontal health and disease. Taken together, the correlation between qPCR and high-throughput sequencing outputs, and early accuracy insights, indicate the strategy offers a prospective route to the development of diagnostic tools for canine periodontal disease.

An unusual case of linear IgA disease affecting only the oral gingiva: a case report.

BACKGROUND: We present a case report on desquamative gingivitis diagnosed as linear IgA disease (LAD), which is a rare autoimmune bullous disease exclusively affecting the oral gingiva. The oral mucosa can be impacted by various autoimmune bullous diseases, and our report focuses on this particular manifestation of LAD. CASE PRESENTATION: This patient presented with atypical symptoms, as frequent blister formation on the gingiva was the primary clinical manifestation. A combination of systemic and local treatment was administered to the patient. Following the treatment, there was a significant improvement observed in both the erythema and the bullous lesions on the gingiva. CONCLUSIONS: A more suitable local treatment strategy should be formulated for patients presenting with oral topical lesions, which clinicians can employ effectively.

Investigation of volatile sulfur compound level and halitosis in patients with gingivitis and periodontitis.

This study aimed to measure the levels of volatile sulfur compounds and investigate the occurrence of halitosis in patients with gingivitis and periodontitis. Additionally, the incidence rates of gingivitis and periodontitis in patients with halitosis were investigated. Through various statistical analyses, we attempted to determine the relationship between periodontal disease and halitosis. One-hundred-and-four participants (52 females and 52 males, mean age: 46.49 ± 16.03 years) were enrolled in this cross-sectional study, comprising 33 healthy controls, 43 patients with gingivitis, and 28 patients with periodontitis. Gas chromatography was used to measure hydrogen sulfide (H2S) and methyl mercaptan (CH3SH), which are representative VSCs. The VSC cut-off values for diagnosing halitosis were 65.79 ppb for women and 79.94 ppb for men. Total VSC level was significantly higher in the gingivitis than the healthy control group (186.72 ± 374.83 ppb vs. 19.80 ± 40.19 ppb, p = 0.035). There was no significant difference between the gingivitis and periodontitis (153.79 ± 278.51 ppb) groups. H2S level was significantly higher in the gingivitis (100.51 ± 183.69 ppb) and periodontitis (91.57 ± 132.06 ppb) groups than in healthy controls (14.97 ± 31.22 ppb), and CH3SH level was significantly higher in gingivitis group (29.31 ± 59.16 ppb) than in the healthy control (5.73 ± 14.10 ppb) (all p < 0.05). Halitosis was found in 3% of healthy controls and 39.5% and 42.9% of patients with gingivitis and periodontitis patients, respectively, making it significantly higher in the gingivitis and periodontitis groups than the healthy controls (p = 0.005). Conversely, among participants with halitosis, 53.1% had gingivitis, 37.5% had periodontitis, and 90.6 incidence had periodontal disease. Multivariate logistic regression analysis to predict the presence of halitosis, found periodontal disease was a significant predictor of halitosis (OR = 3.607, 95% CI 1.023-12.718, p = 0.046). Considering area under curve value for halitosis, the cut-off value of healthy control (H2S:61.5 ppb, CH3SH:3.5 ppb), gingivitis (H2S:50.0 ppb, CH3SH:6 ppb), and periodontitis (H2S:62.0 ppb, CH3SH:3.5 ppb) were (all p < 0.05). Our results emphasize the close and strong relationship between periodontal disease and halitosis through human clinical evidence based on the high co-occurrence rate of mutual diseases. Additionally, the presence of periodontal disease increased the probability of halitosis by 3.607 times. These results suggest that H2S can be used as a biomarker of halitosis in patients with periodontal disease.

"Plasma cell gingivitis" encompasses multiple entities: a retrospective series of 37 cases.

BACKGROUND: Plasma cell gingivitis is defined as gingival inflammation comprised of plasma cell infiltrates. This diagnostic criterion is non-specific and underlying mechanisms remain unknown. OBJECTIVES: We performed a multidisciplinary clinico-pathological review of cases previously identified as "gingivitis with plasma cell infiltrates", with assessment of putative contributing factors and critical appraisal of the final diagnosis. MATERIALS & METHODS: Cases previously identified as "gingivitis with plasma cell infiltrates" between 2000 and 2020 were included from archives from the GEMUB group, a French multidisciplinary network of physicians with expertise on oral mucosa. RESULTS: Among the 37 included cases, multidisciplinary clinico-pathological review allowed differential diagnosis in seven cases (oral lichen planus n=4, plasma cell granuloma n=1, plasmacytoma n=1, and mucous membrane pemphigoid n=1). The remaining cases were classified as "reactive plasma cell gingivitis" (induced by drugs, trauma/irritation or periodontal disease) (n=18) or "idiopathic plasma cell gingivitis" when no contributing factors were identified (n=12). Clinico-pathological characteristics did not differ significantly between "reactive" and "idiopathic" cases, preventing us from identifying specific features of "idiopathic" plasma cell gingivitis. CONCLUSION: "Plasma cell gingivitis" is a polymorphous, non-specific entity with various aetiologies, of which the diagnosis requires multidisciplinary anatomo-clinical correlation for exclusion of secondary causes of plasma cell infiltration. Although our study was limited by its retrospective design, most cases of "plasma cell gingivitis" appeared to be associated with an underlying cause. We propose a diagnostic algorithm to properly investigate such cases.

Computer-assisted periodontal classification vs manual classification among dental students: a comparative pilot study.

OBJECTIVE: The objective of the study was to assess whether computer-assisted periodontal diagnosis can improve the accuracy and homogeneity of classification results obtained by dental students using the 2017 classification of periodontal diseases. METHOD AND MATERIALS: All final year predoctoral dental students from two dental schools were invited to participate in the study. Participants who volunteered for the study were randomly divided into two groups for digital or manual diagnosis, and each participant classified 48 cases. A group of three experienced periodontists provided the reference or gold standard diagnosis. RESULTS: Overall, 27 students completed the evaluation of all cases; 14 students comprised the digital application group and 13 the manual group. The accuracy of the classification results compared with the gold standard committee was 82% for the digital group compared to 50% of the manual group in terms of the extent of gingivitis; 71% vs 56% for the stage of periodontitis; 67% vs 62% for grade of periodontitis; 76% vs 63% for extent of periodontitis; and 43% vs 30% for overall diagnosis accuracy of periodontitis cases respectively. CONCLUSIONS: Computer-assisted classification using newly developed software, within the boundaries of this study, was shown to be a sensible support tool for dental practitioners to use when diagnosing periodontal disease. This digital tool can the clinicians' accuracy of diagnosis primarily in the extent and staging of periodontitis.

Detection of tooth numbering, frenulum attachment, gingival overgrowth, and gingival inflammation signs on dental photographs using convolutional neural network algorithms: a retrospective study.

OBJECTIVES: This study aimed to develop an artificial intelligence (AI) model that can determine automatic tooth numbering, frenulum attachments, gingival overgrowth areas, and gingival inflammation signs on intraoral photographs and to evaluate the performance of this model. METHOD AND MATERIALS: A total of 654 intraoral photographs were used in the study (n = 654). All photographs were reviewed by three periodontists, and all teeth, frenulum attachment, gingival overgrowth areas, and gingival inflammation signs on photographs were labeled using the segmentation method in a web-based labeling software. In addition, tooth numbering was carried out according to the FDI system. An AI model was developed with the help of YOLOv5x architecture with labels of 16,795 teeth, 2,493 frenulum attachments, 1,211 gingival overgrowth areas, and 2,956 gingival inflammation signs. The confusion matrix system and ROC (receiver operator characteristic) analysis were used to statistically evaluate the success of the developed model. RESULTS: The sensitivity, precision, F1 score, and AUC (area under the curve) for tooth numbering were 0.990, 0.784, 0.875, and 0.989; for frenulum attachment these were 0.894, 0.775, 0.830, and 0.827; for gingival overgrowth area these were 0.757, 0.675, 0.714, and 0.774; and for gingival inflammation sign 0.737, 0.823, 0.777, and 0.802, respectively. CONCLUSION: The results of the present study show that AI systems can be successfully used to interpret intraoral photographs. These systems have the potential to accelerate the digital transformation in the clinical and academic functioning of dentistry with the automatic determination of anatomical structures and dental conditions from intraoral photographs.

Evaluation of an advanced oral hygiene regimen on maternity outcomes in a randomized multicenter clinical trial (Oral Hygiene and Maternity Outcomes Multicenter Study).

BACKGROUND: During pregnancy, dental plaque-induced gingivitis prevalence and subsequent risk of periodontal disease increases substantially, as a consequence of both inadequate oral hygiene and changes in sex steroid hormone levels. Although maternal periodontal disease has been associated with adverse pregnancy outcomes, including spontaneous preterm birth, previous clinical trials involving mechanical debridement (eg, scaling and root planing) to remove plaque biofilm have not yielded decreased rates of preterm birth. OBJECTIVE: We hypothesized that an advanced oral hygiene program, including an antibacterial regimen coupled with a power toothbrush and hygiene instruction, may improve the periodontal milieu and reduce the rate of spontaneous preterm birth. Therefore, we conducted a clinical trial of obstetrical patients with moderate-to-severe gingivitis who were randomized to an advanced oral hygiene program vs usual oral hygiene care, and the primary obstetrical outcome compared between the treatment groups was gestational age at delivery. STUDY DESIGN: Obstetrical patients with singleton pregnancies between 8 and 24 weeks' gestation were screened by trained dentists at 2 clinical sites for moderate-to-severe gingivitis (>30 intraoral sites with gingival bleeding on probing). Eligible participants were randomized to an advanced oral hygiene regimen, including antibacterial mouth wash, dental floss, antibacterial toothpaste, a power toothbrush, and intensive oral hygiene education vs standard oral home care instructions and regimen. The primary obstetrical outcome assessed was gestational age at delivery. The overall primary (dental) outcomes were gingival index, bleeding sites, and pocket depth (reported elsewhere). Secondary obstetrical outcomes included birthweight and incidence of preterm birth at <37 weeks' gestation. Regression models were utilized and included factors such as treatment group, gestational age at enrollment, preterm birth history, and potential markers of health disparities (ie, education, employment status). RESULTS: A total of 817 obstetrical patients underwent dental screening at the 2 sites, 789 were identified with moderate-to-severe gingivitis, 746 were randomized, and birth outcomes were available for 613 of the study participants. The gestational age at delivery was 2 days earlier in the control group (P=.040), but the clinical significance of this finding was limited (39.13 vs 38.85 weeks). Overall rates of spontaneous preterm birth <37 weeks and <34 weeks were not statistically different between the 2 treatment groups (7.0% advanced oral hygiene regimen vs 10.3% controls, OR=1.63 (0.90-3.00), P=.11; and 2.3% vs 3.9%, OR=1.88 (0.71-4.98), P=.20, respectively). However, we observed lower rates of spontaneous preterm birth among unemployed participants with less favorable socioeconomic status (4.7% advanced oral hygiene regimen vs 16.0% controls, OR=4.04 (1.34-15.12), P=.01). CONCLUSION: An advanced oral hygiene program may reduce the risk of spontaneous preterm birth among pregnant patients with moderate-to-severe gingivitis and health disparities. This is the same group that may be at highest risk of poor dental hygiene and preterm birth.

Plasma Cell Gingivitis: Clinical and Pathological Case Report.

INTRODUCTION: Plasma cell gingivitis (PCG) is a rare benign condition usually found on marginal and attached gingiva. This case details a generalized PCG, to include the management of the patient and clinicopathologic characteristics of the disorder. CASE PRESENTATION: The patient, a 24-year-old African American female, was referred to the periodontics clinic for severe generalized gingival erythema and edema. Past medical history review was remarkable for sickle cell anemia and systemic lupus erythematosus. The patient was initially prescribed dexamethasone oral rinse (0.5 mg/5 ml) pending biopsy and medical consult for potential causes of any hypersensitivity reaction. The patient also was instructed to discontinue her current type of oral mouthrinse and dentifrice. Biopsy results confirmed a diagnosis of PCG. Resolution of signs and symptoms started 1 month later, and approximately 2 years after initial diagnosis the patient was clinically stable. CONCLUSION: This report describes the management of a diffuse plasma cell gingivitis and reviews pertinent literature on the lesion. The etiology of PCG, although unclear, may be attributable to a hypersensitivity reaction. PCG may mimic other pathological entities, which underscores the importance of microscopic examination in establishing a definitive diagnosis before treatment initiation.

Salivary interleukin-1ß as a biomarker to differentiate between periodontal health, gingivitis, and periodontitis.

BACKGROUND: Periodontal diagnosis is based on recording clinical parameters including bleeding on probing (BOP), probing pocket depth (PPD), and clinical attachment loss (CAL). These techniques may be prone to errors due to different factors. Available biomarkers in the oral biofluid such as interleukin (IL)-1ß could provide solutions for these issues. The study aimed to determine the potential of salivary IL-1ß to differentiate periodontal health from disease and between gingivitis and periodontitis. METHODS: Patients with gingivitis (N.=25), periodontitis (N.=50), and healthy periodontium (N.=25) were recruited for this study. For each patient, whole unstimulated saliva was collected followed by recording periodontal parameters namely; Plaque Index (PI), BOP, PPD, CAL. Level of salivary IL-1ß was assayed by using enzyme-linked immunosorbent assays. Sensitivity and specificity of IL-1ß, to differentiate any given condition, was determined by Receiver operating characteristic curve and area under the curve (AUC). RESULTS: Both BOP and PI were significantly higher in association with gingivitis and periodontitis groups as compared to controls. Concentration of salivary IL-1ß in periodontal health was significantly lower than gingivitis and periodontitis groups. The biochemical analyses showed that salivary IL-1ß differentiated periodontal health from gingivitis (AUC 0.949) and periodontitis (AUC 0.852) but could not discriminate gingivitis from periodontitis (AUC 0.532). The proposed cut-off points to differentiate periodontal health from gingivitis was 103.8 pg/mL, while the value of the biomarker to differentiate periodontal health from periodontitis was 102.0 pg/mL. CONCLUSIONS: Salivary IL-1ß could be a reliable biomarker with a good level of accuracy to differentiate periodontal health from disease but not to discriminate gingivitis from periodontitis.

Salivary cortisol, dehydroepiandrosterone, and chromogranin A levels in patients with gingivitis and periodontitis and a novel biomarker for psychological stress.

Introduction: This study aimed to investigate the neuroendocrine responses based on cortisol, dehydroepiandrosterone (DHEA), cortisol/DHEA ratio, and chromogranin A levels, which reflect the activity of the hypothalamic-pituitary-adrenal axis, according to the presence or absence of psychological stress in patients with gingivitis and periodontitis compared to that in healthy controls. Methods: In total, 117 patients (60 women, mean age: 36.29 ± 19.03 years) participated in this case-control study, comprising 32 healthy controls, 49 patients with gingivitis, and 36 patients with periodontitis. We investigated the presence of psychological stress and salivary characteristics, and analyzed the stress-related biomarkers of cortisol, DHEA, cortisol/DHEA ratio, and chromogranin A in the stimulated saliva. Results: Salivary cortisol and chromogranin A levels increased with the severity of periodontal disease; their levels were the highest in the periodontitis group and were significantly higher in the following descending order: periodontitis, gingivitis, and healthy control groups (all values of p < 0.001). Additionally, the DHEA levels and cortisol/DHEA ratio were higher in the periodontitis group than those in the healthy control group (all values of p < 0.001). A multivariate logistic regression analysis revealed that the factors predicting above-average cortisol levels were periodontitis (odds ratio [OR] = 256.829; p < 0.001), women (OR = 6.365; p = 0.004), and psychological stress (OR = 6.036; p = 0.007); those predicting above-average cortisol/DHEA ratios were periodontitis (OR = 11.436; p < 0.001), psychological stress (OR = 3.977; p = 0.003), and women (OR = 2.890; p = 0.026). Thus, periodontitis and psychological stress were significant and strong predictors of above-average cortisol levels and cortisol/DHEA ratios. In the gingivitis group, salivary cortisol levels (r = 0.381, p = 0.007) and cortisol/DHEA ratios (r = 0.479, p < 0.001) were correlated with the presence of psychological stress. In the periodontitis group, increased cortisol/DHEA ratios (r = 0.412, p = 0.013) and lowered salivary buffer capacities (r = -0.334, p = 0.047) were correlated with the presence of psychological stress. Conclusion: Periodontitis is a multifactorial disease resulting in inflammatory tissue destruction, which differs from gingivitis and a healthy state. Differences in stress-related neuroendocrine markers were revealed based on the severity of periodontal disease. The biomarkers that could be classified according to disease severity were salivary cortisol and chromogranin A levels. Above-average cortisol levels and cortisol/DHEA ratios are significant predictors of psychological stress in patients with gingivitis and periodontitis.

Oral and periodontal assessment at the first trimester of pregnancy: The PERISCOPE longitudinal study.

INTRODUCTION: Periodontal diseases (gingivitis and periodontitis) are chronic non-communicable inflammatory diseases. The risk of developing gingivitis and periodontitis increases during pregnancy. Also, periodontitis increases the risk of developing adverse pregnancy outcomes such as preterm birth and preeclampsia. Early diagnosis of adverse pregnancy outcomes is essential and periodontitis could be an early sign to take into consideration. MATERIAL AND METHODS: We conducted a longitudinal observational study (PERISCOPE study: CNIL, no. 1 967 084 v 0; CER, no. 01-0416) on 121 pregnant women in the first trimester to determine their oral and periodontal health status. We explored the relations between oral and periodontal health status and sociodemographic and behavior characteristics, as well as their course and outcome of pregnancy. RESULTS: A total of 47.1% of the women had periodontitis, of which only 66.7% presented clinical manifestations associated with the disease such as gingival bleeding. These women had a poorer oral and periodontal health, and a higher body mass index, and more of them developed gestational diabetes during the course of pregnancy. The remaining 33.3% showed only discreet and isolated inflammatory signs and, unless thoroughly examined, would have gone undiagnosed for periodontitis. Interestingly these women were more often primiparous, still active professionally and had had a recent oral examination. CONCLUSIONS: The PERISCOPE study is one of the few studies that reports the oral and periodontal health status of pregnant women in the first trimester. Furthermore, the results highlight the need for early oral and periodontal assessment and treatment, even in the absence of exterior clinical signs, in order to prevent periodontal disease aggravation and also, by reducing low grade systemic inflammation, possibly adverse pregnancy outcomes.

Accuracy of Artificial Intelligence-Based Photographic Detection of Gingivitis.

OBJECTIVES: Gingivitis is one of the most prevalent plaque-initiated dental diseases globally. It is challenging to maintain satisfactory plaque control without continuous professional advice. Artificial intelligence may be used to provide automated visual plaque control advice based on intraoral photographs. METHODS: Frontal view intraoral photographs fulfilling selection criteria were collected. Along the gingival margin, the gingival conditions of individual sites were labelled as healthy, diseased, or questionable. Photographs were randomly assigned as training or validation datasets. Training datasets were input into a novel artificial intelligence system and its accuracy in detection of gingivitis including sensitivity, specificity, and mean intersection-over-union were analysed using validation dataset. The accuracy was reported according to STARD-2015 statement. RESULTS: A total of 567 intraoral photographs were collected and labelled, of which 80% were used for training and 20% for validation. Regarding training datasets, there were total 113,745,208 pixels with 9,270,413; 5,711,027; and 4,596,612 pixels were labelled as healthy, diseased, and questionable respectively. Regarding validation datasets, there were 28,319,607 pixels with 1,732,031; 1,866,104; and 1,116,493 pixels were labelled as healthy, diseased, and questionable, respectively. AI correctly predicted 1,114,623 healthy and 1,183,718 diseased pixels with sensitivity of 0.92 and specificity of 0.94. The mean intersection-over-union of the system was 0.60 and above the commonly accepted threshold of 0.50. CONCLUSIONS: Artificial intelligence could identify specific sites with and without gingival inflammation, with high sensitivity and high specificity that are on par with visual examination by human dentist. This system may be used for monitoring of the effectiveness of patients' plaque control.

Plasma Cell Gingivitis and Its Mimics.

Plasma cell gingivitis (PCG) is an inflammatory condition that affects the gingival mucosa of the oral cavity. It is characterized by polyclonal dense plasma cell infiltrate in the connective tissue. Lesions do not respond to prophylactic treatment. Etiology is most likely hypersensitivity to certain antigens (eg, toothpastes, oral rinses, chewing gums, spices). Differential diagnosis of PCG includes reactive, granulomatous, and neoplastic lesions. The diagnostic workup is based on patient's history and the clinicopathologic correlation to rule out mimics of PCG. Dermatologic patch test may be indicated in chronic conditions to identify the allergen.

Salivary macrophage chemokines as potential biomarkers of gingivitis.

OBJECTIVE: The present study aimed to analyze the salivary levels of macrophage-activating factor (MAF), macrophage-chemotactic factor (MCF), and macrophage migration inhibitory factor (MIF) in healthy and gingivitis patients, and to correlate between the concentrations of these chemo attractants with the intensity of gingival inflammation clinically. METHODS: Sixty saliva specimens were collected from periodontally healthy (n = 30), and gingivitis patients (n = 30). Bleeding on probing (BOP), Visible Plaque Index (VPI), and Simplified Modified Gingival Index (SMGI) were recorded through clinical examination. Salivary MAF, MCF, and MIF concentrations were assayed using enzyme-linked immunosorbent assays (ELISA). Statistical analysis was performed using SPSS (version 28). Total mean score for each biomarker was determined, and descriptive bivariate statistics were conducted to characterize the levels of biomarkers among the study groups. The difference in the biomarker levels among the study groups were analyzed by independent sample t test and one-way ANOVA. The diagnostic ability of the biomarkers was further tested by ROC curve analysis. RESULTS: Salivary levels of MAF was not significantly different between periodontally healthy individuals and gingivitis patients. The difference in MCF and MIF levels between patients with gingivitis and those with healthy periodontium was statistically significant (p 0.05 and p 0.001, respectively). When examined across the various stages of disease progression, MIF showed statistically significant difference among the three biomarkers (p 0.05). ROC curve analysis further revealed that area under the curve (AUC) for MIF has a better diagnostic capacity than MCF (AUC 0.981 vs. 0.673). CONCLUSIONS: Our results suggest that MIF could be considered as a potential salivary biomarker for gingivitis.