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Record W4402840987 · doi:10.1016/s2589-7500(24)00147-x

Symptom trajectories in infancy for the prediction of subsequent wheeze and asthma in the BILD and PASTURE cohorts: a dynamic network analysis

2024· article· en· W4402840987 on OpenAlex
Uri Nahum, Olga Gorlanova, Fabienne Decrue, Heide Oller, Edgar Delgado‐Eckert, Andreas Böck, Sven Schulzke, Philipp Latzin, Bianca Schaub, Anne M. Karvonen, Roger Lauener, Amandine Divaret‐Chauveau, Sabina Illi, Caroline Roduit, Erika von Mutius, Urs Frey

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Lancet Digital Health · 2024
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsnot available
FundersLeibniz-GemeinschaftAsthma UK Centre for Applied ResearchUniversität ZürichGottfried Wilhelm Leibniz Universität HannoverBundesministerium für Bildung und ForschungSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungDeutsche ForschungsgemeinschaftAsthma and Lung UKEuropean CommissionSanofiJapanese Society of AllergologyAbbott LaboratoriesNational Science FoundationImperial College LondonDeutsches Zentrum für LungenforschungAstraZenecaMcMaster UniversityEuropean Respiratory SocietyPfizer
KeywordsWheezePastureAsthmaMedicinePediatricsGeographyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Host and environment early-life risk factors are associated with progression of wheezing symptoms over time; however, their individual contribution is relatively small. We hypothesised that the dynamic interactions of these factors with an infant's developing respiratory system are the dominant factor for subsequent wheeze and asthma. METHODS: In this dynamic network analysis we used data from term healthy infants from the Basel-Bern Infant Lung Development (BILD) cohort (435 neonates aged 0-4 weeks recruited in Switzerland between Jan 1, 1999, and Dec 31, 2012) and replicated the findings in the Protection Against Allergy Study in Rural Environments (PASTURE) cohort (498 infants aged 0-12 months recruited in Germany, Switzerland, Austria, France, and Finland between Jan 1, 2002, and Oct 31, 2006). BILD exclusion criteria for the current study were prematurity (<37 weeks), major birth defects, perinatal disease of the neonate, and incomplete follow-up period. PASTURE exclusion criteria were women younger than 18 years, a multiple pregnancy, the sibling of a child was already included in the study, the family intended to move away from the area where the study was conducted, and the family had no telephone connection. Outcome groups were subsequent wheeze, asthma, and healthy. The first outcome was defined as ever wheezed between the age of 2 years and 6 years. Week-by-week correlations of the determining factors with cumulative symptom scores (CSS) were calculated from weeks 2 to 52 (BILD) and weeks 8 to 52 (PASTURE). The complex dynamic interaction between the determining factors and the CSS was assessed via dynamic host-environment correlation network, quantified by a simple descriptor: trajectory function G(t). Wheeze outcomes at age 2-6 years were compared in 335 infants from BILD and 437 infants from PASTURE, and asthma outcomes were analysed at age 6 years in a merged cohort of 783 infants. FINDINGS: CSS was significantly different for wheeze and asthma outcomes and became increasingly important during infancy in direct comparison with all determining factors. Weekly symptoms were tracked for groups of infants, showing a non-linear increase with time. Using logistic regression classification, G(t) distinguished between the healthy group and wheeze or asthma groups (area under the curve>0·97, p<0·0001; sensitivity analysis confirmed significant CSS association with wheeze [BILD p=0·0002 and PASTURE p=0·068]) and G(t) was also able to distinguish between the farming and non-farming exposure groups (p<0·0001). INTERPRETATION: Similarly to other risk factors, CSS had weak sensitivity and specificity to identify risks at the individual level. At group level however, the dynamic host-environment correlation network properties (G(t)) showed excellent discriminative ability for identifying groups of infants with subsequent wheeze and asthma. Results from this study are consistent with the 2018 Lancet Commission on asthma, which emphasised the importance of dynamic interactions between risk factors during development and not the risk factors per se. FUNDING: The Swiss National Science Foundation, the Kühne Foundation, the EFRAIM study EU research grant, the FORALLVENT study EU research grant, and the Leibniz Prize.

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.

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)0.000
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 score0.042
Threshold uncertainty score0.174

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.296
Teacher spread0.281 · 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