Daily Respiratory Research Analysis
Key advances span mechanistic human immunology, diagnostics for respiratory viruses, and precision methods in critical care. A controlled human endotoxemia study reveals impaired myelopoiesis and type I interferon responses during systemic inflammation, a multispecimen approach doubles RSV detection in hospitalized adults, and a Lancet Respiratory Medicine review provides a framework to estimate individualized treatment effects in heterogeneous syndromes like sepsis and acute respiratory distres
Summary
Key advances span mechanistic human immunology, diagnostics for respiratory viruses, and precision methods in critical care. A controlled human endotoxemia study reveals impaired myelopoiesis and type I interferon responses during systemic inflammation, a multispecimen approach doubles RSV detection in hospitalized adults, and a Lancet Respiratory Medicine review provides a framework to estimate individualized treatment effects in heterogeneous syndromes like sepsis and acute respiratory distress syndrome.
Research Themes
- Human mechanistic immunology in systemic inflammation
- Enhanced detection strategies for respiratory viruses (RSV)
- Individualized treatment effect estimation in critical care
Selected Articles
1. Systemic inflammation impairs myelopoiesis and interferon type I responses in humans.
Using a controlled human LPS endotoxemia model spanning both hyperinflammatory and immunosuppressive phases, the authors show that systemic inflammation impairs myelopoiesis and type I interferon responses. Single-cell RNA-seq identified an inflammatory CD163+ population during the acute phase, providing mechanistic insights into human immunoparalysis.
Impact: This mechanistic human study bridges the gap between clinical phenotypes of hyperinflammation/immunosuppression and cellular programs, informing biomarker development and immunomodulatory strategies in sepsis and acute respiratory failure.
Clinical Implications: Findings support patient stratification and timing of immunotherapies in conditions such as sepsis and acute respiratory distress syndrome by identifying impaired myelopoiesis and type I IFN signaling as key axes.
Key Findings
- Controlled human LPS model captured both hyperinflammatory and late immunosuppressive phases of systemic inflammation.
- Single-cell RNA-seq during the acute phase identified an inflammatory CD163+ population.
- Systemic inflammation impaired myelopoiesis and type I interferon responses in humans.
Methodological Strengths
- Controlled human in vivo endotoxemia model enabling causal inference on immune dynamics
- Single-cell transcriptomics for high-resolution cellular and pathway mapping
Limitations
- Abstract provides limited quantitative details on sample size and demographics
- Endotoxemia model may not capture full complexity of clinical sepsis or ARDS
Future Directions: Validate identified cellular programs in patients with sepsis/ARDS, link to outcomes, and test immunomodulatory interventions targeting myelopoiesis and IFN-I pathways.
Systemic inflammatory conditions are classically characterized by an acute hyperinflammatory phase, followed by a late immunosuppressive phase that elevates the susceptibility to secondary infections. Comprehensive mechanistic understanding of these phases is largely lacking. To address this gap, we leveraged a controlled, human in vivo model of lipopolysaccharide (LPS)-induced systemic inflammation encompassing both phases. Single-cell RNA sequencing during the acute hyperinflammatory phase identified an inflammatory CD163
2. Detection by Nasopharyngeal Swabs Alone Underestimates Respiratory Syncytial Virus-Related Hospitalization Incidence in Adults: The Multispecimen Study's Final Analysis.
In 3,669 hospitalized adults, combining NPS, saliva, sputum, and serology increased RSV detection by 112% over NPS alone. Saliva outperformed NPS, and timing mattered: NPS collected a day later detected 30% fewer infections, indicating substantial underestimation when relying on NPS-only testing.
Impact: Provides definitive, multicenter evidence that NPS-only testing underestimates RSV burden and offers a practical correction factor, reshaping surveillance and diagnostic protocols.
Clinical Implications: Surveillance and hospital diagnostics should incorporate saliva, sputum, and serology where feasible; incidence estimates based on NPS alone should be adjusted upward (≈2-fold). Earlier sampling improves sensitivity.
Key Findings
- Using four specimen types increased RSV detection by 112% (95% CI, 86–141%) versus NPS alone.
- Sensitivities: serology 73.0%, sputum 70.1%, saliva 61.4%, NPS 47.2%.
- In congestive heart failure exacerbations, additional specimens increased detection by 267% (95% CI, 85–625%).
- NPS collected ~1 day later detected 30% fewer RSV infections.
Methodological Strengths
- Prospective multicenter enrollment with large sample size
- Head-to-head comparison across four specimen types plus timing analysis
Limitations
- Sputum and paired serology were available in only one-third of participants
- Hospitalized adults ≥40 years may limit generalizability to outpatients or younger populations
Future Directions: Assess cost-effectiveness and feasibility of multispecimen testing in routine care; validate saliva-first strategies in cardiopulmonary subgroups and outpatient settings; refine correction factors by population.
BACKGROUND: Most epidemiologic studies and clinical testing use single nasal/nasopharyngeal swab (NPS) for respiratory syncytial virus (RSV) detection. Studies document that RSV detection improves if another specimen is added to NPS, but the impact of using multiple specimen types has not been assessed. We quantified RSV detection increase using multiple-specimen testing versus NPS alone. METHODS: Hospitalized adults aged ≥40 years with acute respiratory illness were prospectively enrolled in 7 US/Canadian hospitals. NPS, saliva, sputa, and acute/convalescent sera were collected and tested. RESULTS: Among 3669 participants, 100% had NPS, 97.7% saliva, 33.0% sputum, and 33.4% paired serology. RSV detection was 112% higher (95% CI, 86%-141%) using all specimen types as compared with NPS alone. Serology test sensitivity was the highest (73.0%; 95% CI, 65.1%-80.8%), followed by sputum (70.1%; 95% CI, 62.1%-78.0%), saliva (61.4%; 95% CI, 55.4%-67.5%), and NPS (47.2%; 95% CI, 41.1%-53.4%). Among those with congestive heart failure exacerbations, additional specimens increased detection by 267% (95% CI, 85%-625%), and saliva detected more infections than NPS. Among 1013 participants with paired NPSs from different time points, specimens collected on average 1 day later detected 30% fewer RSV infections. CONCLUSIONS: RSV detection increased >100% using 4 specimen types, suggesting a 2-fold correction factor is appropriate for incidence and prevalence studies relying on NPS alone. Saliva was more sensitive than NPS, warranting further study, particularly in cardiac cases.
3. Evidence-based personalised medicine in critical care: a framework for quantifying and applying individualised treatment effects in patients who are critically ill.
This Review presents a practical framework to derive, validate, and apply individualized treatment effect (ITE) estimates in critical care, acknowledging the heterogeneity of treatment effects in syndromes like sepsis and acute respiratory distress syndrome. It highlights statistical and machine-learning approaches for population enrichment and precision therapy.
Impact: By shifting emphasis from average to individualized treatment effects, this framework can improve trial design, patient selection, and bedside decision-making across respiratory critical care.
Clinical Implications: Encourages adoption of ITE modeling and enrichment strategies in trials and practice for conditions like sepsis and ARDS (急性呼吸窮迫症候群), enabling more precise oxygen targets, ventilation strategies, and pharmacotherapy.
Key Findings
- Defines a framework to estimate and validate individualized treatment effects beyond average treatment effects.
- Highlights statistical and machine-learning methods to analyze heterogeneity of treatment effect and enable population enrichment.
- Addresses challenges for clinical implementation, including validation, transportability, and decision-support integration.
Methodological Strengths
- Comprehensive synthesis bridging trial methodology and bedside application
- Actionable framework with validation emphasis for ITE estimation
Limitations
- Narrative review without primary data or systematic PRISMA methodology
- Real-world implementation depends on data quality, external validation, and clinical workflow integration
Future Directions: Prospective validation of ITE tools in platform and adaptive trials; open data/code sharing; pragmatic clinical decision support integrating ITE for sepsis and ARDS.
Clinicians aim to provide treatments that will result in the best outcome for each patient. Ideally, treatment decisions are based on evidence from randomised clinical trials. Randomised trials conventionally report an aggregated difference in outcomes between patients in each group, known as an average treatment effect. However, the actual effect of treatment on outcomes (treatment response) can vary considerably between individuals, and can differ substantially from the average treatment effect. This variation in response to treatment between patients-heterogeneity of treatment effect-is particularly important in critical care because common critical care syndromes (eg, sepsis and acute respiratory distress syndrome) are clinically and biologically heterogeneous. Statistical approaches have been developed to analyse heterogeneity of treatment effect and predict individualised treatment effects for each patient. In this Review, we outline a framework for deriving and validating individualised treatment effects and identify challenges to applying individualised treatment effect estimates to inform treatment decisions in clinical care.