Immediate vs conventional loading of Facility‐Equator system in mandibular overdenture wearers: 1‐year RCT with clinical, biological, and functional evaluation
Bibliographic record
Abstract
Abstract Background The use of immediate loading (IML) is still poorly explored in elderly patients and implant‐retained mandibular overdenture (IMO) wearers. For this reason, more comparisons to conventional loading (CL) are required. Purpose To evaluate the clinical, biological, functional, and oral health‐related quality of life (OHRQOL) influence of CL and IML loading on elders wearing IMO retained by the Facility‐Equator system up to 1 year after implant installation. Material and Methods Twenty edentulous patients received two narrow diameter implants in the mandible; the loading type (CL or IML) was randomized. The clinical parameters were monitored along with prosthetic events, marginal bone loss (MBL) and bone level change (BLC), implant stability quotients (ISQ), masticatory performance outcomes, and Interleukin 1 beta (IL‐1β) and tumor necrosis factor alpha (TNF‐α) levels in the peri‐implant crevicular fluid during the first year of loading. The OHRQoL was assessed via the Oral Health Impact Profile‐EDENT questionnaire. Data were analyzed by the Mann‐Whitney, χ 2 , Wilcoxon paired, and McNemar tests. Results After 1 year, MBL, BLC and ISQ were statistically identical (P > .05) in the CL and IML groups. The probing depth at 12 months in the CL group (2.19 mm) was higher than in the IML group (1.29 mm; P ≤ .0001). TNF‐α was 33.6% higher in the CL group at 6 months ( P = .043), while IL‐1β was significantly higher in the IML group up to 6 months. The survival rate was 90% in the CL group and 85% in the IML group; 33 prosthetic events occurred in CL group and 23 in IML group. Conclusions After 12 months, both loading protocols are viable and result in similar clinical, biological, functional, and OHRQOL outcomes. However, IML generates better adaptation of the peri‐implant tissues, faster improvement in OHRQoL and fewer prosthetic intercurrences than CL.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".