Myocardial infarction (MI) is a major global health concern influenced by diverse risk factors. Despite growing evidence of oral– systemic connections, current MI models largely exclude oral health indicators, reflecting the longstanding separation between dental and medical paradigms. This study introduces a multidomain, interpretable machine learning framework that integrates detailed periodontal and oral hygiene variables, marking one of the first efforts to quantitatively incorporate these features into MI incidence identification. A population-based case-control dataset comprising 1,355 individuals and heterogeneous variables was used to train and evaluate seven supervised classifiers via nested cross-validation. Among them, XGBoost achieved the best performance (AUC = 0.88±0.01; F1 score = 0.74±0.03) and was further probability-calibrated using isotonic regression, yielding a mean Brier score of 0.14±0.01 and demonstrating well-aligned predicted probabilities. SHAP values confirmed the importance of conventional cardiovascular predictors, while several periodontal indicators such as mean clinical attachment loss, plaque index, and gingival bleeding emerged among the most influential features. Sex-stratified SHAP analysis revealed sex-specific patterns in the relative impact of oral features. Additionally, individual-level waterfall plots illustrated how oral inflammation may contribute independently or in combination with conventional factors to MI incidence identification. These findings support a systems-level view of periodontitis as a modifiable, biologically relevant factor in cardiovascular health and underscore the value of considering oral-health markers within screening and management frameworks.

BackgroundIt has been well documented that periodontal treatment decreases the levels of certain disease-associated species in subgingival plaque. Few studies, however, investigate to which extent periodontal therapy restores a health-like subgingival community. Here, we conducted a secondary analysis to evaluate microbiome outcomes of nonsurgical periodontal therapy alone or followed by an intensive antiplaque regimen, analyzing microbiome trajectories at the community level with respect to health.MethodsEighty-six subjects with periodontitis stages II/III were evaluated at baseline and 6 months after receiving scaling and root planing alone (SRP, n = 41) or followed by an antiplaque regimen consisting of use of 0.12% chlorhexidine for 3 months and interdental cleaners for 6 months (SRP + P + S, n = 45). Thirty periodontally healthy subjects served as reference. The subgingival microbiome was characterized by 16S rRNA gene sequencing, and longitudinal within-subject changes were quantified with respect to a healthy plane (HPL) modeled from the reference group.ResultsEvaluation of individual microbiome trajectories showed that only the SRP + P + S group had a statistically significant reduction in distance to the HPL. However, responses were variable in both groups, with only a fraction of individuals changing in the direction of health. Random forest analysis revealed baseline microbiome composition as a greater predictor of microbiome response than type of treatment rendered.ConclusionAn adjunct antiplaque regimen resulted in a greater approximation of the microbiome to the healthy state. However, responses varied greatly among subjects highlighting the need for robust and personalized approaches to restore eubiosis.Plain Language SummaryThis study looked at how different treatments for gum disease change the bacteria in the gums of people with moderate to severe gum problems. Eighty-six people received standard gum treatments, and some also used a mouthwash and special tools to clean between their teeth at home. After 6 months, more people in the group that added the extra cleaning steps had healthier bacteria in their gums than people who received the standard treatment. However, not everyone responded the same way. The study found that the types of bacteria someone had at the start were better at predicting how well the treatment would work, more than the type of treatment itself. This means gum disease treatments may need to be personalized for better results.

It has been well documented that periodontal treatment decreases the levels of certain disease-associated species in subgingival plaque. Few studies, however, investigate to which extent periodontal therapy restores a health-like subgingival community. Here, we conducted a secondary analysis to evaluate microbiome outcomes of nonsurgical periodontal therapy alone or followed by an intensive antiplaque regimen, analyzing microbiome trajectories at the community level with respect to health. Eighty-six subjects with periodontitis stages II/III were evaluated at baseline and 6 months after receiving scaling and root planing alone (SRP, n  = 41) or followed by an antiplaque regimen consisting of use of 0.12% chlorhexidine for 3 months and interdental cleaners for 6 months (SRP + P + S, n  = 45). Thirty periodontally healthy subjects served as reference. The subgingival microbiome was characterized by 16S rRNA gene sequencing, and longitudinal within-subject changes were quantified with respect to a healthy plane (HPL) modeled from the reference group. Evaluation of individual microbiome trajectories showed that only the SRP + P + S group had a statistically significant reduction in distance to the HPL. However, responses were variable in both groups, with only a fraction of individuals changing in the direction of health. Random forest analysis revealed baseline microbiome composition as a greater predictor of microbiome response than type of treatment rendered. An adjunct antiplaque regimen resulted in a greater approximation of the microbiome to the healthy state. However, responses varied greatly among subjects highlighting the need for robust and personalized approaches to restore eubiosis. This study looked at how different treatments for gum disease change the bacteria in the gums of people with moderate to severe gum problems. Eighty-six people received standard gum treatments, and some also used a mouthwash and special tools to clean between their teeth at home. After 6 months, more people in the group that added the extra cleaning steps had healthier bacteria in their gums than people who received the standard treatment. However, not everyone responded the same way. The study found that the types of bacteria someone had at the start were better at predicting how well the treatment would work, more than the type of treatment itself. This means gum disease treatments may need to be personalized for better results.

Intestinal colonization of the oral bacterium Haemophilus parainfluenzae has been associated with Crohn's disease (CD) severity and progression. This study examines the role of periodontal disease (PD) as a modifier for colonization of H. parainfluenzae in patients with CD and explores the mechanisms behind H. parainfluenzae-mediated intestinal inflammation. Fifty subjects with and without CD were evaluated for the presence of PD, and their oral and fecal microbiomes were characterized. PD is associated with increased levels of H. parainfluenzae strains in subjects with CD. Oral inoculation of H. parainfluenzae elicits strain-dependent intestinal inflammation in murine models of inflammatory bowel disease, which is associated with increased intestinal interferon-γ (IFN-γ)+ CD4+ T cells and disruption of the host hypusination pathway. In summary, this study establishes a strain-specific pathogenic role of H. parainfluenzae in intestinal inflammation and highlights the potential effect of PD on intestinal colonization by pathogenic H. parainfluenzae strains in patients with CD.

Recent epidemiological studies have shown that inflammatory bowel disease is associated with periodontal disease. The oral-gut microbiota axis is a potential mechanism intersecting the two diseases. Porphyromonas gingivalis is currently considered a keystone oral pathogen involved in periodontal disease pathogenesis and disease progression. Recent studies have shown that oral ingestion of P. gingivalis leads to intestinal inflammation. However, the molecular underpinnings of P. gingivalis-mediated gut inflammation have remained elusive. In this study, we show that the oral administration of P. gingivalis indeed leads to ileal inflammation and alteration in gut microbiota with significant reduction in bacterial alpha diversity despite the absence of P. gingivalis in the lower gastrointestinal tract. Utilizing an antibiotic-conditioned mouse model, cecal microbiota transfer experiments were performed to demonstrate that P. gingivalis-induced dysbiotic gut microbiota is sufficient to reproduce gut pathology. Furthermore, we observed a significant expansion in small intestinal lamina propria IL9+ CD4+ T cells, which was negatively correlated with both bacterial and fungal alpha diversity, signifying that P. gingivalis-mediated intestinal inflammation may be due to the subsequent loss of gut microbial diversity. Finally, we detected changes in gene expression related to gut epithelial barrier function, showing the potential downstream effect of intestinal IL9+ CD4+ T-cell induction. This study for the first time showed the mechanism behind P. gingivalis-mediated intestinal inflammation where P. gingivalis indirectly induces intestinal IL9+ CD4+ T cells and inflammation by altering the gut microbiota. Understanding the mechanism of P. gingivalis-mediated intestinal inflammation may lead to the development of novel therapeutic approaches to alleviate the morbidity from inflammatory bowel disease patients with periodontal disease.

Aging invokes physiological changes, such as immunosenescence and inflammation, that could increase host susceptibility to oral microbiome shifts that enable periodontitis progression in later life. At present, there is a dearth of studies specifically evaluating the oral microbiome and periodontitis in older adults. We used high-throughput untargeted sequencing methods and functional metagenomic analyses to assess and compare the subgingival biofilm of postmenopausal women (mean age 71 years) according to periodontitis status. Subgingival plaque samples were obtained from 15 postmenopausal women with no periodontitis, and from 15 women with severe periodontitis, determined by probing measures. The 16S rRNA gene (V1–V3 region) was sequenced on the 454 FLX platform. The PICRUSt technique was used to provide information on what the potential functional characteristics of microbiota might be in healthy, compared with diseased, periodontium. The subgingival microbiome associated with periodontitis showed clear differences to that associated with health. Of the 464 species identified, 22.8% had elevated abundance in disease, while only 6.3% had elevated abundance in health. Among the 12 most prevalent organisms in periodontitis, one-half have previously been recognized as periodontal pathogens by other investigators. The subgingival microbiome in periodontitis contained genes that could code for specific activities, including microbial mobility, synthesis of endotoxin, and proteolytic degradation. The healthy microbiome included genes that could code for sustaining microbial life, including encoding for transporters, glycolysis, gluconeogenesis, the Krebs cycle, and protein kinases. In the present study on postmenopausal women, aged 60 and older, the subgingival microbiome differed in composition and potential function between those with and without periodontitis. Studies of functional gene expression, such as transcriptomics, are needed to definitively identify the molecules carrying out functions associated with pathogenic subgingival complexes. This, in turn, could lead to identification of targets for enhanced management of periodontitis and, possibly, other diseases, in later life.

AIM:The goal of the present longitudinal cohort study was to examine patterns of periodontal disease progression at progressing sites and subjects defined based on linear mixed models (LMM) of clinical attachment loss (CAL).MATERIALS AND METHODS:A total of 113 periodontally healthy and 302 periodontitis subjects had their CAL calculated bimonthly for 12 months. LMMs were fitted for each site and the predicted CAL levels used to categorize their progression state. Participants were grouped based on the number of progressing sites into unchanged, transitional and active subjects. Patterns of periodontal disease progression were explored using descriptive statistics.RESULTS:Progression occurred primarily at molars (50% of progressing sites) and inter-proximal sites (72%), affected a higher proportion of deep than shallow sites (2.7% versus 0.7%), and pocketing was the main mode of progression (49%). We found a low level of agreement (47%) between the LMM and traditional approaches to determine progression such as change in CAL ≥3 mm. Fourteen per cent of subjects were classified as active and among those 93% had periodontitis. The annual mean rate of progression for the active subjects was 0.35 mm/year.CONCLUSION:Progressing sites and subjects defined based on LMMs presented patterns of disease progression similar to those previously reported in the literature.

AbstractAimThe goal of this study was to identify progressing periodontal sites by applying linear mixed models (LMM) to longitudinal measurements of clinical attachment loss (CAL).MethodsNinety‐three periodontally healthy and 236 periodontitis subjects had their CAL measured bi‐monthly for 12 months. The proportions of sites demonstrating increases in CAL from baseline above specified thresholds were calculated for each visit. The proportions of sites reversing from the progressing state were also computed. LMM were fitted for each tooth site and the predicted CAL levels used to categorize sites regarding progression or regression. The threshold for progression was established based on the model‐estimated error in predictions.ResultsOver 12 months, 21.2%, 2.8% and 0.3% of sites progressed, according to thresholds of 1, 2 and 3 mm of CAL increase. However, on average, 42.0%, 64.4% and 77.7% of progressing sites for the different thresholds reversed in subsequent visits. Conversely, 97.1%, 76.9% and 23.1% of sites classified as progressing using LMM had observed CAL increases above 1, 2 and 3 mm after 12 months, whereas mean rates of reversal were 10.6%, 30.2% and 53.0% respectively.ConclusionLMM accounted for several sources of error in longitudinal CAL measurement, providing an improved method for classifying progressing sites.

BACKGROUND:In this field trial, the authors assess the feasibility of screening for diabetes and prediabetes in dental practices and in a community health center.METHODS:Dental patients 45 years and older who were not aware of their diabetic status underwent evaluation for diabetes risk with an American Diabetes Association Diabetes Risk Test and with hemoglobin (Hb) A1c measurement. Participants with an HbA1c level of 5.7 percent or greater were referred to their physicians for diagnosis.RESULTS:Of the 1,022 patients screened, 416 (40.7 percent) had an HbA1c blood level of 5.7 percent or greater and were referred for diagnosis. The HbA1c and the American Diabetes Association Diabetes Risk Test were correlated (P < .001). Of the 416 participants who were referred, 35.1 percent received a diagnosis from their physicians within one year; 78.8 percent of these patients were seen in the community health center and 21.4 percent were seen in private dental offices. The diagnoses were diabetes (12.3 percent of patients), high risk of developing diabetes (that is, prediabetes) (23.3 percent) and no diabetes (64.4 percent).CONCLUSIONS:The study results show that screening for prediabetes and diabetes is feasible in a dental office, with acceptance by the dentist and dental office staff members, patients' physicians and patients. Patients from the community health center demonstrated good compliance with referrals to physicians; however, compliance was poor among those in the private dental offices.PRACTICAL IMPLICATIONS:Screening for diabetes and prediabetes in the dental office may provide an important benefit to patients and encourage interprofessional collaboration to achieve a chronic care model in which health care professionals work together to care for a panel of patients.

Background After clinical trials end, continued follow-up of the assembled cohort often is desirable for additional research. Factors influencing participants' decisions to consent to additional follow-up and how these shape posttrial cohorts have not been broadly studied.Purpose We examined how two re-enrollment campaigns and the passage of time altered features of the posttrial cohorts compared with the original Women's Health Initiative (WHI) Hormone Therapy clinical trials.Methods We examined associations that markers of sociodemography, health, lifestyle, and on-trial experiences had with re-enrollment and contrasted the characteristics of successive posttrial cohorts with those of the original enrollees.Results The posttrial enrollment campaigns re-enrolled 81.1% and 82.5% of available women, respectively. Women who re-enrolled tended to have better health characteristics than those not re-enrolled. Compared to women of comparable age in the original cohort, women retained for the second posttrial follow-up less often had a history of cardiovascular disease (odds ratio (OR) = 0.36), hypertension (OR = 0.57), diabetes (OR = 0.59), or measured cognitive deficit (OR = 0.40). These women more often had graduated from high school (OR = 1.72) and had participated in other WHI trials (OR = 1.76).Limitations We have examined experience with creating follow-up cohorts from participants in a single study. Thus, our findings may not apply to other cohorts and protocols.Conclusions Posttrial enrollment in follow-up studies can be successful; however, the characteristics of the resulting cohort may differ substantially from the originally assembled group of trial participants. Collection during the original trial of potential predictors of differential re-enrollment may strengthen interpretation of findings.

Multiplexing arrays increase the throughput and decrease sample requirements for studies employing multiple biomarkers. The goal of this project was to examine the performance of Multiplex arrays for measuring multiple protein biomarkers in saliva and serum. Specimens from the OsteoPerio ancillary study of the Women's Health Initiative Observational Study were used. Participants required the presence of at least 6 teeth and were excluded based on active cancer and certain bone issues but were not selected on any specific condition. Quality control (QC) samples were created from pooled serum and saliva. Twenty protein markers were measured on five multiplexing array panels. Sample pretreatment conditions were optimized for each panel. Recovery, lower limit of quantification (LLOQ) and imprecision were determined for each analyte. Statistical adjustment at the plate level was used to reduce imprecision estimates and increase the number of usable observations. Sample pre-treatment improved recovery estimates for many analytes. The LLOQ for each analyte agreed with manufacturer specifications except for MMP-1 and MMP-2 which were significantly higher than reported. Following batch adjustment, 17 of 20 biomarkers in serum and 9 of 20 biomarkers in saliva demonstrated acceptable precision, defined as <20% coefficient of variation (<25% at LLOQ). The percentage of cohort samples having levels within the reportable range for each analyte varied from 10% to 100%. The ratio of levels in saliva to serum varied from 1∶100 to 28∶1. Correlations between saliva and serum were of moderate positive magnitude and significant for CRP, MMP-2, insulin, adiponectin, GM-CSF and IL-5. Multiplex arrays exhibit high levels of analytical imprecision, particularly at the batch level. Careful sample pre-treatment can enhance recovery and reduce imprecision. Following statistical adjustments to reduce batch effects, we identified biomarkers that are of acceptable quality in serum and to a lesser degree in saliva using Multiplex arrays.

BACKGROUND:The direct effect of periodontal pathogens on atherosclerotic plaque development has been suggested as a potential mechanism for the observed association between periodontal disease and coronary heart disease, but few studies have tested this theory.OBJECTIVES:(i) To assess the association of periodontal pathogens in periodontal pockets with the risk of myocardial infarction (MI) and (ii) to assess whether an increase in the number of periodontal bacterial species increases the risk of MI.METHODS:A total of 313 cases and 747 controls, consisting of Caucasian men and women from Western New York, aged 35 to 69 years, were recruited for this study. The presence of microorganisms was assessed by indirect immunofluorescence microscopy, using species-specific polyclonal and monoclonal serodiagnostic reagents. The presence of six periodontal pathogens, Porphyromonas gingivalis (Pg), Tannerella forsythensis (Tf), Prevotella intermedia (Pi), Campylobacter recta (Cr), Fusobacterium nucleatum (Fn), and Eubacterium saburreum (Es), and their co-occurrence (0-6) was compared with the odds of having myocardial infarction.RESULTS:Univariate analyses revealed a higher percentage of the presence of each bacterium in cases compared to controls. In multivariate analyses, only Tf and Pi were statistically associated with an increase in the odds of having MI [Odds ratio OR=1.62; 95% CI (1.18-2.22); and 1.40; 95% (1.02-1.92), respectively] after adjusting for age, gender, education, cholesterol, high blood pressure, diabetes, and total pack-years of cigarette smoking. An increase in the number of different periodontal bacteria in pockets was also found to increase the odds of MI [adjusted OR=1.14; 95% CI (1.03-1.26)]. Participants who had three species or more of periodontal pathogens had about 2-fold increase in odds of having nonfatal MI than those who did not have any type of bacterial species [OR=2.01 (1.31-3.08)].CONCLUSION:The presence of periodontal pathogens, specifically Tf or Pi, and an increase in total burden of periodontal pathogenic species were both associated with increased odds of having MI. However, further studies are needed to better assess any causal relationship, as well as the biological mechanisms underlying this association.

BACKGROUND:Periodontal disease and cardiovascular disease (CVD) have been the focus of much research, but little is known about their roles in the recurrent event risk in patients with CVD. This study investigates whether periodontal disease is related to recurrent CVD events and mortality in survivors of incident myocardial infarction (MI).METHODS:Participants (668 males and 216 females; mean age: 54 + or - 8.5 years) were recruited (1997 through 2004) from two western New York county hospitals and completed an interviewer-administered questionnaire regarding lifestyle habits, clinical measurements, and a comprehensive dental examination. The periodontal disease status was measured by the mean clinical attachment loss (AL). Follow-up surveys assessed hospitalizations or medical procedures; cardiovascular events were validated by medical records. A National Death Index (NDI) Plus search was conducted. The outcome was recurrent fatal and non-fatal cardiovascular events (International Classification of Diseases codes 390 to 450).RESULTS:After an average follow-up of 2.9 years, 154 events were reported. Among never-smokers, the adjusted hazard ratio (95% confidence interval) for the mean clinical AL (millimeters) was 1.43 (1.09 to 1.89). No associations were found in ever-smokers (clinical AL by smoking interaction: P <0.05).CONCLUSION:These findings indicate that periodontal disease may be an important factor in determining recurrent cardiovascular events in MI patients and not merely a marker for the effects of cigarette smoking.

BACKGROUNDIn the Periodontitis and Vascular Events (PAVE) pilot study, periodontal therapy was provided as an intervention in a secondary cardiac event prevention model through five coordinated cardiac-dental centers.METHODSSubjects were randomized to either community care or protocol provided scaling and root planing to evaluate effects on periodontal status and systemic levels of high-sensitivity C-reactive protein (hs-CRP).RESULTSAfter 6 months, there was a significant reduction in mean probing depth and extent of 4- or 5-mm pockets. However, there were no significant differences in attachment levels, bleeding upon probing, or extent of subgingival calculus comparing subjects assigned to protocol therapy (n = 151) to those assigned to community care (n = 152). Using intent-to-treat analyses, there was no significant effect on serum hs-CRP levels at 6 months. However, 48% of the subjects randomized to community care received preventive or periodontal treatments. Secondary analyses demonstrated that consideration of any preventive or periodontal care (i.e., any treatment) compared to no treatment showed a significant reduction in the percentage of people with elevated hs-CRP (values >3 mg/l) at 6 months. However, obesity nullified the periodontal treatment effects on hs-CRP reduction. The adjusted odds ratio for hs-CRP levels >3 mg/l at 6 months for any treatment versus no treatment among non-obese individuals was 0.26 (95% confidence interval: 0.09 to 0.72), adjusting for smoking, marital status, and gender.CONCLUSIONThis pilot study demonstrated the critical role of considering obesity as well as rigorous preventive and periodontal care in trials designed to reduce cardiovascular risk.

BACKGROUND:During the last 15 years, a substantial number of population-based, clinical, laboratory, and animal studies have been published that reported findings on the relationship between periodontal disease and cardiovascular disease. The Periodontitis and Vascular Events (PAVE) pilot study was conducted to investigate the feasibility of a randomized secondary prevention trial to test whether treatment of periodontal disease reduces the risk for cardiovascular disease. This article describes the occurrence of adverse events during the pilot study.METHODS:The PAVE pilot study was a multicenter, randomized trial comparing periodontal therapy to community dental care. Baseline and follow-up clinic visits included a periodontal examination; blood, subgingival plaque, and crevicular fluid specimen collection; and medical and dental histories. Telephone follow-up contacts were scheduled to occur 3 months after randomization and every 6 months thereafter to assess adverse events or endpoints.RESULTS:Cardiovascular adverse events occurred with similar frequency (23 versus 24 [P = 0.85] in the community control and the treatment groups, respectively). There were 15 serious adverse events (SAEs) with a non-significantly higher percentage occurring in the community care group (6.6% versus 3.3%; P = 0.19). A time-to-event analysis of patterns of SAEs indicated that subjects in the periodontal therapy group tended to be less likely to experience an SAE over the entire 25 months of the study.CONCLUSION:For those individuals who remained in the study, it appears that provision of periodontal scaling and root planing treatment to individuals with heart disease resulted in a similar pattern of adverse events as seen in the community care group, which also received some treatment.

BACKGROUND:Population-based clinical and laboratory studies have reported findings providing support for a possible relationship between periodontal disease and cardiovascular disease. The Periodontitis and Vascular Events (PAVE) pilot study was conducted to investigate the feasibility of a randomized secondary prevention trial to test whether treatment of periodontal disease reduces the risk for cardiovascular disease.METHODS:Five clinical centers recruited participants who had documented coronary heart disease and met study criteria for periodontal disease. Eligible participants were randomized to receive periodontal therapy provided by the study or community dental care. Follow-up telephone calls and clinic visits were planned to alternate at 3-month intervals after randomization, with all participants followed until at least the 6-month clinic visit. Participants were followed for adverse events and periodontal and cardiovascular outcomes.RESULTS:A total of 303 participants were randomized. Recruitment that involved active participation of a cardiologist with responsibility for the patients worked best among the strategies used. Of those who had not withdrawn, 93% completed the 6-month contact. During follow-up, 11% of the 152 subjects in the community dental care group reported receiving periodontal therapy outside of the study.CONCLUSIONS:If appropriate recruitment strategies are used, this pilot study demonstrated that it is feasible to conduct a secondary prevention trial of periodontal therapy in patients who have had coronary heart disease. If a community dental care group is used, sample size estimation needs to take into account that a non-trivial proportion of participants in this group may receive periodontal therapy outside of the study.

BACKGROUNDPublic health and other population-based studies often depend on participants' self-reported disease status to assess prevalence, incidence, and disease trends. We sought to assess the feasibility of self-reported periodontal disease measures using dental history questions combined with demographic and medical history to predict periodontal disease.METHODSWe evaluated results from two separate population-based studies carried out at the University at Buffalo, Buffalo, New York, i.e., the "Periodontal Infection and Risk for Myocardial Infarction Study," a study of 1,578 adults assessing the association between periodontal disease and myocardial infarction and the "Periodontal Disease Research Center" (the Erie County Study), an epidemiologic risk assessment study of 1,438 adults. In each study, an extensive list of oral health questions was asked, and a comprehensive medical history, blood analysis using chemistry and hematology tests, and demographic data were collected.RESULTSUsing a predefined measure of severity of periodontal disease, we compared patients with severe disease to all others (i.e., those with moderate and no or mild disease). We examined areas under the curve (AUC) of the receiver operating curve to determine the best models, adding one, two, or three dental variables in all possible combinations. The AUC maximized at 0.76, and the combined sensitivity and specificity maximized at 142 and were comparable in both studies.CONCLUSIONSSelf-reported measures of periodontal disease are moderately predictive of clinical attachment loss. The demographic variables of age, race, smoking, gender, and diabetes mellitus accounted for much of the predictive power for self-reported periodontal disease; however, increases in sensitivity and specificity in the C statistics occurred when questions, including "Gum surgery in the past?," "Sore gums in the past?," "Scaling in the past?," "Bleeding gums now?," "Periodontal surgery in the past 2 years?," and "Chewing satisfaction?," were added to the model.

Background: Studies examining the association between periodontal disease and coronary heart disease have shown a consistent but weak to moderate relationship. Limited data have been reported in women and the role of smoking has not been fully clarified. Methods/Results: A population-based case–control study examining the association between periodontal disease (PD) and acute non-fatal myocardial infarction (MI) was conducted in Erie and Niagara counties in Western New York State. Cases (574) were discharged alive from local hospitals with MI diagnosis. Controls (887) were county residents randomly selected from the NY State Department of Motor Vehicles rolls and Health Care Financing Administration files. Periodontal disease was assessed using clinical attachment loss (CAL). Among men (415 cases), the odds ratio (OR) of the association between mean CAL (mm) and MI, adjusting for the effects of age, body mass index (BMI), physical activity, hypertension, cholesterol, diabetes, and total pack-years of cigarette smoking was 1.34 (1.15–1.57). In women (120 cases), the corresponding OR was 2.08 (1.47–2.94). The estimate of this association among non-smokers, also adjusting for age, gender, BMI, physical activity, hypertension, cholesterol, diabetes, and total pack-years of cigarette smoking, was 1.40 (1.06–1.86), while it was 1.49 (1.26–1.77) among smokers. Conclusions: This study provides evidence of an association between PD and incident MI in both genders. This association appears to be independent from the possible confounding effect of smoking.