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Unrecognized Ciliary Motility Disorders in Neutrophilic Severe Asthma Exacerbations

2024· article· en· W4396503975 on OpenAlexaff
S. Thawanaphong, Lucia Gonzalez Bravo, Katherine Radford, C. Venegas Garrido, Melanie Kjarsgaard, Adil Adatia, L. Dyment, Myrna Dolovich, Parameswaran Nair

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsUniversity of AlbertaSt. Joseph’s Healthcare HamiltonMcMaster University
Fundersnot available
KeywordsAsthmaMedicineMotilityIntensive care medicineImmunologyBiologyCell biology

Abstract

fetched live from OpenAlex

Abstract Background Airway bacterial infections are frequent in severe asthma and are often under-appreciated as contributors to symptoms and exacerbations. We report our experience using integrative diagnostic methods to identify ciliary motility disorders as contributors to neutrophilic exacerbations in patients with severe asthma. Methods Targeted exome sequencing for primary ciliary dyskinesia (PCD) was performed on 52 patients with severe asthma who met predefined criteria (≥ 3 respiratory infections or intense sputum neutrophilia, within a 2-year period, along with evidence of type 2 inflammation, including peripheral or sputum eosinophilia, elevated fractional exhaled nitric oxide (FeNO), or elevated serum immunoglobulin E), and without other obvious immunodeficiencies. A subset of patients with PCD-related gene variant(s) underwent ciliary beat frequency (CBF) analysis from nasal epithelial brushings ( N = 20 with analyzable data), nasal nitric oxide (nNO) measurement ( N = 15), and T1/2/17 sputum cytokine assays ( N = 18). Results Among 52 patients (mean age 54.2 ± 15.1 years; 59.6% female), 32(61.5%) had PCD-related gene variants. CBF was reduced in 19/20(95%) patients who underwent motility studies (mean CBF of 8.8 ± 2.7 Hz; normal 14.2 ± 1.0 Hz), and correlated significantly with FEV 1 (r s =0.65, P = 0.0017) and inversely with peak sputum neutrophils (r s =-0.62, P = 0.0097). Subnormal nNO levels (< 250 nL/min) were observed in 12/15(80%) patients; 3/15(20%) were < 77 nL/min (PCD threshold). 5 patients showed FeNO discordance (> 25 ppb). Cytokines associated with inflammasome activation were increased in sputum in majority of patients with PCD-related gene variants. Sputum-guided strategy and 7% hypertonic saline treatment enable significant inhaled corticosteroid doses reduction across the entire population and airway-eosinophilia subgroup ( P = 0.0026 and P = 0.0273). Oral corticosteroid doses were reduced in 6/8(75%), and biologics were not initiated in 26/32(81.3%). FEV 1 improved by 130 ± 291mL, P = 0.0273. Conclusions Ciliary dyskinesias are prevalent in patients with severe asthma. Identifying ciliary motility disorders can guide effective treatment and reduce unnecessary biologics use in severe asthma when symptoms are infection-driven. Even variants of uncertain significance in PCD-related genes may be associated with airway infections due to ciliary dysfunction, proven by ciliary beat frequency analysis. nNO could be a useful screening tool, but its optimal cutoff in this population needs further study.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.271
Teacher spread0.256 · 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 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".

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Citations1
Published2024
Admission routes1
Has abstractyes

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