Evaluation of Protein Adsorption and Osseointegration Potential of Polyetheretherketone versus Titanium Dental Implants: A Systematic Review
Bibliographic record
Abstract
Introduction: The success of implant therapy depends on a number of parameters, including bone volume implant shape, surface topography, the patient’s overall health, and local factors. Despite the fact that polyetheretherketone (PEEK) implants have undergone a lot of alterations, only a small number of studies have examined the bioactivity and osseointegration of PEEK implants with titanium. Aim: To summarise and evaluate protein adsorption and osseointegration capacity of PEEK and titanium dental implants. Materials and Methods: Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were used and PROSPERO (CRD42023415494) registration was done. Electronic databases were searched for studies assessing the outcome in terms of protein adsorption and osseointegration capacity of PEEK and titanium dental implants. Quality assessment of included studies was evaluated using the Newcastle-Ottawa Scale (NOS). Results: Depending on inclusion and exclusion criteria, seven studies fulfilled the eligibility criteria and were included in qualitative synthesis. Risk of bias assessment revealed that all the included studies were largely comparable in methodological quality. All the included studies had moderate to low-risk of bias with all the respective domains. All the included studies revealed that PEEK with optimal surface roughness might hold great potential for protein adsorption and osseointegration capacity. Conclusion: Within the limitations of the study, it was found that compared to titanium, PEEK is less osseoconductive and bioactive. PEEK is therefore unsuitable for use as a dental implant in its unmodified form. Implantitis and implant failure occurs from improper osseoconductivity and bioactivity of dental implants.
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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 | 0.014 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.014 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".