Purpose Diabetes mellitus (DM) is an important health problem throughout the world. Association between DM and oral diseases has been reported and dental clinic is indicated to be one of the suitable venues for the screening of DM. The purpose of this paper is to determine patients’ attitude toward DM screening in dental clinics. Design/methodology/approach The anonymous, self-administered questionnaires of five-point response scale questions were distributed to convenience samples of adult patients (⩾25 years) attending one of the dental settings. These dental settings were divided into the university/hospital-based dental clinics (encompassing two university-based and five hospital-based dental clinics) or the private dental clinics (encompassing two private, and one special (after office hour) clinic of a faculty of dentistry). The questions could be categorized into three groups regarding importance, willingness, and agreement of DM screening in dental settings. Results are presented as percentage by respondents based upon the number of responses for each question. The favorable outcomes which were defined as responses of either scale of 4 or 5 were also summarized according to dental settings. The χ2 test for comparison was used to compare the favorable outcomes between the two settings. Findings A total of 601 completed questionnaires were collected; 394 from university/hospital-based dental clinics and 207 from two private clinics and a special (after office hour) clinic of a faculty of dentistry. Overall, the majority of respondents in both university/hospital-based and private practice settings felt that it is important to have a dentist conduct a screening (84.8 vs 79.5 percent). The majority of patients in both groups were willing to receive blood pressure examination (95.0 vs 92.0 percent), weight and height measurements (94.7 vs 94.0 percent), saliva/oral fluid investigation (86.4 and 86.9 percent) and finger-stick blood test (83.8 vs 83.9 percent). More than 75 percent of all respondents agreed with diabetes screening in dental clinics. Originality/value The majority of respondents supported the screening of DM in dental settings and they were willing to have a screening test by the dentist. Patient acceptance is an important key to be successful in the screening of DM in dental settings.
Multivariate analysis with binary response is extensively utilized in dental research due to variations in dichotomous outcomes. One of the analyses for binary response variable is binary logistic regression, which explores the associated factors and predicts the response probability of the binary variable. This article aims to explain the statistical concepts of binary logistic regression analysis applicable to the field of dental research, including model fitting, goodness of fit test, and model validation. Moreover, interpretation of the model and logistic regression are also discussed with relevant examples. Practical guidance is also provided for dentists and dental researchers to enhance their basic understanding of binary logistic regression analysis.
Background: Diabetes mellitus (DM) is one of the top causes of death in many places of the world. Diagnosing DM in the early stage is necessary to avoid severe cases and death. Objectives: To evaluate the knowledge of association between DM and periodontal disease (PD) among Thai physicians and assess their attitudes towards DM screening in dental clinics in Thailand. Methods: Online survey of currently practicing physicians in Thailand was conducted on voluntary basis using the newly developed questionnaire. Result: We received 403 responses that are statistically sufficient to represent the entire population of currently practicing physicians in Thailand. A total of 97.3% of all responses indicate that Thai physicians have knowledge about the association between DM and PD. More than 90% know that DM has an effect on PD; however, 70% know about the effect of untreated PD in DM patients. Most of physicians think that DM screening in dental clinics is important (79.1%) and are ready to accept referred cases for definite DM diagnosis from a dentist (84.1%). The concerned issues among the participants were the accuracy of the test results in DM screening (73%) and ability of a dentist to perform the screening (71.5%). Conclusions: The majority of participating physicians have adequate knowledge about the bidirectional relationship between DM and PD. They have a positive attitude towards DM screening in dental setting. The collaboration between physicians and dental professionals should be established to reduce the number of undiagnosed DM patients and enhance the medical care of DM patients.
This study aimed to compare the screening methods between point-of-care (POC) testing and hospital-based methods for potential type 2 DM and abnormal glucose regulation (AGR) in a dental setting. A total of 274 consecutive subjects who attended the Faculty of Dentistry, Mahidol University, Bangkok, Thailand, were selected. Demographic data were collected. HbA1c was assessed using a finger prick blood sample and analyzed with a point-of-care (POC) testing machine (DCA Vantage®). Hyperglycemia was defined as POC HbA1c ≥ 5.7%. Random blood glucose (RBG) was also evaluated using a glucometer (OneTouch® SelectSimple™) and hyperglycemia was defined as RBG ≥ 110 mg/dl or ≥140 mg/dl. The subjects were then sent for laboratory measurements for fasting plasma glucose (FPG) and HbA1c. The prevalence of AGR (defined as FPG ≥ 100 mg/dl or laboratory HbA1c ≥ 5.7%) and potential type 2 DM (defined as FPG ≥ 126 mg/dl or laboratory HbA1c ≥ 6.5%) among subjects was calculated and receiver operating characteristic (ROC) analysis was performed using FPG and HbA1c for the diagnosis of AGR and potential type 2 DM. The prevalence of hyperglycemia defined as POC HbA1c ≥ 5.7%, RBG ≥ 110 mg/dl, and RBG ≥ 140 mg/dl was 49%, 63%, and 32%, respectively. After the evaluation using laboratory measurements, the prevalence of AGR was 25% and 17% using laboratory FPG and HbA1c criteria, respectively. Based on the ROC curves, the performances of POC HbA1c and RBG in predicting FPG-defined potential type 2 DM were high (AUC = 0.99; 95% CI 0.98–0.99 and AUC = 0.94; 95% CI 0.86–1.0, respectively) but lower in predicting AGR (AUC = 0.72; 95% CI 0.67–0.78 and AUC = 0.65; 95% CI 0.59–0.70, respectively). This study suggested that POC testing might be a potential tool for screening of subjects with potential type 2 DM in a dental setting.
This study aimed to find a potential biomarker that can be used to diagnose prediabetic condition by comparing the salivary bacterial microbiomes between Thai dental patients with normoglycemia (NG) and those with potential prediabetes (PPG) conditions. Thirty-three subjects were randomly recruited. Demographic data were collected along with oral examination and unstimulated salivary collections. The salivary bacterial microbiomes were identified by high-throughput sequencing on the V3–V4 region of the bacterial 16S rRNA gene. Microbiomes in this study were composed of 12 phyla, 19 classes, 29 orders, 56 families, 81 genera, and 184 species. To check the validity of the selection criterion for prediabetes, we adopted two separate criteria to divide samples into PPG and NG groups using glycated hemoglobin A1c (HbA1c) or fasting plasma glucose (FPG) levels. Using the HbA1c level resulted in the significant reduction of Alloprevotella, Neisseria, Rothia, and Streptococcus abundances in PPG compared with those in NG (p-value < 0.05). On the other hand, the abundance of Absconditabacteriales was significantly reduced whereas Leptotrichia, Stomatobaculum, and Ruminococcaceae increased in the PPG group when the samples were classified by the FPG level (p-value < 0.05). It is implied that the group classifying criterion should be carefully concerned when investigating relative abundances between groups. However, regardless of the criteria, Rothia is significantly dominant in the NG groups, suggesting that Rothia might be a potential prediabetic biomarker. Due to the small sample size of this study, further investigation with a larger sample size is necessary to ensure that Rothia can be a potential biomarker for prediabetes in Thai people.
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