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Record W2035100222 · doi:10.1002/lary.20630

Bilateral simultaneous cochlear implantation in children: Our first 50 cases

2009· article· en· W2035100222 on OpenAlexaff
James D. Ramsden, Blake C. Papsin, Randy Leung, Adrian L. James, Karen A. Gordon

Bibliographic record

VenueThe Laryngoscope · 2009
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsCochlear implantationAudiologyMedicineCochlear implant

Abstract

fetched live from OpenAlex

OBJECTIVES/HYPOTHESIS: To assess the safety and surgical technique of bilateral simultaneous cochlear implantation in children. STUDY DESIGN: Prospective case series at a tertiary academic pediatric hospital. METHODS: Surgical times, complications, and patient outcomes are reported from the first 50 consecutive simultaneous cochlear implants performed at the Hospital for Sick Children between 2005 and 2008. These results were compared to the same measures in a group of sequentially implanted children consecutively implanted from 2001 to 2008. RESULTS: The group of children receiving simultaneous bilateral cochlear implants showed no difference in complications, length of hospital stay, or use of analgesia and antiemetics compared with children receiving single implants. The simultaneously implanted children had a reduced cumulative surgical time and hospital stay than is required for bilateral implantation performed sequentially. CONCLUSIONS: Bilateral simultaneous cochlear implantation in this series of children was safe and required no significant increase in surgical time and hospital stay compared with unilateral procedures.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.019
GPT teacher head0.282
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations52
Published2009
Admission routes1
Has abstractyes

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