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Record W2104389125 · doi:10.5539/gjhs.v5n5p102

Hearing Loss in Patients with Systemic Lupus Erythematosus

2013· article· en· W2104389125 on OpenAlexvenueno aff
Mahnaz Abbasi, Zohreh Yazdi, Amir Mohammad Kazemifar, Zahra Zarin Bakhsh

Bibliographic record

VenueGlobal Journal of Health Science · 2013
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHearing lossTinnitusSensorineural hearing lossAudiometryDiseasePure tone audiometryAudiologySystemic diseasePediatricsInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Systemic lupus erythematosus has its unique complications which warrant careful examination and assessment during follow/up visits of patients. The present study was conducted to evaluate prevalence of hearing loss in patients with SLE. MATERIALS & METHODS: At present a case- control study has been performed on 45 patients with SLE in a clinic of a teaching university hospital, Qazvin city, Iran. The patients were examined and evaluated for auditory and hearing problems as well as parameters related to their disease severity and progression. The control group was selected from the same clinic. RESULTS: Five patients (11.1%) complained from hearing loss, 4 patients s (8.9%) complained from otorrhea, 3 patients (6.7%) had tinnitus in research group, moreover twelve patients (26.7%) in case group and 4 patients (8.9%) in control group had sensorineural hearing loss. The difference was found to be statistically significant. No statistical significant relationship was found between severity, age of onset, and duration of the disease, and the lab tests of the patients with hearing loss. CONCLUSION: The present study implies that patients with systemic lupus erythematosus may develop sensorineural hearing loss during their course of the disease. It is recommended that audiology examination and/or audiometry become a part of routine follow/up studies of the patients.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.108
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.319
Teacher spread0.298 · 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.

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

Citations45
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueGlobal Journal of Health ScienceSame topicSystemic Lupus Erythematosus ResearchFrench-language works237,207