A Comparative Analysis of Marginal Bone Loss of Hydrophilic Implants versus non-hydrophilic Implants placed on Edentulous Ridge in Mandibular Implant Overdenture
Bibliographic record
Abstract
Objective: This systematic review aims to evaluate the clinical outcomes of hydrophilic versus non-hydrophilic dental implants, focusing on key parameters such as marginal bone loss, implant survival rates, and bone-to-implant contact (BIC). The review seeks to determine whether hydrophilic surfaces offer a significant clinical advantage and to identify areas for future research. Materials and Methods: A comprehensive literature search was conducted across databases including PubMed, Scopus, and Cochrane Library, covering studies published from 2015 to 2023. Inclusion criteria were randomized controlled trials, prospective and retrospective studies, and in vivo experiments comparing hydrophilic and non-hydrophilic implants. Data extraction focused on outcomes related to marginal bone loss, implant survival, and BIC. Studies were assessed for methodological quality using the Cochrane Risk of Bias tool and the Newcastle-Ottawa Scale. Results: A total of 10 studies met the inclusion criteria, encompassing 450 implants in various clinical settings. The findings revealed that hydrophilic implants generally demonstrated lower marginal bone loss and higher BIC percentages compared to non-hydrophilic implants, with survival rates exceeding 97% in most studies. However, the differences in outcomes were not consistently significant across all studies, highlighting variability in results based on implant type, patient demographics, and follow-up duration. Conclusion: Hydrophilic implants show potential advantages in terms of marginal bone loss and BIC, particularly in early loading protocols. However, further long-term studies with standardized methodologies are needed to confirm these benefits and optimize clinical guidelines for implant selection.
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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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".