Refine
Document Type
- Article (22)
Language
- English (22)
Has Fulltext
- yes (22)
Is part of the Bibliography
- no (22)
Keywords
- periodontitis (11)
- - (7)
- cohort study (3)
- Biofilm (2)
- caries (2)
- epidemiology (2)
- periodontal treatment (2)
- tooth loss (2)
- 25‐Hydroxyvitamin D 2 (1)
- C-reactive protein (1)
- Cold atmospheric plasma (1)
- Cold plasma (1)
- Coronavirus (1)
- Dental implant (1)
- Epidemiology (1)
- Individualization (1)
- Infection control (1)
- Mendelian Randomization Analysis (1)
- Mendelian randomization (1)
- Metanalysis (1)
- Non-surgical periodontal therapy (1)
- Occupational dentistry (1)
- Peri-implantitis (1)
- Periodontal medicine (1)
- Periodontitis (1)
- Powder (1)
- RCT (1)
- Risk factor (1)
- Study of Health in Pomerania (1)
- Surface treatment (1)
- Titanium surface (1)
- Tooth loss (1)
- Vitamin D (1)
- Water jet (1)
- bacteria (1)
- biomarkers (1)
- biostatistics (1)
- bone remodelling (1)
- bone turnover marker (1)
- clinical attachment level (1)
- clinical trial (1)
- dental (1)
- dental flossing (1)
- depression (1)
- directed acyclic graphs (1)
- genetic correlation (1)
- genetic correlation analysis (1)
- hemoglobin A1c (1)
- individualized medicine (1)
- inflammation (1)
- inter-dental cleaning (1)
- interdental brushing (1)
- lipoprotein profile (1)
- longitudinal cohort study (1)
- measurement error (1)
- mendelian randomization analysis (1)
- metabolism (1)
- metabolomics (1)
- number of missing teeth (1)
- obesity (1)
- periodontal disease (1)
- periodontal diseases (1)
- personalized medicine (1)
- phenotyping (1)
- population-based imaging (1)
- powered tooth brush (1)
- powered toothbrush (1)
- prediabetic state (1)
- prediction modelling (1)
- probing depth (1)
- prospective cohort study (1)
- psoriasis (1)
- radiomics (1)
- registry-based analysis (1)
- regression analysis (1)
- risk factors (1)
- serum markers (1)
- subgroup analysis (1)
- tooth extraction (1)
- treatment planning (1)
- whole-body magnetic resonance imaging (1)
Institute
- Zentrum für Zahn-, Mund- und Kieferheilkunde (8)
- Poliklinik für Kieferorthopädie, Präventive Zahnmedizin und Kinderzahnheilkunde (5)
- Poliklinik für Zahnerhaltung, Parodontologie und Endodontologie (4)
- Institut für Klinische Chemie und Laboratoriumsmedizin (3)
- Klinik und Poliklinik für Mund-, Kiefer- und Gesichtschirurgie/Plastische Operationen (3)
- Klinik für Psychiatrie und Psychotherapie (2)
- Institut für Biochemie (1)
- Institut für Community Medicine (1)
- Institut für Diagnostische Radiologie und Neuroradiologie (1)
- Klinik und Poliklinik für Augenheilkunde (1)
Publisher
- Wiley (9)
- SAGE Publications (4)
- Springer Nature (3)
- BioMed Central (BMC) (1)
- Frontiers Media S.A. (1)
- Hindawi (1)
- IOP Publishing (1)
- MDPI (1)
- Public Library of Science (PLoS) (1)
Because of some disadvantages of chemical disinfection in dental practice (especially denture cleaning), we investigated the effects of physical methods on Candida albicans biofilms. For this purpose, the antifungal efficacy of three different low-temperature plasma devices (an atmospheric pressure plasma jet and two different dielectric barrier discharges (DBDs)) on Candida albicans biofilms grown on titanium discs in vitro was investigated. As positive treatment controls, we used 0.1% chlorhexidine digluconate (CHX) and 0.6% sodium hypochlorite (NaOCl). The corresponding gas streams without plasma ignition served as negative treatment controls. The efficacy of the plasma treatment was determined evaluating the number of colony-forming units (CFU) recovered from titanium discs. The plasma treatment reduced the CFU significantly compared to chemical disinfectants. While 10 min CHX or NaOCl exposure led to a CFU log10 reduction factor of 1.5, the log10 reduction factor of DBD plasma was up to 5. In conclusion, the use of low-temperature plasma is a promising physical alternative to chemical antiseptics for dental practice.
Evidence is limited regarding whether periodontal treatment improves hemoglobin A1c (HbA1c) among people with prediabetes and periodontal disease, and it is unknown whether improvement of metabolic status persists >3 mo. In an exploratory post hoc analysis of the multicenter randomized controlled trial “Antibiotika und Parodontitis” (Antibiotics and Periodontitis)—a prospective, stratified, double-blind study—we assessed whether nonsurgical periodontal treatment with or without an adjunctive systemic antibiotic treatment affects HbA1c and high-sensitivity C-reactive protein (hsCRP) levels among periodontitis patients with normal HbA1c (≤5.7%, n = 218), prediabetes (5.7% < HbA1c < 6.5%, n = 101), or unknown diabetes (HbA1c ≥ 6.5%, n = 8) over a period of 27.5 mo. Nonsurgical periodontal treatment reduced mean pocket probing depth by >1 mm in both groups. In the normal HbA1c group, HbA1c values remained unchanged at 5.0% (95% CI, 4.9% to 6.1%) during the observation period. Among periodontitis patients with prediabetes, HbA1c decreased from 5.9% (95% CI, 5.9% to 6.0%) to 5.4% (95% CI, 5.3% to 5.5%) at 15.5 mo and increased to 5.6% (95% CI, 5.4% to 5.7%) after 27.5 mo. At 27.5 mo, 46% of periodontitis patients with prediabetes had normal HbA1c levels, whereas 47.9% remained unchanged and 6.3% progressed to diabetes. Median hsCRP values were reduced in the normal HbA1c and prediabetes groups from 1.2 and 1.4 mg/L to 0.7 and 0.7 mg/L, respectively. Nonsurgical periodontal treatment may improve blood glucose values among periodontitis patients with prediabetes (ClinicalTrials.gov NCT00707369).
Prediction models learn patterns from available data (training) and are then validated on new data (testing). Prediction modeling is increasingly common in dental research. We aimed to evaluate how different model development and validation steps affect the predictive performance of tooth loss prediction models of patients with periodontitis. Two independent cohorts (627 patients, 11,651 teeth) were followed over a mean ± SD 18.2 ± 5.6 y (Kiel cohort) and 6.6 ± 2.9 y (Greifswald cohort). Tooth loss and 10 patient- and tooth-level predictors were recorded. The impact of different model development and validation steps was evaluated: 1) model complexity (logistic regression, recursive partitioning, random forest, extreme gradient boosting), 2) sample size (full data set or 10%, 25%, or 75% of cases dropped at random), 3) prediction periods (maximum 10, 15, or 20 y or uncensored), and 4) validation schemes (internal or external by centers/time). Tooth loss was generally a rare event (880 teeth were lost). All models showed limited sensitivity but high specificity. Patients’ age and tooth loss at baseline as well as probing pocket depths showed high variable importance. More complex models (random forest, extreme gradient boosting) had no consistent advantages over simpler ones (logistic regression, recursive partitioning). Internal validation (in sample) overestimated the predictive power (area under the curve up to 0.90), while external validation (out of sample) found lower areas under the curve (range 0.62 to 0.82). Reducing the sample size decreased the predictive power, particularly for more complex models. Censoring the prediction period had only limited impact. When the model was trained in one period and tested in another, model outcomes were similar to the base case, indicating temporal validation as a valid option. No model showed higher accuracy than the no-information rate. In conclusion, none of the developed models would be useful in a clinical setting, despite high accuracy. During modeling, rigorous development and external validation should be applied and reported accordingly.
Periodontitis is one of the most prevalent oral diseases worldwide and is caused by multifactorial interactions between host and oral bacteria. Altered cellular metabolism of host and microbes releases a number of intermediary end products known as metabolites. There is an increasing interest in identifying metabolites from oral fluids such as saliva to widen the understanding of the complex pathogenesis of periodontitis. It is believed that some metabolites might serve as indicators toward early detection and screening of periodontitis and perhaps even for monitoring its prognosis in the future. Because contemporary periodontal screening methods are deficient, there is an urgent need for novel approaches in periodontal screening procedures. To this end, we associated oral parameters (clinical attachment level, periodontal probing depth, supragingival plaque, supragingival calculus, number of missing teeth, and removable denture) with a large set of salivary metabolites (n = 284) obtained by mass spectrometry among a subsample (n = 909) of nondiabetic participants from the Study of Health in Pomerania (SHIP-Trend-0). Linear regression analyses were performed in age-stratified groups and adjusted for potential confounders. A multifaceted image of associated metabolites (n = 107) was revealed with considerable differences according to age groups. In the young (20 to 39 y) and middle-aged (40 to 59 y) groups, metabolites were predominantly associated with periodontal variables, whereas among the older subjects (≥60 y), tooth loss was strongly associated with metabolite levels. Metabolites associated with periodontal variables were clearly linked to tissue destruction, host defense mechanisms, and bacterial metabolism. Across all age groups, the bacterial metabolite phenylacetate was significantly associated with periodontal variables. Our results revealed alterations of the salivary metabolome in association with age and oral health status. Among our comprehensive panel of metabolites, periodontitis was significantly associated with the bacterial metabolite phenylacetate, a promising substance for further biomarker research.
For the goal of individualized medicine, it is critical to have clinical phenotypes at hand which represent the individual pathophysiology. However, for most of the utilized phenotypes, two individuals with the same phenotype assignment may differ strongly in their underlying biological traits. In this paper, we propose a definition for individualization and a corresponding statistical operationalization, delivering thereby a statistical framework in which the usefulness of a variable in the meaningful differentiation of individuals with the same phenotype can be assessed. Based on this framework, we develop a statistical workflow to derive individualized phenotypes, demonstrating that under specific statistical constraints the prediction error of prediction scores contains information about hidden biological traits not represented in the modeled phenotype of interest, allowing thereby internal differentiation of individuals with the same assigned phenotypic manifestation. We applied our procedure to data of the population-based Study of Health in Pomerania to construct a refined definition of obesity, demonstrating the utility of the definition in prospective survival analyses. Summarizing, we propose a framework for the individualization of phenotypes aiding personalized medicine by shifting the focus in the assessment of prediction models from the model fit to the informational content of the prediction error.
Abstract
Background
Twenty five‐hydroxy vitamin D (25OHD) levels have been proposed to protect against periodontitis based on in vitro and observational studies but evidence from long‐term randomized controlled trials (RCTs) is lacking. This study tested whether genetically proxied 25OHD is associated with periodontitis using Mendelian randomization (MR).
Methods
Genetic variants strongly associated with 25OHD in a genome‐wide association study (GWAS) of 417,580 participants of European ancestry were used as instrumental variables, and linked to GWAS summary data of 17,353 periodontitis cases and 28,210 controls. In addition to the main analysis using an inverse variance weighted (IVW) model, we applied additional robust methods to control for pleiotropy. We also undertook sensitivity analyses excluding single nucleotide polymorphisms (SNPs) used as instruments with potential pleiotropic effects and used a second 25OHD GWAS for replication. We identified 288 SNPs to be genome‐wide significant for 25OHD, explaining 7.0% of the variance of 25OHD levels and providing ≥90% power to detect an odds ratio (OR) of ≤ 0.97.
Results
MR analysis suggested that a 1 standard deviation increase in natural log‐transformed 25OHD was not associated with periodontitis risk (IVW OR = 1.04; 95% confidence interval (CI): 0.97–1.12; P‐value = 0.297). The robust models, replication, and sensitivity analyses were coherent with the primary analysis.
Conclusions
Collectively, our findings suggest that 25OHD levels are unlikely to have a substantial effect on the risk of periodontitis, but large long‐term RCTs are needed to derive definitive evidence on the causal role of 25OHD in periodontitis.
The Study of Health in Pomerania (SHIP), a population-based study from a rural state in northeastern Germany with a relatively poor life expectancy, supplemented its comprehensive examination program in 2008 with whole-body MR imaging at 1.5 T (SHIP-MR). We reviewed more than 100 publications that used the SHIP-MR data and analyzed which sequences already produced fruitful scientific outputs and which manuscripts have been referenced frequently. Upon reviewing the publications about imaging sequences, those that used T1-weighted structured imaging of the brain and a gradient-echo sequence for R2* mapping obtained the highest scientific output; regarding specific body parts examined, most scientific publications focused on MR sequences involving the brain and the (upper) abdomen. We conclude that population-based MR imaging in cohort studies should define more precise goals when allocating imaging time. In addition, quality control measures might include recording the number and impact of published work, preferably on a bi-annual basis and starting 2 years after initiation of the study. Structured teaching courses may enhance the desired output in areas that appear underrepresented.
Background
Observational and in-vivo research suggested a bidirectional relationship between depression and periodontitis. We estimated the genetic correlation and examined directionality of causation.
Methods
The study used summary statistics from published genome wide association studies, with sample sizes ranging from 45,563 to 797,563 individuals of European ancestry. We performed linkage disequilibrium score regression (LDSC) to estimate global correlation and used Heritability Estimation from Summary Statistics (ρ-HESS) to further examine local genetic correlation. Latent Heritable Confounder Mendelian randomization (LHC-MR), Causal Analysis using Summary Effect estimates (CAUSE), and conventional MR approaches assessed bidirectional causation.
Results
LDSC observed only weak genetic correlation (rg = 0.06, P-Value = 0.619) between depression and periodontitis. Analysis of local genetic correlation using ρ-HESS did not reveal loci of significant local genetic covariance. LHC-MR, CAUSE and conventional MR models provided no support for bidirectional causation between depression and periodontitis, with odds ratios ranging from 1.00 to 1.06 in either direction.
Conclusions
Results do not support shared heritability or a causal connection between depression and periodontitis.