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Record W4366815623 · doi:10.1159/000530784

Association of Alopecia Areata with Sensorineural Hearing Loss: A Systematic Review and Meta-analysis

2023· review· en· W4366815623 on OpenAlexaboutno aff
Kuang‐Hsu Lien, Tzong-Yun Ger, Ching‐Chi Chi

Bibliographic record

VenueDermatology · 2023
Typereview
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAlopecia areataSensorineural hearing lossOdds ratioMeta-analysisHearing lossTinnitusAudiologyCohort studyCase-control studyCohortDermatologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Immune-mediated melanocyte-related pathogenesis in alopecia areata (AA) may cause sensorineural hearing loss (SNHL). However, the relation between AA and SNHL has been unclear. Therefore, we aimed to investigate this association between AA and SNHL. METHODS: We performed a systematic review and searched MEDLINE and Embase on July 25, 2022, for cross-sectional, case-control, or cohort studies that examined the association of AA with SNHL. The Newcastle-Ottawa Scale was used to evaluate their risk of bias. A random-effects model meta-analysis was performed to obtain the mean differences in frequency-specific hearing thresholds between AA patients and age-matched healthy controls and the pooled odds ratio for SNHL in relation to AA. RESULTS: We included 5 case-control studies and 1 cohort study, with none of them rated with high risk of biases. The meta-analysis showed AA patients had significantly higher mean differences in pure-tone hearing thresholds at 4,000 Hz and 12,000-12,500 Hz. The meta-analysis also found increased odds for SNHL among patients with AA (OR: 3.18; 95% CI: 2.06-4.89; I2 = 0%). CONCLUSIONS: AA is associated with an increase of SNHL, especially at high frequencies. Otologic consultation may be indicated if AA patients present with hearing loss or tinnitus.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0100.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.209
GPT teacher head0.378
Teacher spread0.169 · 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 teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations7
Published2023
Admission routes1
Has abstractyes

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