Polysomnographic airflow shapes and site of collapse during drug-induced sleep endoscopy.

BACKGROUND: Differences in the pharyngeal site of collapse influence efficacy of non-continuous positive airway pressure therapies for obstructive sleep apnoea (OSA). Notably, complete concentric collapse at the level of the palate (CCCp) during drug-induced sleep endoscopy (DISE) is associated with reduced efficacy of hypoglossal nerve stimulation, but CCCp is currently not recognisable using polysomnography. Here we develop a means to estimate DISE-based site of collapse using overnight polysomnography. METHODS: 182 OSA patients provided DISE and polysomnography data. Six polysomnographic flow shape characteristics (mean during hypopnoeas) were identified as candidate predictors of CCCp (primary outcome variable, n=44/182), including inspiratory skewness and inspiratory scoopiness. Multivariable logistic regression combined the six characteristics to predict clear presence (n=22) versus absence (n=128) of CCCp (partial collapse and concurrent tongue base collapse excluded). Odds ratios for actual CCCp between predicted subgroups were quantified after cross-validation. Secondary analyses examined complete lateral wall, tongue base or epiglottis collapse. External validation was performed on a separate dataset (ntotal=466). RESULTS: CCCp was characterised by greater scoopiness (ß=1.5±0.6 per 2sd, multivariable estimate±se) and skewness (ß=11.4±2.4) compared with non-CCCp. The odds ratio for CCCp in predicted positive versus negative subgroups was 5.0 (95% CI 1.9-13.1). The same characteristics provided significant cross-validated prediction of lateral wall (OR 6.3, 95% CI 2.4-16.5), tongue base (OR 3.2, 95% CI 1.4-7.3) and epiglottis (OR 4.4, 95% CI 1.5-12.4) collapse. CCCp and lateral wall collapse shared similar characteristics (skewed, scoopy), diametrically opposed to tongue base and epiglottis collapse characteristics. External validation confirmed model prediction. CONCLUSIONS: The current study provides a means to recognise patients with likely CCCp or other DISE-based site of collapse categories using routine polysomnography. Since site of collapse influences therapeutic responses, polysomnographic airflow shape analysis could facilitate precision site-specific OSA interventions.

Association between the systemic immune inflammation index and periodontitis: a cross-sectional study.

BACKGROUND: Periodontitis is a chronic oral inflammatory disease that seriously affects people's quality of life. The purpose of our study was to investigate the correlation between the systemic immune inflammation index (SII) and periodontitis by utilizing a large national survey. This will establish a reference for the early identification and management of periodontitis. METHODS: This study comprised the adult US population who participated in a national periodontitis surveillance project during the six years from 2009 to 2014. Through the utilization of univariate and multivariate weighted logistic regression, we investigated the correlation between the systemic immune inflammation index and periodontitis. Additionally, we employed sensitivity analyses to evaluate the robustness of our findings. RESULTS: The study involved 10,366 participants with an average age of 51.00 years, of whom 49.45% were male (N = 5126) and 50.55% were female (N = 5240). The prevalence of periodontitis is estimated to be about 38.43% in the US adults aged 30 or older population. Our logistic regression models indicated a positive association between a SII higher than 978 × 109/L and periodontitis. The elder group (aged 50 or older) with SII higher than 978 × 109/L demonstrated a significant correlation with periodontitis in the fully adjusted model (Odds Ratio [OR] = 1.409, 95% Confidence Interval [CI] 1.037, 1.915, P = 0.022). However, there is no statistical difference among adults aged 30 to 50. The robustness of our findings was confirmed through sensitivity analyses. CONCLUSIONS: Our study highlights that SII is associated with periodontitis in a nationally representative sample of US adults. And the SII is significantly associated with a high risk of periodontitis in individuals aged 50 or older.

High prevalence of orofacial pain in juvenile fibromyalgia as detected by a novel tool specifically devised for children and adolescents.

OBJECTIVES: To examine the prevalence of temporomandibular disorders (TMD) in patients with juvenile fibromyalgia syndrome (JFS) and identify TMD characteristics specifically associated to JFS. METHODS: Signs and symptoms of TMD were assessed using a novel clinical tool specifically devised for children that consists of: 1. a self-report multiple-choice questionnaire; 2. a protocol for the clinical examination of the orofacial region. Multivariate logistic regression model was used to identify TMD features associated with JFS. RESULTS: Thirty JFS patients (median age 15.5 years) and 45 healthy controls (median age 15.0 years) were included in this cross-sectional study. Orofacial pain was reported by 26 of 30 JFS patients (86.7%) and by 3 of 45 controls (6.7%; p<0.001). Pain on TMJ palpation was present in 18 of 30 JFS patients (60%) and in 5 of 45 controls (11.1%; p<0.001). Median values of maximum spontaneous mouth opening, voluntary active opening and assisted passive opening were significantly higher in JFS patients than in controls. On multiple regression analysis spontaneous orofacial pain (OR: 21.0; p=0.005), diffuse tenderness on palpation of the masticatory muscles (OR: 14.9; p=0.026) and TMJ hypermobility (OR 1.42; p=0.008) were independently associated with JFS. CONCLUSIONS: The high prevalence of TMD in JFS highlights the need for a broader interdisciplinary evaluation of JFS patients. TMJ hypermobility, in addition to orofacial and masticatory muscle pain, is an important clue for the diagnosis of TMD in adolescents with JFS. Elucidating the link between these disorders will advance individualised management and improve treatment efficacy.

Association of individual and combined exposures of 10 metals with periodontitis: Results from a large population-based study.

AIMS: To systematically investigate the association between individual and combined metal exposure and periodontitis. METHODS: Data encompassing complete periodontal examinations and metal detection in blood and urine samples were procured from the National Health and Nutrition Examination Survey (NHANES) 2011-2014. Three statistical methods, namely weighted logistic regression, Bayesian kernel machine regression (BKMR), and weighted quantile sum (WQS) regression, were used to evaluate the independent and combined associations between metals and periodontitis. RESULTS: Elevated concentrations of blood cadmium (odds ratio [OR]: 1.73, 95% confidence interval [CI]: 1.15-2.61) and blood lead (OR: 1.17, 95 %CI: 1.02-1.34) exhibited a positive association with periodontitis, even after adjusting for potential confounding factors. The BKMR and WQS regression suggested that the co-exposure of metals was also positively associated with periodontitis. Moreover, estradiol and albumin were identified as potential mediators in the relationship between the WQS index of the 10 metals in blood and periodontitis explaining 25.36% and 2.02% of the relationship, respectively. Furthermore, generally consistent patterns of associations between metals and periodontitis and mediating roles of estrogen and albumin were observed after a series of sensitivity analyses. CONCLUSION: This study provides evidence of positive associations between elevated levels of cadmium, lead or metal mixture and periodontitis, which may be partially mediated by sex hormones and oxidative stress indicators.

Contribution of individual and cumulative social determinants of health underlying gender disparities in periodontitis in a representative US population: A cross-sectional NHANES study.

AIM: To examine the impact of both individual and cumulative social determinants of health (SDoH) on the likelihood of developing periodontitis, while also exploring any gender disparities in this relationship. MATERIALS AND METHODS: Data of self-reported SDoH domains and sub-items based on Healthy People 2030 were obtained from the U.S. National Health and Nutrition Examination Surveys between 1999 and 2014. Logistic regression models, weighted by survey responses, were used to examine the relationship between SDoH (including eight sub-items and the cumulative number of unfavourable SDoH) and periodontitis. The results were further analysed by gender. RESULTS: A total of 18,075 participants (8867 males and 9208 females) were included in the main analysis, of which 5814 (32.2%) had periodontitis. The study found that certain unfavourable SDoH were individually associated with higher odds of periodontitis, and the cumulative number of unfavourable SDoH was positively linked to the odds of developing periodontitis. Furthermore, males exposed to more unfavourable SDoH appeared to be more susceptible to developing periodontitis than females. CONCLUSIONS: The findings suggest that unfavourable SDoH, especially when they accumulate, are associated with an increased odds of periodontitis and contribute to gender disparities within the U.S.

Associations between different triglyceride glucose index-related obesity indices and periodontitis: results from NHANES 2009-2014.

BACKGROUND: This study aimed to explore the associations between triglyceride glucose (TyG) index-related obesity indices and periodontitis within the American population. METHODS: This cross-sectional investigation utilized data from the National Health and Nutrition Examination Survey (NHANES) for 2009-2014. The association between the TyG-waist-to-height ratio (TyG-WHtR), TyG-weight-adjusted-waist index (TyG-WWI), TyG-waist circumference (TyG-WC), or TyG-body mass index (TyG-BMI) and periodontitis was investigated utilizing multivariable logistic regression model, subgroup, and dose-response curve analyses. RESULTS: This study enrolled 4,808 adult participants. Except for TyG-BMI, which did not exhibit a relationship with periodontitis, TyG-WHtR, [odds ratio (OR) (95% confidence interval (CI))] = 2.83 [1.58-5.10], P = 0.002], TyG-WWI [OR (95% CI) = 7.50 (3.06-18.34), P < 0.001], and TyG-WC [OR (95% CI) = 2.12 (1.23-3.64), P = 0.011] were all associated with periodontitis. Participants in the highest quartile displayed an elevated risk of periodontitis relative to their counterparts in the lowest quartile, as evidenced for TyG-WWI [OR (95% CI) = 1.72 (1.26-2.33), P = 0.001] and TyG-WC [OR (95% CI) = 1.50 (1.13-1.99), P = 0.009] in the full adjustment model. Subgroup analyses suggested more pronounced positive associations between these indices and periodontitis in participants who were < 60 years old, had a BMI ≥ 25, and did not have diabetes. The dose-response curve indicated linear responses in these associations. CONCLUSIONS: This investigation identified a significant and stable association between TyG-WHtR, TyG-WWI, or TyG-WC and periodontitis, which implies a robust correlation between high insulin resistance and susceptibility to periodontitis in the American population.

The association between polyunsaturated fatty acids and periodontitis: NHANES 2011-2014 and Mendelian randomisation analysis.

BACKGROUND: We aimed to explore the association and potential causality between polyunsaturated fatty acids concentrations and the risk of periodontal disease. MATERIALS AND METHODS: Data were collected from the 2011-2014 National Health and Nutrition Examination Survey (NHANES). Weighted logistic regression analysis and restricted cubic spline (RCS) analysis were used to analyse the associations of the concentrations of omega-3 and omega-6 fatty acids and the omega-6/omega-3 fatty acids ratio with the risk of periodontitis. E-value and propensity score matching (PSM) analyses were used for sensitivity analyses. In addition, two-sample Mendelian randomisation (MR) analyses were performed to assess the potential causal impact of the concentrations of those fatty acids on periodontitis risk. RESULTS: A total of 2462 participants from the NHANES were included. Logistic regression analysis revealed that high omega-3 fatty acids levels were negatively associated with the risk of developing periodontitis (P < 0.05), while the omega-6/omega-3 fatty acids ratio was positively associated with the risk of developing periodontitis (P < 0.05). There was no significant association between omega-6 concentrations and the risk of periodontitis. The findings mentioned above were confirmed by analysis following a 1:1 PSM. Furthermore, MR examination of the two samples indicated no possible causal link between the risk of periodontitis and the concentrations of omega-3 or omega-6 fatty acids or the ratio of omega-6 to omega-3 fatty acids (P > 0.05). CONCLUSION: Although omega-3 fatty acids and the omega-6/omega-3 fatty acids ratio were associated with the risk of periodontitis in cross-sectional studies, the MR results did not support a causal relationship between them. Therefore, there is no indication that an increase in the omega-3 fatty acids concentration or a decrease in the omega-6/omega-3 fatty acids ratio may be beneficial for preventing periodontitis.

The influence factors on pit and fissure sealing behavior of 12-year-old children: a cross-sectional study in Zhejiang, China.

BACKGROUND: In the 21st century, dental caries remains a global burden, particularly severely affecting the growth and quality of life of 12-year-old children. Fortunately, pit and fissure sealing (PFS) procedures can effectively prevent molars from caries. Hence, this study focused on the relationship between PFS and oral epidemiological factors in 12-year-old children. METHODS: A cross-sectional survey was conducted in 12-year-old children from 11 cities in Zhejiang Province. Their dental conditions were collected through questionnaires, as well as basic information such as relevant family information, oral health knowledge and behavior. Then, logistic regression analysis was used to identify the influencing factors associated with PFS. RESULTS: A total of 1204 children were included, with 252 in the PFS group and 952 in the non-PFS group. There were significant differences between the two groups in terms of decayed, missing and filled teeth (DMFT) score, first permanent molar DMFT score, residential area, educational level of parents, tooth-brushing frequency, use of dental floss, oral examination in a medical institution, having taken courses on oral health care, as well as having knowledge that tooth brushing could effectively prevent gingival inflammation, PFS could protect teeth, and oral disease may affect general health. According to further logistic regression analysis, the independent factors influencing PFS included use of dental floss [odds ratios (OR) = 1.672, 95% confidence intervals (CI) = 1.235-2.263, P = 0.001], having taken courses on oral health care (OR = 0.713, 95% CI = 0.515-0.988, P = 0.042), having knowledge that tooth brushing is effective in preventing gingival inflammation (OR = 0.627, 95% CI = 0.389-0.987, P = 0.044) and having knowledge that PFS can protect teeth (OR = 0.589, 95% CI = 0.438-0.791, P < 0.001). CONCLUSION: PFS can reduce the mean DMFT score of 12-year-old children. Independent influencing factors of PFS consist of use of dental floss, having taken courses on oral health care, oral health behavior and knowledge level.

Genetic Association between the Risk of Dental Caries and MTR Gene Polymorphism in Chinese Children.

Early childhood caries (ECC) is common in children. Little is known about the genetic association of the methionine synthesis reductase (MTRR) gene rs1801394 and methionine synthetase (MTR) gene rs1805087 polymorphisms with ECC, which was examined in the Chinese Han population. Genotyping was performed using the buccal mucosa from 150 normal and 150 ECC children. For genotype and allele distribution comparison, Chi-square test and multiple logistic regression analysis were performed. The odd ratio (OR) and 95% confidence interval (CI) were calculated. MTR gene rs1805087 AG genotype distribution in the ECC group was clearly different from the control group (P = 0.029), and the ECC risk in cases with AG genotype was 0.525 times lower than those carrying AA genotype (95% CI = 0.292-0.942). Logistic regression analysis after adjustment for other clinical indicators determined that the MTR gene rs1805087 AG genotype was still strongly associated with susceptibility to ECC (OR = 0.499, 95% CI = 0.273-0.913, P = 0.024). Significant association was also seen for sugary food intakes (OR = 1.965, 95% CI = 1.162-3.321, P = 0.012), tooth brushing (OR = 0.569, 95% CI = 0.356-0.924, P = 0.023) and sex (OR = 0.562, 95% CI = 0.349-0.907, P = 0.018) with ECC risk. No notable genetic association was found between MTRR gene rs1801394 polymorphism and ECC risk. MTR gene rs1805087 polymorphism may aggrandize the susceptibility to ECC, and AA genotype appeared to be a dangerous element for the development of ECC.

Glycemic Control and Oral Health Outcomes in Patients With Diabetes: Insights From a Nationwide Korean Survey.

BACKGROUND: Diabetes is recognized as a risk factor for various inflammatory conditions, including periodontitis. There exists a bidirectional relationship between glycemic control and oral health in individuals with diabetes. This study aimed to analyze the link between glycemic control and oral health status among Korean patients with diabetes. METHODS: Using data from a population-based nationwide survey conducted between 2007 and 2019, we identified 70,554 adults with diabetes-related information. The study population included 9,090 individuals diagnosed with diabetes and 61,164 healthy controls. The association between glycemic control, defined by mean glycated hemoglobin (HbA1c) values, and various oral health measures, such as tooth brushing frequency, periodontitis, denture wearing, Decayed, Missing, and Filled Teeth (DMFT) index, number of remaining teeth, and past-year dental clinic visits, was evaluated using multivariate logistic regression analyses. RESULTS: Compared to the control group, patients with diabetes exhibited a higher prevalence of periodontitis (88.6% vs. 73.3%), complete dentures (5.0% vs. 1.5%), and elevated DMFT index (33.2% vs. 26.7%) (all P < 0.001). Multivariate analyses revealed significant associations between diabetes and several oral health factors: denture status (No denture: adjusted odds ratio [aOR], 0.784; 95% confidence interval [CI], 0.627-0.979), and having fewer permanent teeth (0-19) (aOR, 1.474; 95% CI, 1.085-2.003). Additionally, a positive correlation was found between higher HbA1c levels and the risk of having fewer remaining teeth (0-19) (HbA1c < 6.5%: aOR, 1.129; 95% CI, 0.766-1.663; 6.5% ≤ HbA1c < 8.0%: aOR, 1.590; 95% CI, 1.117-2.262; HbA1c ≥ 8%: aOR, 1.910; 95% CI, 1.145-3.186) (P for trends = 0.041). CONCLUSION: We found a positive association between diabetes and poor oral health, as well as a noteworthy relationship between reduced permanent teeth (≤ 19) and glycemic control. These insights emphasize the critical role of oral health management in diabetic care and underscore the importance of maintaining effective glycemic control strategies for overall health and well-being in patients with diabetes.

Logistic Regression Analysis of LC-MS/MS Data of Monomers Eluted from Aged Dental Composites: A Supervised Machine-Learning Approach.

Compound identification by database searching that matches experimental with library mass spectra is commonly used in mass spectrometric (MS) data analysis. Vendor software often outputs scores that represent the quality of each spectral match for the identified compounds. However, software-generated identification results can differ drastically depending on the initial search parameters. Machine learning is applied here to provide a statistical evaluation of software-generated compound identification results from experimental tandem MS data. This task was accomplished using the logistic regression algorithm to assign an identification probability value to each identified compound. Logistic regression is usually used for classification, but here it is used to generate identification probabilities without setting a threshold for classification. Liquid chromatography coupled with quadrupole-time-of-flight tandem MS was used to analyze the organic monomers leached from resin-based dental composites in a simulated oral environment. The collected tandem MS data were processed with vendor software, followed by statistical evaluation of these results using logistic regression. The assigned identification probability to each compound provides more confidence in identification beyond solely by database matching. A total of 21 distinct monomers were identified among all samples, including five intact monomers and chemical degradation products of bisphenol A glycidyl methacrylate (BisGMA), oligomers of bisphenol-A ethoxylate methacrylate (BisEMA), triethylene glycol dimethacrylate (TEGDMA), and urethane dimethacrylate (UDMA). The logistic regression model can be used to evaluate any database-matched liquid chromatography-tandem MS result by training a new model using analytical standards of compounds present in a chosen database and then generating identification probabilities for candidates from unknown data using the new model.

Multiple imputation methods for missing multilevel ordinal outcomes.

BACKGROUND: Multiple imputation (MI) is an established technique for handling missing data in observational studies. Joint modelling (JM) and fully conditional specification (FCS) are commonly used methods for imputing multilevel data. However, MI methods for multilevel ordinal outcome variables have not been well studied, especially when cluster size is informative on the outcome. The purpose of this study is to describe and compare different MI strategies for dealing with multilevel ordinal outcomes when informative cluster size (ICS) exists. METHODS: We conducted comprehensive Monte Carlo simulation studies to compare the performance of five strategies: complete case analysis (CCA), FCS, FCS+CS (including cluster size (CS) in the imputation model), JM, and JM+CS under various scenarios. We evaluated their performance using a proportional odds logistic regression model estimated with cluster weighted generalized estimating equations (CWGEE). RESULTS: The simulation results showed that including CS in the imputation model can significantly improve estimation accuracy when ICS exists. FCS provided more accurate and robust estimation than JM, followed by CCA for multilevel ordinal outcomes. We further applied these strategies to a real dental study to assess the association between metabolic syndrome and clinical attachment loss scores. The results based on FCS + CS indicated that the power of the analysis would increase after carrying out the appropriate MI strategy. CONCLUSIONS: MI is an effective tool to increase the accuracy and power of the downstream statistical analysis for missing ordinal outcomes. FCS slightly outperforms JM when imputing multilevel ordinal outcomes. When there is plausible ICS, we recommend including CS in the imputation phase.

Development and international validation of logistic regression and machine-learning models for the prediction of 10-year molar loss.

AIM: To develop and validate models based on logistic regression and artificial intelligence for prognostic prediction of molar survival in periodontally affected patients. MATERIALS AND METHODS: Clinical and radiographic data from four different centres across four continents (two in Europe, one in the United States, and one in China) including 515 patients and 3157 molars were collected and used to train and test different types of machine-learning algorithms for their prognostic ability of molar loss over 10 years. The following models were trained: logistic regression, support vector machine, K-nearest neighbours, decision tree, random forest, artificial neural network, gradient boosting, and naive Bayes. In addition, different models were aggregated by means of the ensembled stacking method. The primary outcome of the study was related to the prediction of overall molar loss (MLO) in patients after active periodontal treatment. RESULTS: The general performance in the external validation settings (aggregating three cohorts) revealed that the ensembled model, which combined neural network and logistic regression, showed the best performance among the different models for the prediction of MLO with an area under the curve (AUC) = 0.726. The neural network model showed the best AUC of 0.724 for the prediction of periodontitis-related molar loss. In addition, the ensembled model showed the best calibration performance. CONCLUSIONS: Through a multi-centre collaboration, both prognostic models for the prediction of molar loss were developed and externally validated. The ensembled model showed the best performance in terms of both discrimination and validation, and it is made freely available to clinicians for widespread use in clinical practice.

Does Preoperative Surgical Delay Lead to Increased Postsurgical Length of Stay or Reoperation in Patients With Severe Odontogenic Infections?

BACKGROUND: While severe odontogenic infections can be life-threatening and emergent surgery can be required more often, surgical management in the operating room (OR) is completed as soon as feasible. However, provider schedules and OR availability can occasionally lead to longer delays before surgery, but their effect on outcomes is unknown. PURPOSE: The purpose of this study was to determine the association of preoperative surgical delay with postsurgical length of stay (LOS) and reoperation in patients with severe odontogenic infections. STUDY DESIGN, SETTING, SAMPLE: The authors conducted a retrospective cohort study consisting of all adult patients treated in the OR with incision and drainage for odontogenic infections from 1/1/2015 to 7/30/2021 at a large, urban academic hospital. PREDICTOR VARIABLE: The primary predictor variable was the length of presurgical delay-the number of hours between arrival in the emergency department and the start of surgery. MAIN OUTCOME VARIABLES: The primary outcome variable was the postsurgical LOS and the secondary outcome variable was the rate of reoperation. COVARIATES: Demographics, medical history, exam findings, diagnosis, and treatment-related variables were also analyzed. ANALYSES: Descriptive and bivariate analyses were performed along with multivariable linear and logistic regression. A P value of < .05 was considered significant. RESULTS: There were 401 patients included in the study with 50.9% men and a mean age of 39.1 years. Increased length of presurgical delay (hours) was associated with a decreased postsurgical LOS (ß = -0.05 days, P = .01) and length of presurgical delay was not associated with reoperation (P = .51) in the unadjusted analyses. However, length of presurgical delay was not found to be associated with either LOS (ß = -0.02, 95% confidence interval (CI) -0.05 to 0.01, P = .12) or reoperation (adjusted odds ratio (aOR) 1.0, 95% CI 0.96 to 1.02, P = .67) in the adjusted analyses. CONCLUSIONS AND RELEVANCE: The association of decreased length of presurgical delay with increased postsurgical LOS in the unadjusted analysis could reflect the practice of rapid intervention for the most ill patients. After adjusting for number of spaces, a primary indicator of infection severity, length of presurgical delay was not associated with either LOS or return to the operating room.

The Association of Periodontal Disease with Low Birth Weight Infants: A Case Control Study.

OBJECTIVE: To determine the association between periodontal disease and low birth weight among pregnant women. METHODS: Data for this case-control study was collected from June 2019 till February 2020. All women in the Gynecology Department of Lady Willingdon Hospital, Lahore, who had delivered a baby within the last 24 h were invited to participate. Women who delivered babies less than 2.5 kg were considered as 'cases' (having low birth weight - LBW - infants) and those having babies of 2.5 kg or more were categorized as 'controls' (normal birth weight infants). The selected sample was matched for age, general health (indicated by mean upper arm circumference) and Hemoglobin levels. Intraoral examination was conducted and gingival color and appearance; calculus, bleeding on probing, CPITN (Community Periodontal Index of Treatment Needs) and CAL (clinical attachment loss) were recorded. A binary logistic regression analysis was conducted to determine the predictors of LBW infants. The predictors were further confirmed by applying chi-squared test for categorical variables and independent sample T test for quantitative variables. RESULTS: A total of 60 cases and 120 controls were recruited. The logistic regression model suggested that CPITN score (OR 14.893, 95% CI 4.896, 45.301); CAL (OR 2.148, 95% CI 1.271, 3.631); calculus (OR 25.099, 95% CI 1.916, 328.771); mode of delivery (OR 0.175 95% CI 0.060, 0.514); and gingival recession (OR 0.237, 95% CI 0.078, 0.715) were significant predictors of LBW. CONCLUSION: Periodontal disease was found to be a significant predictor of LBW infants.

Factors associated with knowledge about pharmacological management of pregnant women in Peruvian dental students: a logistic regression analysis.

BACKGROUND: Clinical management to maintain or restore oral health through the use of drugs during pregnancy is crucial, since at this stage physiological changes significantly influence the absorption, distribution and elimination of the drug, considering also that excessive administration of drugs during this period may have adverse effects on the mother and/or fetus. Therefore, the aim of the present study was to evaluate the factors associated with knowledge of pharmacological management of pregnant women in dental students of a Peruvian university located in the capital and province. METHODS: This analytical, cross-sectional, prospective and observational study assessed 312 Peruvian dental students from third to fifth year of study between February and April 2022. A validated questionnaire of 10 closed questions was used to measure knowledge about pharmacological management in pregnant women. A logit model was used to assess the influence of the variables: gender, age, year of study, marital status, place of origin and area of residence. A significance of p < 0.05 was considered. RESULTS: The 25.96, 55.13 and 18.91% of the dental students showed poor, fair and good knowledge about pharmacological management in pregnant women; respectively. In addition, it was observed that students under 24 years of age and those from the capital were significantly (p < 0.05) 44% less likely to have poor knowledge of pharmacological management in pregnant women compared to those aged 24 years or older (OR = 0.56; CI: 0.34-0.92) and those from the province (OR = 0.56; CI: 0.32-0.98); respectively. Finally, those in their third and fourth year of study were significantly three times more likely to have poor knowledge (OR = 3.17; CI: 1.68-5.97 and OR = 3.88; CI: 2.07-7.31; respectively) compared to fifth year dental students. CONCLUSION: The knowledge of dental students about pharmacological management in pregnant women was predominantly of fair level. In addition, it was observed that being under 24 years of age and being from the capital city were protective factors against poor knowledge, while being a third- and fourth-year student was a risk factor. Finally, gender, marital status and area of residence were not influential factors in the level of knowledge.

Top-Down Proteomics of Human Saliva, Analyzed with Logistic Regression and Machine Learning Methods, Reveal Molecular Signatures of Ovarian Cancer.

Ovarian cancer (OC) is the most lethal of all gynecological cancers. Due to vague symptoms, OC is mostly detected at advanced stages, with a 5-year survival rate (SR) of only 30%; diagnosis at stage I increases the 5-year SR to 90%, suggesting that early diagnosis is essential to cure OC. Currently, the clinical need for an early, reliable diagnostic test for OC screening remains unmet; indeed, screening is not even recommended for healthy women with no familial history of OC for fear of post-screening adverse events. Salivary diagnostics is considered a major resource for diagnostics of the future. In this work, we searched for OC biomarkers (BMs) by comparing saliva samples of patients with various stages of OC, breast cancer (BC) patients, and healthy subjects using an unbiased, high-throughput proteomics approach. We analyzed the results using both logistic regression (LR) and machine learning (ML) for pattern analysis and variable selection to highlight molecular signatures for OC and BC diagnosis and possibly re-classification. Here, we show that saliva is an informative test fluid for an unbiased proteomic search of candidate BMs for identifying OC patients. Although we were not able to fully exploit the potential of ML methods due to the small sample size of our study, LR and ML provided patterns of candidate BMs that are now available for further validation analysis in the relevant population and for biochemical identification.

Oral health-related quality of life and depressive symptoms in adults: longitudinal associations of the English Longitudinal Study of Ageing (ELSA).

BACKGROUND: Little is known about the relationship between oral health status and depressive symptoms in adults in England. The aim of this study was to examine the longitudinal association between oral health parameters and depressive symptoms in adults in England. METHODS: Data were obtained from the English Longitudinal Study of Aging (ELSA), which included information on self-rated oral health, oral impairment in daily life (Oral Impacts on Daily Performances, OIDP), and depressive symptoms (Center for Epidemiologic Studies Depression Scale, CES-D) in 6790 adults aged ≥ 50 years. Wave 3 data were used as baseline, while Waves 5 and 7 were used for follow-up assessments. Logistic regression was used to determine whether depressive symptoms at baseline anticipated self-rated oral health and OIDP and whether oral health status (at baseline) was associated with the development of depressive symptoms at follow-up assessment. RESULTS: Participants with poor self-rated oral health were at higher risk of developing depressive symptoms, even after adjusting for behavioral, clinical, and sociodemographic characteristics (OR = 1.69, 95% CI 1.38-2.07). Similarly, having oral impacts on daily performances were associated with the development of depressive symptoms: The OR for developing depressive symptoms at Wave 5 or 7 was 2.19 (95% CI 1.62-2.96) after adjustment for all covariates. Participants with depressive symptoms at baseline were more likely to report poor self-rated oral health (OR = 1.93, 95% CI 1.52-2.44) or one or more oral impacts (OR = 1.86, 95% CI 1.45-2.40) at follow-up than those without depressive symptoms at baseline, even after adjusting for confounders. CONCLUSIONS: In the present study, a bidirectional association was found between depressive symptoms and poor oral health in older adults. Maintaining good oral health in older adults may be a protective factor against depressive symptoms. Therefore, more attention should be paid to promoting oral health awareness in older adults, including encouraging regular dental checkups, proper toothbrushing and flossing techniques, and healthy lifestyles.

Construction of an Analysis Model of mRNA Markers in Menstrual Blood Based on Naïve Bayes and Multivariate Logistic Regression Methods.

OBJECTIVES: To establish the menstrual blood identification model based on Naïve Bayes and multivariate logistic regression methods by using specific mRNA markers in menstrual blood detection technology combined with statistical methods, and to quantitatively distinguish menstrual blood from other body fluids. METHODS: Body fluids including 86 menstrual blood, 48 peripheral blood, 48 vaginal secretions, 24 semen and 24 saliva samples were collected. RNA of the samples was extracted and cDNA was obtained by reverse transcription. Five menstrual blood-specific markers including members of the matrix metalloproteinase (MMP) family MMP3, MMP7, MMP11, progestogens associated endometrial protein (PAEP) and stanniocalcin-1 (STC1) were amplified and analyzed by electrophoresis. The results were analyzed by Naïve Bayes and multivariate logistic regression. RESULTS: The accuracy of the classification model constructed was 88.37% by Naïve Bayes and 91.86% by multivariate logistic regression. In non-menstrual blood samples, the distinguishing accuracy of peripheral blood, saliva and semen was generally higher than 90%, while the distinguishing accuracy of vaginal secretions was lower, which were 16.67% and 33.33%, respectively. CONCLUSIONS: The mRNA detection technology combined with statistical methods can be used to establish a classification and discrimination model for menstrual blood, which can distignuish the menstrual blood and other body fluids, and quantitative description of analysis results, which has a certain application value in body fluid stain identification.

Dentist's Visits and Risk of Brain Abscess: A Nationwide, Population-Based Case-Control Study.

BACKGROUND: Brain abscesses are frequently caused by oral cavity bacteria, but whether dental status and invasive dental procedures are important risk factors is unknown. METHODS: A nationwide, population-based, case-control study examined the association between dentist's visits and invasive dental procedures and risk of brain abscess caused by oral cavity bacteria from 1989 through 2016. Date of brain abscess diagnosis was considered the index date. Using risk-set sampling, 10 population controls per case were individually matched by age, sex, and residential area. Conditional logistic regression was used to compute odds ratios with 95% confidence intervals (CIs), adjusted for comorbidity. RESULTS: We identified 362 patients with culture-proven brain abscess caused by oral cavity bacteria. The median age was 53 years (interquartile range, 39-65 years) and 220 (61%) were male. Invasive dental procedures within 6 months before the index date was observed in 21 of 362 (6%) patients with brain abscess and 179 of 3257 (5%) population controls (adjusted odds ratio [aOR], 1.07 [95% CI, .67-1.70]). Two hundred thirteen of 362 (59%) patients with brain abscess had visited their dentist within 1 year before the index date compared with 1944 of 3257 (60%) of population controls (aOR, 0.99 [95% CI, .77-1.26]). Using no dentist's visits as reference, we observed aORs of 0.95 (95% CI, .64-1.40) for 1-2 visits within 3 years of the index date and 1.01 (95% CI, .76-1.35) for 3 or more visits. CONCLUSIONS: Recent invasive dental procedures and number of dentist's visits were not associated with culture-verified brain abscess caused by oral cavity bacteria.