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Record W2194060305 · doi:10.1186/s13223-015-0105-x

Marked improvement of neuropsychiatric symptoms following control of allergy symptoms with the use of humanized murine anti-IgE antibody (omalizumab) in 2 patients with severely limited expressive language

2015· article· en· W2194060305 on OpenAlexvenueno aff
Harumi Jyonouchi

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2015
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsnot available
FundersAutism Research Institute
KeywordsMedicineAnxietyOmalizumabCognitionAllergyPopulationImmunoglobulin EAffect (linguistics)ImmunologyPediatricsAntibodyPsychiatryPsychology

Abstract

fetched live from OpenAlex

Flare-up of allergic rhinitis has been implicated in worsening neuropsychiatric symptoms such as hyperactivity and anxiety in the general population, mostly supported by epidemiological data. However, it is unknown how such respiratory allergy symptoms affect behavioral symptoms in patients with intellectual disability and limited expressive language. These patients may express more severe behavioral symptoms partly due to frustration and anxiety, being under-diagnosed and undertreated secondary to a lack of proper communication means. Herein, we present two cases of patients with severely limited expressive language , in whom we observed marked improvement in behavioral symptoms and even cognitive activity following control of their symptoms of allergic rhinitis with the use of omalizmab, a humanized anti-IgE antibody. The presented cases indicate that clinicians need to be aware of profound effects of allergy rhinitis on neuropsychiatric symptoms in individuals with limited expressive language.

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)0.002
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.001
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 head0.012
GPT teacher head0.269
Teacher spread0.257 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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