Impact of rehabilitation with dental implants on the quality of life of patients undergoing maxillofacial reconstruction: a systematic review
Bibliographic record
Abstract
PURPOSE: Maxillofacial reconstruction with dental implants in microvascular tissue flaps aims to improve mastication. However, the quality of life (QoL) impact of this intervention is yet to be determined. This systematic review assessed the QoL impact of maxillofacial reconstruction with implant-supported teeth compared to no dental rehabilitation, removable dentures, and obturator (modified denture). Additionally, we examined instruments applied to measure QoL in maxillofacial reconstruction. METHODS: Databases Ovid Medline and Embase, Scopus, Web of Science and Handle on QoL were searched. Cohort, case-control and randomized controlled trials (RCT) were narratively synthesized for QoL captured through validated instruments. Study methodological quality was assessed using Cochrane Risk of Bias 2 and Risk of Bias in Non-randomized studies of Exposure. Instruments underwent COSMIN content validity analysis. RESULTS: Of a total of 2735 studies screened, the three included studies (two cohort and one RCT) showed improved QoL with maxillofacial reconstruction compared to obturator and no dental rehabilitation. However, these studies have high risk of bias due to confounding. None of the instruments achieved a sufficient relevance rating for maxillofacial reconstruction, having been designed for other target populations and there is no evidence on their content validity for this population, but the EORTC QLQ30 H&N35 satisfied more COSMIN criteria than the UW-QOL and OHIP-14. CONCLUSION: Although studies showed favourable QoL with maxillofacial reconstruction involving dental implants, these have high risk of bias and further studies are needed to establish the impact. Existing QoL instruments lack content validity and tailored instruments are needed for QoL evaluation in maxillofacial reconstruction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".