Histopathological analysis of biopsies of “peri‐implant inflammatory lesions.” Everything is not what it seems
Bibliographic record
Abstract
BACKGROUND: Peri-implantitis is the inflammatory process, which most commonly affects the therapy with dental implants. However, there are other reactive and neoplastic entities, mainly benign but also malignant, which also take place in the peri-implant mucosa. There is little information about the histopathological analysis of these peri-implant inflammatory diseases. PURPOSE: To analyze the histopathological diagnosis of biopsies located in the peri-implant mucosa that showed an inflammatory clinical appearance. MATERIALS AND METHODS: We have made a retrospective study of 111 peri-implant biopsies analyzed in the Oral and Maxillofacial Pathology Unit of the Dental Clinic Service at the University of the Basque Country, from January 2001 to December 2018. These samples corresponded to 84 women and 27 men, whose mean age was 59 years. We performed a standard histological processing with paraffin embedding, and sections were stained with H&E and PAS. All cases were analyzed following a specific diagnostic histopathological protocol. A descriptive statistical analysis was carried out with the obtained data. RESULTS: Lesions located in the mandible (64.8%) were more frequent and 34.2% of the biopsies arrived without a presumptive clinical diagnosis. "Inflammatory peri-implant lesion" or peri-implantitis was the most common clinical diagnosis. Histopathologically, the majority of the lesions were peri-implant nonspecific inflammatory hyperplasia (60.3%), followed by peripheral giant cell granuloma (18.1%), pyogenic granuloma (lobular capillary hemangioma) (14.4%), actinomicotic infection (3.6%), and squamous cell carcinoma (3.6%). Individually, peri-implant lesions were more common among women and in the mandible, except for actinomicotic infection and squamous cell carcinoma. CONCLUSIONS: An important percentage of cases whose initial presumptive clinical diagnosis was "peri-implant inflammatory lesion" truly corresponded to other reactive and neoplastic processes. Thus, it is key to always submit all the tissue removed during the implant surgery, in order to perform a good histopathological study and achieve the correct final diagnosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".