Daily Respiratory Research Analysis
Three papers advance respiratory science and care: a transparent, interpretable AI system enables flexible-channel sleep apnea diagnosis across 15,807 polysomnograms; mechanistic multi-omic profiling of RSV distinguishes infected versus bystander host responses and identifies required host factors; and pediatric ARDS data show chest wall versus lung mechanics cannot be reliably inferred without esophageal manometry, with direct implications for safe ventilator pressures.
Summary
Three papers advance respiratory science and care: a transparent, interpretable AI system enables flexible-channel sleep apnea diagnosis across 15,807 polysomnograms; mechanistic multi-omic profiling of RSV distinguishes infected versus bystander host responses and identifies required host factors; and pediatric ARDS data show chest wall versus lung mechanics cannot be reliably inferred without esophageal manometry, with direct implications for safe ventilator pressures.
Research Themes
- Transparent and interpretable AI for sleep apnea diagnosis across clinical and home settings
- Host–pathogen interactions and required host factors in RSV infection
- Ventilator mechanics in pediatric ARDS and the role of esophageal manometry
Selected Articles
1. Transparent artificial intelligence-enabled interpretable and interactive sleep apnea assessment across flexible monitoring scenarios.
Using 15,807 PSGs from seven cohorts, a transparent and interpretable AI achieved 0.738–0.810 accuracy for four-level sleep apnea severity and R²=0.92–0.96 for AHI prediction, with 99.8% within one severity grade. The system delivered expert-logic visualizations and reached 0.970 sensitivity using only oximetry, supporting scalable screening across clinical and home settings.
Impact: This work demonstrates a large-scale, externally validated, interpretable AI for sleep apnea across flexible signal configurations, overcoming key adoption barriers and enabling cost-effective screening.
Clinical Implications: Supports accurate screening and severity estimation using limited signals (e.g., oximetry), facilitates triage and home-to-clinic care pathways, and enables transparent clinician–patient decision-making.
Key Findings
- Analyzed 15,807 PSGs across seven multi-ethnic cohorts with external validation.
- Achieved 0.738–0.810 accuracy for four-level severity and 99.8% within one severity grade.
- Predicted AHI with R²=0.92–0.96 on external cohorts; oximetry-only sensitivity reached 0.970.
- Delivered multi-level, expert-logic interpretable visualizations and nightly risk reports.
Methodological Strengths
- Large multi-cohort external validation with diverse populations (n=15,807).
- Transparent, expert-logic interpretability enabling clinical auditability.
Limitations
- Retrospective modeling; prospective impact on outcomes and workflows not yet tested.
- Generalizability to varied home devices and populations requires prospective evaluation.
Future Directions: Prospective, multi-site clinical implementation trials; regulatory validation; integration with wearable/wireless oximetry and telemedicine; health-economic evaluations.
2. Defining the host dependencies and the transcriptional landscape of RSV infection.
Combining genome-wide CRISPR knockout screens with single-cell RNA-seq, the study maps RSV host dependencies and reveals divergent transcriptional programs: interferon-stimulated genes in bystanders and unfolded protein response/cellular stress in infected cells. Multiple host factors required for RSV were identified and contextualized against 29 screens across 17 viruses.
Impact: Provides mechanistic insight into cell-type-specific host responses during RSV infection and a catalog of required host factors, offering targets for host-directed antivirals and biomarkers.
Clinical Implications: Identified host factors and response patterns could inform host-directed therapies and predictive biomarkers; translation requires in vivo validation and druggability assessment.
Key Findings
- Interferon-stimulated genes are predominantly expressed in bystander-activated cells, not in RSV-infected cells.
- RSV-infected cells upregulate unfolded protein response and cellular stress pathways.
- Genome-wide CRISPR screens identified multiple host factors essential for RSV infection and were contextualized across 29 screens of 17 other viruses.
Methodological Strengths
- Integration of functional genomics (CRISPR knockout) with single-cell transcriptomics.
- Cross-viral contextualization against dozens of prior screens enhances generalizability of findings.
Limitations
- Primarily in vitro cellular models; lacks in vivo validation of targets.
- Clinical translation and therapeutic efficacy remain to be demonstrated.
Future Directions: Validate host factors in in vivo models; assess druggability and safety of host-directed interventions; develop biomarkers reflecting bystander versus infected-cell programs.
3. Differentiating Lung From Chest Wall Mechanics Is Difficult Without Esophageal Manometry in Children With Acute Respiratory Distress Syndrome.
In 207 PARDS patients (750 patient-days), E_L/E_RS had weak ties to routine variables; C_RS correlated strongly with lung compliance and only modestly predicted high/low E_L/E_RS (AUC 0.73/0.60). Day-to-day E_L/E_RS changes were not predictable. Raising Pplat above 28 cmH2O when C_RS is low may be inappropriate without esophageal manometry.
Impact: Provides actionable evidence that routine variables cannot reliably substitute for esophageal manometry to discern lung vs chest wall mechanics, directly influencing safe ventilator pressure limits in children.
Clinical Implications: Avoid increasing Pplat beyond recommended thresholds solely based on low C_RS; consider esophageal manometry to individualize transpulmonary pressures in PARDS.
Key Findings
- Median E_L/E_RS was 0.83; C_RS weakly correlated with E_L/E_RS but strongly with lung compliance (r=0.94).
- C_RS modestly discriminated high (>0.9) vs low (<0.7) E_L/E_RS (AUC 0.73/0.60); day-to-day E_L/E_RS changes were unpredictable.
- Implication: elevating Pplat when C_RS is impaired may be inappropriate without esophageal pressure measurement.
Methodological Strengths
- Secondary analysis of an RCT dataset with esophageal manometry across 207 children.
- Comprehensive multivariable modeling over 750 patient-days.
Limitations
- Secondary analysis; not designed to test interventional thresholds or outcomes.
- Generalizability may be limited to quaternary PICU settings with manometry expertise.
Future Directions: Prospective trials testing manometry-guided ventilation in PARDS; pragmatic studies on feasibility and outcomes of wider manometry adoption.