An evidenced-based scoring index to determine the periodontal prognosis on molars

Metatranscriptomic analysis shows functional alterations in subgingival biofilm in young smokers with periodontitis: a pilot study

OBJECTIVE

This study aimed to assess the influence of smoking on the subgingival metatranscriptomic profile of young patients affected by stage III/IV and generalized periodontal disease.

METHODOLOGY

In total, six young patients, both smokers and non-smokers (n=3/group), who were affected by periodontitis were chosen. The STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for case-control reporting were followed. Periodontal clinical measurements and subgingival biofilm samples were collected. RNA was extracted from the biofilm and sequenced via Illumina HiSeq. Differential expression analysis used Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and differentially expressed genes were identified using the Sleuth package in R, with a statistical cutoff of ≤0.05.

RESULTS

This study found 3351 KEGGs in the subgingival biofilm of both groups. Smoking habits altered the functional behavior of subgingival biofilm, resulting in 304 differentially expressed KEGGs between groups. Moreover, seven pathways were modulated: glycan degradation, galactose metabolism, glycosaminoglycan degradation, oxidative phosphorylation, peptidoglycan biosynthesis, butanoate metabolism, and glycosphingolipid biosynthesis. Smoking also altered antibiotic resistance gene levels in subgingival biofilm by significantly overexpressing genes related to beta-lactamase, permeability, antibiotic efflux pumps, and antibiotic-resistant synthetases.

CONCLUSION

Due to the limitations of a small sample size, our data suggest that smoking may influence the functional behavior of subgingival biofilm, modifying pathways that negatively impact the behavior of subgingival biofilm, which may lead to a more virulent community.

Periodontal and microbiological evaluation in cleft lip/palate patients undergoing orthodontic treatment: A cross-sectional study

BACKGROUND

The present cross-sectional study was undertaken to evaluate the periodontal and microbiological parameters in patients with surgically repaired unilateral cleft lip and palate (UCLP) undergoing orthodontic correction in comparison to patients without any cleft or orthodontic treatment.

METHODS

A total of 120 patients, out of initial 148 patients, between the age group 6 and 18 years were enrolled and divided into four groups with 30 patients each: non-cleft patients without orthodontic treatment in Group 1, non-cleft patients undergoing fixed orthodontic treatment in Group 2, patients with UCLP without any orthodontic treatment in Group 3, and patients with UCLP undergoing fixed orthodontic treatment in Group 4. Periodontal parameters including plaque index (PI), gingival index (GI), gingival bleeding index (GBI), community periodontal index of treatment needs (CPITN) index, pocket probing depth (PD), and tooth mobility were measured in all the groups. The subgingival plaque samples of all the patients were subjected to microbial evaluation using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS) for clinical diagnosis.

RESULTS

The periodontal parameters were significantly raised in Group 4, followed by Group 3 and Group 2 in comparison to Group 1 (p < 0.01), thereby suggesting poor periodontal health in patients with UCLP undergoing orthodontic treatment. Statistically significant differences (p < 0.01) in counts of micro-organisms among the groups were observed for P. gingivalis, P. intermedia, Veillonella, and Capnocytophaga, with the highest proportions in Group 4, indicating a deteriorating oral health in these patients.

CONCLUSION

Poor periodontal and microbial health in patients with UCLP undergoing orthodontic treatment indicates a need for reinforcement of oral hygiene practices among these patients.

Systematic Review of Prognosis Models in Predicting Tooth Loss in Periodontitis

This study reviews and appraises the methodological and reporting quality of prediction models for tooth loss in periodontitis patients, including the use of regression and machine learning models. Studies involving prediction modeling for tooth loss in periodontitis patients were screened. A search was performed in MEDLINE via PubMed, Embase, and CENTRAL up to 12 February 2022, with citation chasing. Studies exploring model development or external validation studies for models assessing tooth loss in periodontitis patients for clinical use at any time point, with all prediction horizons in English, were considered. Studies were excluded if models were not developed for use in periodontitis patients, were not developed or validated on any data set, predicted outcomes other than tooth loss, or were prognostic factor studies. The CHARMS checklist was used for data extraction, TRIPOD to assess reporting quality, and PROBAST to assess the risk of bias. In total, 4,661 records were screened, and 45 studies were included. Only 26 studies reported any kind of performance measure. The median C-statistic reported was 0.671 (range, 0.57-0.97). All studies were at a high risk of bias due to inappropriate handling of missing data (96%), inappropriate evaluation of model performance (92%), and lack of accounting for model overfitting in evaluating model performance (68%). Many models predicting tooth loss in periodontitis are available, but studies evaluating these models are at a high risk of bias. Model performance measures are likely to be overly optimistic and might not be replicated in clinical use. While this review is unable to recommend any model for clinical practice, it has collated the existing models and their model performance at external validation and their associated sample sizes, which would be helpful to identify promising models for future external validation studies.

Influence of mobility on the long-term risk of tooth extraction/loss in periodontitis patients. A systematic review and meta-analysis

The aim of this systematic review (SR) was to assess whether tooth mobility (TM) increases the risk of tooth extraction/loss. The protocol was registered in PROSPERO database (CRD42023485425). The focused PECO questions were as follows: (1) "In patients with periodontitis, undergoing periodontal treatment, are teeth affected by mobility at higher risk of being extracted/lost compared to non-mobile teeth, with a minimum follow-up of 10 years?" and (2) "In these patients, does varying degrees of tooth mobility increase the risk of tooth extraction/loss, with a minimum follow-up of 10 years?". Results were reported according to PRISMA statement. Electronic and manual searches were conducted to identify longitudinal studies. The different assessments of tooth mobility were pooled into three groups: TM0: Undetectable tooth mobility, TM1: Horizontal/Mesio-distal mobility ≤1 mm, TM2: Horizontal/Mesio-distal mobility >1 mm or vertical tooth mobility. Tooth loss was the primary outcome. Various meta-analyses were conducted, including subgroup analyses considering different follow-up lengths and the timing of TM assessment, along with sensitivity analyses. A trial sequential analysis was also performed. Eleven studies were included (1883 patients). The mean follow-up range was 10-25 years. The weighted total of included teeth, based on the sample size, was 18 918, with a total of 1604 (8.47%) extracted/lost teeth. The overall rate of tooth extraction/loss increased with increasing mobility: TM0 was associated with a 5.85% rate (866/14822), TM1 with the 11.8% (384/3255), TM2 with the 40.3% (339/841). Mobile teeth (TM1/TM2) were at an increased risk for tooth extraction/loss, compared to TM0 (HR: 2.85; [95% CI 1.88-4.32]; p < .00001). TM1 had a higher risk than TM0 (HR: 1.96; [95% CI 1.09-3.53]; p < .00001). TM2 had a higher risk than TM1 (HR: 2.85; [95% CI 2.19-3.70]; p < .00001) and TM0 (HR: 7.12; [95% CI 3.27-15.51]; p < .00001). The results of the tests for subgroup differences were not significant. Sensitivity meta-analyses yielded consistent results with other meta-analyses. Within the limits of the quality of the studies included in the meta-analyses, mobile teeth were at higher risk of being extracted/lost in the long-term and higher degrees of TM significantly influenced clinicians' decision to extract a tooth. However, most teeth can be retained in the long-term and thus TM should not be considered a reason for extraction or a risk factor for tooth loss, regardless of the degree of TM.

Ten-year prognostic outcomes of molar survival using the Miller-Mcentire Periodontal Prognostic Index - A longitudinal prospective study

Background

A 10-year survival analysis was performed to assess the predictive validity of the periodontal risk score (formerly known as Miller-McEntire Periodontal Prognostic Index [MMPPI]) to predict long-term survival of periodontally diseased molars in a longitudinally assessed cohort.

Materials and Methods

The MMPPI scores were computed at baseline by summarizing scores allocated for individual factors. The cohort was treated, followed up, and placed under regular periodontal maintenance. Molar survival data collected up to 10 years of follow-up were analyzed. Cox proportional regression was performed, and hazards ratio (HR) were computed for each prognostic factor and the MMPPI score. To estimate the predictive value of MMPPI, a receiver operating curve (ROC) curve analysis was performed.

Results

From 1032 molars, 155 molars were extracted over the 10-year follow-up duration. Cox proportional hazard analysis showed significant hazard ratios for tooth loss for the component variables significant HR was noted for age: 4.92 (3.34:7.27), smoking: 1.74 (1.38-2.22), diabetes: 1.66 (1.49-1.86), molar type: 1.39 (1.15-1.67), probing depth: 2.00 (1.63-2.46), furcation: 2.64 (2.30-3.03), mobility: 3.45 (2.98-4.01), and total MMPPI score: 1.98 (1.85-2.12). ROC curve analysis showed an area under the curve value of 0.94 for the MMPPI index as a predictor of molar loss at 8 years, and the Youden index was maximized at the optimal cutoff point score of 7.

Conclusions

All component scores of MMPPI showed significant hazard ratios at 10 years. These findings support the previous results from the 5-year analysis of this university-based cohort and warrant validation in independent cohorts.

Advancements in Methods of Classification and Measurement Used to Assess Tooth Mobility: A Narrative Review

Evaluating tooth mobility is clinically significant, not only for diagnosing periodontal tissues but also in determining the overall periodontal treatment plan. Numerous studies related to tooth mobility have been conducted over the years, including the proposal of various classifications as well as the development of electronic devices for objective measurement. However, there is still no consensus on the measurement methods and criteria for assessing tooth mobility. In this study, we provide a comprehensive review of past and current tooth mobility classification and measurement methods. In order to propose a new method to intuitively evaluate tooth mobility based on previous studies, a digital approach capable of recording tooth micromovements induced by dynamic load should be considered.

Machine Learning in Predicting Tooth Loss: A Systematic Review and Risk of Bias Assessment

Predicting tooth loss is a persistent clinical challenge in the 21st century. While an emerging field in dentistry, computational solutions that employ machine learning are promising for enhancing clinical outcomes, including the chairside prognostication of tooth loss. We aimed to evaluate the risk of bias in prognostic prediction models of tooth loss that use machine learning. To do this, literature was searched in two electronic databases (MEDLINE via PubMed; Google Scholar) for studies that reported the accuracy or area under the curve (AUC) of prediction models. AUC measures the entire two-dimensional area underneath the entire receiver operating characteristic (ROC) curves. AUC provides an aggregate measure of performance across all possible classification thresholds. Although both development and validation were included in this review, studies that did not assess the accuracy or validation of boosting models (AdaBoosting, Gradient-boosting decision tree, XGBoost, LightGBM, CatBoost) were excluded. Five studies met criteria for inclusion and revealed high accuracy; however, models displayed a high risk of bias. Importantly, patient-level assessments combined with socioeconomic predictors performed better than clinical predictors alone. While there are current limitations, machine-learning-assisted models for tooth loss may enhance prognostication accuracy in combination with clinical and patient metadata in the future.

Comparison Study of Diagnosis and Treatment Planning for Dental Infections between Dental Students and Practitioners

This study aimed to access the knowledge in diagnosing dental infections and the practice in treatment planning for the affected teeth among dental practitioners (DPs) and senior (final-year) students. A survey questionnaire containing two cases (Case A; periodontal abscess and Case B; periapical abscess) with four questions per case was delivered to potential participants. Fifty-nine DPs voluntarily participated in the survey. For senior students, the case study was a part of their course requirements; one of the two cases (either Case A or B) was randomly assigned to the 126 seniors. The distribution of responses was significantly different between the DP and senior groups except for the diagnosis of Case B (Fisher’s exact test; p = 0.05). Only 31% of the participants diagnosed Case A as periodontal abscess; most of them selected periodontal surgery as the first treatment option. Despite a high agreement in diagnosing Case B, the choice of treatment was significantly different; the most frequent treatment option was extraction (51%) from the DP group and root canal retreatment (57%) from the senior group. The study revealed that the diagnosis of periodontal abscess was more challenging than that of periapical abscess among dental professionals.

A 5-year prospective validation of the Miller–McEntire Periodontal Prognostic Index

Background:

Materials and Methods:

Results:

Conclusions:

External validation and comparison of the predictive performance of 10 different tooth-level prognostic systems

AIM

Tooth-level prognostic systems can be used for treatment planning and risk assessment. This retrospective longitudinal study aimed to evaluate the prognostic performance of 10 different tooth-level risk assessment systems in terms of their ability to predict periodontal-related tooth loss (TLP).

MATERIALS AND METHODS

Data were retrieved retrospectively from patients who received surgical and non-surgical periodontal treatment. Data on medical history and smoking status at baseline and the last maintenance visit were collected. Ten tooth-level prognostic systems were compared using both univariate and multivariate Cox proportional hazard regression models to analyse the prognostic capability of each system for predicting TLP risk.

RESULTS

One-hundred and forty-eight patients with 3787 teeth, followed-up for a mean period of 26.5 ± 7.4 years, were evaluated according to 10 different tooth-level prognostic systems, making up a total of 37,870 individual measurements. All compared prognostic systems were able to stratify the risk of TLP at baseline when different classes of association were compared. After controlling for maintenance, age, and gender, all systems exhibited excellent predictive capacity for TLP with no system scoring a Harrell's C-index less than 0.925.

CONCLUSIONS

All tooth-level prognostic systems displayed excellent predictive capability for TLP. Overall, the Miller and McEntire system may have shown the best discrimination and model fit, followed by the Nunn et al. system.

Multivariate outcome evaluation of furcation-involved molars treated with non-surgical mechanical therapy alone or combined with open flap debridement: A retrospective study

BACKGROUND

This retrospective study assessed the effect of non-surgical and surgical mechanical therapy for furcation-involved molars.

METHODS

Furcation defects treated and followed for at least 1 year were selected. Data relative to the clinical outcomes were recorded. The immediate (3- to 6-month) clinical outcomes and the long-term survival of the treated molars were assessed. The potential variables influencing the treatment outcomes through multi-level regression analysis, and Cox Proportional-Hazards Models were also analyzed.

RESULTS

One hundred and eighty-four molars were included with an average follow-up of 7.52 years. At the 3- to 6-month re-evaluation 1.39 ± 0.99 mm pocket depth reduction, 0.88 ± 1.29 mm clinical attachment gain, and a 0.51 ± 1.13 mm increase in recession was observed. The 5- and 10-year survival rates were 88.3% and 61.3%, respectively. The horizontal and vertical extent of furcation involvement, baseline probing depth, mucoperiosteal flap elevation, and the frequency of supportive periodontal therapy influenced the clinical outcomes and tooth survival.

CONCLUSION

Non-surgical and surgical mechanical root debridement is a viable treatment for the management of furcation involved molars with shallow horizontal and vertical components.

Development of a prognostic tool: based on risk factors for tooth loss after active periodontal therapy

Objectives

The aim of this study was to develop a prognostic tool to estimate long-term tooth retention in periodontitis patients at the beginning of active periodontal therapy (APT).

Material and methods

Tooth-related factors (type, location, bone loss (BL), infrabony defects, furcation involvement (FI), abutment status), and patient-related factors (age, gender, smoking, diabetes, plaque control record) were investigated in patients who had completed APT 10 years before. Descriptive analysis was performed, and a generalized linear-mixed model-tree was used to identify predictors for the main outcome variable tooth loss. To evaluate goodness-of-fit, the area under the curve (AUC) was calculated using cross-validation. A bootstrap approach was used to robustly identify risk factors while avoiding overfitting.

Results

Only a small percentage of teeth was lost during 10 years of supportive periodontal therapy (SPT; 0.15/year/patient). The risk factors abutment function, diabetes, and the risk indicator BL, FI, and age (≤ 61 vs. > 61) were identified to predict tooth loss. The prediction model reached an AUC of 0.77.

Conclusion

This quantitative prognostic model supports data-driven decision-making while establishing a treatment plan in periodontitis patients. In light of this, the presented prognostic tool may be of supporting value.

Clinical relevance

In daily clinical practice, a quantitative prognostic tool may support dentists with data-based decision-making. However, it should be stressed that treatment planning is strongly associated with the patient’s wishes and adherence. The tool described here may support establishment of an individual treatment plan for periodontally compromised patients.

Association, prediction, generalizability: Cross-center validity of predicting tooth loss in periodontitis patients

OBJECTIVES

To predict patients' tooth loss during supportive periodontal therapy across four German university centers.

METHODS

Tooth loss in 897 patients in four centers (Kiel (KI) n = 391; Greifswald (GW) n = 282; Heidelberg (HD) n = 175; Frankfurt/Main (F) n = 49) during supportive periodontal therapy (SPT) was assessed. Our outcome was annualized tooth loss per patient. Multivariable linear regression models were built on data of 75 % of patients from one center and used for predictions on the remaining 25 % of this center and 100 % of data from the other three centers. The prediction error was assessed as root-mean-squared-error (RMSE), i.e., the deviation of predicted from actually lost teeth per patient and year.

RESULTS

Annualized tooth loss/patient differed significantly between centers (between median 0.00 (interquartile interval: 0.00, 0.17) in GW and 0.09 (0.00, 0.19) in F, p = 0.001). Age, smoking status and number of teeth before SPT were significantly associated with tooth loss (p < 0.03). Prediction within centers showed RMSE of 0.14-0.30, and cross-center RMSE was 0.15-0.31. Predictions were more accurate in F and KI than in HD and GW, while the center on which the model was trained had a less consistent impact. No model showed useful predictive values.

CONCLUSION

While covariates were significantly associated with tooth loss in linear regression models, a clinically useful prediction was not possible with any of the models and generalizability was not given. Predictions were more accurate for certain centers.

CLINICAL RELEVANCE

Association should not be confused with predictive value: Despite significant associations of covariates with tooth loss, none of our models was useful for prediction. Usually, model accuracy was even lower when tested across centers, indicating low generalizability.

Analyzing the predictability of the Kwok and Caton periodontal prognosis system: A retrospective study

BACKGROUND

The aim of this study was to analyze the predictability of the Kwok and Caton periodontal prognosis system by investigating tooth survival within a 64-month period and to compare this to other well-established prognosis systems.

METHODS

This retrospective study included the records of patients who had a minimum of two dental exams at least 12 months apart at a single University-affiliated Dental Center. Data including patients' age, sex, length of follow-up period, initial tooth prognosis, revised tooth prognosis, tooth type, and number of teeth lost at the latest exam were recorded. Descriptive analysis was used for data interpretation.

RESULTS

A total of 4,046 teeth from 174 patients qualified for the study. Teeth with initial poorer prognosis had a higher chance of being extracted compared with those with a better initial prognosis. Tooth survival rate at the latest follow-up for those with an initial favorable, questionable, unfavorable, and hopeless prognosis was 97.9%, 90.7%, 62.5%, and 17.7%, respectively. Teeth initially assigned to a poorer prognosis category had a higher proportion that changed to a worse prognosis at the latest periodontal exam.

CONCLUSIONS

The Kwok and Caton prognosis system can predictably determine tooth survivability within a 5-year period. The defined categories of this prognosis system are more reliable than that of other systems in the short-term. However, long-term (>5 years) prediction accuracy of this prognosis system needs further investigation.

Declassifying Mobility Classification

INTRODUCTION

Tooth mobility is often discussed among dental health care providers according to a numerical scale (ie, 1, 2, or 3) without a clear understanding of the definition of each category. Thus, a comprehensive review to examine and discuss the various classifications is needed. The aim of this comprehensive review was to discuss the main clinical classifications of tooth mobility.

METHODS

The authors conducted electronic searches in MEDLINE, Scopus, and PubMed. Additionally, the authors manually searched the textbooks, gray literature, and bibliographies of all relevant articles.

RESULTS

The most commonly referenced clinical index for mobility was the Miller index; yet, many other mobility classifications exist as well as modifications of those indexes. The literature has been very inconsistent and at times inaccurate when classifying mobility; using various stages of mobility using grades, classes, and scores interchangeably and not defining the meaning of the actual numerical scores/terminologies are common problems.

CONCLUSIONS

In order to avoid ambiguity and provide clarity regarding the impact of degrees of mobility when used clinically, this review comprehensively discusses different classifications and definitions of tooth mobility with attention to the importance of using them consistently and accurately. There is a need to standardize 1 classification for mobility.

Clinical decision support model for tooth extraction therapy derived from electronic dental records

STATEMENT OF PROBLEM

Tooth extraction therapy serves as a key initial step in many prosthodontic treatment plans. Dentists must make an appropriate decision on the tooth extraction therapy considering multiple determinants and whether a clinical decision support (CDS) model might help.

PURPOSE

The purpose of this retrospective records study was to construct a CDS model to predict tooth extraction therapy in clinical situations by using electronic dental records (EDRs).

MATERIAL AND METHODS

The cohort involved 4135 deidentified EDRs of 3559 patients from the database of a prosthodontics department. Knowledge-based algorithms were first proposed to convert raw data from EDRs into structured data for feature extraction. Redundant features were filtered by a recursive feature-elimination method. The tooth extraction problem was then modeled alternatively as a binary or triple classification problem to be solved by 5 machine learning algorithms. Five machine learning algorithms within each model were compared, as well as the efficiency between 2 models. In addition, the proposed CDS was verified by 2 prosthodontists.

RESULTS

The triple classification model outperformed the binary model with the F1 score of the Extreme Gradient Boost (XGBoost) algorithm as 0.856 and 0.847, respectively. The XGBoost outperformed the other 4 algorithms. The accuracy, precision, and recall of the XGBoost algorithm were 0.962, 0.865, and 0.830 in the binary classification and 0.924, 0.879, and 0.836 in the triple classification, respectively. The performance of the 2 prosthodontists was inferior to the models.

CONCLUSIONS

The CDS model for tooth extraction therapy achieved high performance in terms of decision-making derived from EDRs.

Effects of adjunctive probiotic L. reuteri lozenges on S/RSD outcomes at molar sites with deep pockets

AIM

To evaluate effects of probiotic Lactobacillus reuteri (L. reuteri) lozenges as an S/RSD adjunct on site-level changes at molars with deep pockets.

MATERIALS AND METHODS

447 molar sites with pockets ≥ 5 mm from a previous randomized clinical trial of adjunctive L. reuteri lozenges for 28 days were analyzed. Multilevel mixed-effect models (MLM) were constructed to analyze site-level outcomes "change in CAL" and "pocket closure" (residual PPD < 5 mm) in placebo and probiotic groups at 90 and 180 days. Possible patient-, tooth-, and site-level predictors were analyzed as fixed-effects.

RESULTS

Estimated change in CAL in probiotic (90 day: 0.87 mm, 180 day: 0.68 mm) was greater than placebo treated molar sites (90 day: 0.73 mm, 180 day: 0.66 mm) and the relative risk (RR) of pocket closure in the probiotic group (90 day: 1.7, 180 day: 1.6) was higher as compared to placebo. Furcation involvement and BOP at site predicted significantly worse treatment outcomes.

CONCLUSION

As compared to S/RSD with placebo, a 28-day course of adjunctive probiotic L. reuteri lozenges improved CAL change at molar sites with ≥ 5 mm deep pockets and conferred a higher probability of shallow residual pocket depth. Presence of furcation-involvement and bleeding on probing worsened treatment outcomes.

Microbiological evaluation of LOCATOR® Legacy attachments: A cross-sectional clinical study

Objective

This retrospective cross‐sectional study aimed to evaluate quantitatively the oral microbiome in the tri‐lobe central cavity of Locator Legacy attachment and verify whether it harbors a different, potentially more pathogenic, bacterial spectrum than the adjacent edentulous ridge.

Materials and Methods

Edentulous patients rehabilitated with implant overdentures using Locator Legacy attachments were recruited for this study. The clinical examination comprised probing depths, mobility, peri‐implant, and periodontal health along with intraoral swabs for microbiological evaluation, polymerase chain reaction (PCR) testing, and candida culture. The swabs were collected from the trilobed cavity of the attachment and the adjacent edentulous ridge. PCR was performed to detect six specific bacteria, Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, Tannerella forsythia, Treponema denticola, Prevotella intermedia, and Parvimonas micra. Statistical analyses were performed using McNemar's test and Wilcoxon's rank sum test with the significance set to p < .05.

Results

A total of 50 participants with a mean age of 71.5 ± 9.6 years participated in the study. No significant differences in the microbiome were found between samples from the ridge and the attachment. No significantly different numbers in the candida cultures were identified, and the presence of a removable prostheses did not demonstrate a significant association with the prevalence of candida.

Conclusions

Within the limits of this study and the investigated bacterial species, the trilobed cavity of the attachment does not seem to increase the bacterial load.

Evidence-Based Update on Diagnosis and Management of Gingivitis and Periodontitis

This article is an overview to update the practicing general dental practitioner about clinically relevant evidence-based topics published in the recent past in the diagnosis, etiopathogenesis, and management of gingivitis and periodontitis.

Evaluation of periodontally diseased molars in diabetics with Miller-McEntire Periodontal Prognostic Index

Aim and Objective:

The aim of this study was to prospectively determine and establish the periodontal prognosis of diseased molars in diabetic patients using the Miller–McEntire Periodontal Prognostic Index (MMPPI) with an additional criterion for diabetes (changes in glycosylated hemoglobin levels), at 2-year postperiodontal therapy.

Materials and Methods:

A sample of 200 molars in 25 patients with diabetes mellitus (DM) and chronic periodontitis were evaluated. The prognostic parameters evaluated include age, probing depth (PD), mobility, furcation involvement, diabetes, and molar type. The total score calculated from all parameters was used considered prognosis score for each molar. All patients were evaluated at baseline and 2-year posttreatment.

Results:

The results of this study suggest that following prognostic factors, DM (hazard ratio [HR] =5.2), age (HR = 0.4), and molar type (HR = 0.6) were clinically significant at the end of the 2-year posttherapy from baseline. A total of 4 (2%) teeth were extracted from the 200 teeth with a mean of 0.02 for the tooth lost during 2-year posttreatment. Significant improvements (P < 0.05) in the frequency PD, furcation, and mobility scores were noted at 2 years.

Conclusions:

These findings demonstrate that score for DM as prognostic criterion is a valid addition to MMPPI. The factors such as DM, age, and molar type can impact the prognosis of molar survival. Studies with a larger sample size and longer follow-up are required to affirm the findings of this preliminary study.

Prospective evaluation of periodontally diseased molars in smokers using the Miller-McEntire Periodontal Prognostic Index

BACKGROUND

The purpose of this 2-year prospective survival analysis study is to determine a statistically validated periodontal prognostic score for diseased molars in smokers using the Miller-McEntire Periodontal Prognostic Index (MMPPI).

MATERIALS AND METHODS

Two hundred molars were evaluated from 25 patients who were smokers with moderate-to-severe chronic periodontitis. The factors evaluated included age, probing depth, mobility, furcation involvement, smoking, and molar type. A modified, 5 level, scoring criterion for smoking based on smoking-dose was adopted. MMPPI was computed as the sum of scores for all six prognostic factors. Appropriate periodontal treatment and supportive periodontal therapy were provided. All patients were evaluated at baseline and 2 years posttreatment. Hazard risk ratio (HR) was computed for each prognostic factor.

RESULTS

A total of 3 (1.5%) teeth of the 200 molars were extracted over the 2-year follow-up duration, with a mean of 0.015 teeth lost. The HR was found as significantly higher for three individual prognostic factors: mobility (HR = 5.57, P = 0.02), smoking (HR = 3.35, P = 0.04), and furcation involvement (HR = 7.30, P = 0.01). Significant and positive HR (HR = 1.70, P = 0.01) was noted for the total MMPPI score, validating its prognostic value for molar survival at 2 years prospectively.

CONCLUSIONS

The findings of the current study demonstrate the prognostic validity of MMPPI incorporating a more detailed smoking score criterion. The factors smoking, furcation involvement, and mobility significantly impacted the likelihood of survival of periodontally diseased molars. Further studies with a larger sample size and longer follow-up are required to confirm these findings.

Introduction of a prediction model to assigning periodontal prognosis based on survival time

AIMS

To develop a prediction model for tooth loss due to periodontal disease (TLPD) in patients following periodontal maintenance (PM), and assess its performance using a multicentre approach.

MATERIAL AND METHODS

A multilevel analysis of eleven predictors of TLPD in 500 patients following PM was carried out to calculate the probability of TLPD. This algorithm was applied to three different TLPD samples (369 teeth) gathered retrospectively by nine periodontist, associating several intervals of probability with the corresponding survival time, based on significant differences in the mean survival time. The reproducibility of these associations was assessed in each sample (One-way ANOVA and pairwise comparison with Bonferroni corrections).

RESULTS

The model presented high specificity and moderate sensitivity, with optimal calibration and discrimination measurements. Seven intervals of probability were associated with seven survival time and these associations contained close to 80% of the cases: the probability predicted the survival time at this percentage. The model performed well in the three samples, as the mean survival time of each association were significantly different within each sample, while no significant differences between the samples were found in pairwise comparisons of means.

CONCLUSIONS

This model might be useful for predicting survival time in different TLPD samples.

A novel mouthpiece prevents bite injuries caused by intraoperative transcranial electric motor-evoked potential monitoring

PURPOSE

Intraoperative transcranial motor-evoked potential monitoring causes contraction of the masseter muscles, which may cause injuries to the oral cavity and damage to the orotracheal tube. We developed a mouthpiece made from vinyl-silicone impression material to prevent these injuries. The purpose of this study was to examine its efficacy and safety.

METHODS

Twenty-two patients undergoing spinal surgery under transcranial motor-evoked potential monitoring were fitted with bespoke vinyl-silicone mouthpieces by dentists before surgery. On induction of general anesthesia and orotracheal intubation, the mouthpiece was attached to the upper and lower dental arches. A lateral cervical X-ray was taken at the end of surgery to examine the condition of the orotracheal tube. The incidence of endotracheal tube deformation was compared with an historic control group of 20 patients in whom a conventional gauze bite block had been previously used before induction of the mouthpiece. The oral cavity was examined by a dentist the day before surgery and 3 days postoperatively, and intraoral injuries were recorded.

RESULTS

No endotracheal tube deformation was found in 22 patients fitted with the new mouthpiece. The incidence of tube deformation (none of 22 patients, 0 %) was significantly lower than in those who had been fitted with the gauze bite block (9 of 20 patients, 45.0 %; p < 0.001). Application of the mouthpiece resulted in no tongue or tooth injuries.

CONCLUSION

A novel mouthpiece reduced the incidence of damage to the endotracheal tube caused by intraoperative transcranial motor-evoked potential monitoring.

Using prognostic factors from case series and cohort studies to identify individuals with poor long-term outcomes during periodontal maintenance

BACKGROUND

The accuracy of applying prognostic factors to individual patients is uncertain.

AIM/METHOD

The aim was to apply prognostic factors from several outcome studies (case series and cohort) to identify: (1) patients who lost a tooth/teeth during periodontal maintenance; (2) patients who were non-responding to treatment; (3) patients needing re-treatment during periodontal maintenance. In addition, tooth loss was related to initial prognosis and it was determined which of the prognostic factors were also risk factors. Chi squared analysis was carried out for the outcomes of patients with-, and without prognostic factors. Significance level was set at p ≤ 0.05. Sensitivity and specificity was calculated for patients with and without prognostic factors.

RESULTS

The prognostic factors only identified a small proportion of patients who lost teeth (34-38%). Combining the prognostic factors resulted in a lower accuracy. A higher proportion of patients with no prognostic factors lost teeth (53.8-96.2%). The chance of identifying a non-responding patient based on family history was 5.9%, for stress 32.4%, and for heavy smoking 8.7%. Significantly more patients (29/40 , χ² = 16.2 p < 0.05) with initial uncertain/poor prognosis and significantly fewer patients (11/40, χ² = 16.2, p < 0.05) with erratic/no compliance needing re-treatment were identified. 21 of 40 patients (52.5%) (p = 0.655) with family history needing retreatment were identified. Combining the prognostic factors identified 5-22% out of a total of 40% of patients needing re-treatment. six out of nine (67%) teeth with an initial hopeless prognosis were lost, 10/109 (9%) teeth with a poor prognosis were lost, 11/346 (3%) teeth with a moderate prognosis were lost and 9/1972 (0.46%) of teeth with a good prognosis were lost. None of the prognostic factors was found also to be a risk factor for developing periodontal diseases.

CONCLUSION

Applying prognostic factors to identify individual patients with poor long-term outcomes is associated with low accuracy.

Videoscope-assisted minimally invasive periodontal surgery (V-MIS)

AIM

Small incision surgery has become routine in many areas of medicine but has not been widely accepted in periodontal therapy. A videoscope to assist minimally invasive surgery (MIS) has been developed. The clinical outcomes from MIS performed using this videoscope (V-MIS) are reported.

MATERIALS AND METHODS

Patients were evaluated for residual defects following non-surgical therapy consisting of root planing with local anaesthetic. Thirty patients having 110 sites with residual pocket probing depth (PPD) of at least 5 mm, 2 mm loss of clinical attachment level (CAL), and radiographic evidence of bone loss were surgically treated. V-MIS was performed utilizing the videoscope for surgical visualization.

RESULTS

At re-evaluation 6 months post surgery, there was a statistically significant improvement (p < .001) in mean PPD and CAL (PPD 3.88 ± 1.02 mm, CAL 4.04 ± 1.38 mm) in 1, 2, and 3 wall defects. All PPD at re-evaluation were 3 mm or less. There was a mean post-surgical increase in soft tissue height (0.13 ± 0.61 mm, p = 0.168) with a decrease in recession.

CONCLUSIONS

The improvement in PPD and CAL from V-MIS, in the authors' opinion, appears to be favourable when compared to previously reported results of periodontal regenerative surgery. The lack of post-surgical recession following V-MIS has not been reported with traditional regenerative surgery.