Monolithic zirconia outperforms metal-ceramic in mechanical reliability for single implant crowns but lacks long-term validation
Bibliographic record
Abstract
A COMMENTARY ON: Malhotra T, Kumar Yadav B, Singh Phukela S et al. A comparative evaluation of prosthetic and biologic outcomes as influenced by two different implant restorative materials: a prospective, split-mouth study. Int J Prosthodont. 2025; https://doi.org/10.11607/ijp.8729 . DESIGN: This was a prospective split-mouth study, where each patient received monolithic zirconia and metal-ceramic implant-supported crowns on contralateral sides in the same arch. This design guaranteed direct intra-patient comparison, reducing inter-individual variability. CASE SELECTION: Twenty partially edentulous patients (14 males, 6 females) were selected based on strict inclusion criteria, ensuring bilateral posterior implant placement with opposing natural dentition. Patients with parafunctional habits, active periodontal disease, or systemic conditions affecting bone metabolism were excluded. STUDY TIMELINE: Implant placement and prosthetic restoration were performed per standard clinical protocols. The study assessed outcomes at baseline, 1-year, and 2-year follow-ups, measuring prosthetic integrity, periodontal health, and inflammatory markers. DATA ANALYSIS: Clinical indices (plaque index, bleeding on probing, probing depth), peri-implant crevicular fluid biomarkers (MMP-8 levels), and prosthetic performance (USPHS criteria) were statistically analysed using chi-square tests, ANOVA, and Student t-tests, with significance set at P < 0.05. RESULTS: Both materials showed 100% implant and prosthetic survival rate over 2 years. Metal-ceramic crowns exhibited higher incidences of ceramic chipping and screw loosening, while monolithic zirconia crowns demonstrated greater mechanical stability but poorer aesthetic match. No significant differences in marginal bone loss (MBL) or MMP-8 inflammatory marker levels were observed between groups. However, higher plaque index (PI) and probing depth (PD) were recorded for metal-ceramic crowns. CONCLUSIONS: Monolithic zirconia crowns demonstrate superior mechanical reliability and fewer technical complications but have aesthetic limitations compared to metal-ceramic crowns. Biologic outcomes were comparable between both materials. Clinicians should weigh mechanical durability versus aesthetic demands when selecting implant-supported restorations. Further long-term studies are recommended to validate these findings.
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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 | 0.019 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.013 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".