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Daily Respiratory Research Analysis

3 papers

Three high-impact respiratory studies emerged today: a multicenter lung CT vision foundation model (LCTfound) that advances diagnostic and prognostic imaging across eight tasks; a large, pragmatic cluster RCT in Vietnam showing a stepped anti‑inflammatory reliever strategy with budesonide–formoterol reduces exacerbations and hospitalizations in undifferentiated chronic respiratory disease; and real‑world evidence from Argentina demonstrating strong effectiveness of RSV maternal immunization in p

Summary

Three high-impact respiratory studies emerged today: a multicenter lung CT vision foundation model (LCTfound) that advances diagnostic and prognostic imaging across eight tasks; a large, pragmatic cluster RCT in Vietnam showing a stepped anti‑inflammatory reliever strategy with budesonide–formoterol reduces exacerbations and hospitalizations in undifferentiated chronic respiratory disease; and real‑world evidence from Argentina demonstrating strong effectiveness of RSV maternal immunization in preventing infant hospitalizations.

Research Themes

  • AI-enabled lung imaging foundation models for multi-task clinical utility
  • Stepped anti-inflammatory reliever strategies for chronic respiratory disease in resource-limited settings
  • Maternal immunization for RSV and infant hospitalization prevention

Selected Articles

1. A lung CT vision foundation model facilitating disease diagnosis and medical imaging.

87.5Level IVCohortNature communications · 2025PMID: 41339572

LCTfound is a large-scale lung CT foundation model trained on 105,184 scans that jointly encodes imaging and clinical data to support eight clinical tasks, outperforming strong baselines across centers. It provides a unified, deployable framework for diagnosis, prognosis, reconstruction, and navigation, potentially standardizing AI-assisted thoracic imaging.

Impact: A scalable, multicenter-validated foundation model for lung CT is likely to reshape AI-enabled imaging workflows and catalyze research across diagnosis, prognosis, and therapy planning.

Clinical Implications: If prospectively validated and integrated, this model could improve consistency and speed of thoracic imaging interpretation, enhance lesion detection/segmentation, support treatment planning, and enable advanced reconstruction in low-dose or sparse-view settings.

Key Findings

  • Trained on 105,184 multicenter lung CT scans with diffusion-based pretraining and joint imaging–clinical encoding.
  • Supports eight tasks (enhancement, virtual CTA, sparse-view reconstruction, segmentation, diagnosis, prognosis, response prediction, 3D navigation).
  • Consistently outperformed leading baselines across multiple centers, providing a unified deployable framework.

Methodological Strengths

  • Large multicenter dataset (105,184 CT scans) with comprehensive, multi-task evaluations.
  • Advanced training (diffusion-based pretraining) and joint encoding of imaging and clinical data.

Limitations

  • Lack of prospective, randomized clinical deployment studies demonstrating impact on patient outcomes.
  • Generalizability and fairness across diverse scanners, populations, and institutions require further auditing.

Future Directions: Prospective clinical trials, regulatory-grade validation, fairness auditing across demographics and scanners, and integration studies assessing workflow efficiency, safety, and outcome benefits.

2. Implementation of a stepped anti-inflammatory reliever therapy intervention with budesonide-formoterol 160/4·5 mcg by Turbuhaler versus usual care for adults presenting during exacerbations of obstructive lung disease suggestive of asthma or chronic obstructive pulmonary disease in a resource-limited setting: an open-label, cluster randomised trial.

83.5Level IRCTEClinicalMedicine · 2025PMID: 41340863

In a 52-week, open-label cluster RCT (n=3095) across 40 district facilities in Vietnam, a stepped budesonide–formoterol anti‑inflammatory reliever strategy reduced moderate/severe exacerbations (RR 0.79) and hospitalizations (RR 0.74) versus usual care, with similar mortality and serious adverse events. Effects were consistent irrespective of baseline eosinophils.

Impact: This pragmatic, scalable intervention can be rapidly adopted in resource-limited settings to reduce exacerbations and hospitalizations in undifferentiated chronic respiratory disease.

Clinical Implications: Adopting a simple stepped budesonide–formoterol reliever algorithm with periodic review can standardize care, reduce exacerbations, and lower hospital burden where diagnostic and medication access is limited.

Key Findings

  • Reduced moderate/severe exacerbations: 28.6% vs 36.0% (RR 0.794; p=0.03) over 12 months.
  • Lower respiratory hospitalizations: 17.4% vs 24.1% (RR 0.737; p=0.05); mortality and grade 3–4 adverse events were similar.
  • No significant interaction by baseline blood eosinophils, supporting broad applicability.

Methodological Strengths

  • Large, multicenter, cluster randomized pragmatic design with 52-week follow-up.
  • Clinically relevant outcomes (exacerbations, hospitalizations) and subgroup analysis by eosinophils.

Limitations

  • Open-label design with potential performance bias and cluster-level contamination.
  • Undifferentiated disease population; limited diagnostic phenotyping and lack of spirometric confirmation.

Future Directions: Cost-effectiveness analyses, implementation research across other LMICs, phenotyping to refine step assignment, and head-to-head comparisons with alternative simplified strategies.

3. Impact and effectiveness of RSV maternal immunization on infant hospitalizations in Buenos Aires: a hospital-based, multicentre, retrospective surveillance cohort study.

76Level IICase-controlLancet regional health. Americas · 2025PMID: 41341162

In a multicenter hospital-based surveillance with a nested test‑negative analysis, maternal RSVpreF immunization showed high effectiveness against infant RSV‑ALRTI hospitalization (VE 80.8% <3 months; 66.1% <6 months), with marked reductions in PICU admissions and prolonged stays, and a one‑third population‑level reduction in infant hospitalizations.

Impact: Provides timely real-world effectiveness data supporting maternal RSV vaccination policies and resource allocation to reduce severe infant respiratory disease.

Clinical Implications: Health systems can expect substantial reductions in RSV-related infant hospitalizations, PICU admissions, and lengthier stays by implementing maternal RSV immunization, especially targeting the third trimester.

Key Findings

  • Vaccine effectiveness against RSV‑ALRTI hospitalization: 80.8% (<3 months) and 66.1% (<6 months).
  • VE against PICU admission 87.2% and against prolonged hospitalization 88.6% (<6 months).
  • Population-level impact: 33.6% reduction in RSV‑ALRTI hospitalizations (infants <6 months) in 2024 vs expected from prior years; number needed to immunize ≈84.

Methodological Strengths

  • Hospital-based multicenter surveillance over seven years with nested test‑negative design.
  • Adjusted analyses for key confounders (age, sex, comorbidities, epidemiological week).

Limitations

  • Retrospective design with potential residual confounding and data completeness limits.
  • Generalizability limited to participating hospitals and early implementation period; VE sample relatively small.

Future Directions: Expand surveillance to diverse regions, evaluate durability across seasons, assess co‑administration and coverage strategies, and perform cost‑effectiveness analyses.