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Record W1834200914 · doi:10.1111/hdi.12062

Intratympanic steroid injection for sudden sensorineural hearing loss in a patient on hemodialysis

2013· article· en· W1834200914 on OpenAlexvenueno aff
Rui‐Xin Wu, Chun‐Chi Chen, Chih‐Hung Wang, Hsin‐Chien Chen

Bibliographic record

VenueHemodialysis International · 2013
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHemodialysisSepsisIncidence (geometry)End stage renal diseaseDiseaseIntensive care medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Sudden sensorineural hearing loss (SSNHL) is being described with increasing incidence among patients with end-stage renal disease (ESRD) undergoing hemodialysis (HD). There are no widely accepted guidelines in the medical literature for the appropriate management of this medical emergency. Administration of systemic steroids remains the mainstay of the management of SSNHL in conjunction with the supportive treatment, in this vulnerable group of patients, as well. However, encouraged by the evolving evidence on the efficacy of the intratympanic steroid injections (ITSI) in the treatment of SSNHL among patients without renal disease--we successfully treated SSNHL in an elderly diabetic with sepsis due to bilateral pneumonitis undergoing regular HD treatment with multiple ITSI and antibiotics resulting in complete recovery of hearing function within 3 months of onset of the first symptoms.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.263
Teacher spread0.239 · 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 designCase report
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

Citations13
Published2013
Admission routes1
Has abstractyes

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