A Comparison of the Success of Root Resected Molars and Molar Position Implants in Function in a Private Practice: Results of up to 15‐Plus Years
Bibliographic record
Abstract
BACKGROUND: When faced with a furcated molar, today's clinician must decide between a number of treatment options, including root resection, tooth removal, and implant placement. This paper assesses the results in one private clinical practice of root resection and subsequent restoration or molar implant placement and subsequent restoration. Clinical considerations in treatment selection are discussed. METHODS: A retrospective analysis of treated patients was carried out by examining active and inactive patient charts. When patients had discontinued therapy, every effort was made to determine the reason for leaving the private practice, so as to assess the impact of previously undocumented treatment failure on the statistics in question. RESULTS: A total 701 root resected molars and 1,472 molar implants were evaluated after > or = 15 and 13 years in function, respectively. Resection of the distal root of a mandibular molar demonstrated the lowest success rate (75%). All other success rates for various root resected molars in function ranged from 95.2% to 100%. Lone standing implants in second molar positions demonstrated the lowest success rate (85%). All other implant use in molar positions demonstrated a success rate ranging from 97.0% to 98.6%. Root resected molars and molar implants demonstrated the highest degree of failure when they were lone standing terminal abutments. Seven out of 23 (30.4%) root resected molar failures, and 17 of 45 (37.8%) of the molar implant failures were associated with untreated parafunction. Cumulative success rates were 96.8% for root resected molars and 97.0% for molar implants. Success and failure are discussed by tooth and/or implant position, and resected root, where applicable. Possible ramifications of these findings upon treatment planning are also reviewed. CONCLUSIONS: Both molar root resection and appropriate restoration and molar implant placement and restoration demonstrated a high degree of success in function. However, this success rate is markedly affected when either the root resected molar or molar implant is a lone standing terminal abutment. Care must be taken to choose the appropriate treatment modality for a given patient scenario.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".