Factors Affecting Care and Maintenance of Complete Denture Prostheses (CDP)-A Literature Review
Bibliographic record
Abstract
BACKGROUND: The prevalence of edentulism which is a major public health concern globally relating to extensive loss of teeth had reduced. For Edentulous Patients (EDPs), Complete Denture Prostheses (CDP) therapy is a known mode of treatment to improve the overall health and the Oral Health Related-Quality of Life (OHRQoL) with appropriate care and maintenance for its longevity. AIM: This literature review had been conducted containing the aim to gather the proficiency and ideas related to the factors that affect the care and maintenance of CDP and how it benefits the EDPs related to good CDP care practices. METHODS: Numerous electronic databases which included Scopus, Embase, Google Scholar and Open Grey literature in English language was used to search for the articles from January 1st 2005 to October 1st 2021 on factors that influenced care and maintenance of CDP. Associated article titles were chosen which was narrowed down to abstract of interested articles and the final 20 preferred full articles were reviewed. The selected articles in this study was analyzed using thematic analysis and their themes were grouped accordingly. RESULTS: Five themes were thematically identified as factors affecting care and maintenance of CDP: social and cultural factors, economic and demographical factors, policy related factors, physical factors and health service related factors. All articles reviewed demonstrated that every factor is highly essential when it comes to taking appropriate care and maintenance of CDP for EDPs. CONCLUSION: The current evidence suggests that social, cultural, economical, demographical, policy, physical and health service related factors all significantly constitute towards effective care and maintenance of CDP for EDPs. Furthermore, the results derived from this research is essential in the development of effective post-operative guidelines for appropriate care and maintenance of CDP.
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".