Comparison of Three Luting Cements for Prefabricated Zirconia Crowns in Primary Molar Teeth: a 36-month Randomized Clinical Trial.
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to evaluate and compare the long-term clinical retention and gingival health of prefabricated zirconia crowns (PZCs) in primary molar teeth cemented using three luting cements. METHODS: Primary molar teeth restored with PZCs (n equals 30 per group) were cemented using glass ionomer cement (GIC), resin-modified GIC (BioCem™), or adhesive resin cement (APC technique: air- particle abrasion, zirconia primer, composite resin). Crown retention, plaque accumulation, and gingival status were evaluated over three years; cumulative crown survival was assessed using Kalpan-Meier analysis. Plaque gingival scores were analyzed for within and between groups using repeated measures one-way analysis of variance. RESULTS: The survival of PZCs cemented using GIC was 76.7 percent, 70 percent for APC, and 50 percent for BioCem™ after three years. The mean survival for PZC in the GIC group (35.5 months) was significantly higher than for APC (34.7 months), and BioCem™ (33 months; P=0.019). Plaque accumulation around GIC-luted crowns was significantly lower (P<0.001; three-year follow-up); gingival outcomes were uniformly favorable between groups. No crown fracture was observed throughout the study period. CONCLUSIONS: Prefabricated zirconia crowns cemented using traditional glass ionomer cement have superior retention and lower plaque accumulation compared to BioCem™ and APC after three years. PZCs provided long-term favorable gingival health outcomes irrespective of the cement used for luting the crowns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 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 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".