An IoT-based aptasensor biochip for the diagnosis of periodontal disease.

Severe periodontitis affects nearly 1 billion individuals worldwide, highlighting the need for early diagnosis. Here, an integrated system consisting of a microfluidic chip and a portable point-of-care (POC) diagnostic device is developed using a polymethyl methacrylate (PMMA) chip fabrication and a three-dimensional printing technique, which is automatically controlled by a custom-designed smartphone application to routinely assess the presence of a specific periodontitis biomarker, odontogenic ameloblast-associated protein (ODAM). A sandwich-type fluorescence aptasensor is developed on a microfluidic chip, utilizing aptamer pair (MB@OD64 and OD35@FAM) selectively binding to target ODAM. Then this microfluidic chip is integrated into an automated Internet of Things (IoT)-based POC device, where fluorescence intensity, as a signal, from the secondary aptamer binding to ODAM in a sandwich-type binding reaction on the microfluidic chip is measured by a complementary metal oxide semiconductor (CMOS) camera with a 488 nm light-emitting diode (LED) excitation source. Obtained signals are processed by a microprocessor and visualized on a wirelessly connected smartphone application. This integrated biosensor system allows the rapid and accurate detection of ODAM within 30 min with a remarkable limit of detection (LOD) of 0.011 nM under buffer conditions. Clinical application is demonstrated by successfully distinguishing between low-risk and high-risk individuals with 100 % specificity. A strong potential in the translation of this fluorescence-based microfluidic aptasensor integrated with an IoT-based POC system is expected to be employed for non-invasive, on-site, rapid, and accurate ODAM detection, facilitating periodontitis diagnosis.

Development and validation of a rule-based algorithm to identify periodontal diagnosis using structured electronic health record data.

AIM: To develop and validate an automated electronic health record (EHR)-based algorithm to suggest a periodontal diagnosis based on the 2017 World Workshop on the Classification of Periodontal Diseases and Conditions. MATERIALS AND METHODS: Using material published from the 2017 World Workshop, a tool was iteratively developed to suggest a periodontal diagnosis based on clinical data within the EHR. Pertinent clinical data included clinical attachment level (CAL), gingival margin to cemento-enamel junction distance, probing depth, furcation involvement (if present) and mobility. Chart reviews were conducted to confirm the algorithm's ability to accurately extract clinical data from the EHR, and then to test its ability to suggest an accurate diagnosis. Subsequently, refinements were made to address limitations of the data and specific clinical situations. Each refinement was evaluated through chart reviews by expert periodontists at the study sites. RESULTS: Three-hundred and twenty-three charts were manually reviewed, and a periodontal diagnosis (healthy, gingivitis or periodontitis including stage and grade) was made by expert periodontists for each case. After developing the initial version of the algorithm using the unmodified 2017 World Workshop criteria, accuracy was 71.8% for stage alone and 64.7% for stage and grade. Subsequently, 16 modifications to the algorithm were proposed and 14 were accepted. This refined version of the algorithm had 79.6% accuracy for stage alone and 68.8% for stage and grade together. CONCLUSIONS: Our findings suggest that a rule-based algorithm for suggesting a periodontal diagnosis using EHR data can be implemented with moderate accuracy in support of chairside clinical diagnostic decision making, especially for inexperienced clinicians. Grey-zone cases still exist, where clinical judgement will be required. Future applications of similar algorithms with improved performance will depend upon the quality (completeness/accuracy) of EHR data.

Association between raftlin and presepsin levels with periodontal healthy and disease conditions.

OBJECTIVE: The aim of this study was to examine the association between Raftlin and Presepsin levels in periodontal healthy/diseases, hypothesizing a change in their levels. Also, the study aimed to determine their potential role in diagnosing and predicting the prognosis of periodontal diseases. DESIGN: A cross-sectional study design was used, including 20 periodontally healthy individuals, 21 gingivitis patients, and 21 periodontitis patients. Clinical measurements and gingival crevicular fluid (GCF) sample collection were conducted, and the levels of Raftlin and Presepsin were analyzed. Statistical analysis was performed to evaluate the differences and correlations among the groups. RESULTS: Raftlin and Presepsin levels displayed significant variations among groups in both total amount (mean values for Raftlin in periodontitis, gingivitis, and healthy were 33.42, 17.45, 7.70 pg/30 s, respectively; for Presepsin, values were 3.98, 3.01, 1.92 pg/30 s, respectively) (p < 0.001) and concentration levels (pg/µl) (p = 0.007 for Raftlin, p = 0.026 for Presepsin). Particularly noteworthy were the concentration distinctions observed exclusively between the periodontitis and healthy groups. CONCLUSIONS: The present study offers preliminary insights into the presence and variations of raftlin and prepsepsin in the GCF across different periodontal conditions. While these findings hint at a potential role for these markers in periodontal disease, further research is essential to fully understand their diagnostic and prognostic capabilities.

Artificial intelligence in salivary biomarker discovery and validation for oral diseases.

Salivary biomarkers can improve the efficacy, efficiency, and timeliness of oral and maxillofacial disease diagnosis and monitoring. Oral and maxillofacial conditions in which salivary biomarkers have been utilized for disease-related outcomes include periodontal diseases, dental caries, oral cancer, temporomandibular joint dysfunction, and salivary gland diseases. However, given the equivocal accuracy of salivary biomarkers during validation, incorporating contemporary analytical techniques for biomarker selection and operationalization from the abundant multi-omics data available may help improve biomarker performance. Artificial intelligence represents one such advanced approach that may optimize the potential of salivary biomarkers to diagnose and manage oral and maxillofacial diseases. Therefore, this review summarized the role and current application of techniques based on artificial intelligence for salivary biomarker discovery and validation in oral and maxillofacial diseases.

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.

Unstable periodontal disease and its association with sleep-disordered breathing.

Periodontal therapy results in successful disease management for some patients, but patients whose periodontal disease cannot be managed with standard-of-care protocols are treated repeatedly without success. For this set of patients, a systemic rather than an oral origin is possible. This clinical study investigated the connection between unresolved periodontal disease and sleep-disordered breathing (SDB) in 71 patients (44 women and 27 men), aged 19 to 75 years (mean, 45 years), who were enrolled in periodontal maintenance therapy for Stage I or II periodontitis. The results of an at-home sleep testing device served as the basis for evaluating 4 SDB screening tools: Papillary Bleeding Index (PBI), Epworth Sleepiness Scale (ESS) questionnaire, STOP-Bang questionnaire, and salivary cortisol testing. At-home sleep testing indicated that 33 participants had an apnea-hypopnea index ≥ 5, signifying probable obstructive sleep apnea. A finding of unstable periodontal disease (PBI ≥ 2) was able to identify 21 of these 33 participants, while the ESS and STOP-Bang questionnaires identified only 2 and 6 participants, respectively. The difference between the PBI and both the ESS and STOP-Bang questionnaires was statistically significant (P < 0.05; 2-sample proportion test). There was no relationship between participants' cortisol levels and the PBI findings. This clinical study found a link between unresolved periodontal disease and SDB. The results of this study suggested that the PBI is a reliable, objective means for general dentists to identify SDB in patients with unresolved periodontal disease. Once identified, these patients can be referred for treatment to address their SDB, which may positively impact management of their periodontal disease.

Periodontal examination and screening.

Periodontal screening is an important tool in dental practice, and the BPE system is recommended. Clinically, visual examination should identify inflammatory change, recession and enlargement. However, detailed periodontal charting is required in all patients with significant levels of disease. In addition, radiographic examination is important to verify loss of bone and to show root anatomy.

Screening and Preventive Interventions for Oral Health in Adults: US Preventive Services Task Force Recommendation Statement.

Importance: Oral health is fundamental to health and well-being across the life span. Dental caries (cavities) and periodontal disease (gum disease) are common and often untreated oral health conditions that affect eating, speaking, learning, smiling, and employment potential. Untreated oral health conditions can lead to tooth loss, irreversible tooth damage, and other serious adverse health outcomes. Objective: The US Preventive Services Task Force (USPSTF) commissioned a systematic review to evaluate screening and preventive interventions for oral health conditions in adults. Population: Asymptomatic adults 18 years or older. Evidence Assessment: The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of screening for oral health conditions (eg, dental caries or periodontal disease) performed by primary care clinicians in asymptomatic adults. The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of preventive interventions for oral health conditions (eg, dental caries or periodontal disease) performed by primary care clinicians in asymptomatic adults. Recommendations: The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of routine screening performed by primary care clinicians for oral health conditions, including dental caries or periodontal-related disease, in adults. (I statement) The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of preventive interventions performed by primary care clinicians for oral health conditions, including dental caries or periodontal-related disease, in adults. (I statement).

Screening, Referral, Behavioral Counseling, and Preventive Interventions for Oral Health in Adults: A Systematic Review for the US Preventive Services Task Force.

Importance: Dental caries and periodontal disease are common adult oral health conditions and potentially amenable to primary care screening and prevention. Objective: To systematically review the evidence on primary care screening and prevention of dental caries and periodontal disease in adults to inform the US Preventive Services Task Force. Data Sources: MEDLINE, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews (to October 3, 2022); surveillance through July 21, 2023. Study Selection: Diagnostic accuracy studies of primary care screening instruments and oral examination; randomized and nonrandomized trials of screening and preventive interventions; cohort studies on primary care oral health screening and preventive intervention harms. Data Extraction and Synthesis: One investigator abstracted data; a second checked accuracy. Two investigators independently rated study quality. Diagnostic accuracy data were pooled using a bivariate mixed-effects binary regression model. Main Outcomes and Measures: Dental caries, periodontal disease, morbidity, quality of life, harms; and diagnostic test accuracy. Results: Five randomized clinical trials, 5 nonrandomized trials, and 6 observational studies (total 3300 participants) were included. One poor-quality trial (n = 477) found no difference between oral health screening during pregnancy vs no screening in caries, periodontal disease, or birth outcomes. One study (n = 86) found oral health examination by 2 primary care clinicians associated with low sensitivity (0.42 and 0.56) and high specificity (0.84 and 0.87) for periodontal disease and with variable sensitivity (0.33 and 0.83) and high specificity (0.80 and 0.93) for dental caries. Four studies (n = 965) found screening questionnaires associated with a pooled sensitivity of 0.72 (95% CI, 0.57-0.83) and specificity of 0.74 (95% CI, 0.66-0.82) for periodontal disease. For preventive interventions no study evaluated primary care counseling or dental referral, and evidence from 2 poor-quality trials (n = 178) of sealants, and 1 fair-quality and 4 poor-quality trials (n = 971) of topical fluorides, was insufficient. Three fair-quality trials (n = 590) of persons with mean age 72 to 80 years found silver diamine fluoride solution associated with fewer new root caries lesions or fillings vs placebo (mean reduction, -0.33 to -1.3) and decreased likelihood of new root caries lesion (2 trials; adjusted odds ratio, 0.4 [95% CI, 0.3-0.7]). No trial evaluated primary care-administered preventive interventions. Conclusions and Relevance: Screening questionnaires were associated with moderate diagnostic accuracy for periodontal disease. Research is needed to determine benefits and harms of oral health primary care screening and preventive interventions.

Knowledge and practice attitudes regarding the relationship between diabetes and periodontitis: a survey among Swiss endocrinologists and general physicians.

BACKGROUND: The objective of the present survey is to assess the knowledge about the relationship between oral health and diabetes and to identify the practice behaviors of Swiss endocrinologists and general practitioners regarding oral health in diabetic patients. METHODS: A thirty- item questionnaire was mailed to 428 internists and 99 endocrinologists working in the French speaking part of Switzerland. Participants were asked about their awareness of the relationship between diabetes and periodontal disease, their practice behaviors as well as their willingness for an interdisciplinary education and collaboration with oral health professionals. The questions were answered according to a three-point or five-point Likert scale. RESULTS: The response rate was 23%. All participants were aware of the inflammatory and infectious nature of periodontal disease. They all agreed that good periodontal health is important for overall health. However, most of the practitioners responded that only rarely received information during their education curricula on the link between systemic and oral health or concerning periodontal problems in diabetic patients (60.9% for endocrinologists and 54.1% for general physicians); thus, only a minority of health practitioners addresses oral health care to their patients (13% and 15.3%, respectively). Both endocrinologists and general health physicians agreed that an oral health screening could be included in their practice (79% for both groups). CONCLUSIONS: An interdisciplinary education and collaboration among medical and dental health providers should be established to effectively prevent, manage, and control both diabetes and periodontal disease in diabetic patients.

Molecular detection of oral Trichomonas tenax in periodontal disease patients by polymerase chain reaction -based 18S rRNA gene.

Trichomonas tenax, an oral flagellated protozoon found in humans, potentially associated with the inflammation of periodontal tissues and decreased immunity that causes the tissue damage and tooth loss from chronic infection. Currently, there is a lack of data regarding the prevalence of T. tenax infection in Thailand. Therefore, this study aimed to measure prevalence of T. tenax in periodontal disease patients by using polymerase chain reaction (PCR) to amplify the 18S ribosomal RNA (18S rRNA) gene and to determine the factors associated with the presence of this protozoan. A cross-sectional descriptive study was conducted among 230 patients with periodontal disease, who visited the oral health center of Suranaree University of Technology Hospital, Thailand from 2021 to 2022. Dental plaque specimens were collected and examined to identify the presence of T. tenax using the PCR-based 18S rRNA gene. The occurrence of factors associated with T. tenax infection was analyzed by the chi-square test and binary logistic regression. The prevalence of T. tenax infection was 13.48% (31/230), in patients, including 96.77% (30/31) and 3.23% (1/31) in periodontitis and gingivitis patients, respectively. The presence of T. tenax was associated with periodontal disease (p<0.001) and the Periodontal Screening and Record (PSR) index (p=0.001). The significant risk factors for T. tenax infection were periodontitis (ORadj=239.89, 95% CI=23.801-2417.746), no-underlying disease (ORadj=0.31, 95% CI=0.099-0.942), and male sex (ORadj=0.25, 95% CI=0.062-0.981). Dentists should be concerned about this oral protozoan in periodontitis patients. Furthermore, epidemiologic studies of T. tenax are still needed to investigate the mechanism of pathogenesis from T. tenax infection.

Influence of decision-making algorithms on the diagnostic accuracy using the current classification of periodontal diseases-a randomized controlled trial.

OBJECTIVES: To examine the influence of the decision-making algorithms published by Tonetti and Sanz in 2019 on the diagnostic accuracy in two differently experienced groups of dental students using the current classification of periodontal diseases. MATERIALS AND METHODS: Eighty-three students of two different clinical experience levels were randomly allocated to control and study group, receiving the staging and grading matrix, resulting in four subgroups. All diagnosed two patient cases with corresponding periodontal charts, panoramic radiographs, and intraoral photographs. Both presented severe periodontal disease (stage III, grade C) but considerably differed in complexity and phenotype according to the current classification of periodontal diseases. Controls received the staging and grading matrix published within the classification, while study groups were additionally provided with decision-trees published by Tonetti and Sanz. Obtained data was analyzed using chi-square test, Spearman's rank correlation, and logistic regression. RESULTS: Using the algorithms significantly enhanced the diagnostic accuracy in staging (p = 0.001*, OR = 4.425) and grading (p < 0.001**, OR = 30.303) regardless of the clinical experience. In addition, even compared to the more experienced control, less experienced students using algorithms showed significantly higher accuracy in grading (p = 0.020*). No influence on the criteria extent could be observed comparing study groups to controls. CONCLUSION: The decision-making algorithms may enhance diagnostic accuracy in dental students using the current classification of periodontal diseases. CLINICAL RELEVANCE: The investigated decision-making algorithms significantly increased the diagnostic accuracy of differently experienced under graduated dental students and might be beneficial in periodontal education.

Evaluating the Turkish validity and reliability of the Brief Illness Perception Questionnaire in periodontal diseases.

Background: The Brief Illness Perception Questionnaire (Brief IPQ) is a widely used multifactorial scale that assesses the individuals' perceptions of illness. Although there are studies investigating the psychometric properties of the Brief IPQ in many languages, the Turkish version of Brief IPQ on periodontal diseases has not been revealed so far. This study aimed to evaluate the Turkish validity and reliability of the Brief IPQ and contribute to the literature. It is also aimed to evaluate the patients' illness perception with periodontal disease and to reveal the possible effects of the disease on the patients' daily life. Methods: This cross-sectional study was conducted with 209 patients with periodontal diseases (137 gingivitis and 72 periodontitis cases). Sociodemographic characteristics and clinical periodontal measurements of all patients were recorded. The Turkish versions of the Brief IPQ and the HAD Scale were applied to the patients via face-to-face. The construct validity was determined using confirmatory factor analysis. Test-retest reliability and internal consistency were performed using ICC test and Cronbach's alpha, respectively. The concurrent validity was determined by using Spearman's correlation coefficient. Results: The confirmatory factor analysis showed that the scale has one factor. The Spearman's correlation coefficient results were found 0.843 and 0.854 for concurrent validity. Cronbach's alpha value of the scale was 0.944 in the internal consistency analysis. ICC value was found to be 0.987 for test-retest reliability. Floor/ceiling effects were considered not to be present. Conclusions: It was found that the Turkish version of The Brief Illness Perception Questionnaire is valid and reliable. Brief IPQ may be used to determine the illness perception in patients with periodontal diseases.

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.

First molecular detection of Entamoeba gingivalis subtypes in individuals from Turkey.

Entamoeba gingivalis is a parasitic protozoan that colonizes the human oral cavity and there are two subtypes (ST1 and ST2) that have been identified to date. However, there are no reports on the molecular detection or characterization of E. gingivalis in Turkey. The objective of this study was to detect the presence of E. gingivalis in Turkish healthy individuals and those with periodontal disease and to subtype the isolates using molecular techniques. Samples from the oral cavity of 94 individuals were taken and the presence of E. gingivalis was determined by PCR using primers for SsrRNA and the amplicons were then confirmed by DNA sequencing. Each participant completed a questionnaire that included demographic data, habits and lifestyle, as well as health status. The presence of E. gingivalis was detected in a total of 19 samples (11 patients and eight healthy individuals). Molecular characterization determined that 12 samples belonged to ST1 and seven samples belonged to ST2. The presence of E. gingivalis was higher in patients with periodontal disease than in healthy individuals, and this association was statistically significant (P < .05). This study constitutes the first report of molecular detection and subtyping of E. gingivalis in Turkey.

Improving Periodontal Disease Management With Artificial Intelligence.

Periodontitis is a common inflammatory disease of the adult population, with an incidence positively correlated with age. A lack of standardization relating to periodontitis diagnosis and management, however, can often result in instances of undiagnosed and untreated oral disease. Progressive approaches to care, such as incorporating artificial intelligence (AI) technology into dental practice software, can assist dental providers in standardizing the diagnosis of periodontitis and contribute to increased treatment acceptance by improving patients' health literacy and understanding of their periodontal condition. The use of AI technology can enhance clinical efficiency, improve provider standardization, facilitate clinical decision-making, and promote intra- and interprofessional collaboration. AI-powered radiograph analysis provides objective data to assist dentists in their clinical decision-making and diagnostic consistency.

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.