Rate and Demographic and Clinical Predictors of Initiation of Non-Surgical Periodontal Therapy: A Retrospective Chart Review Study
Bibliographic record
Abstract
Background: Periodontitis is a highly prevalent inflammatory disease that compromises individuals’ oral health, overall health, and quality of life. Non-surgical periodontal therapy (NSPT) has been found to prevent the progression of periodontitis and restore periodontal health. Evidence on patient engagement in this therapy remains limited. Understanding the factors leading to NSPT acceptance and initiation is crucial for improving patient outcomes. Objective: Assess the rate and demographic and clinical predictors of initiation of recommended NSPT in patients enrolled in the periodontology graduate program at the University of Alberta. Methods: This retrospective chart review study involved all patients aged 18 years or older who were recommended NSPT following a baseline assessment of their periodontal status between September 2017 December 2023. Clinical records on appointment attendance, demographic variables (age and sex), and clinical variables (clinical attachment level, missing teeth, and diabetes status) were retrieved from the program database. Descriptive statistics were used to summarize the outcome and predictive variables, while bivariate and multivariate logistic regression were performed to identify demographic and clinical predictors of NSPT initiation. Results: NSPT was recommended for 1,292 patients. Among these patients, 738 (57.1%) were female, 496 (38.4%) were seniors, and 8.5% were adults or young adults. Based on clinical attachment level, 939 (72.7%) had severe periodontitis, and 353 (27.3%) had mild/moderate periodontitis. Additionally, 11.5% of patients reported having diabetes and 463 (35.8%) had four or more missing teeth. Of all patients, 986 (76.3%) attended the first clinical appointment related to NSPT. Clinical attachment level (OR: 2.38, 95% CI: 1.8-3.1) and age (OR: 1.2, 95% CI: 1.1-1.3) independently predicted NSPT initiation; however, in a more parsimonious adjusted model, only clinical attachment level (OR: 2.44, 95% CI: 1.8–3.3) remained a significant predictor. Specifically, patients with severe periodontitis based on clinical attachment level had higher odds of initiating NSPT compared to those with mild/moderate periodontitis (OR: 2.44, 95% CI: 1.8–3.3). Conclusion: Approximately one in four patients did not initiate the recommended NSPT. While disease severity was found to predict initiation, further research using both quantitative and qualitative approaches is needed to gain a deeper understanding of the factors leading to non-initiation of NSPT.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".