Cochlear Implantation in Postmeningitic Deafness
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To propose guidelines in the management of a profound bilateral sensorineural hearing loss after bacterial meningitis. STUDY DESIGN: Retrospective chart review. PATIENTS: All 40 postmeningitic cochlear implantation surgeries performed between August 1987 and April 2007. METHODS: Descriptive analysis of data on the cause of meningitis, preoperative imaging evaluation, age at implantation, time elapsed between meningitis and implantation, and relevant surgical findings. RESULTS: Twenty-seven children and 13 adults with postmeningitic deafness were implanted. Mean age was 3 years 8 months for the children and 44 years and 10 months for the adults. The mean time delay between meningitis and surgery was 2 years 1 month for children and 28 years for adults. Eighteen children (67%) were implanted within a year. Labyrinthitis ossificans was evidenced at surgery in 62% of patients. Intraoperative cochlear ossification was classified according to the scale described by Smullen and Balkany (2005). Stage II ossification was seen in 3 patients within 49 days, with 1 of them as soon as 21 days. There was a partial insertion in 9 patients secondary to ossification. Open-set speech discrimination was achieved by 37% of the children (10 of 27) and 23% of the adults (3 of 13). CONCLUSION: We recommend early cochlear implantation for patients with bilateral profound deafness secondary to meningitis.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".