The significance of vertical platform discrepancies and splinting on marginal bone levels for adjacent dental implants
Bibliographic record
Abstract
OBJECTIVE: The aim of this retrospective study was to investigate the influence of vertical platform discrepancies for splinted and non-splinted adjacent implants on radiographic marginal bone loss (RMBL). METHODS: Data from January 2000 to February 2021 were collected from the electronic charts of 156 patients with 337 implants at the UCSF School of Dentistry. Five different implant restoration categories were evaluated for radiographic evidence of proximal RMBL. Patients with (1) two adjacent single crowns, (2) two adjacent splinted crowns, (3) three-unit bridges supported by two implants, (4) three adjacent single crowns, and (5) three adjacent splinted crowns. Inclusion required baseline radiograph taken at the time of prosthesis delivery or final impression, and follow-up radiographs at least 12 months after restorations have been in function. Measurements assessed included vertical distance between adjacent implant platforms and proximal RMBL around implants. Odds ratios (ORs) and 95% confidence interval (95% CI) of implants with ≥1 mm RMBL between different type of restorations were calculated. RESULTS: In general, prostheses supported by splinted adjacent implants demonstrated a significant association with the presence of ≥1 mm RMBL (OR = 2.55, 95% CI = 1.17-5.17, p = 0.018) when compared to prostheses supported by non-splinted adjacent implants. In addition, prostheses with a vertical platform discrepancy ≥0.5 mm demonstrated a significant association with the presence of ≥1 mm RMBL (OR = 4.30, 95% CI = 1.85 to 10.01, p = 0.007) when compared to prostheses with a vertical platform discrepancy <0.5 mm. When adjacent implants had ≥0.5 mm vertical platform discrepancy, the majority (66.67%) of three splinted adjacent crowns had at least one implant with ≥1 mm RMBL. This was followed by two splinted adjacent crowns (58.97%), three-unit bridge (25.93%), two single adjacent crowns (24.24%), and three single adjacent crowns (18.18%). When adjacent implants had ≥1 mm vertical platform discrepancy, there was an increased percentage of implants with ≥1 mm RMBL. The restorative design associated with the highest percent of implants with bone loss was three splinted adjacent crowns (70%), two splinted adjacent crowns (61.11%), three single adjacent crowns (40%), and three-unit bridge and two single adjacent implants (21.05%). Three splinted adjacent crowns were significantly associated with ≥1 mm RMBL when compared to three-unit bridge (OR 6.56, 95% CI 1.59-27.07). Similarly, two splinted crowns were significantly associated with ≥1 mm RMBL when compared to two single crowns (OR = 2.50, 95% CI = 1.08-5.79). CONCLUSION: Two or three adjacent implants placed with a vertical platform discrepancy, when splinted together, are associated with higherincidence of ≥1 mm RMBL than non-splinted restorations.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".