Daily Respiratory Research Analysis
Analyzed 212 papers and selected 3 impactful papers.
Summary
Three impactful respiratory studies stood out today: a validated 6‑variable risk score (BLISS) predicting 2‑year COPD hospital admissions; real‑world, two‑season effectiveness of single‑dose nirsevimab preventing infant RSV hospitalizations using target‑trial emulation; and a rigorously developed/validated exposure questionnaire (HP‑SAQE) that improves identification of causative antigens in hypersensitivity pneumonitis. Together, they advance prognosis, prevention, and diagnosis across respiratory medicine.
Research Themes
- Prognostic risk stratification in COPD
- Real-world prevention of RSV hospitalizations in infants
- Diagnostic exposure assessment in hypersensitivity pneumonitis
Selected Articles
1. Two-season effectiveness of a single nirsevimab dose against RSV hospitalisation in healthy term-born infants: a population-based case-control study, Spain, October 2023 to March 2025.
Using target-trial emulation in a nationwide case–control design, a single dose of nirsevimab reduced RSV hospitalisations by about two-thirds over infants’ first two seasons, with very high effectiveness in season one and attenuated, possibly underestimated effectiveness in season two. No rebound in RSV hospitalisations among immunised children was observed.
Impact: This robust real-world analysis provides timely, policy-relevant evidence that single-dose nirsevimab substantially reduces RSV hospitalisations at scale, informing immunisation strategies and resource planning.
Clinical Implications: Supports broad infant prophylaxis with nirsevimab to curb RSV hospitalisations, optimise seasonal clinic loads, and prioritise first-season coverage, while monitoring second-season protection and equity of access.
Key Findings
- Two-season effectiveness against RSV hospitalisation was 64% (catch-up) and 67% (at-birth).
- First-season effectiveness was very high: 78% (catch-up) and 84% (at-birth).
- Second-season estimates were low to null (−8% to 20%), potentially underestimated due to survivor bias; no rebound in hospitalisations among immunised children.
- Causal per-protocol effects estimated using cloning, censoring, and inverse-probability weighting in a target-trial emulation framework.
Methodological Strengths
- Target-trial emulation with cloning, censoring, and IPW to approximate causal effects from observational data.
- Population-based, multicentre design with matching by province and birth date across two RSV seasons.
Limitations
- Observational design subject to residual confounding and misclassification.
- Second-season effectiveness estimates may be biased (survivor bias) and need cautious interpretation.
Future Directions: Assess durability across additional seasons, evaluate dosing strategies for sustained protection, and study effectiveness in preterm/medically complex infants and diverse settings.
BACKGROUNDIn autumn 2023, Spain recommended nirsevimab to all infants born after 1 April 2023, as catch-up or at-birth immunisation.AIMWe estimated effectiveness of a single nirsevimab dose against respiratory syncytial virus (RSV) hospitalisations throughout two seasons in healthy term-born infants.METHODSCases were children born 1 April 2023 through 31 March 2024 after 35 gestation weeks without major comorbidities and hospitalised for RSV infection between 2023 immunisation campaign onset and 31 March 2025. We selected four healthy population-density controls per case, matched by province and birth date. Using target trial emulation, causal per-protocol effectiveness was estimated for catch-up (within 30 days of 2023 campaign onset) and at-birth immunisation (within 14 days of life) through cloning, censoring and inverse-probability-weighted conditional logistic regression.RESULTSWe included 235/905 cases/controls for catch-up and 334/1,292 cases/controls for at-birth immunisation (first season), and 188/713 cases/controls for catch-up and 328/1,269 cases/controls for at-birth immunisation (second season). Two-season effectiveness was 64% (95% confidence interval (CI): 52-72) and 67% (95% CI: 59-74) for catch-up and at-birth immunisation, respectively, compared with 78% (95% CI: 70-84) and 84% (95% CI: 79-88) during first season and -8% (95% CI: -88 to 38) and 20% (95% CI: -21 to 46) during second season.CONCLUSIONNirsevimab was an effective long-term population-level intervention, decreasing RSV hospitalisations by two-thirds during the first two seasons of life. Effectiveness during second season was low or null, although it may be underestimated due to unavoidable survivor bias. The RSV hospitalisation rate among immunised children did not rebound in the second season.
2. Prognostic score for predicting respiratory admissions among patients with chronic obstructive pulmonary disease in primary care: development and validation in population cohorts (Birmingham Lung Improvement Studies (BLISS)).
A 6-variable BLISS score (age, CAT, prior 12-month respiratory admissions, BMI, diabetes, and FEV1% predicted) predicted 2-year respiratory admissions with C-statistics ~0.71–0.73 and good calibration across development and two external validation cohorts. Decision-curve analyses showed net clinical benefit and superiority over existing scores.
Impact: Delivers a practical, externally validated risk tool for COPD admissions using readily available data, enabling proactive, risk-stratified care planning in primary care.
Clinical Implications: Supports targeted interventions (e.g., pulmonary rehab referral, vaccination, action plans, closer follow-up) for high-risk COPD patients and informs resource allocation.
Key Findings
- Six predictors formed the BLISS score: age, CAT, prior 12-month respiratory admissions, BMI, diabetes, and FEV1% predicted.
- Performance: C-statistic 0.73 (internal), 0.73 (ECLIPSE), and 0.71 (CPRD); calibration slopes ~0.87–0.92 across cohorts.
- Decision-curve analysis showed greater net benefit than individual predictors and the Bertens’ score.
- Robust across subgroups in CPRD; four of six variables are routinely available in primary care.
Methodological Strengths
- Large-scale external validation in two independent cohorts (ECLIPSE, CPRD) with calibration and decision-curve analyses.
- Bootstrapping to adjust for optimism and robust multivariable model selection from 23 candidates.
Limitations
- Observational cohorts; impact on clinical outcomes not yet tested in implementation trials.
- Generalizability beyond UK primary care and ECLIPSE populations needs further evaluation.
Future Directions: Prospective impact studies to assess changes in care processes and admissions; integration into EHRs with clinical decision support; validation in non-UK and low-resource settings.
OBJECTIVE: To predict the two year risk of respiratory admission to hospital among individuals with chronic obstructive pulmonary disease (COPD), with the development and validation (internal and external) of a prognostic score.DESIGN: Model development and validation in population cohorts.SETTING: Birmingham Lung Improvement Studies (BLISS) cohort of new and existing patients with COPD in primary care (model development and internal validation); Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) international cohort and UK primary care Clinical Practice Research Datalink (CPRD) Aurum database linked with Hospital Episode Statistics (external validation).PARTICIPANTS: 1894 patients with new and existing COPD from BLISS cohort; 1749 patients with moderate to very severe COPD from ECLIPSE cohort; 27 340 patients with COPD from CPRD Aurum database linked with Hospital Episode Statistics.MAIN OUTCOME MEASURES: One or more respiratory admissions within two years of cohort entry for development, internal validation, and external validation in CPRD; severe exacerbation within two years for external validation in ECLIPSE cohort. The model was developed from 23 candidate predictors by using multivariable logistic regression with bootstrapping for internal validation and adjustment for overfitting and optimism. Discrimination and calibration were assessed at each stage. Net benefit of the score (clinical utility) was examined across a range clinically relevant risk thresholds compared with use of individual score components. Subgroup and sensitivity analyses were conducted in the CPRD. The BLISS score was directly compared with the Bertens' score in the ECLIPSE cohort. Clinical implementation was explored with relevant stakeholders.RESULTS: Six predictors were retained (age, COPD Assessment Test score, respiratory admissions in the previous 12 months, body mass index, diabetes, forced expiratory volume in 1 second % predicted) to form the BLISS score for estimating an individual's two year risk of respiratory admission. The score had similar discrimination performance on internal validation (optimism adjusted C statistic 0.73 (95% confidence interval 0.70 to 0.77)) and external validation (ECLIPSE: C=0.73 (0.71 to 0.76); CPRD: C=0.71 (0.70 to 0.72)) and good calibration performance in the BLISS (slope=0.87 (95% confidence interval 0.73 to 1.02), CPRD (0.89 (0.85 to 0.93)), and ECLIPSE (0.92 (0.79 to 1.05) cohorts). Stratified analysis in the CPRD cohort showed that it was robust in different population subgroups. Net benefit analyses showed superiority of the BLISS score over individual predictors and the Bertens' score (C=0.68 (0.65 to 0.71); calibration slope 0.68 (0.56 to 0.81)).CONCLUSIONS: The BLISS score showed good performance in estimating individual risk of respiratory admission (within two years) in cohorts containing patients from different settings and geographical locations and with different severities of COPD. Four of the included six variables are readily available in primary care records, and two are partially available but easy to collect. Impact evaluations are now needed to fully study use of the score in clinical care.
3. Development and validation of the Hypersensitivity Pneumonitis South Asian Questionnaire for Exposure (HP-SAQE): a novel, qualitative and quantitative tool.
HP‑SAQE, built from literature synthesis and a two-round multinational Delphi, combines 17 qualitative and 4 quantitative exposure items (score 0–14) and discriminates HP from non‑HP ILD with AUC 0.79 (derivation) and 0.86 (validation). It is translated into Hindi, Tamil, and Sinhala and aligned to multidisciplinary diagnosis.
Impact: Provides a standardized, validated exposure assessment for HP in South Asia, addressing a key diagnostic gap and enabling reproducible exposure phenotyping.
Clinical Implications: Supports systematic exposure history-taking in suspected HP, improves case ascertainment for multidisciplinary teams, and facilitates targeted antigen avoidance and public health interventions.
Key Findings
- Expert consensus (≥70%) identified 17 qualitative and 4 quantitative items; HP‑SAQE score 0–14.
- Derivation cohort (n=40): mean score HP vs non‑HP 10.2 vs 6.7 (p=0.001), AUC 0.791.
- Validation cohort (n=163): mean score HP vs non‑HP 9.4 vs 4.13 (p<0.001), AUC 0.858; site AUCs 0.705–0.967.
- Tool translated into Hindi, Tamil, and Sinhala after pilot testing.
Methodological Strengths
- Systematic review to identify candidate exposures and two-round Delphi with 39 pulmonologists across four countries.
- Prospective derivation and multicentre external validation against multidisciplinary discussion diagnosis; strong AUCs and cross-site robustness.
Limitations
- Derivation sample was modest (n=40), and tool performance outside South Asia remains to be established.
- Self-reported exposures may be prone to recall bias; impact on clinical outcomes was not assessed.
Future Directions: Validate HP‑SAQE in other regions and occupational settings, integrate into ILD clinics/EHRs, and test whether use improves diagnostic yield and outcomes.
INTRODUCTION: There is an unmet need for a validated qualitative and quantitative tool to assess environmental exposures in patients with interstitial lung disease (ILD). This study aimed to develop and validate a comprehensive tool to systematically identify exposures in patients with ILD.METHODS: A systematic literature search was completed to identify exposures associated with more than five documented hypersensitivity pneumonitis (HP) cases. These exposures were evaluated through a two-round Delphi survey involving 39 pulmonologists from India, Sri Lanka, Pakistan and Nepal. The questionnaire was prospectively derived at one centre and validated across five centres in India and Sri Lanka. The HP South Asian Questionnaire for Exposure (HP-SAQE) was validated against the gold standard multidisciplinary discussion diagnosis, distinguishing HP from non-HP ILD.RESULTS: The literature search screened 5170 records and included 407 studies, identifying 24 exposures. A 50-item Delphi survey achieved expert consensus (>70%) on 17 qualitative and 4 quantitative items (six questions) by 39 pulmonologists. HP-SAQE score ranged from 0 to 14. After pilot testing, the questionnaire was translated into Hindi, Tamil and Sinhala. In the derivation cohort (n=40), the HP-SAQE score was significantly higher in patients with HP versus non-HP (mean: 10.2±1.6 vs 6.7±4.2; p=0.001). This finding was validated in a separate cohort (n=163; mean: 9.4±2.2 vs 4.13±4.28; p<0.001). Receiver operating characteristic curve analysis showed good diagnostic performance (area under the receiver operating characteristic curve, AUC: 0.791 derivation; 0.858 validation, centre-wise AUCs 0.705-0.967).CONCLUSION: The HP-SAQE is the first qualitative and quantitative exposure assessment tool for patients with ILD that has a good diagnostic performance.