A Prospective Multicenter Study on the Performance of a Bone-Anchored Hearing Implant Using Minimally Invasive Ponto Surgery
Bibliographic record
Abstract
INTRODUCTION: The minimally invasive Ponto surgery (MIPS) was launched in 2015 as a straightforward, fast single-stage surgical solution designed to minimize postoperative complications and deliver improved cosmetic outcomes for placement of percutaneous bone-anchored hearing systems (BAHS). OBJECTIVE: To investigate the proportion of Ponto implant/abutment complexes providing a reliable sound processor anchorage 3 months after MIPS. SUBJECT POPULATION: Sixty-four adult patients undergoing BAHS treatment using the MIPS. STUDY METHODS: A 12-month prospective, multinational, multicenter single-arm investigation. All patients underwent implant placement using MIPS with endpoints at 7 days, 21 days, 3, 6, and 12 months. Implant stability, skin reactions, pain and numbness, sound processor usage, and patient-reported quality of life measures were assessed. RESULTS: No severe intraoperative complications were reported, and average procedure duration was 10.5±9.1 minutes. 96.6% of Ponto implant/abutment complexes provided a reliable sound processor anchorage 3 months after MIPS. Two spontaneous implant losses were registered before the 3-month endpoint at 40 days and 57 days post-MIPS. At 3 months after MIPS, 98.2% of implant sites were judged to be completely healed, 96.5% of patients had no adverse skin reactions, 89.5% reported no pain, and 98.2% reported no numbness. Patient-reported outcomes indicated quality of life improvements for the majority of patients. CONCLUSIONS: The MIPS procedure continues to be a safe and efficient surgical technique for BAHS. Low intraoperative and postoperative complication rates paired with low rates of adverse skin reactions, pain, and numbness can be expected from the procedure.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".