Early Outcomes of a New Active Transcutaneous Bone Conduction Implant in Pediatric Patients
Bibliographic record
Abstract
OBJECTIVE: To describe the early surgical and audiometric outcomes in pediatric patients implanted with a new active transcutaneous bone conduction implant system. STUDY DESIGN: Retrospective case review. SETTING: Tertiary pediatric hospital. PATIENTS: Pediatric patients (18 or younger) with conductive or mixed hearing loss that completed postoperative aided testing following implantation with the Cochlear Osia system from December 2019 to December 2020. INTERVENTION: Rehabilitative. MAIN OUTCOME MEASURE: Preoperative air conduction (AC), preoperative bone conduction (BC), and postoperative aided thresholds were compared. Pure-tone averages (PTA), air-bone gap (ABG), and functional gain were calculated. Surgical complications and patient satisfaction were summarized from the chart review. RESULTS: Sixteen patients (20 implants) met the inclusion criteria. The average age at the time of implantation was 12.9 ± 2.4 years. The preoperative AC and BC thresholds were 64.4 dB (±11.9 dB) and 7.9 dB (±4.90 dB), respectively, with an average ABG of 56.5 dB (±12.8 dB). The average postoperative aided threshold was 21.2 dB (± 4.25 dB) with a mean functional gain of 43.1 dB (±10.2 dB). One patient developed seroma postoperatively, which was treated conservatively. No other complications were reported over a mean follow-up time of 7.1 ± 4 months. For 13 patients with previous passive bone conduction implants or devices, the Osia system was universally favored. CONCLUSIONS: The new active transcutaneous bone conduction system showed favorable early clinical and audiometric outcomes. Repeated processor connectivity issues represent a potential area for future device development. This is the largest pediatric case series to date.Level of Evidence: Level 4-Retrospective Review.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".