Kindler Syndrome and Periodontal Disease: Review of the Literature and a 12‐Year Follow‐Up Case
Bibliographic record
Abstract
BACKGROUND: The association of aggressive periodontitis with Kindler syndrome was based on a single case in 1996 and later confirmed with a larger population. Since then, significant research has greatly increased our understanding of the molecular pathology of this disorder. We review recent advances in the molecular mechanisms of the syndrome and present a maintenance case report of a patient who has been followed in our clinic. METHODS: A female patient who was diagnosed with Kindler syndrome and aggressive periodontitis at the age of 16 years has been followed and treated in our clinic for 12 years. Her main treatment has been maintenance therapy following her initial treatment and restorative work previously documented. Gingival biopsies obtained during the recent extraction of hopeless maxillary molars were used for histologic assessment of gingival tissue attachment apparatus and to isolate gingival fibroblasts. Reverse transcription-polymerase chain reaction (RT-PCR) was performed using these cells to confirm the lack of expression of kindlin-1. RESULTS: RT-PCR showed the total loss of kindlin-1 mRNA in cultured gingival fibroblasts, supporting the clinical diagnosis of Kindler syndrome. Tissue biopsies revealed atypical pocket epithelium. Maintenance therapy has been moderately successful. Teeth that were recently lost had a poor prognosis at the initial assessment. The patient's gingiva and oral mucosa continue to be fragile with episodes of sloughing and inflammation. CONCLUSIONS: Periodontitis in Kindler syndrome responds to maintenance therapy, but the gingiva and oral mucosa continue to display an abnormal appearance with white patches. Histologic findings suggest that the junctional epithelium in Kindler syndrome may be abnormal and could explain why these patients have periodontal disease. Attachment loss progressed around teeth with an initial guarded or poor prognosis. Teeth that started with a good or fair prognosis continue to have a fair prognosis. Limited dental implant treatment is being considered.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".