Gram‐negative enteric rods/Pseudomonas colonization in mucositis and peri‐implantitis of implants restored with cemented and screwed reconstructions: A cross‐sectional study
Bibliographic record
Abstract
PURPOSE: To evaluate the association between Gram-negative enteric rods and Pseudomonas with mucositis and peri-implantitis, in implants restored with cemented and screw-retained reconstructions. MATERIALS AND METHODS: Individuals treated with implants, diagnosed with peri-implant mucositis and or peri-implantitis, participated in this study. Microbiota from the implant and the gingival sulcus of two neighboring teeth were also studied. The microorganisms were identified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. RESULTS: A total of 52 and 51 implants cemented and screwed restored were evaluated in 31 patients. The presence of Gram-negative enteric rods/Pseudomonas (P = .01) was significantly higher in the cemented restored implants. When the unit of analysis was the implant, the presence of Gram-negative enteric rods/Pseudomonas was associated with cemented restored implants after adjustment for possible confounders (odds ratio [OR] = 3.7; 95% CI, 1.4-10; P = .01); besides, peri-implantitis was statistically significant in the multivariate model (P = .008). Considering the patient as a unit of analysis, peri-implantitis was associated with cemented restored implants (OR = 9.4; 95% CI, 2-46; P = .006); this statistically significant association remained after adjusting for potential confounders (OR = 6.8; 95% CI, 1.3-37; P = .02). CONCLUSION: The presence of Gram-negative enteric rods/Pseudomonas was associated with cemented restored implants; besides, peri-implantitis was associated with cemented restored implants.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".