A Retrospective Case Series of Minimally Invasive Ponto Surgery In Two Pediatric Centres
Bibliographic record
Abstract
Objective: Minimally Invasive Ponto Surgery (MIPS) is a type of bone anchored hearing system performed through a puncture hole that has been reported to minimize soft tissue trauma, decrease operative time, and have favorable outcomes. Due to it being a relatively new procedure there remains a paucity of pediatric outcomes data. Our objective was to study MIPS outcomes in the pediatric population. Design: Retrospective review. Setting: The study was performed at two tertiary pediatric otolaryngology centres between 2016-2019. Participants: Pediatric patients from two tertiary pediatric otolaryngology clinics who underwent MIPS between 2016-2019. Main Outcome Measures: Outcomes included indication for surgery, implant and abutment type, overlying skin thickness, skin-to-skin time, Holgers score at three, six and twelve months, revision surgery and time to abutment fitting. Results and Conclusions: Fourteen patients, two with bilateral procedures met inclusion criteria (mean age= 8.07 ± 2.87years). The main etiology for the hearing loss was microtia (64%). The mean overlying skin thickness was 5.13 ± 3.18mm. Across all visits, 9.44% had Holger’s scores >2, which is classified as an adverse skin reaction. One of these patients required surgery to address skin overgrowth. One implant loss (6.3%) was reported, but found to be in the setting of trauma. Mean MIPS Skin to skin times were found to be 12.4 ± 2.6 minutes, markedly different that the Baha® Attract and Connect found to be 56 and 53 minutes respectively. This study represents the largest pediatric MIPS cohort to date, and our results are similar to published adult studies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.004 | 0.001 |
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".