A systematic review on patient perceptions and clinician‐reported outcomes when comparing digital and analog workflows for complete dentures
Bibliographic record
Abstract
PURPOSE: To compare digitally fabricated complete dentures to conventionally fabricated dentures using patient- and clinician-reported outcome measures. METHODS: This review was structured according to PRISMA guidelines with the protocol registered in the PROSPERO database (CRD42024526069). An electronic search of the databases with a defined search strategy was completed within PubMed/MEDLINE and Web of Science from January 2000 to March 2024. Grey literature and article references were searched. Articles were screened by title and abstract, and the remaining articles were screened by full-text review. Articles accepted for inclusion were subjected to a risk-of-bias assessment using Cochrane Collaboration tools (RoB 2 and ROBINS-I). RESULTS: From an initial pool of 704 articles, 15 studies met the selection criteria, of which the majority were published within the past 3 years. Within the included studies, there was inconsistency in the assessment methods of patient- and clinician-reported outcomes, making it challenging to draw definitive conclusions. Generally, digital dentures had superior cost-effectiveness and prosthesis fabrication time. Patient satisfaction and denture quality were not consistently improved with digital technology. CONCLUSIONS: Studies showed indications of patient satisfaction with digital and conventional dentures. Digital technology may enhance clinical workflows. A trend emerged that milled dentures performed better than printed dentures. Clinicians adopting digital technology into removable prosthodontics may have a learning curve to overcome, and they should consider the patient-clinician relationship in addition to clinical outcomes to achieve patient satisfaction. Additional studies with standardized tools for assessing patient satisfaction are required to enable meaningful comparisons between digital and conventional workflows.
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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 | 0.023 | 0.112 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".