Soft tissue complications after small incision pediatric cochlear implantation
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To report and analyze the soft tissue complications of 462 consecutive cochlear implants using a minimal access approach at a single institution. STUDY DESIGN: A retrospective case series analysis was performed. METHODS: A database of all patients implanted at our institution between January 2002 and December 2007 was searched, and 385 consecutive patients were identified. Postcochlear implantation notes and case records were searched for soft tissue complications. Soft tissue complications were divided into minor and major complications. All devices were implanted using a minimal access technique with device fixation in all but five patients. RESULTS: There were 385 consecutive children implanted with 462 cochlear implants. Of these, 322 were primary single-sided implants, 124 bilateral implants, and 16 reimplants for device failure. Median follow up was 2.9 years. There were two minor complications: one minor seroma and one postoperative hematoma, both were managed conservatively. There were five major complications: two soft tissue infections, one extrusion, and two major seromas leading to device migration. Four of the five major complications involved loss of device fixation. Three out of the five major complications required device explantation; the decision not to reimplant was made in two cases. CONCLUSIONS: An overall soft tissue complication rate of 1.51% (7/462) at our institution supports the use of a small incision technique combined with device fixation as a safe method of cochlear implantation. We believe that good fixation is especially important in pediatric implantation, because of the thinner soft tissue envelope and increased frequency of minor head trauma.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".