Association Between the Severity of Periodontitis and Temporomandibular Joint Symptoms in Patients Requiring Prosthodontic Rehabilitation: A Cross-Sectional Study
Bibliographic record
Abstract
Introduction Periodontitis and temporomandibular joint (TMJ) disorders are prevalent conditions that may influence prosthodontic treatment outcomes, owing to their impact on occlusal stability and jaw function. Understanding this association is critical for optimizing treatment planning and improving patient outcomes. This study investigated the relationship between the severity of periodontitis and clinical TMJ symptoms in patients requiring prosthodontic restoration, with the aim of providing evidence-based guidance for integrated clinical management. Materials and methods A cross-sectional observational study was conducted on 80 adult patients (aged 18-55 years) with different stages of periodontitis and a clinical indication for prosthodontic rehabilitation, excluding those with systemic diseases affecting the TMJ or prior TMJ surgery. Periodontal status was assessed using probing depth, clinical attachment loss, and cone-beam computed tomography (CBCT) to evaluate condylar morphology and the articular eminence angle. TMJ symptoms were evaluated through clinical examination of jaw movement, joint sounds, and tenderness. The Fonseca Anamnestic Index (FAI) was used to assess the presence and intensity of symptoms of temporomandibular joint disorders (TMDs). Prosthodontic treatment plans and occlusal characteristics were documented. Data were analyzed using the chi-square test, the Kruskal-Wallis test, and principal component analysis (PCA), with a significance level of p < 0.05. Results Significant associations were found between the severity of periodontitis and TMJ symptoms, particularly tenderness on palpation and changes in condylar morphology. Functional impairments, including reduced mouth opening and increased deviation, worsened with the severity of periodontitis. The FAI, which reflects pain and dysfunction, progressively escalated across the periodontal groups. Structural changes, such as steeper articular eminence inclination, were prominent in patients with severe periodontitis. PCA identified a TMJ pathology continuum driven by periodontitis severity. Conclusion The severity of periodontitis was correlated with worsened TMJ symptoms, impacting prosthodontic treatment planning. Integrated periodontal and TMJ management is essential for optimizing functional restoration and patient comfort during prosthodontic care.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".