A cost analysis of a long‐term prospective study of patients treated with immediately loaded implant‐supported mandibular overdentures
Bibliographic record
Abstract
BACKGROUND: The economic burden for patients seeking treatment with implant-supported prostheses has not been given adequate attention. PURPOSE: To document long-term costs from a prospective trial on edentulous patients treated with mandibular implant-supported overdentures and 2 loading protocols. MATERIALS AND METHODS: The direct clinical and time costs for 35 patients receiving an immediate-loading protocol (ILP) and 40 patients with a conventional-loading protocol, over 14 years of observation, were analyzed in 2016 Canadian dollars as a base year. Quality of life (QoL) for the ILP was measured using the OHIP-20 questionnaire. RESULTS: The ILP was associated with higher complication costs ($870.77 ± 692.24 vs $85.73 ± 133.14) with resultant higher maintenance costs ($1746.37 ± 892.68 vs $853.04 ± 276.21) (P < .05). OHIP results showed a sustained improvement in QoL through the first 5 year of follow-up. A worsening of QoL, specifically the functional-related OHIP scores, was noted at 14 years. Incremental cost-effectiveness ratios indicated that the accrued maintenance costs for the ILP made the treatment less cost-effective over time. CONCLUSIONS: This long-term study confirmed that ILP is associated with higher maintenance costs and varying subjective QoL measurements. Clinical treatment protocols should be evaluated over a long period and address different perspectives.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".