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Record W1997579132 · doi:10.1186/1710-1492-6-s3-p32

Association of parental FEF25-75% during a methacholine challenge and children's PC20 and diagnosis of asthma

2010· article· en· W1997579132 on OpenAlexaffvenueabout
Douglas Houlbrook, A.B. Becker, CD Ramsey

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2010
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of ManitobaHealth Canada
Fundersnot available
KeywordsMethacholineMedicineAsthmaLung functionPulmonary function testingAirwayAirway hyperresponsivenessLungPediatricsInternal medicineRespiratory diseaseAnesthesia

Abstract

fetched live from OpenAlex

There is evidence that paternal and maternal lung function influence children's pulmonary function. To date, the most widely used pulmonary function test (PFT) to assess airway responsiveness is the PC20 (concentration of methacholine required to decrease FEV1 by 20%). However, other measures of parental lung function may be better predictors of airway responsiveness or asthma development in their children. The study population included children born in 1995 in Manitoba, who were enrolled in a nested case-control birth cohort study (Study of Asthma Genes and the Environment (SAGE). Both index children and their parents underwent PFTs and methacholine challenges to determine their PC20. Parents often had a normal PC20 but a change in flow at mid-lung volumes (forced expiratory flow at 25-75% vital capacity) was noted. Therefore, we measured parental PC30 (concentration of methacholine required to decrease FEF 25-75% by 30%) and its association with their child's PC20 and physician diagnosed asthma. A positive PC30 was measured at a concentration of ≤ 8 mg/ml. Children were assessed at age 12-13 by a pediatric allergist for a diagnosis of asthma. Odds ratios (OR) were calculated to examine the relationship between parental PC30 and a child's PC20 and asthma. This relationship was further explored by gender. Overall 114 children and their parents were included in this analysis. Of the 114 children, 47 were females (21 asthma) and 67 were boys (23 asthma). No significant relationship was seen between children diagnosed with asthma and having a parent with a PC30 ≤ 8 (OR 1.07; 95% CI 0.49-2.37) or both parents PC30 >8. 112 children [45 females (23 with PC20 ≤ 8) and 67 males (46 with PC20 ≤ 8)] fit the criteria for having a PC20 and participating parents. In children with a PC20 ≤ 8 there was no relationship between having one parent with PC30 ≤ 8 (OR 1.18; 95% CI .54-2.63) or both parents having a PC30 >8. When we examined gender specific relationships, there was no association between fathers PC30 and having a son diagnosed with asthma (OR 1.32; 95% CI 0.5-3.5) or daughters with a diagnosis of asthma (OR 1.07; 95% CI 0.33-3.48). Similarly, there was no significant association between the father's PC30 and their child's PC20 being ≤ 8 mg/ml. In moms with a PC30 ≤ 8 mg/ml there was no association with sons that had a PC20 ≤ 8 mg/ml (OR 1.0; 95% CI 0.51-2.0); However moms with a PC30 ≤ 8 were significantly more likely to have a daughter with a PC20 ≤ 8 (OR 3.56; 95% CI 1.55-8.21). In addition, there was a significant relationship between mom's PC30 being ≤ 8 and a daughter having physician diagnosed asthma (OR2.34; 95% CI 1.04-5.44). The relationship was in the same direction between maternal PC30 and a son's diagnosis of asthma, however this was not significant (OR 2.0; 95% CI 0.99-4.05). There was no relationship between children's asthma and PC20 and parental airway responsiveness measured as PC30. There was a statistically significant relationship between daughter's airway responsiveness and asthma and mothers' airway responsiveness as a PC30 FEF 25-75%. Maternal mid-flow responsiveness may be helpful in identifying risk for the development of pediatric asthma. Mid lung flow changes in mothers may represent a maternal genetic influence on the development of asthma in children.

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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)0.004
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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.295
Teacher spread0.285 · 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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Citations0
Published2010
Admission routes3
Has abstractyes

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