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Record W2766822821 · doi:10.1080/00016489.2017.1385845

Eosinophilic otitis media diagnosis using flow cytometric immunophenotyping

2017· article· en· W2766822821 on OpenAlexaff
Issam Saliba, Musaed Alzahrani, Xiaoduan Weng, Alain Bestavros

Bibliographic record

VenueActa Oto-Laryngologica · 2017
Typearticle
Languageen
FieldMedicine
TopicSinusitis and nasal conditions
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineImmunophenotypingOtitisEosinophilAsthmaEosinophilicInternal medicinePrednisoneCohortDexamethasoneEffusionProspective cohort studyGastroenterologyPathologyFlow cytometryImmunologySurgery

Abstract

fetched live from OpenAlex

OBJECTIVES: (1) To assess the ability of flow cytometric immunophenotyping to detect and quantitate eosinophils in patients with eosinophilic otitis media (EOM). (2) to evaluate the association of EOM to bronchial asthma. METHODS: Twenty-one patients with chronic otorrhea or middle ear effusion (MEE) were included in this prospective cohort study. Group I composed of 10 patients (14 ears) and associated to bronchial asthma. Group II included 11 patients (11 ears) without bronchial asthma. Samples of MEE were sent for flow cytometric analysis at initial presentation. Patients with positive eosinophils on flow cytometric immunophenotyping were analyzed after one-month course of dexamethasone eardrops. RESULTS: EOM was diagnosed in all patients of group I and in three patients of group II. The mean eosinophils percentage was 43.5% and 14.2% for group I and group II, respectively (p = .006). Those patients showed a significant response to dexamethasone eardrops, both on clinical examination and on flow cytometric analysis with a decrease in eosinophil levels post-treatment. However, this improvement was temporary and symptoms recurred after treatment cessation. Bronchial asthma was not associated to all patients with EOM. CONCLUSION: Diagnosis of EOM remained mostly clinical; flow cytometry immunophenotyping of MEE may be helpful as an additional tool in diagnosis and monitoring the response to treatment, particularly in non-asthmatic 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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.077
GPT teacher head0.324
Teacher spread0.246 · 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 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

Citations8
Published2017
Admission routes1
Has abstractyes

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