Characterization of retentive capacity of the subpericranial pocket in cochlear implants with and without a pedestal
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To quantify the retentive capacity (RC) of the subpericranial pocket (SpP) in children undergoing cochlear implantation (CI) and measure improvements in RC with the addition of a pedestal to the device base. Retention of a CI in an SpP relies on the integrity of surrounding tissues to determine device position and resist movement from external forces. We hypothesize that device position can be controlled and resistance to movement can be improved with placement of a small pedestal on the base of the CI receiver stimulator. STUDY DESIGN: Analysis of prospectively assembled data. METHODS: Ninety-seven patients (145 devices) underwent CI (48 bilateral, 49 unilateral). Intraoperatively, a force gauge measured the displacement force on a template Nucleus 5 (Cochlear Corporation, Sydney, Australia) implant placed in an SpP prior to routine suture fixation of a standard device. In 47 patients (64 devices), displacement forces were also measured for a custom template Nucleus 5 implant with pedestal. RESULTS: Average RC of the SpP for the standard device was 5.59 N ± 2.73 standard deviation (SD), which increased to 9.401 N ± 4.6267 SD with a pedestaled device. Resistance to displacement decreased significantly across trials in both groups (P <.0001). Retentive capacity of the SpP increased significantly with the addition of a pedestaled device (P < .0001). The interaction between device and trial was also found to be significant (P = .05). CONCLUSIONS: The RC of the SpP in children and the ability to resist device migration in the absence of fixation may improve with the addition of a pedestal attached to the device. LEVEL OF EVIDENCE: 2b. Laryngoscope, 126:1175-1179, 2016.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".