The new periodontal disease classification: Level of agreement on diagnoses and treatment planning at various dental education levels

Structure, governance and delivery of specialist training programs in periodontology and implant dentistry

AIM

To update the competences and learning outcomes and their evaluation, educational methods and education quality assurance for the training of contemporary specialists in periodontology, including the impact of the 2018 Classification of Periodontal and Peri-implant Diseases and Conditions (2018 Classification hereafter) and the European Federation of Periodontology (EFP) Clinical Practice Guidelines (CPGs).

METHODS

Evidence was gathered through scientific databases and by searching for European policies on higher education. In addition, two surveys were designed and sent to program directors and graduates.

RESULTS

Program directors reported that curricula were periodically adapted to incorporate advances in diagnosis, classification, treatment guidelines and clinical techniques, including the 2018 Classification and the EFP CPGs. Graduates evaluated their overall training positively, although satisfaction was limited for training in mucogingival and surgical procedures related to dental implants. Traditional educational methods, such as didactic lectures, are still commonly employed, but they are now often associated with more interactive methods such as case-based seminars and problem-based and simulation-based learning. The evaluation of competences/learning outcomes should employ multiple methods of assessment.

CONCLUSION

An update of competences and learning outcomes of specialist training in periodontology is proposed, including knowledge and practical application of the 2018 Classification and CPGs. Harmonizing specialist training in periodontology is a critical issue at the European level.

The PocketPerio application significantly increases the accuracy of diagnosing periodontal conditions in didactic and chairside settings

The study aimed to determine the accuracy of diagnosing periodontal conditions using the developed web-based PocketPerio application and evaluate the user's perspective on the use of PocketPerio. First, 22 third-year dental students (DS3) diagnosed ten cases without PocketPerio (control) and with PocketPerio (test) during a mock examination. Then, 105 DS3, 13 fourth-year dental students (DS4), and 32 senior second-year International Standing Program students (ISP2) used PocketPerio chairside. Statistical analysis was performed using a non-parametric paired two-tailed test of significance with the Wilcoxon matched-pairs signed rank test. The null hypothesis that PocketPerio did not increase the accuracy of periodontal diagnoses was rejected at α < 0.01. Periodontal diagnoses made using PocketPerio correlated with those made by periodontics faculty ("gold standard") in all cases. During the mock examination, PocketPerio significantly increased the accuracy of periodontal diagnoses compared to the control (52.73 vs. 13.18%, respectively). Chairside, PocketPerio significantly increased the accuracy of primary (100 vs. 40.0%) and secondary (100 vs. 14.25%) periodontal diagnoses compared to the respective controls. Students regardless of their training year felt more confident in diagnosing periodontal conditions using PocketPerio than their current tools, provided positive feedback on its features, and suggested avenues for its further development.

Development and validation of a rule-based algorithm to identify periodontal diagnosis using structured electronic health record data

AIM

To develop and validate an automated electronic health record (EHR)-based algorithm to suggest a periodontal diagnosis based on the 2017 World Workshop on the Classification of Periodontal Diseases and Conditions.

MATERIALS AND METHODS

Using material published from the 2017 World Workshop, a tool was iteratively developed to suggest a periodontal diagnosis based on clinical data within the EHR. Pertinent clinical data included clinical attachment level (CAL), gingival margin to cemento-enamel junction distance, probing depth, furcation involvement (if present) and mobility. Chart reviews were conducted to confirm the algorithm's ability to accurately extract clinical data from the EHR, and then to test its ability to suggest an accurate diagnosis. Subsequently, refinements were made to address limitations of the data and specific clinical situations. Each refinement was evaluated through chart reviews by expert periodontists at the study sites.

RESULTS

Three-hundred and twenty-three charts were manually reviewed, and a periodontal diagnosis (healthy, gingivitis or periodontitis including stage and grade) was made by expert periodontists for each case. After developing the initial version of the algorithm using the unmodified 2017 World Workshop criteria, accuracy was 71.8% for stage alone and 64.7% for stage and grade. Subsequently, 16 modifications to the algorithm were proposed and 14 were accepted. This refined version of the algorithm had 79.6% accuracy for stage alone and 68.8% for stage and grade together.

CONCLUSIONS

Our findings suggest that a rule-based algorithm for suggesting a periodontal diagnosis using EHR data can be implemented with moderate accuracy in support of chairside clinical diagnostic decision making, especially for inexperienced clinicians. Grey-zone cases still exist, where clinical judgement will be required. Future applications of similar algorithms with improved performance will depend upon the quality (completeness/accuracy) of EHR data.

Electronic periodontal tool integration to enrich clinical diagnosis

PURPOSE/OBJECTIVES

The objective of this study was to evaluate the effectiveness of an Electronic-Periodontal-Diagnosis-Tool (EPDT) to facilitate the formulation of a correct periodontal diagnosis and analyze students' perceptions of the use of the EPDT.

METHODS

Fifty Year-3 students who recently started their clinical training, were randomly assigned to two groups. Two clinical scenarios involving challenging periodontal diagnoses, each one with unique components, variables, and categories were distributed with specific instructions. The cases were analyzed to determine the correct periodontal diagnosis-half without the use of the EPDT and half with the use of the EPDT. A post-exercise discussion conducted by the faculty explained the answer rationales. The students completed an anonymous/voluntary survey to evaluate their perceptions. Statistical analysis using likelihood ratio chi-square tests and a generalized linear model evaluated whether the use of the EPDT resulted in higher percentages of correct diagnoses.

RESULTS

EPDT use resulted in a three times higher percentage of correct classifications than no tool use (48% versus 16%), which the investigators considered an important effect of the EPDT. The generalized-linear-model assessment confirmed that EPDT resulted in better classifications (p < 0.0001). The feedback about the perceptions of the EPDT was favorable.

CONCLUSION

Students using the EPDT resulted in higher percentages of correct diagnoses. The EPDT provided students with a useful framework to determine the correct periodontal diagnoses, which is essential in providing appropriate treatments.

Periodontal diagnosis and treatment planning - An assessment of the understanding of the new classification system

OBJECTIVES

Substantial variations are seen among clinicians in the diagnosis and treatment planning of periodontal diseases. Accurate diagnosis and treatment planning are fundamental requirements for effective outcome-based patient care. The aim of this study was to evaluate the understanding of the American Academy of Periodontology and the European Federation of Periodontology 2017 periodontal disease classifications in diagnoses and treatment plans across four study groups.

METHODS

The study recruited at least 20 participants in each of the four study groups. These included 1) Periodontal faculty and residents at Indiana University School of Dentistry (IUSD-PF) 2) IUSD general practice faculty (IUSD-GPF), 3) private practice periodontists (PPP), and 4) general practitioners (GP). The participants were provided with 10 HIPPA de-identified case records and a link to a survey. The survey comprised five demographic questions and two questions on diagnosis and treatment plan for each case along with a fixed list of responses. The responses were then compared against gold standards that were determined by a group of three board-certified periodontists.

RESULTS

Overall, for diagnostic questions, GP (69%) were correct significantly less often than IUSD-PF (86%, p < 0.001), IUSD-GPF (79%, p = 0.002), and PPP (80%, p = 0.001). No significant differences (p > 0.05) in the overall correct treatment plan responses were found among the four groups (IUSD-PF: 69%, IUSD-GPF: 62%, PPP: 68%, and GP: 60%). The multi-rater kappas for with-in-group agreement on overall diagnosis ranged from 0.36 (GP) to 0.55 (IUSD-PF) and on overall treatment plan ranged from 0.32 (IUSD-GPF) to 0.42 (IUSD-PF). Overall agreement for diagnosis and treatment plans among the four groups was relatively low and none of the groups were statistically different from each other (p > 0.05).

CONCLUSION

Regular participation in calibration sessions may lead to more accurate adoption of the 2017 periodontal classification and thereby help provide consistent diagnosis and treatment.

Effects of periodontal clinical database software in resident training during COVID-19 pandemic: a prospective observational study

BACKGROUND

Dental residents in Guangdong, China, had fewer medical practice opportunities because of the pandemic of COVID-19. This study aimed to evaluate whether a case-based learning (CBL) approach using a periodontal clinical database software (PCDS) could improve residents' achievement in the exam of the standardized residency training (SRT) program.

METHODS

Forty-four dental residents volunteered and completed this trial. Within 12 weeks, all residents admitted periodontal patients 5 days a week and participated in a case-based learning course using PCDS once a week. Two online case-based examinations were used to evaluate their diagnostic and therapeutic performance before and after training. The total accuracy rate of examinations and the accuracy rate of subitems were analyzed using paired samples T-test. The Bonferroni correction is used for multiple testing adjustments, and p < 0.05 was considered statistical significance.

RESULTS

After training, the total accuracy rate of SRT exams raised from 65 to 76%. There was a significant difference in the accuracy rate before and after training (Mean = 0.103, SD = 0.141, p < 0.001). The accuracy of radiographic examination (type of alveolar bone absorption and hard tissue lesion of tooth) and making treatment plan was significantly improved after training (p < 0.005). However, residents' performance in diagnosing periodontitis and predicting the prognosis of affected teeth was not improved.

CONCLUSIONS

The PCDS and CBL method effectively improved the residents' achievement in SRT examination, especially in identifying the type of resorption of alveolar bone and the hard tissue lesion of a tooth by radiographic examination and making an appropriate treatment plan for a periodontitis patient. More effective teaching approaches are needed to improve residents' accuracy of diagnosis of periodontitis using the 2018 classification in China.