Diabetes in the dental office: using NHANES III to estimate the probability of undiagnosed disease

The relationship with and effect of oral microbiota on NLRP3 inflammatory pathway in type 2 diabetes mellitus

OBJECTIVE

The aim of this study was to explore the correlation between oral microbiota and NLRP3 inflammasome in type 2 diabetes, and to preliminarily explore their possible impact on type 2 diabetes.

DESIGN

The 16S rDNA sequencing technique was used to analyze the microbial composition in the saliva of patients with T2DM and healthy people. Real-time quantitative PCR (RT-qPCR) was used to detect the expression levels of T2DM-related inflammatory cytokines in the blood of two groups.

RESULTS

The relative abundances of Fusobacteriota and Campilobacterota in the saliva of patients with T2DM were lower than those of healthy people (P < 0.05), whereas the relative abundance of Proteobacteria in patients with T2DM was higher than that of healthy people (P < 0.05). In addition, real-time quantitative PCR results showed changes in inflammasome-associated factors in the blood of patients with T2DM and healthy people. Compared with healthy individuals, the relative expression levels of lipopolysaccharide (LPS), apoptosis-associated point-like protein (ASC), Caspase-1, Caspase-11, nucleotide-binding oligomerization domain-like receptor family pyrin domain containing 3 (NLRP3), and interleukin (IL)-1β were significantly higher in the blood of patients with T2DM, whereas the expression level of insulin receptor substrate-1 (IRS-1) was reduced (P < 0.05).

CONCLUSIONS

Our research suggested that changes in the ratio of oral microbial taxa might increase the expression levels of inflammatory and T2DM-related factors by activating the NLRP3 inflammasome pathway. This discovery indicated the imbalance in oral microbiota might have a certain influence on diabetes by triggering an inflammatory response, and provided a new idea for the relationship between T2DM and oral microbiota.

Association of Epstein-Barr virus, cytomegalovirus and lipocalin with periodontitis in type 2 diabetic subjects

OBJECTIVE

The current study aims to evaluate and compare the lipocalin, adiponectin and periodontal viruses in the generalized periodontitis patients with and without diabetes mellitus.

MATERIALS AND METHODS

Seventy subjects were grouped into 35 systemically healthy (GP) and 35 patients with diabetes mellitus (GP+DM). The periodontal parameters, demographic and diabetic variables were evaluated in both the groups. The subgingival tissue samples were procured from the diseased sites and were analysed for the detection of EBV, CMV, HSV and protein markers by real-time polymerase chain reaction (RT-PCR) and lipocalin and adiponectin were identified by enzyme-linked immunosorbent assay (ELISA).

RESULTS

The demographic variables such as age and BMI did not differ between the groups. PI and CAL were found to be significantly higher in GP+DM (p < 0.05). EBV (82.9%), CMV (71.4%) and protein marker: lipocalin were also found to be statistically highly significant in GP+DM and adiponectin was found to be higher in GP group and reduced in GP+DM group (p < 0.0001).

CONCLUSION

The increased prevalence of EBV and CMV and lipocalin with reduced levels of adiponectin in patients with diabetes and periodontitis which may show aggravation of the diabetic status of the periodontitis patients thereby reinforcing a strong Periodontitis-DM continuum.

The Complex Interrelationship between Diabetes Mellitus, Oral Diseases and General Health

There is emerging evidence that several oral diseases and conditions can be associated with DM. Dental caries, hyposalivation, fungal diseases and endodontics lesions may represent potential oral complications that can be aggravated by chronic hyperglycemia. Individuals with DM have a low perception of oral diseases which can lead to clinically important oral and systemic complications. This review aims to provide data on the most common oral signs and symptoms related to DM and to explore the mechanisms that might explain associations between DM and oral diseases in order to clarify the risks posed by poor oral health in DM. Since the linkage between oral diseases and DM is part of multifactorial aspects related to chronic hyperglycemic status and several common conditions affecting the whole body, both require rigorous self-control from patients and attention from medical and dental professionals.

Subgingival microbiome in periodontitis and type 2 diabetes mellitus: an exploratory study using metagenomic sequencing

Purpose

To explore differences in the subgingival microbiome according to the presence of periodontitis and/or type 2 diabetes mellitus (T2D), a metagenomic sequencing analysis of the subgingival microbiome was performed.

Methods

Twelve participants were divided into 4 groups based on their health conditions (periodontitis, T2D, T2D complicated with periodontitis, and generally healthy). Subgingival plaque was collected for metagenomic sequencing, and gingival crevicular fluids were collected to analyze the concentrations of short-chain fatty acids.

Results

The shifts in the subgingival flora from the healthy to periodontitis states were less prominent in T2D subjects than in subjects without T2D. The pentose and glucuronate interconversion, fructose and mannose metabolism, and galactose metabolism pathways were enriched in the periodontitis state, while the phosphotransferase system, lipopolysaccharide (LPS) and peptidoglycan biosynthesis, bacterial secretion system, sulfur metabolism, and glycolysis pathways were enriched in the T2D state. Multiple genes whose expression was upregulated from the red and orange complex bacterial genomes were associated with bacterial biofilm formation and pathogenicity. The concentrations of propionic acid and butyric acid were significantly higher in subjects with periodontitis, with or without T2D, than in healthy subjects.

Conclusions

T2D patients are more susceptible to the presence of periodontal pathogens and have a higher risk of developing periodontitis. The pentose and glucuronate interconversion, fructose and mannose metabolism, galactose metabolism, and glycolysis pathways may represent the potential microbial functional association between periodontitis and T2D, and butyric acid may play an important role in the interaction between these 2 diseases. The enrichment of the LPS and peptidoglycan biosynthesis, bacterial secretion system, and sulfur metabolism pathways may cause T2D patients to be more susceptible to periodontitis.

Systematic review of studies examining contribution of oral health variables to risk prediction models for undiagnosed Type 2 diabetes and prediabetes

Objective

To conduct systematic review applying “preferred reporting items for systematic reviews and meta‐analyses statement” and “prediction model risk of assessment bias tool” to studies examining the performance of predictive models incorporating oral health‐related variables as candidate predictors for projecting undiagnosed diabetes mellitus (Type 2)/prediabetes risk.

Materials and Methods

Literature searches undertaken in PubMed, Web of Science, and Gray literature identified eligible studies published between January 1, 1980 and July 31, 2018. Systematically reviewed studies met inclusion criteria if studies applied multivariable regression modeling or informatics approaches to risk prediction for undiagnosed diabetes/prediabetes, and included dental/oral health‐related variables modeled either independently, or in combination with other risk variables.

Results

Eligibility for systematic review was determined for seven of the 71 studies screened. Nineteen dental/oral health‐related variables were examined across studies. “Periodontal pocket depth” and/or “missing teeth” were oral health variables consistently retained as predictive variables in models across all systematically reviewed studies. Strong performance metrics were reported for derived models by all systematically reviewed studies. The predictive power of independently modeled oral health variables was marginally amplified when modeled with point‐of‐care biological glycemic measures in dental settings. Meta‐analysis was precluded due to high inter‐study variability in study design and population diversity.

Conclusions

Predictive modeling consistently supported “periodontal measures” and “missing teeth” as candidate variables for predicting undiagnosed diabetes/prediabetes. Validation of predictive risk modeling for undiagnosed diabetes/prediabetes across diverse populations will test the feasibility of translating such models into clinical practice settings as noninvasive screening tools for identifying at‐risk individuals following demonstration of model validity within the defined population.

Knowledgeability, Attitude and Practice Behaviors of Dental Providers Toward Provisions of Integrated Care Delivery for Patients With Prediabetes/Diabetes: Wisconsin Statewide Survey

Introduction: To conduct a statewide survey among Wisconsin-based dental providers evaluating current knowledgeability, attitudes and practice behaviors surrounding management of patients with diabetes/prediabetes in the dental setting. The study explored perceptions on feasibility, value, barriers, and current status of integrated care model (ICM) adoption by dental practices

Materials and Methods: A 32-question paper-based survey was mailed to all licensed dentists and dental hygienists practicing in Wisconsin. The study was conducted over a 4 week period in 2019. The survey instrument was adapted from a previous validated survey and was expanded to include questions on ICM adoption. Content and validity analyses and beta testing were conducted prior to dissemination of the survey. Descriptive statistics and chi-square tests were applied for data analyses. Thematic analyses was performed on open-ended questions.

Results: Survey response rate was 12% (N = 854/7,356) representing 41% dentists and 59% dental hygienists. While 68% reported educating patients on oral health-diabetes association, only 18% reported medical consultations to inform dental treatment, and “frequent” (22%) or “occasional” (40%), medical triage. Knowledge-based questions were correctly answered by &gt;70% of participants. While 50% valued chair-side glycemic screening and 85% supported non-invasive chair-side screening to identify at-risk patients,&gt;88% relied on patient-reported diabetic status. Barriers to ICM adoption included time investment (70%), patient activation/cooperation (62%), cost (50%), insurance coverage (50%), infrequent interdisciplinary communication (46%), lack of equipment (33%) and provider (31%).

Conclusion: Low rates of ICM adoption, chair-side testing, medical consultation and triage, and need for educational curricula reform were identified.

What is the future of Periodontal Medicine?

In the last five decades, considerable progress has been made towards understanding the etiology and pathogenesis of periodontal diseases and their interactions with the host. The impact of an individual periodontal condition on systemic homeostasis became more evident because of this knowledge and prompted advances in studies that associate periodontitis with systemic diseases and conditions. The term Periodontal Medicine describes how periodontal infection/inflammation can affect extraoral health. This review presents the current scientific evidence on the most investigated associations between periodontitis and systemic diseases and conditions, such as cardiovascular diseases, diabetes, preterm birth and low birth weight, and pneumonia. Additionally, other associations between periodontitis and chronic inflammatory bowel disease, colorectal cancer, and Alzheimer's disease that were recently published and are still poorly studied were described. Thus, the aim of this review was to answer the following question: What is the future of Periodontal Medicine? Epidemiological evidence and the evidence of biological plausibility between periodontitis and general health reinforce the rationale that the study of Periodontal Medicine should continue to advance, along with improvements in the epidemiological method, highlighting the statistical power of the studies, the method for data analysis, the case definition of periodontitis, and the type of periodontal therapy to be applied in intervention studies.

Inflammatory Status and Glycemic Control Level of Patients with Type 2 Diabetes and Periodontitis: A Randomized Clinical Trial

Background: Based on the holistic approach to prevention diabetic disease, the role of periodontal inflammation in type 2 diabetes mellitus (T2DM) is under intensive scrutiny. Data from clinical trials have shown benefit from a periodontal therapy in providing patients with type 2 diabetes improvement despite relatively disappointing long-terms response rates. The aim of this study was to investigate the short-term glycemic control level and systemic inflammatory status after periodontal therapy. Methods: This was a randomized trial with a 6-months follow-up. Participants aged 56.4 ± 7.9 years with diagnosed type 2 diabetes and periodontitis were enrolled. Among the 187 type 2 diabetic patients, 93 were randomly assigned to receive non-surgical periodontal treatment immediately and 94 to receive the delayed treatment. Within and between groups comparison was done during the study period, and the differences between groups were assessed. Results: The difference between HbA1c values at baseline (Mdn = 7.7) and 6 months after non-surgical periodontal treatment (Mdn = 7.2) was statistically significant, U = 3174.5, p = 0.012, r = 0.187. However, although technically a positive correlation, the relationship between the glycated hemoglobin value and periodontal variables was weak. The differences between both the groups over 6 months were not statistically considerable, failing to reach statistical significance. At 6 months the difference between groups about the C-reactive protein (CRP) levels was statistically significant, U=1839.5, p = 0, r = 0.472, with a lower concentration for the intervention group. Furthermore, the intervention group showed a statistically significant difference between baseline and 6 months evaluation (U = 2606.5, p = 0, r = 0.308). Conclusions: The periodontal intervention potentially may allow individuals with type 2 diabetes to improve glycemic control and CRP concentrations, and diabetes alters the periodontal status.

Are diabetes and dental care providers in the Republic of Mauritius advising patients about the importance of oral health in diabetes management?

Diabetes and dental care providers may greatly contribute in the early detection of oral diseases and diabetes, respectively, and in the prevention of complications of diabetes. However, there is limited collaboration and referrals between these two groups of health professionals.

OBJECTIVE

To investigate whether diabetic providers are addressing the importance of oral care in the management of diabetes and whether dental care providers are advising their patients with diabetes about the importance of glycaemic control.

METHOD

Descriptive statistics was used to report data collected from 720 patients with diabetes using a closed-end questionnaire. Logistic regression analysis revealed the factors significantly impacting whether participants received advice from healthcare providers.

RESULTS

The majority of participants did not receive advice from either diabetes (84%) or dental (75%) care providers regarding the reciprocal nature of diabetes and periodontitis. The factors significantly affecting receiving advice from diabetes care providers were place of residence (p = 0.003), self-reported type of diabetes (p = 0.000) receiving advice from dental care providers (p = 0.000); from dental care providers - education (p = 0.020), place of residence (p = 0.004), the number of years since diagnosis of diabetes (p = 0.002), frequency of dental visits (p = 0.000) and receiving advice from diabetes care providers (p = 0.000).

CONCLUSION

Diabetes and dental care providers in Mauritius are not addressing oral health care as an essential component of diabetes care. Patients with diabetes are neither being advised about the importance of regular dental visits by their treating doctor, nor about the importance of glycaemic control in the prevention of oral complications by their dentist.

Evaluation of a questionnaire-based diabetes screening concept in German patients with Stage III or IV periodontitis: A practice-based study

BACKGROUND

This practice-based retrospective study evaluated a screening method for diabetes mellitus (DM) in patients with Stage III or IV periodontitis using the FINDRISC questionnaire.

METHODS

Patients with Stage III or IV periodontitis who received FINDRISC screening in a German private dental practice were recruited. Individuals with positive FINDRISC scores (≥12, FINDRISC+) were referred for diabetological examination. Several general and periodontal findings from the patients' documentation were recorded and analyzed.

RESULTS

A total of 179 patients (52.65 ± 11.49 years) were included. In DM screening, 24.6% (n = 44) patients were FINDRISC+, including all patients with currently known DM (21 of 21). Of the remaining FINDRISC+ patients, 82.6% (19 of 23) visited their general practitioner, and 63.2% (12 of 19, 7.6% of total cohort) had an HbA1c ≥5.7%. Accordingly, 75% of the FINDRISC+ patients were diabetologically conspicuous (HbA1c ≥ 5.7%), including those with already known DM. Patients with previously unknown DM showed higher mean age, more missing teeth, a higher periodontitis stage (more Stage IV) and more frequently teeth with suppuration compared with the diabetologically inconspicuous individuals (P <0.01).

CONCLUSION

The FINDRISC questionnaire is appropriate for patients with Stage III or IV periodontitis and can be recommended in dental practice setting.

Development and validation of a screening model for diabetes mellitus in patients with periodontitis in dental settings

OBJECTIVES

To identify predictors in patient profiles and to develop, internally validate, and calibrate a screening model for diabetes mellitus (DM) in patients with periodontitis in dental settings MATERIALS AND METHODS: The study included 204 adult patients with periodontitis. Patients' socio-demographic characteristics, general health status, and periodontal status were recorded as potential predictors. The diabetic status was considered the outcome, classified into no DM, prediabetes (pre-DM), or DM. Multinomial logistic regression analysis was used to develop the model. The performance and clinical values of the model were determined.

RESULTS

Seventeen percent and 47% of patients were diagnosed with DM and pre-DM, respectively. Patients' age, BMI, European background, cholesterol levels, previous periodontal treatment, percentage of the number of teeth with mobility, and with gingival recession were significantly associated with the diabetic status of the patients. The model showed a reasonable calibration and moderate to good discrimination with area under the curve (AUC) values of 0.67 to 0.80. The added predictive values for ruling in the risk of DM and pre-DM were 0.42 and 0.11, respectively, and those for ruling it out were 0.05 and 0.17, respectively.

CONCLUSIONS

Predictors in patient profiles for screening of DM and pre-DM in patients with periodontitis were identified. The calibration, discrimination, and clinical values of the model were acceptable.

CLINICAL RELEVANCE

The model may well assist clinicians in screening of diabetic status of patients with periodontitis. The model can be used as a reliable screening tool for DM and pre-DM in patients with periodontitis in dental settings.

The added value of periodontal measurements for identification of diabetes among Saudi adults

BACKGROUND

The aims of this study were to develop a prediction model for identification of individuals with diabetes based on clinical and perceived periodontal measurements; and to evaluate its added value when combined with standard diabetes screening tools.

METHODS

The study was carried out among 250 adults attending primary care clinics in Riyadh (Saudi Arabia). The study adopted a case-control approach, where diabetes status was first ascertained, and the Finnish Diabetes Risk Score (FINDRISC), Canadian Diabetes Risk questionnaire (CANRISK), and periodontal examinations were carried out afterward.

RESULTS

A periodontal prediction model (PPM) including three periodontal indicators (missing teeth, percentage of sites with pocket probing depth ≥6 mm, and mean pocket probing depth) had an area under the curve (AUC) of 0.694 (95% Confidence Interval: 0.612-0.776) and classified correctly 62.4% of participants. The FINDRISC and CANRISK tools had AUCs of 0.766 (95% CI: 0.690-0.843) and 0.821 (95% CI: 0.763-0.879), respectively. The addition of the PPM significantly improved the AUC of FINDRISC (P = 0.048) but not of CANRISK (P = 0.144), with 26.8% and 9.8% of participants correctly reclassified, respectively. Finally, decision curve analysis showed that adding the PPM to both tools would result in net benefits among patients with probability scores lower than 70%.

CONCLUSIONS

This study showed that periodontal measurements could play a role in identifying individuals with diabetes, and that addition of clinical periodontal measurements improved the performance of FINDRISC and CANRISK.

Association between periodontitis and glycosylated haemoglobin before diabetes onset: a cross-sectional study

OBJECTIVES

The aim of the present cross-sectional study was to investigate the association between serum glycosylated haemoglobin (HbA1c) levels and periodontal status in patients with periodontitis (CP) and periodontally healthy controls. Furthermore, the objectives were to determine if the periodontitis influenced the serum HbA1c levels.

MATERIALS AND METHODS

A total of 93 patients with CP and 95 periodontally healthy subjects were enrolled in the present study using a cross-sectional design. At baseline, patients were examined and characterized on a regular basis for blood serum parameters and non-fasting blood samples levels. In all patients, a full periodontal examination was performed and clinical attachment loss (CAL) was the primary outcome variable chosen. The spearman correlation, a stepwise multivariable linear regression, and Jonckheere-Terpstra tests were applied in order to assess the relationship between HbA1c levels and periodontitis.

RESULTS

Patients in the CP group presented a significantly higher median serum level of HbA1c [40.9 (31.2; 45.6) mmol/mol)] compared to patients in the healthy control group [35.3 (29.6; 38.6) mmol/mol)] (p < 0.001). HbA1c levels were negatively correlated with the number of teeth and positively correlated with C-reactive protein levels and all periodontal parameters (p < 0.001). Moreover, there was a significant decrease in the number of teeth when HbA1c levels increased (P-trend < 0.001), while there was a significant increase in periodontal parameters (CAL, p = 0.002); PD, p = 0.008; BOP, p < 0.001) when levels of HbA1c increased.

CONCLUSIONS

Patients with CP and undiagnosed diabetes presented significantly higher serum levels of HbA1c compared to periodontally healthy controls. Moreover, the presence of periodontitis was positively correlated with serum HbA1c levels before diabetes onset.

CLINICAL RELEVANCE

HbA1c levels were positively correlated with the severity of periodontitis before diabetes onset.

Improving Oral Health in Older Adults and People With Disabilities: Protocol for a Community-Based Clinical Trial (Good Oral Health)

Background

Low-income older adults experience disparities in oral health problems, including caries and periodontal disease, that can exacerbate already high levels of chronic and acute health problems. Behavioral interventions have been shown to improve oral health status but are typically administered in institutional rather than community settings. Furthermore, multiple simultaneous interventions at different levels in the locations where people live and work are likely to have more impact and sustainability than single interventions in clinical settings.

Objective

This paper outlines a protocol for conducting a bilingual 5-year community-based trial of a bilevel intervention that addresses community norms, beliefs, intentions, and practices to improve oral health hygiene of vulnerable older adults living in publicly subsidized housing. The intervention utilizes (1) a face-to-face counseling approach (adapted motivational interviewing [AMI]) and (2) resident-run oral health campaigns in study buildings.

Methods

The study’s modified fractional factorial crossover design randomizes 6 matched buildings into 2 conditions: AMI followed by campaign (AB) and campaign followed by AMI (BA). The total intervention cycle is approximately 18 months in duration. The design compares the 2 interventions alone (T0-T1), and in different sequences (T1-T2), using a self-reported survey and clinical assessment to measure Plaque Score (PS) and Gingival Index (GI) as outcomes. A final timepoint (T3), 6 months post T2, assesses sustainability of each sequence. The intervention is based on the Fishbein integrated model that includes both individual and contextual modifiers, norms and social influence, beliefs, attitudes, efficacy, and intention as predictors of improvements in PS, GI, and oral health quality of life. The cognitive and behavioral domains in the intervention constitute the mechanisms through which the intervention should have a positive effect. They are tailored through the AMI and targeted to building populations through the peer-facilitated oral health campaigns. The sample size is 360, 180 in each condition, with an attrition rate of 25%. The study is funded by National Institute of Dental and Craniofacial Research (NIDCR) and has been reviewed by University of Connecticut and NIDCR institutional review boards and NIDCR’s clinical trials review procedures.

Results

When compared against each other, the face-to-face intervention is expected to have greater positive effects on clinical outcomes and oral health quality of life through the mediators. When sequences are compared, the results may be similar but affected by different mediators. The arm consisting of the BA is expected to have better sustainability. The protocol’s unique features include the comparative effectiveness crossover design; the introduction of new emotion-based mediators; the balancing of fidelity, tailoring, and targeting; and resident engagement in the intervention.

Conclusions

If successful, the evaluated interventions can be scaled up for implementation in other low-income congregate living and recreational settings with older adult collectives.

Trial Registration

ClinicalTrials.gov NCT02419144; https://clinicaltrials.gov/ct2/show/NCT02419144

International Registered Report Identifier (IRRID)

DERR1-10.2196/14555

Oral microbiota-induced periodontitis: a new risk factor of metabolic diseases

It has recently become evident that the periodontium (gingiva, desmodontal ligament, cementum and alveolar bone) and the associated microbiota play a pivotal role in regulating human health and diseases. The oral cavity is the second largest microbiota in the body with around 500 different bacterial species identified today. When disruption of oral cavity and dysbiosis occur, the proportion of strict anaerobic Gram-negative bacteria is then increased. Patients with periodontitis present 27 to 53% more risk to develop diabetes than the control population suggesting that periodontitis is an aggravating factor in the incidence of diabetes. Moreover, dysbiosis of oral microbiota is involved in both periodontal and metabolic disorders (cardiovascular diseases, dyslipidaemia …). The oral diabetic dysbiosis is characterized by a specific bacteria Porphyromonas, which is highly expressed in periodontal diseases and could exacerbate insulin resistance. In this review, we will address the nature of the oral microbiota and how it affects systemic pathologies with a bidirectional interaction. We also propose that using prebiotics like Akkermansia muciniphila may influence oral microbiota as novel therapeutic strategies. The discovery of the implication of oral microbiota for the control of metabolic diseases could be a new way for personalized medicine.

Development of non-invasive diabetes risk prediction models as decision support tools designed for application in the dental clinical environment

The objective was to develop a predictive model using medical-dental data from an integrated electronic health record (iEHR) to identify individuals with undiagnosed diabetes mellitus (DM) in dental settings. Retrospective data retrieved from Marshfield Clinic Health System's data-warehouse was pre-processed prior to conducting analysis. A subset was extracted from the preprocessed dataset for external evaluation (Nvalidation) of derived predictive models. Further, subsets of 30%-70%, 40%-60% and 50%-50% case-to-control ratios were created for training/testing. Feature selection was performed on all datasets. Four machine learning (ML) classifiers were evaluated: logistic regression (LR), multilayer perceptron (MLP), support vector machines (SVM) and random forests (RF). Model performance was evaluated on Nvalidation. We retrieved a total of 5319 cases and 36,224 controls. From the initial 116 medical and dental features, 107 were used after performing feature selection. RF applied to the 50%-50% case-control ratio outperformed other predictive models over Nvalidation achieving a total accuracy (94.14%), sensitivity (0.941), specificity (0.943), F-measure (0.941), Mathews-correlation-coefficient (0.885) and area under the receiver operating curve (0.972). Future directions include incorporation of this predictive model into iEHR as a clinical decision support tool to screen and detect patients at risk for DM triggering follow-ups and referrals for integrated care delivery between dentists and physicians.

Undetected Dysglycemia Is an Important Risk Factor for Two Common Diseases, Myocardial Infarction and Periodontitis: A Report From the PAROKRANK Study

OBJECTIVE

Information on the relationship among dysglycemia (prediabetes or diabetes), myocardial infarction (MI), and periodontitis (PD) is limited. This study tests the hypothesis that undetected dysglycemia is associated with both conditions.

RESEARCH DESIGN AND METHODS

The PAROKRANK (Periodontitis and Its Relation to Coronary Artery Disease) study included 805 patients with a first MI and 805 matched control subjects. All participants without diabetes (91%) were examined with an oral glucose tolerance test. Abnormal glucose tolerance (AGT) (impaired glucose tolerance or diabetes) was categorized according to the World Health Organization. Periodontal status was categorized from dental X-rays as healthy (≥80% remaining alveolar bone height), moderate (79-66%), or severe (<66%) PD. Odds ratios (ORs) and 95% CIs were calculated by logistic regression and were adjusted for age, sex, smoking, education, marital status, and explored associated risks of dysglycemia to PD and MI, respectively.

RESULTS

AGT was more common in patients than in control subjects (32% vs. 19%; P < 0.001) and was associated with MI (OR 2.03; 95% CI 1.58-2.60). Undetected diabetes was associated with severe PD (2.50; 1.36-4.63) and more strongly in patients (2.35; 1.15-4.80) than in control subjects (1.80; 0.48-6.78), but not when categorized as AGT (total cohort: 1.07; 0.67-1.72). Severe PD was most frequent in subjects with undetected diabetes, and reversely undetected diabetes was most frequent in patients with severe PD.

CONCLUSIONS

In this large case-control study previously undetected dysglycemia was independently associated to both MI and severe PD. In principal, it doubled the risk of a first MI and of severe PD. This supports the hypothesis that dysglycemia drives two common diseases, MI and PD.

Evaluation of Knowledge, Attitudes and Oral Health-related Nutritional Performance of Diabetic Patients Referred to the Diabetes Research Center in Isfahan-Iran, 2016

Background:

Type II diabetes is a chronic disease, with an ever-increasing incidence, concomitant with an increase in the number of the elderly. It is one of the conditions that can affect the orodental health. In general, the diabetes-related oral problems include dental caries, xerostomia, oral candidiasis, periodontal diseases and consumption of inappropriate foodstuff.

Objective:

The aim of this study was to evaluate knowledge, attitudes and oral health-related nutritional performance of diabetic patients referred to the diabetes center research in Isfahan-Iran, 2016.

Methods:

In the present cross-sectional study, 362 diabetic subjects (142 females and 220 males) referred to the Research Center for Endocrine Glands and Metabolism in Isfahan, were evaluated after being selected by simple random sampling technique. The frequency distribution of demographic data (gender, marital status, occupation, affliction with orodental diseases, disease history, and use of medications and supplements) were evaluated. The relationships of the variables above and the knowledge, attitude and performance scores of the subjects were evaluated. Data were analyzed with independent t-test, Pearson’s correlation coefficient and Spearmen’s correlation coefficient.

Results:

There were no significant relationships between orodental diseases and the mean scores of knowledge, attitudes and performance of the subjects. The mean scores of knowledge, attitudes and performance of the subjects were 33.8 ± 11.2, 53.311.01 and 53.7 ± 6.9 out of 100, respectively.

Conclusion:

The oral-health related nutritional knowledge of diabetic subjects was poor. Programs should be prepared to improve the knowledge and oral health-related nutritional performance of diabetic patients.

Prevalence of undiagnosed diabetes and pre-diabetes in chronic periodontitis patients assessed by an HbA1c chairside screening protocol

OBJECTIVES

The objective of the present study was to implement a chairside diabetes screening strategy for the identification of undiagnosed hyperglycaemia in periodontal patients.

MATERIALS AND METHODS

Measurement of HbA1c was performed in patients (n = 139) diagnosed with periodontal disease to determine possible unknown hyperglycaemia. Patients fulfilled the criteria for screening according to the questionnaire by the Centers for Disease Control and Prevention (CDC). The Cobas® b101 in vitro diagnostic system was used for the measurement of glycosylated haemoglobin (HbA1c) in capillary blood. Body mass index (BMI) and waist circumference were also measured to determine splanchnic obesity. Periodontal parameters were assessed with an automated probe and included probing depth, clinical attachment loss, bleeding on probing and presence/absence of plaque.

RESULTS

Most patients had moderate periodontitis. Almost 25% of the subjects tested were found to have unknown hyperglycaemia while 80.5% of them had splanchnic obesity. A significant association was found between HbA1c and BMI (Mann-Whitney test; p = 0.0021) as well as between HbA1c and waist circumference (Spearman rho test; p = 0.0007). No differences were observed regarding periodontal parameters between subjects exhibiting HbA1c ≥ 5.7% and those with HbA1c < 5.7% (Mann-Whitney test; p > 0.05) although those with HbA1c ≥ 5.7% displayed higher proportions of sites with clinical attachment loss > 5 mm (z test with Bonferroni corrections; p < 0.05).

CONCLUSIONS

Periodontal patients, especially those with a bigger than normal BMI and waist circumference, are a target group worth screening for diabetes.

CLINICAL RELEVANCE

The dental practitioner can contribute significantly to the worldwide effort of health care professionals in diabetes screening and referring for early diagnosis of the disease.

Awareness and practice about the association between periodontal diseases and diabetes mellitus: a cross-sectional study in Western Saudi Arabia among health care providers

Purpose

This study aims to assess the awareness and practices of dental and medical practitioners regarding the bidirectional relationship between periodontal diseases and diabetes mellitus.

Patients and methods

A cross-sectional survey of randomly selected dentists and physicians practicing in Jeddah. Participants were asked several questions concerning their awareness and practices on periodontal complications, and the bidirectional link between periodontal diseases and diabetes mellitus (DM).

Results

A total of 560 general practitioners (284 dentists and 276 physicians) participated in the study. There were no significant differences between the two groups regarding any sociodemographic characteristics. Overall, the awareness of all participants was low in all aspects. Moreover, dentists’ awareness and practices were significantly better than physicians as majority of the questions were about the association between periodontal diseases and DM.

Conclusion

The awareness and practices about the link between periodontal diseases and DM should be improved among dental and medical practitioners to effectively prevent and control periodontal diseases and DM.

Prediabetes and Diabetes Screening in Dental Care Settings: NHANES 2013 to 2016

Introduction

Early recognition of prediabetes may prevent progression to diabetes, yet not all adults are aware of their prediabetes risk. To reach all adults unaware of their risk, additional risk assessment strategies are warranted.

Objectives

The objective of this study was to evaluate the potential scope of benefit from prediabetes risk assessment in the dental care setting and to identify characteristics of dental patients likely to unknowingly have prediabetes or diabetes.

Methods

Data from 10,472 adults in the National Health and Nutrition Examination Survey from 2013 to 2014 and 2015 to 2016 were analyzed for associations among prediabetes/diabetes risk factors, health care use, and hemoglobin A1C levels according to chi-square tests and multivariate logistic regression.

Results

A total of 7.73% of US adults had seen a dentist but not a medical provider in the past 12 mo. The composition of this subpopulation was significantly different from that who saw a medical provider, in ways that might affect their diabetes risk. In addition, 31.27% of this subpopulation would be identified as being at high risk for prediabetes according to the CDC Prediabetes Screening Test (Centers for Disease Control and Prevention), and 15.83% had hemoglobin A1C levels indicative of undiagnosed prediabetes or diabetes. Screening in a dental setting would have the highest odds of identifying someone unaware of his or her diabetes risk among those who were non-White, obese, or ≥45 y old.

Conclusion

Extrapolation from this analysis indicates that screening for prediabetes at dental visits has the potential to alert an estimated 22.36 million adults of their risk for prediabetes or diabetes. Incorporating prediabetes or diabetes risk assessment into routine dental visits may enable 1) those with prediabetes to take action to decrease their risk of developing diabetes and 2) those with diabetes to engage in treatment to decrease their risk of diabetes-related complications.

Knowledge Transfer Statement

Screening for prediabetes and diabetes during dental visits has the potential to raise patients' awareness of diabetes risk and prevent prediabetes from progressing to diabetes. For some patients, the dental visit may be the only point of contact with the health care system, which heightens the importance of including diabetes risk assessment for patient well-being.

Screening models for undiagnosed diabetes in Mexican adults using clinical and self-reported information

BACKGROUND

Prevalence of diabetes in Mexico has constantly increased since 1993. Since type 2 diabetes may remain undiagnosed for many years, identification of subjects at high risk of diabetes is very important to reduce its impact and to prevent its associated complications.

OBJECTIVE

To develop easily implementable screening models to identify subjects with undiagnosed diabetes based on the characteristics of Mexican adults.

SUBJECTS AND METHODS

Screening models were developed using datasets from the 2006 and 2012 National Health and Nutrition Surveys (NHNS). Variables used to develop the multivariate logistic regression models were selected using a backward stepwise procedure. Final models were validated using data from the 2000 National Health Survey (NHS).

RESULTS

The model based on the 2006 NHNS included age, waist circumference, and systolic blood pressure as explanatory variables, while the model based on the 2012 NHNS included age, waist circumference, height, and family history of diabetes. The sensitivity and specificity values obtained from the external validation procedure were 0.74 and 0.62 (2006 NHNS model) and 0.76 and 0.55 (2012 NHNS model) respectively.

CONCLUSIONS

Both models were equally capable of identifying subjects with undiagnosed diabetes (∼75%), and performed satisfactorily when compared to other models developed for other regions or countries.

Screening for Diabetes Risk Using Integrated Dental and Medical Electronic Health Record Data

Undiagnosed diabetes and prediabetes present a serious public health challenge. We previously reported that data available in the dental setting can serve as a tool for early dysglycemia identification in a primarily Hispanic, urban population. In the present study, we sought to determine how the identification approach can be recalibrated to detect diabetes or prediabetes in a White, rural cohort and whether an integrated dental-medical electronic health record (iEHR) offers further value to the process. We analyzed iEHR data from the Marshfield Clinic, a health system providing care in rural Wisconsin, for dental patients who were ≥21 y of age, reported that they had never been told they had diabetes, had an initial periodontal examination of at least 2 quadrants, and had a glycemic assessment within 3 mo of that examination. We then assessed the performance of multiple predictive models for prediabetes/diabetes. The study outcome, glycemic status, was gleaned from the medical module of the iEHR based on American Diabetes Association blood test cutoffs. The sample size was 4,560 individuals. Multivariate logistic regression revealed that the best performance was achieved by a model that took advantage of the iEHR. Predictors included age, sex, race, ethnicity, number of missing teeth, percentage of teeth with at least 1 pocket ≥5 mm from the dental EHR, and overweight/obesity, hypertension, hyperlipidemia, and smoking status from the medical EHR. The model achieved an area under the receiver operating characteristic curve of 0.71 (95% confidence interval, 0.69-0.72), yielding a sensitivity of 0.70 and a specificity of 0.62. Across a range of populations, informed by certain patient characteristics, dental care team members can play a role in helping to identify dental patients with undiagnosed diabetes or prediabetes. The accuracy of the prediction increases when dental findings are combined with information from the medical EHR. Knowledge Transfer Statement: Prediabetes and diabetes often go undiagnosed for many years. Early identification and care can lead to improved glycemic outcomes and prevent wide-ranging morbidity, including adverse oral health consequences, in affected individuals. Information available in the dental office can be used by clinicians to identify those who remain undiagnosed or are at risk; the accuracy of this prediction increases when combined with information from the medical electronic health record.

Different views of dentists and general medical practitioners on dental care for patients with diabetes mellitus and coronary heart diseases: results of a questionnaire-based survey in a district of Germany

BACKGROUND

The aim of this questionnaire-based study was to evaluate the views of dentists (Ds) and general medical practitioners (GPs) on different aspects of dental care for patients with diabetes mellitus (DM) or coronary heart disease (CHD).

METHODS

Reliable and comparable questionnaires for Ds and GPs, with 23 questions, were sent to 1,000 randomly selected Ds and 1,000 randomly selected GPs. Questions were asked about patients with DM or CHD regarding their dental care and potentially related issues (e.g. antibiotic prophylaxis). The responses received within 12 weeks were evaluated and statistically analysed using chi-square and Mann-Whitney U tests (P < 0.05).

RESULTS

The response rate was 39% (n = 391) for Ds and 18% (n = 181) for GPs. Both groups stated that they used the medical history as well as patient interviews to assess patients. However, only 55% of Ds assumed correct identification of every at-risk patient compared with 100% of GPs (P < 0.01). Furthermore, Ds speculated that they inform their patients more often about their at-risk status than do GPs (P < 0.01). Neither Ds nor GPs appeared to be confident in their knowledge about adequate antibiotic prophylaxis. Interdisciplinary collaboration was considered insufficient, although Ds had a higher rate of regular collaboration (68% for Ds vs. 40% for GPs; P < 0.01).

CONCLUSION

Ds and GPs have differing views on dental care of patients with DM or CHD, and Ds showed more interest in this issue. These results might partially explain the insufficient collaboration between Ds and GPs.

Status Update on Translation of Integrated Primary Dental-Medical Care Delivery for Management of Diabetic Patients

Escalating prevalence of both diabetes and periodontal disease, two diseases associated with bi-directional exacerbation, has been reported. Periodontal disease represents a modifiable risk factor that may reduce diabetes onset or progression, and integrated models of cross-disciplinary care are needed to establish and manage glycemic control in affected patients. An ad-hoc environmental scan of current literature and media sought to characterize factors impacting status of integrated care models based on review of the existing evidence base in literature and media surrounding: (1) current cross-disciplinary practice patterns, (2) epidemiological updates, (3) status on risk assessment and screening for dysglycemia in the dental setting, (4) status on implementation of quality metrics for oral health, (5) care model pilots, and (6) public health perspectives. The survey revealed: escalating prevalence of diabetes and periodontitis globally; greater emphasis on oral health assessment for diabetic patients in recent medical clinical practice guidelines; high knowledgeability surrounding oral-systemic impacts on diabetes and growing receptivity to medical-dental integration among medical and dental providers; increasing numbers of programs/studies reporting on positive impact of emerging integrated dental-medical care models on diabetic patient healthcare access and health outcomes; a growing evidence base for clinically significant rates of undiagnosed dysglycemia among dental patients reported by point-of-care pilot studies; no current recommendation for population-based screening for dysglycemia in dental settings pending a stronger evidence base; improved definition of true periodontitis prevalence in (pre)/diabetics; emerging recognition of the need for oral health quality indicators and tracking; evidence of persistence in dental access disparity; updated status on barriers to integration. The potential benefit of creating clinically-applicable integrated care models to support holistic management of an escalating diabetic population by targeting modifiable risk factors including periodontitis is being recognized by the health industry. Cross-disciplinary efforts supported by high quality research are needed to mitigate previously- and newly-defined barriers of care integration and expedite development and implementation of integrated care models in various practice settings. Implementation of quality monitoring in the dental setting will support definition of the impact and efficacy of interventional clinical care models on patient outcomes.

Periodontitis induced by Porphyromonas gingivalis drives periodontal microbiota dysbiosis and insulin resistance via an impaired adaptive immune response

OBJECTIVE

To identify a causal mechanism responsible for the enhancement of insulin resistance and hyperglycaemia following periodontitis in mice fed a fat-enriched diet.

DESIGN

We set-up a unique animal model of periodontitis in C57Bl/6 female mice by infecting the periodontal tissue with specific and alive pathogens like Porphyromonas gingivalis (Pg), Fusobacterium nucleatum and Prevotella intermedia. The mice were then fed with a diabetogenic/non-obesogenic fat-enriched diet for up to 3 months. Alveolar bone loss, periodontal microbiota dysbiosis and features of glucose metabolism were quantified. Eventually, adoptive transfer of cervical (regional) and systemic immune cells was performed to demonstrate the causal role of the cervical immune system.

RESULTS

Periodontitis induced a periodontal microbiota dysbiosis without mainly affecting gut microbiota. The disease concomitantly impacted on the regional and systemic immune response impairing glucose metabolism. The transfer of cervical lymph-node cells from infected mice to naive recipients guarded against periodontitis-aggravated metabolic disease. A treatment with inactivated Pg prior to the periodontal infection induced specific antibodies against Pg and protected the mouse from periodontitis-induced dysmetabolism. Finally, a 1-month subcutaneous chronic infusion of low rates of lipopolysaccharides from Pg mimicked the impact of periodontitis on immune and metabolic parameters.

CONCLUSIONS

We identified that insulin resistance in the high-fat fed mouse is enhanced by pathogen-induced periodontitis. This is caused by an adaptive immune response specifically directed against pathogens and associated with a periodontal dysbiosis.

Predicting Risk of Type 2 Diabetes by Using Data on Easy-to-Measure Risk Factors

INTRODUCTION

Statistical models for assessing risk of type 2 diabetes are usually additive with linear terms that use non-nationally representative data. The objective of this study was to use nationally representative data on diabetes risk factors and spline regression models to determine the ability of models with nonlinear and interaction terms to assess the risk of type 2 diabetes.

METHODS

We used 4 waves of data (2005-2006 to 2011-2012) on adults aged 20 or older from the National Health and Nutrition Examination Survey (n = 5,471) and multivariate adaptive regression splines (MARS) to build risk models in 2015. MARS allowed for interactions among 17 noninvasively measured risk factors for type 2 diabetes.

RESULTS

A key risk factor for type 2 diabetes was increasing age, especially for those older than 69, followed by a family history of diabetes, with diminished risk among individuals younger than 45. Above age 69, other risk factors superseded age, including systolic and diastolic blood pressure. The additive MARS model with nonlinear terms had an area under curve (AUC) receiver operating characteristic of 0.847, whereas the 2-way interaction MARS model had an AUC of 0.851, a slight improvement. Both models had an 87% accuracy in classifying diabetes status.

CONCLUSION

Statistical models of type 2 diabetes risk should allow for nonlinear associations; incorporation of interaction terms into the MARS model improved its performance slightly. Robust statistical manipulation of risk factors commonly measured noninvasively in clinical settings might provide useful estimates of type 2 diabetes risk.

Follow-up with primary care providers for elevated glycated haemoglobin identified at the dental visit

OBJECTIVES

This study examined patient experiences after receiving elevated diabetes screening values using blood collected at a dental clinic. It explores patients' reactions to screening, whether or not they sought recommended medical follow-up, and facilitating factors and barriers to obtaining follow-up care.

METHODS

At the comprehensive care clinics at a large, urban College of Dentistry in the United States, haemoglobin A1C (HbA1C) values were obtained from 379 study participants who had not been previously diagnosed with diabetes. In all, 169 (44.6%) had elevated HbA1C values. We analysed quantitative and qualitative data concerning these patients' follow-up with primary care providers (PCPs).

RESULTS

We were able to contact 112 (66.3%) of the 169 study participants who had an elevated HbA1C reading. Of that group, 61 (54.5%) received recommended follow-up care from a PCP within 3 months, and an additional 28 (25.0%) said they intended to seek such care. Qualitative themes included the following: the screening letter - opportunity or burden, appreciation for the 3-month follow-up call and barriers to medical follow-up that included the following: lack of knowledge about diabetes, not understanding the importance of follow-up, busyness, financial concerns, fear and denial.

CONCLUSIONS

Quantitative and qualitative data demonstrate that dentists, dental hygienists and nurses are well poised to discover and translate new models of patient-centred, comprehensive care to patients with oral and systemic illness.

Toward Big Data Analytics: Review of Predictive Models in Management of Diabetes and Its Complications

Diabetes is one of the top priorities in medical science and health care management, and an abundance of data and information is available on these patients. Whether data stem from statistical models or complex pattern recognition models, they may be fused into predictive models that combine patient information and prognostic outcome results. Such knowledge could be used in clinical decision support, disease surveillance, and public health management to improve patient care. Our aim was to review the literature and give an introduction to predictive models in screening for and the management of prevalent short- and long-term complications in diabetes. Predictive models have been developed for management of diabetes and its complications, and the number of publications on such models has been growing over the past decade. Often multiple logistic or a similar linear regression is used for prediction model development, possibly owing to its transparent functionality. Ultimately, for prediction models to prove useful, they must demonstrate impact, namely, their use must generate better patient outcomes. Although extensive effort has been put in to building these predictive models, there is a remarkable scarcity of impact studies.

Application and applicability of non-invasive risk models for predicting undiagnosed prevalent diabetes in Africa: A systematic literature search

BACKGROUND AND PURPOSE

Prediction algorithms are increasingly advocated in diabetes screening strategies, particularly in developing countries. We conducted a systematic review to assess the application and applicability of existing non-invasive prevalent diabetes risk models to populations within Africa.

DESIGN

systematic review data sources A systematic search of English literatures in Medline via PubMed from 1999 until June, 2014. Study selection Included studies had to report on the development, validation or implementation of a model that was primarily constructed to predict prevalent undiagnosed diabetes using non-laboratory based predictors.

DATA EXTRACTION

Data were extracted on the type of statistical model, type and range of predictors in the model, performance measures in both internal and external validation, and whether the model was developed from, validated or implemented in an African population.

RESULTS

Twenty-three studies reporting on non-invasive prevalent diabetes models were identified. Ten from Europe (some with multiethnic populations), nine models were developed among Asian population, two from the USA and two from the Middle-East. The c-statistics for these models ranged from 0.65 to 0.88 in the development studies, and from 0.63 to 0.80 in the validation studies. Twenty models were validated, and none in Africa. Among predictors commonly included in models, parental/family history of diabetes and personal history of hypertension appear to be more prone to measurement errors in the African context.

CONCLUSION

Existing prevalent diabetes prediction models have not been applied to African populations, and issues with the measurement of key predictors make their applicability likely inaccurate.

Screening for prediabetes and type 2 diabetes in dental offices

Objectives

Most Americans see dentists at least once a year. Chair‐side screening and referral may improve diagnosis of prediabetes and diabetes. In this study, we developed a multivariate model to screen for dysglycemia (prediabetes and diabetes defined as HbA1c ≥5.7 percent) using information readily available to dentists and assessed the prevalence of dysglycemia in general dental practices.

Methods

We recruited 1,033 adults ≥30 years of age without histories of diabetes from 13 general dental practices. A sample of 181 participants selected on the basis of random capillary glucose levels and periodontal status underwent definitive diagnostic testing with hemoglobin A1c. Logistic models were fit to identify risk factors for dysglycemia, and sample weights were applied to estimate the prevalence of dysglycemia in the population ≥30 years of age.

Results

Individuals at high risk for dysglycemia could be identified using a questionnaire that assessed sex, history of hypertension, history of dyslipidemia, history of lost teeth, and either self‐reported body mass index ≥35 kg/m² (severe obesity) or random capillary glucose ≥110 mg/dl. We estimate that 30 percent of patients ≥30 years of age seen in these general dental practices had dysglycemia.

Conclusions

There is a substantial burden of dysglycemia in patients seen in general dental practices. Simple chair‐side screening for dysglycemia that includes or does not include fingerstick random capillary glucose testing can be used to rapidly identify high‐risk patients.

Practical implications

Further studies are needed to demonstrate the acceptability, feasibility, effectiveness, and cost‐effectiveness of chair‐side screening.

Point-of-Care HbA1c Testing with the A1cNow Test Kit in General Practice Dental Clinics: A Pilot Study Involving Its Accuracy and Practical Issues in Its Use

With millions of at-risk people undiagnosed with pre-diabetes and diabetes, there is a need to identify alternate screening sites for out-of-range glucose values. We examined practical issues and accuracy (relative to High Performance Liquid Chromatography testing in a laboratory) in the use of the A1cNow point of care device for this screening in general practice dental clinics at a large University-based Dental College. Health care professionals obtained evaluable readings for only 70% of the subjects, even after two attempts, and its use according to manufacturer's instructions was often challenging in the busy environment of the dental clinic. At thresholds for pre-diabetes and diabetes established by the American Diabetes Association, sensitivities of the A1cNow kit relative to the HPLC method were 91.9% and 100%, respectively. However, specificities for pre-diabetes and diabetes were 66.7% and 82.4%, respectively, indicating many false positive results. A better strategy for diabetes screening may involve a laboratory-based analysis approach that is patient- and provider-friendly, with minimal burden to the dental team.

The effect of periodontal therapy on glycaemic control in a Hispanic population with type 2 diabetes: a randomized controlled trial

OBJECTIVE

In the Mexican-American population, the prevalence of Type 2 diabetes mellitus (T2DM) is as high as 50% of the population. This randomized controlled clinical trial was designed to elucidate how treatment of periodontal disease affects HbA1c values in this population.

MATERIALS AND METHODS

One hundred and fifty-four T2DM patients with periodontal disease were enrolled in the study. The test group was treated with scaling and root planing (SRP); the control group received oral hygiene instructions. At baseline and 4-6 weeks after therapy, a complete periodontal examination was performed. Blood was collected at baseline and 4 months later for HbA1c levels.

RESULTS

One hundred and twenty-six individuals completed the study. Baseline mean ± SD HbA1c for the test and control groups were 9.0 ± 2.3% and 8.4 ± 2.0% respectively. Non-significant difference in HbA1c reductions (0.6 ± 2.1% and 0.3 ± 1.7%) was found between test and control groups at 4 months. Comparisons of the periodontal clinical parameters between the test and control groups found significant differences with improved results in the test subjects.

CONCLUSIONS

No statistically significant differences were found in the changes of HbA1c levels between test and control groups. Non-surgical periodontal therapy improved the magnitude of change in periodontal parameters as compared to the control subjects. ClinicalTrials.gov Identifier: NCT01128374.

Risk factors for periodontal disease

Risk factors play an important role in an individual's response to periodontal infection. Identification of these risk factors helps to target patients for prevention and treatment, with modification of risk factors critical to the control of periodontal disease. Shifts in our understanding of periodontal disease prevalence, and advances in scientific methodology and statistical analysis in the last few decades, have allowed identification of several major systemic risk factors for periodontal disease. The first change in our thinking was the understanding that periodontal disease is not universal, but that severe forms are found only in a portion of the adult population who show abnormal susceptibility. Analysis of risk factors and the ability to statistically adjust and stratify populations to eliminate the effects of confounding factors have allowed identification of independent risk factors. These independent but modifiable, risk factors for periodontal disease include lifestyle factors, such as smoking and alcohol consumption. They also include diseases and unhealthy conditions such as diabetes mellitus, obesity, metabolic syndrome, osteoporosis, and low dietary calcium and vitamin D. These risk factors are modifiable and their management is a major component of the contemporary care of many periodontal patients. Genetic factors also play a role in periodontal disease and allow one to target individuals for prevention and early detection. The role of genetic factors in aggressive periodontitis is clear. However, although genetic factors (i.e., specific genes) are strongly suspected to have an association with chronic adult periodontitis, there is as yet no clear evidence for this in the general population. It is important to pursue efforts to identify genetic factors associated with chronic periodontitis because such factors have potential in identifying patients who have a high susceptibility for development of this disease. Many of the systemic risk factors for periodontal disease, such as smoking, diabetes and obesity, and osteoporosis in postmenopausal women, are relatively common and can be expected to affect most patients with periodontal disease seen in clinics and dental practices. Hence, risk factor identification and management has become a key component of care for periodontal patients.

Improved diabetes screening using an extended predictive feature search

BACKGROUND

Screening entire populations for diabetes is not cost-effective. Hence, an efficient screening process must select those people who are at high risk for diabetes. In this study, we investigated whether screening procedures could be improved using an extended predictive feature search.

MATERIALS AND METHODS

In order to develop our model and identify persons with diabetes (prevalence) we used data from years of the National Health and Nutrition Examination Survey (2005-2010), which has not been explored for this purpose before. We calculated all combinations of predictors in order to identify the optimal subset, and we used a linear logistic classification model to predict diabetes. V-fold cross-validation was used for the process of including variables and for validating the final models. This new model was compared with two established models.

RESULTS

In total, 5,398 participants were included in this study. Among these, 478 participants had unidentified diabetes. The established models had a receiver operating characteristics curve for the area under the curve (AUC) of 0.74 and 0.71 compared with an AUC of 0.78 for the new model, showing a significant difference (P<0.05). A proposed cutoff point for the established models yielded respective sensitivities/specificities of 63%/72% and 40%/72% compared with the new model, which had a sensitivity/specificity of 70%/72%.

CONCLUSIONS

Our data indicate that simple healthcare and economic information such as ratio of family income to poverty can add value in deciding who is at risk of unknown diabetes by using extended investigations of predictor combinations.

Association between oral health status and type 2 diabetes mellitus among Sudanese adults: a matched case-control study

AIM

The purpose of this study was to compare the clinical and subjective oral health indicators of type 2 diabetic patients (T2DM) with age and gender matched non-diabetic controls. A second aim was to identify clinical and subjective oral health indicators that discriminate between well-controlled and poorly controlled T2DM patients as well as between patients with long and short duration of the disease.

METHODS

A total of 457 individuals participated in the study (154 T2DM cases and 303 non-diabetic controls). The T2DM group was sub-divided according to metabolic control [(well-controlled: glycosylated haemoglobin test 8%), (poorly controlled: glycosylated haemoglobin test > 8%)] and according to duration of T2DM [(long duration: >10 years), (short duration: 10 years)]. Participants were interviewed using a structured questionnaire including socio-demographics, lifestyle and oral health related quality of life factors. The clinical examination comprised full mouth probing depths, plaque index, tooth mobility index, furcation involvement and coronal and root surface caries.

RESULTS

The T2DM patients presented with more probing depths 4 mm, furcation involvement, tooth mobility, missing teeth, and oral impacts on daily performance (OIDP). The corresponding adjusted odds ratios and their 95% confidence intervals were 4.07 (1.74-9.49), 2.96 (1.36-6.45), 5.90 (2.26-15.39), 0.23 (0.08-0.63) and 3.46 (1.61-7.42), respectively. Moreover, the odds ratio was 2.60 (1.21-5.55) for the poorly controlled T2DM patients to have high levels of mobility index and 2.94 (1.24-6.94) for those with long duration of T2DM to have high decayed, missed and filled teeth (DMFT) values.

CONCLUSION

This study revealed that chronic periodontitis, tooth mobility, furcation involvement and OIDP were more prevalent among T2DM patients compared to their non-diabetic controls.

Type 2 diabetes and edentulism as chronic co-morbid factors affecting Indian elderly: an overview

In past 50 years, type 2 diabetes has emerged as one of the major public health problem. India leads the world with the largest number of diabetic patients and has a huge elderly population. The present article discusses the effect of diabetes and edentulism on the overall general health of elderly. The prevalence of type 2 diabetes and edentulism in Indian elderly and their inter-relationship has been discussed. Dentists must provide optimum oral care with special attention towards comprehensive periodontal management and oral hygiene awareness among diabetics to prevent tooth loss. Dental and medical professionals can improve patient management of the oral and overall effects of diabetes by implementing various awareness programs; organizing camps; distributing informative pamphlets and dietary counseling. Dentists can detect undiagnosed cases of diabetes and refer patients to physicians for further evaluation and management.

Dental clinics as potent sources for screening undiagnosed diabetes and prediabetes

INTRODUCTION

This pilot study investigated the efficacy of dental clinics as potent sources for screening diabetes and prediabetes in undiagnosed individuals.

METHODS

Data were randomly collected from 385 patients (aged 40 years and older) visiting dental clinics. Patients already having a diagnosis of diabetes and/or prediabetes were excluded. Demographic data, body mass index and family and dental histories were recorded. Signs and symptoms of diabetes were investigated. Random blood glucose levels (RBGLs) were recorded. Individuals with RBGL ≥110 mg/dL underwent the oral glucose tolerance test and the glycosylated hemoglobin test (HbA1c).

RESULTS

Of the 385 patients, 60% (232) had RBGL <110 mg/dL, whereas 40% (153) had RBGL ≥110 mg/dL. Prevalence of confirmed diabetes and prediabetes among the study participants was 16.4% and 15.8%, respectively. Body mass index was significantly higher among patients with diabetes and prediabetes as compared with healthy controls. HbA1c level was statistically significantly higher among patients with diabetes than among patients with prediabetes. Symptoms of polyuria and polydipsia were significantly higher among patients with diabetes than in those without diabetes.

CONCLUSIONS

A high percentage of undiagnosed type 2 diabetes and prediabetes among patients visiting dental clinics was found compared with that reported in the medical literature. Further studies with a lager sample size are needed to confirm these results.

Effectiveness of screening for diabetes mellitus in dental health care

AIMS

  The aim of the present study was to test the effectiveness of opportunistic blood glucose screening in a cooperational framework between dental and primary health care.

METHODS

  Altogether, 1568 subjects, age 20-75 years, with no previous history of diabetes, who came for a regular dental examination, had their non-fasting blood glucose measured with a portable blood glucose meter. Subjects with a concentration of ≥ 6.7 mmol/l (121 mg dl(-1) ) were referred to their primary healthcare centre for follow-up. The outcome, a diagnosis of diabetes mellitus, was obtained from primary healthcare centre and hospital patient records, during 3 years after screening.

RESULTS

  Of the 155 (9.9%) subjects who screened positive, 139 (89.7%) came to their primary healthcare centre within the 3-year follow-up period and nine (5.8%) were diagnosed as having diabetes mellitus according to the World Health Organization criteria. Of the 1413 subjects who screened negative, 1137 (80.5%) came to the primary healthcare centre and eight (0.6%) were found to have diabetes mellitus. Screening sensitivity was 52.9%, specificity 90.6% and positive predictive value 5.8%. The number of subjects needed to screen to find one case of diabetes was 196. Delineating the study population to those 40- to 75-year-olds with a BMI ≥ 25 kg/m(2) , and 30-to 75-year-olds with a BMI ≥ 30 kg/m(2) , the numbers needed to screen was reduced to 96.

CONCLUSIONS

  Cooperation between dental and primary care for high blood glucose screening and follow-up appears to be a feasible method for early diagnosis of diabetes.

Tooth loss, pocket depth, and HbA1c information collected in a dental care setting may improve the identification of undiagnosed diabetes

SUBJECTS

A total of 506 adults participated in this study. The study population was recruited from a pool of new patients presenting to the Columbia University College of Dental Medicine over a 12-month period (April 2009 to March 2010). New patients were screened to determine potential eligibility for participation based on 2 criteria: age and knowledge of their diabetes status. Non-Hispanic white adults were required to be 40 years old or older and Hispanic or non-white adults were required to be 30 years or older. Additionally, all potential participants had to respond that a health care provider had never told them that they had diabetes or prediabetes. This screening yielded 601 individuals. From this group, 535 were selected based on having 1 of 4 self-reported risk factors (hypertension, high cholesterol, overweight, or a family history of diabetes). These 535 adults continued with a periodontal examination and an HbA1c test. Five hundred six participants returned for a follow-up visit to collect blood for a fasting plasma glucose (FPG) test.

KEY RISK/STUDY FACTOR

HbA1c test, and dentate and periodontal status.

MAIN OUTCOME MEASURE

FPG level.

MAIN RESULTS

Among the 535 individuals participating in the study, 161 were determined potentially to be prediabetic (FPG was 100-125 mg/dL) and 21 potentially to be diabetic (FPG ≥ 126 mg/dL). Receiver operating characteristics (ROCs) via logistic regression was used to assess model performance and calculate key findings. The area under the curve of a multivariate regression model that included oral health status indicators and all 4 self-reported risk factors had a predicted value of 0.68 (confidence interval [CI]: 0.63, 0.73) for abnormal FPG (≥100 mg/dL). A model with just the percentage of periodontal pockets ≥5 mm and the number of missing teeth had a predicted value of 0.65 (CI: 0.60, 0.70). When the test results from HbA1C were added to the simpler model, the predictive value improved to 0.79 (CI: 0.75, 0.83). The authors also determined that the presence of 4 or more missing teeth or having pocket depth of 5 mm or more involving more than 25% of the sites identified 73% of the true cases (ie, abnormal FPG).

CONCLUSIONS

Dental care professionals have the potential to identify patients at risk for diabetes and refer them to a physician for follow-up evaluation.

Assessment and management of patients with diabetes mellitus in the dental office

Diabetes mellitus is a serious chronic disease that affects many dental patients. Dental professionals have the potential and responsibility to assume an active role in the early identification, assessment, and management of their patients who present with or are at risk of developing diabetes. Close maintenance, meticulous monitoring of individual patient needs, and close collaboration with other health care professionals involved in the care will enable better control of the oral complications of diabetes and contribute to the better management of the patient's overall health status.

A novel intraoral diabetes screening approach in periodontal patients: results of a pilot study

BACKGROUND

This pilot study examines whether a novel diabetes screening approach using gingival crevicular blood (GCB) could be used to test for hemoglobin A1c (HbA1c) during periodontal visits.

METHODS

Finger-stick blood (FSB) samples from 120 patients and GCB samples from those patients with adequate bleeding on probing (BOP) were collected on special blood collection cards and analyzed for HbA1c levels in a laboratory. The Pearson correlation coefficient was used to measure correlation between FSB and GCB HbA1c values for 75 paired FSB and GCB samples. A receiver-operator characteristic curve (ROC) analysis was performed to determine an optimal GCB HbA1c criterion value for a positive diabetes screen.

RESULTS

For the 75 paired samples, the Pearson correlation coefficient was 0.842. The ROC analysis identified a criterion value of 6.3% for the GCB HbA1c test with high sensitivity (0.933) and high specificity (0.900), corresponding to FSB HbA1c values ≥6.5% (in the diabetes range). Using this GCB HbA1c criterion value for 27 additional paired samples, in which there was an unidentified component observed to coelute within the elution window of GCB HbA1c in the laboratory, there was agreement between FSB and GCB values for 24 of the pairs according to whether both were within or outside of the diabetes range.

CONCLUSION

Using a criterion value of 6.3%, GCB samples are acceptable for HbA1c testing to screen for diabetes in most persons with BOP at the GCB collection site.