CHEST

BackgroundAccurate prediction of exacerbation risk enables personalised chronic obstructive pulmonary disease (COPD) care. We developed and validated a generalisable model to predict the individualised rate and severity of COPD exacerbations. MethodsWe pooled data from three COPD trials on patients with a history of exacerbations. We developed a mixed-effect model to predict exacerbations over one-year. Severe exacerbations were those requiring inpatient care. Predictors were a history of exacerbations, age, sex, body mass index, smoking status, domiciliary oxygen therapy, lung function, symptom burden, and current medication use. ECLIPSE, a multicentre cohort study, was used for external validation. ResultsThe development dataset included 2,380 patients (mean 64{middle dot}7 years, 1373 [57{middle dot}7%] men, mean exacerbation rate 1{middle dot}42/year, 0{middle dot}29/year [20{middle dot}5%] severe). When validated against all COPD patients in ECLIPSE (n=1819, mean 63{middle dot}3 years, 1186 [65{middle dot}2%] men, mean exacerbation rate 1{middle dot}20/year, 0{middle dot}27/year [22{middle dot}2%] severe), the area-under-curve was 0{middle dot}81 (95%CI 0{middle dot}79-0{middle dot}83) for [≥]2 exacerbations and 0{middle dot}77 (95%CI 0{middle dot}74-0{middle dot}80) for [≥]1 severe exacerbation. Predicted rates were 0{middle dot}25/year for severe and 1{middle dot}31/year for all exacerbations, close to the observed rates (0{middle dot}27/year and 1{middle dot}20/year, respectively). In ECLIPSE patients with a prior exacerbation history (n=996, mean 63{middle dot}6 years, 611 (61{middle dot}3%) men, mean exacerbation rate 1{middle dot}82/year, 0{middle dot}40/year [22{middle dot}0%] severe), the area-under-curve was 0{middle dot}73 (95%CI 0{middle dot}70-0{middle dot}76) for [≥]2 exacerbations and 0{middle dot}74 (95%CI 0{middle dot}70-0{middle dot}78) for [≥]1 severe exacerbation. Calibration was accurate for severe exacerbations (predicted=0{middle dot}37/year, observed=0{middle dot}40/year) and all exacerbations (predicted=1{middle dot}80/year, observed=1{middle dot}82/year). The model is accessible at http://resp.core.ubc.ca/ipress/accept. InterpretationThis model can be used as a decision tool to personalise COPD treatment and prevent exacerbations. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSPreventing future exacerbations is a major goal in COPD care. Because of adverse effects, preventative treatments should be reserved for those at a higher risk of future exacerbations. Predicting exacerbation risk in individual patients can guide these clinical decisions. A 2017 systematic review reported that of the 27 identified COPD exacerbation prediction tools, only two had reported external validation and none was ready for clinical implementation. To find the studies that were published afterwards, we searched PubMed for articles on development and validation of COPD exacerbation prediction since 2015, using the search terms "COPD", "exacerbation", "model", and "validation". We included studies that reported prediction of either the risk or the rate of exacerbations and excluded studies that did not report external validation. Our literature search revealed two more prediction models neither of which was deemed generalisable due to lack of methodological rigour, or local and limited nature of the data available to investigators. Added value of this studyWe used data from three randomised trials to develop ACCEPT, a clinical prediction tool based on routinely available predictors for COPD exacerbations. We externally validated ACCEPT in a large, multinational prospective cohort. To our knowledge, ACCEPT is the first COPD exacerbation prediction tool that jointly estimates the individualised rate and severity of exacerbations. Successful external validation of ACCEPT showed that its generalisability can be expanded across geography and beyond the setting of therapeutic trials. ACCEPT is designed to be easily applicable in clinical practice and is readily accessible as a web application. Implications of all the available evidenceCurrent guidelines rely on a history of exacerbations as the sole predictor of future exacerbations. Simple clinical and demographic variables, in aggregate, can be used to predict COPD exacerbations with improved accuracy. ACCEPT enables a more personalised approach to treatment based on routinely collected clinical data by allowing clinicians to objectively differentiate risk profiles of patients with similar exacerbation history. Care providers and patients can use individualised exacerbation risk estimates to decide on preventive therapies based on objectively-established or patient-specific thresholds for treatment benefit and harm. COPD clinical researchers can use this tool to target enriched populations for enrolment in clinical trials.

ObjectivesTo examine whether high flow nasal oxygen (HFNO), continuous positive airway pressure (CPAP), or noninvasive ventilation (NIV) strategies impact mortality, the need for invasive mechanical ventilation (IMV), or hospital and intensive care unit (ICU) length of stay compared to standard oxygen therapy (SOT) or each other in patients with severe or critical COVID-19 with acute hypoxemic respiratory failure. MethodsA rapid review of randomized controlled trials (RCTs) identified through published systematic and rapid reviews supplemented with a search of bibliographic databases. RCTs were eligible if they compared HFNO, CPAP, or NIV to SOT or another ventilation strategy. Studies were screened, selected, and extracted by a single reviewer and checked by a second reviewer. We assessed risk of bias of included studies using the Cochrane Risk of bias tool and used the grading of recommendations, assessment, development, and evaluation (GRADE) approach to judge the certainty of the evidence for mortality, need for IMV, and hospital and ICU length of stay. We sought RCT evidence for non-COVID-19 patients with acute hypoxemic respiratory failure and acute respiratory distress to inform additional comparisons and to supplement the available data for COVID-19. ResultsA total of 5 RCTs comparing ventilation strategies in patients with severe or critical COVID-19 were included. Patient and study characteristics were extracted and evidence and certainty of evidence assessments were completed for comparisons of HFNO and CPAP to standard oxygen therapy and NIV and CPAP to HFNO. An additional 22 RCTs of non-COVID-19 patients were also included and considered. Results from meta-analysis suggest reductions in mortality and IMV with HFNO (RR mortality 0.87 (0.66-1.13), IMV 0.89 (0.77-1.03); low quality evidence) or CPAP (RR mortality 0.87 (0.64-1.18) low quality evidence, IMV 0.81 (0.67-0.98) moderate quality evidence) compared to SOT. Helmet NIV may reduce IMV (RR 0.69 (0.43-1.09)) and CPAP may reduce IMV (RR 0.69 (0.43-1.09)) and hospital (1.67 days fewer (5.43 fewer-2.09 more) or ICU length of stay (1.02 days fewer (3.97 fewer-1.93 more)) compared to HFNO (low quality evidence). ConclusionsThis rapid systematic review highlights the available evidence to support the use of noninvasive ventilation strategies including high flow nasal oxygen, noninvasive ventiltaion (e.g., BiPAP), or CPAP in hospitalized patients with severe or critical COVID-19 and acute hypoxemic respiratory failure who do not need emergent intubation. Findings based on moderate to very low certainty evidence suggest that noninvasive ventilation may be considered as an alternative to standard oxygen therapy to reduce hypoxemia and dyspnea. Additional high quality RCTs are warranted to reduce uncertainty and to fill in important knowledge gaps.

ObjectivesRisk prediction models are increasingly used at point of care to support personalized treatment decisions. This study created and evaluated two Information, Education, and Communication (IEC) resources to improve public understanding of a risk prediction tool for Chronic Obstructive Pulmonary Disease (COPD) management. MethodsWe created a 5-minute video and a pamphlet explaining the burden of COPD and how a prediction model generates quantitative estimates of, and benefit of certain treatments for, exacerbations of the disease. These tools were tested among students and researchers in public health. A patient partner was engaged throughout to ensure the materials were accessible and patient-centered. ResultsTwenty-five individuals participated (80% female; 60% aged 25-64). After reviewing the materials, 92% of participants agreed to the statement "I am familiar with the idea of precision medicine approach". Most (72%) felt they received sufficient information about the tool, and 92% believed such materials could support patient decision. Participants stated that the materials were clear, detailed, and written in plain language. Participants preferred the pamphlet (68%) over the video (44%). Suggestions for improvement included expanding content on how the tool works. ConclusionsThe findings of this study provided a better understanding of how to present complex medical information around precision medicine that is accessible and meaningful to diverse audiences. We will improve our materials based on these comments, and continue to make them available at https://resp.core.ubc.ca/show/patient_committee_2025

BackgroundMixed trial results suggest that some ventilated patients with acute respiratory distress syndrome (ARDS) benefit from high PEEP while others may be harmed, indicating heterogeneity of treatment effect (HTE). This study applies data-driven predictive approaches to uncover HTE and re-examines previously hypothesized HTE. This manuscript serves as a pre-registration of planned external validation of our trained models. MethodsWe identified eight randomized trials, and obtained individual patient data (IPD) from three of them (ALVEOLI, LOVS, EXPRESS), as our train cohort. We used effect modelling to predict individualized treatment effects (predicted 28-day mortality risk difference between PEEP strategies) across patient subgroups stratified by observed tertiles ([&le;]8 cmH2O, 9-11 cmH2O, [&ge;]12 cmH2O). Candidate effect modelling methods included meta-learners and technique-specific methods. Optimal methods were selected through leave-one-trial-out cross-validation, evaluating the methods performances in each PEEP tertile using AUC-benefit. We trained final models using the best performing methods implemented with or without forward selection (which yielded sufficient AUC-benefit), and additional final models by selecting the variables that yielded consistency in the forward selections performed in the cross validation, if any. We further evaluated earlier hypothesized HTE comparing (1) patients with baseline PaO2/FiO2 [&le;] 200 versus > 200 mmHg, and (2) patients with hypoinflammatory versus hyperinflammatory subphenotypes. Preliminary findingsIn the lower PEEP tertile ([&le;]8 cmH2O), an X-learner implemented without, and an S-learner implemented with forward selection (both with flexible base learners), yielded the highest AUC benefits and were used to train final models. In the high PEEP tertile ([&ge;]12 cmH2O), only the causal forest implemented with forward selection yielded an AUC benefit exceeding zero. Respiratory-system compliance (CRS) was consistently selected in the forward selections of cross validation, and was used to train an extra final causal forest model, with predicted effects shifting from harm to benefit for CRS 26.5 mL/cmH2O or higher. Higher PEEP benefited patients with baseline PaO2/FiO2 [&le;]200 mmHg (OR 0.80, 95% CI 0.66-0.98), incurred harm among those with PaO2/FiO2 >200 mmHg (OR 1.74, 95% CI 1.02-2.98; interaction P=0.01). This HTE was strongest when PaO2/FiO2 was measured at low PEEP ([&le;]8 cmH2O), reduced at mid-level PEEP (9-11 cmH2O), and negligible at high PEEP ([&ge;]12 cmH2O). A second-order interaction showed significant heterogeneity of HTE (ie, second-order heterogeneity) across PEEP tertiles (P=0.03). Preliminary ConclusionsOur preliminary findings indicated that baseline CRS [&ge;] 26.5 mL/cmH2O predicts benefit, while CRS < 26.5 mL/cmH2O predicts harm from high PEEP when CRS is measured at high baseline PEEP ([&ge;]12 cmH2O). Similarly, baseline PaO2/FiO2 [&le;] 200 mmHg predicts benefit, while PaO2/FiO2 > 200 mmHg predicts harm from high PEEP when PaO2/FiO2 is measured at a low baseline PEEP ([&le;]8 cmH2O). Using data from the LOVS trial, we investigated HTE for high PEEP between hypo- and hyperinflammatory subphenotypes but found none, despite significant HTE observed earlier in the ALVEOLI trial.

IntroductionUnilateral hypoglossal nerve stimulation (HGNS) is an approved surgical therapy for obstructive sleep apnea (OSA), but its efficacy is limited by obesity and unfavorable (laterally directed) pharyngeal collapse patterns. This study tested whether the effect of body mass index (BMI) on HGNS efficacy differs by pharyngeal collapse pattern, specifically comparing laterally directed and anteroposterior (AP) collapse. MethodsWe pooled data from two independent HGNS cohorts (n=760) to evaluate the interaction between BMI and pharyngeal collapse pattern on HGNS efficacy. Collapse sites were identified via drug-induced sleep endoscopy (DISE) and grouped as laterally directed or AP directed. Multivariable mixed model regression evaluated the association between HGNS efficacy, largely based on optimal setting AHI during titration polysomnogram (primary: percent reduction in apnea-hypopnea index [AHI]; secondary: success defined as [&ge;]50% AHI reduction to <15 events/h) and the interaction between collapse pattern and BMI, adjusting for baseline AHI, partial collapse, surgical center, type of follow-up sleep study, and prior or concomitant pharyngeal surgery. ResultsGreater BMI was associated with a larger reduction in HGNS efficacy in those with lateral collapse (-19.7% [95% CI: -33.2, -6.2] per 5 kg/m{superscript 2}) than in those with AP collapse (-3.8% [-8.0, 0.36]; p-interaction=0.027). In lateral collapse, greater BMI reduced the odds of treatment success (odds ratio [95% CI]: 4.4 [1.4, 14.3] per 5 kg/m{superscript 2}), with no significant effect in AP collapse (1.1 [0.75, 1.5]; p-interaction=0.023). ConclusionThe impact of BMI on HGNS efficacy varies by collapse pattern. Tailoring BMI criteria to collapse pattern may improve HGNS candidate selection.

Background: Anxiety affects 22-56% of patients with COPD. It is independently associated with increased exacerbations, readmissions, and mortality. Medical hypnosis transiently alleviates state anxiety in severe COPD, and attenuates experimentally-induced dyspnoea in healthy volunteers. We aimed to assess the efficacy of hypnosis as adjunct therapy for anxiety during Pulmonary Rehabilitation (PR) versus an active comparator controlling for general motivation and relaxation. Methods. HYPNOBPCO_2 was a single-centre, phase 2, cluster-randomised, active-comparator, parallel-group, superiority trial done at Centre Hospitalier de Bligny, France. Adults +30 years with established COPD, mMRC dyspnoea grade +2, and +10 pack-years were eligible. Consecutive pulmonary rehabilitation cohorts (clusters) were randomly assigned (1:1) to medical hypnosis or structured relaxation, both adjunctive to a 4-week inpatient PR. The primary outcome was the six-item State-Trait Anxiety Inventory (STAI-6) at week 4, analysed in the intention-to-treat population. Secondary outcomes were sensory and affective dyspnoea (Multidimensional Dyspnea Profile sensory and affective sub-scales, COPD Assessment Test) and functional capacity (6-minute walk distance). A moderation analysis tested whether the hypnosis effect varied with baseline sensory and affective dyspnoea burden using Bayesian inference. This trial was registered prospectively (NCT04868357) and the protocol published. Findings. Between 27/09/2021 and 31/01/2024, 79 participants in 24 clusters were randomised (medical hypnosis n = 36, age 64.9 [8.3], 20 female; relaxation n = 43, age 67.4 [9.1], 23 female). Anxiety improved in both arms (deltaSTAI-6 = -5.72, posterior probability of reduction beyond MCID = 0.93). Medical hypnosis did not show an advantage over relaxation overall (deltaSTAI-6 = 0.95; posterior probability of reduction beyond MCID = 0.12). Medical hypnosis did show an advantage that scaled with baseline dyspnoea profile: in patients with high sensory and low affective burden, the predicted anxiety reduction relative to relaxation was larger and more probable (deltaSTAI-6 = -9.26; posterior probability of reduction beyond the 3-point MCID = 0.81). No clinically important safety issues were associated with either intervention and there were no deaths. Interpretation. Anxiety improved under both adjunctive mind-body interventions. The usefulness of hypnosis beyond relaxation was predicted by baseline dyspnoea profile, concentrating in patients with predominantly sensory burden. Future trials should focus on evaluating complementary interventions against burden phenotypes, ultimately paving the way for personalized interventions. Funding. Helebor Foundation; Agence Nationale de la Recherche.

RationaleChronic obstructive pulmonary disease (COPD) is a leading cause of death but with variable progression. ObjectiveEstimate factors influencing transition rates between PRISm and GOLD stages. MethodsUsing a Markov multistate model, transition rates between GOLD-0, PRISm and GOLD-1, GOLD-2 and GOLD 3-4 were estimated for 5,728 US adult ever cigarette users from the COPDGene cohort over 10-years. We calculated one and five-year transition probabilities for progressive and regressive transitions and estimated the mean sojourn time for severity states. Main ResultsGOLD-1 and PRISm individuals spent the least time in any single stage (GOLD-1: 6 years; PRISm: 7 years). PRISm and GOLD-1 individuals were equally likely to transition to GOLD-2 vs. GOLD-0 (PRISm: HR 1.09, 95% confidence interval [CI] 0.90-1.33, GOLD-1 (HR 1.15, 95%CI 0.93-1.42) per five-year period, but rarely transition between PRISm and GOLD-1. Individuals at GOLD-0 were equally likely to progress to GOLD-1 or PRISm (HR 1.11, 95%CI 0.93-1.31) but the transient time for this stage was the longest of any GOLD stage (16 years, 95%CI 15.2-17.3). GOLD-2 was the most likely stage to progress (HR 2.4, 95%CI 1.9-3.02) to GOLD 3-4 vs. regress to GOLD-1. For GOLD-2 individuals, current smoking status (HR 0.84, 95%CI 0.67-1.06) or intensity (HR 0.84, 95%CI 0.54-1.29) was not associated with disease progression. ConclusionsGOLD-1 and PRISm are the most transient stages equally likely to regress to GOLD-0 or progress to GOLD-2 and may benefit from smoking cessation interventions. GOLD-2 individuals are the most likely to progress and may benefit most from targeted disease interventions.

Background-Research questionChronic Obstructive Pulmonary Disease (COPD) is a leading cause of mortality. Predicting mortality risk in COPD patients can be important for disease management strategies. Although scores for all-cause mortality have been developed previously, there is limited research on factors that may directly affect COPD-specific mortality. Study design-Methodsused probabilistic (causal) graphs to analyze clinical baseline COPDGene data, including demographics, spirometry, quantitative chest imaging, and symptom features, as well as gene expression data (from year-5). ResultsWe identified factors linked to all-cause and COPD-specific mortality. Although many were similar, there were differences in certain comorbidities (all-cause mortality model only) and forced vital capacity (COPD-specific mortality model only). Using our results, we developed VAPORED, a 7-variable COPD-specific mortality risk score, which we validated using the ECLIPSE 3-yr mortality data. We showed that the new model is more accurate than the existing ADO, BODE, and updated BODE indices. Additionally, we identified biological signatures linked to all-cause mortality, including a plasma cell mediated component. Finally, we developed a web page to help clinicians calculate mortality risk using VAPORED, ADO, and BODE indices. InterpretationGiven the importance of predicting COPD-specific and all-cause mortality risk in COPD patients, we showed that probabilistic graphs can identify the features most directly affecting them, and be used to build new, more accurate models of mortality risk. Novel biological features affecting mortality were also identified. This is an important step towards improving our identification of high-risk patients and potential biological mechanisms that drive COPD mortality.

BackgroundLarge population-based DNA biobanks linked to electronic health records (EHRs) may provide novel opportunities to identify genetic drivers of ARDS. Research QuestionCan we develop an EHR-based algorithm to identify ARDS in a biobank database, and can this validate a previously reported ARDS genetic risk factor? Study Design and MethodsWe analyzed two parallel genotyped cohorts: a prospective biomarker cohort of critically ill adults (VALID), and a retrospective cohort of hospitalized participants enrolled in a de-identified EHR biobank (BioVU). ARDS was identified by clinician-investigator review in VALID and an EHR algorithm in BioVU (EHR-ARDS). We tested the association between the MUC5B promoter polymorphism rs35705950 with development of ARDS, and assessed if age modified this genetic association in each cohort. ResultsIn VALID, 2,795 patients were included, age was 55 [43, 66] (median [IQR]) years, and 718 (25.7%) developed ARDS. In BioVU, 9,025 hospitalized participants were included, age was 60 [48, 70] years, and 1,056 (11.7%) developed EHR-ARDS. We observed a significant age-related interaction effect on ARDS in VALID: among older patients, rs35705950 was associated with increased ARDS risk (OR: 1.44; 95%CI 1.08-1.92; p=0.012) whereas among younger patients this effect was absent (OR: 0.84; 95%CI: 0.62-1.14; p=0.26). In BioVU, rs35705950 was associated with increased risk for EHR-ARDS among all participants (OR: 1.20; 95%CI: 1.00-1.43, p=0.043) and this did not vary by age. The polymorphism was also associated worse oxygenation in mechanically ventilated BioVU participants, but had no association with oxygenation in VALID. InterpretationThe MUC5B promoter polymorphism was associated with ARDS in two cohorts of at-risk adults. Although age-related effect modification was observed only in VALID, BioVU identified a consistent association between MUC5B and ARDS risk regardless of age, and a novel association with oxygenation impairment. Our study highlights the potential for EHR biobanks to enable precision-medicine ARDS studies.

BackgroundA low respiratory arousal threshold (ArTH) has been linked to reduced continuous positive airway pressure (CPAP) adherence in obstructive sleep apnea (OSA) via a multi-trait model developed in the RICCADSA trial. Our objective was to validate the prior model in a large, real-world cohort and explore alternative linear and non-linear approaches for predicting CPAP adherence. Research QuestionDoes a previously derived multi-trait model linking low ArTH to poor CPAP adherence remain valid in a diverse real-world population and do alternative linear or non-linear approaches offer improved predictive performance? MethodsAdults with OSA from the SNOOzzzE-cohort who initiated CPAP within 1 year of in-lab polysomnography (2017-2019) were included. Pathophysiological traits (Vpassive, Vactive, loop gain, ArTH, ventilatory response to arousal) were estimated from polysomnography. Poor (vs good) adherence was defined as [&le;]2.48h/night at month 1 (1st sample quartile). The prior models performance was evaluated via the area under the curve (AUC) and adherence comparisons. Secondary analyses tested a de novo linear regression and a latent profile analysis (LPA)-derived trait-cluster model. ResultsAmong 744 participants (45% women, 47% non-White), median CPAP adherence was 4.8 h/night at 1 month. The prior models AUC was 0.51 (95%-CI 0.46-0.55), with no usage differences between predicted poor vs good adherers. A new linear model overfit in training (AUC=0.85) but failed in testing (AUC=0.55). LPA identified a "Low ArTH Driven" cluster with persistently lower adherence at months 2-3 (P<.05) and a "Low ArTH & High loop gain" cluster whose usage stabilized after month 1. ConclusionsThe prior model did not generalize to this diverse clinical cohort. LPA identified a "Low ArTH Driven" endotype with persistently low CPAP adherence, suggesting potential for targeted interventions pending external validation.

BackgroundHyperbaric oxygen therapy (HBOT) after out-of-hospital cardiac arrest (OHCA) remained untested in humans despite promising preclinical evidence. We thus evaluated feasibility, safety, and early biological signals of HBOT across distinct clinical cohorts and exposure subgroups. MethodsThis prospective single centre randomized controlled multi-cohort study enrolled (i) intensive care (ICU) patients as soon as possible after return of spontaneous circulation (ROSC) (maximum 24 hours), (ii) long-term OHCA survivors, and (iii) healthy volunteers. Within each cohort, participants were stratified into HBOT exposure groups (no, one, or five sessions). Assessments included serial laboratory biomarkers (endothelial, inflammatory, oxidative stress, neuronal, myocardial), vascular stiffness, neurocognitive testing, and psychological questionnaires. Changes from baseline were analysed using Wilcoxon and Kruskal-Wallis tests, alongside adjusted general linear models (GLM) with key clinical covariates. ResultsHBOT delivery was feasible and safe, with full follow-up achieved across all three cohorts. In ICU patients, inflammatory (TNF-, CRP), oxidative stress (MPO, TBARS, ROMO-1), and endothelial dysfunction markers (ET-1, ADMA) improved over time, while neuronal injury (NSE) showed partial attenuation; signals were most evident in the 1x and 5x HBOT exposure groups. Among long-term survivors, global and domain-specific cognition, arterial stiffness (pulse wave velocity), and psychological measures improved, with effects primarily observed in HBOT groups. Volunteers exhibited stable cognition but reproducible PWV reductions in HBOT groups, indicating a vascular effect beyond the post-cardiac arrest context. ConclusionIn this feasibility study, HBOT was successfully implemented across ICU patients, survivors, and healthy volunteers, with dose-stratified exposure subgroups. Converging biological signals indicate the potential of HBOT towards an attenuation of systemic inflammation and oxidative stress, recovery of endothelial and vascular function, and mitigation of neuronal and myocardial injury. These early findings provide a rationale for further evaluations of HBOT as a pleiotropic intervention targeting the endothelium-inflammation-injury axis after cardiac arrest.

BackgroundTrials have not directly compared biologics for the treatment of asthma. ObjectiveTo comparative the relative efficacy of biologics in asthma. MethodsWe searched MEDLINE, EMBASE, CENTRAL, and clinicaltrials.gov from inception to May 31, 2022, for randomized trials addressing biologic therapies for asthma. Reviewers worked independently and in duplicate to screen references, extract data, and assess risk of bias. We performed a frequentist network meta-analysis and assessed the certainty of evidence using the GRADE approach. We present dichotomous outcomes as absolute risk differences per 1000 patients and relative risk (RR) with 95% confidence intervals (95% CI) and continuous outcomes as mean difference (MD) and 95% CI. ResultsWe identified 64 trials, including 26,630 patients. For patients with eosinophilic asthma, tezepelumab (329 fewer exacerbations per 1000 [95% CI 272.6 to 366.6 fewer]) and dupilumab (319.6 fewer exacerbations per 1000 [95% CI 272.6 to 357.2 fewer]) reduce exacerbations compared to placebo (high certainty). Tezepelumab (MD 0.24 L [95% CI 0.16 to 0.32]) and dupilumab (0.25 L (95% CI 0.21 to 0.29) improve lung function (FEV1) compared to placebo (high certainty). Both tezepelumab (110.97 fewer hospital admissions per 1000 (95% CI 94.53 to 120.56 fewer) and dupilumab (97.27 fewer hospitalizations [4.11 to 124.67 fewer]) probably reduce hospital admissions compared to placebo (moderate certainty). For patients with low eosinophils, biologics probably do not improve asthma outcomes. For these patients, tezepelumab (MD 0.1 L [95% CI 0 to 0.19]) and dupilumab (MD 0.1 L [95% CI 0 to 0.20)] may improve lung function (low certainty). ConclusionTezepelumab and dupilumab are effective at reducing exacerbations. For patients with low eosinophils, however, clinicians should probably be more judicious in use of biologics, including tezepelumab since they probably do not confer substantial benefit.

BackgroundBoth continuous positive airway pressure (CPAP) and high-flow nasal oxygenation (HFNO) have been recommended for acute respiratory failure in COVID-19. However, uncertainty exists regarding effectiveness and safety. MethodsIn the Recovery-Respiratory Support multi-center, three-arm, open-label, adaptive, randomized controlled trial, adult hospitalized patients with acute respiratory failure due to COVID-19, deemed suitable for treatment escalation, were randomly assigned to receive CPAP, HFNO, or conventional oxygen therapy. Comparisons were made between each intervention and conventional oxygen therapy. The primary outcome was a composite of tracheal intubation or mortality within 30-days. ResultsOver 13-months, 1272 participants were randomized and included in the analysis (380 (29.9%) CPAP; 417 (32.8%) HFNO; 475 (37.3%) conventional oxygen therapy). The need for tracheal intubation or mortality within 30-days was lower in the CPAP group (CPAP 137 of 377 participants (36.3%) vs conventional oxygen therapy 158 of 356 participants (44.4%); unadjusted odds ratio 0.72; 95% CI 0.53 to 0.96, P=0.03). There was no difference between HFNO and conventional oxygen therapy (HFNO 184 of 414 participants (44.4%) vs conventional oxygen therapy 166 of 368 participants (45.1%); unadjusted odds ratio 0.97; 95% CI 0.73 to 1.29, P=0.85). ConclusionsCPAP, compared with conventional oxygen therapy, reduced the composite outcome of intubation or death within 30 days of randomisation in hospitalized adults with acute respiratory failure due to COVID-19. There was no effect observed, compared with conventional oxygen therapy, with the use of HFNO. (Funded by the UK National Institute for Health Research; ISRCTN 16912075).

RationaleAccelerated decline in lung function contributes to the development of chronic respiratory disease. Despite evidence for a genetic component, few genetic associations with lung function decline have been identified. ObjectivesTo evaluate genome-wide associations and putative downstream functionality of genetic variants with lung function decline in diverse general population cohorts. MethodsWe conducted genome-wide association study (GWAS) analyses of decline in the forced expiratory volume in the first second (FEV1), forced vital capacity (FVC), and their ratio (FEV1/FVC) in participants across six cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. Genotypes were imputed to TOPMed (CHARGE cohorts) or Haplotype Reference Consortium (HRC) (UK Biobank) reference panels, and GWAS analyses used generalized estimating equation models with robust standard error. Models were stratified by cohort, ancestry, and sex, and adjusted for important lung function confounders and genotype principal components. Results were combined in cross-ancestry and ancestry-specific meta-analyses. Selected top variants were tested for replication in two independent COPD-enriched cohorts. Measurements and Main ResultsOur discovery analyses included 52,056 self-reported White (N=44,988), Black (N=5,788), Hispanic (N=550), and Chinese American (N=730) participants with a mean of 2.3 spirometry measurements and 8.6 years of follow-up. Functional mapping of GWAS meta-analysis results identified 361 distinct genome-wide significant (p<5E-08) variants in one or more of the FEV1, FVC, and FEV1/FVC decline phenotypes, which overlapped with previously reported genetic signals for several related pulmonary traits. Of these, 8 variants, or 20.5% of the variant set available for replication testing, were nominally associated (p<0.05) with at least one decline phenotype in COPD-enriched cohorts (White [N=4,778] and Black [N=1,118]). Using the GWAS results, gene-level analysis implicated 38 genes, including eight (XIRP2, GRIN2D, SATB1, MARCHF4, SIPA1L2, ANO5, H2BC10, and FAF2) with consistent associations across ancestries or decline phenotypes. Annotation class analysis revealed significant enrichment of several regulatory processes for corticosteroid biosynthesis and metabolism. Drug repurposing analysis identified 43 approved compounds targeting eight of the implicated 38 genes. ConclusionsOur multi-ancestry GWAS meta-analyses identified numerous genetic loci associated with lung function decline. These findings contribute knowledge to the genetic architecture of lung function decline, provide evidence for a role of endogenous corticosteroids in the etiology of lung function decline, and identify drug targets that merit further study for potential repurposing to slow lung function decline and treat lung disease.

PurposeThe goal of this study was to compare noninvasive respiratory support to invasive mechanical ventilation as the initial respiratory support in COVID-19 patients with acute hypoxemic respiratory failure. MethodsAll patients admitted to a large healthcare network with acute hypoxemic respiratory failure associated with COVID-19 and requiring respiratory support were eligible for inclusion. We compared patients treated initially with noninvasive respiratory support (noninvasive positive pressure ventilation by facemask or high flow nasal oxygen) with patients treated initially with invasive mechanical ventilation. The primary outcome was time-to-in-hospital death analyzed using an inverse probability of treatment weighted Cox model adjusted for potential confounders. Secondary outcomes included unweighted and weighted assessments of mortality, lengths-of-stay (intensive care unit and hospital) and time-to-intubation. ResultsOver the study period, 2354 patients met inclusion criteria. Nearly half (47%) received invasive mechanical ventilation first and 53% received initial noninvasive respiratory support. There was an overall 38% in-hospital mortality (37% for invasive mechanical ventilation and 39% for noninvasive respiratory support). Initial noninvasive respiratory support was associated with an increased hazard of death compared to initial invasive mechanical ventilation (HR: 1.61, p < 0.0001, 95% CI: 1.33 - 1.94). However, patients on initial noninvasive respiratory support also experienced an increased hazard of leaving the hospital sooner, but the hazard ratio waned with time (HR: 0.97, p < 0.0001, 95% CI: 0.96 - 0.98). ConclusionThese data show that the COVID-19 patients with acute hypoxemic respiratory failure initially treated with noninvasive respiratory support had an increased hazard of in-hospital death.

BackgroundChronic obstructive pulmonary disease (COPD) is a complex disorder with a high degree of interindividual variability. Gastrointestinal dysfunction is common in COPD patients and has been proposed to influence the clinical progression of the disease. Using the presence of bile acid(s) (BA) in bronchoalveolar lavage fluid (BAL) as a marker of gastric aspiration, we evaluated the relationships between BAs, clinical outcomes, and bacterial lung colonisation. MethodsWe used BAL specimens from a cohort of COPD patients and healthy controls. Bile acids were profiled and quantified in BAL supernatants using mass spectrometry. Microbial DNA was extracted from BAL cell pellets and quantified using qPCR. We profiled the BAL microbiota using an amplicon sequencing approach targeting the V3-V4 region of the 16S rRNA gene. ResultsDetection of BAs in BAL was more likely at earliest clinical stages of COPD and was independent of the degree of airway obstruction. BAL specimens with BAs demonstrated higher bacterial biomass and lower diversity. Likewise, the odds of recovering bacterial cultures from BAL were higher if BAs were also detected. Detection of BAs in BAL was not associated with either inflammatory markers or clinical outcomes. We also observed different bacterial community types in BAL, which were associated with different clinical groups, levels of inflammatory markers, and the degree of airway obstruction. ConclusionDetection of BAs in BAL was associated with different parameters of airway ecology. Further studies are needed to evaluate whether BAs in BAL can be used to stratify patients and for predicting disease progression trajectories.

RationalePatients with idiopathic pulmonary fibrosis have poor health-related quality of life. ObjectiveDetermine whether a modified yoga program in patients with idiopathic pulmonary fibrosis improves quality of life compared to usual care. MethodsRandomized controlled, non-blinded, pilot clinical trial lasting 12 weeks with 2 arms involving 63 adults with idiopathic pulmonary fibrosis. The yoga program-arm consisted of interventions such as seated postures, breathing and meditation exercises designed by authors for idiopathic pulmonary fibrosis patients. The control arm continued with usual standard of care. Analysis of covariance was performed; no multiplicity adjustments were made on account of this being a pilot study. MeasurementsThe primary outcomes were week-12 scores in seven patient-reported instruments, each with sub-domains, totaling 21 outcomes. Results60 of the 63 participants (32 randomized to yoga; 31 receiving standard of care) completed the study (one death in each arm and one withdrawal in yoga group). Analysis of covariance for week-12 scores, adjusting for baseline scores and confounders, revealed significant treatment effects favoring yoga in the L-IPF cough domain (-9.29 points, 95% CI -18.37 to -0.20; p=0.045), in the L-IPF total score (-7.11, 95% CI -13.15 to -1.06; p=0.022), and in the R-scale-PF cough domain (-1.18, 95% CI - 2.27 to -0.10; p=0.034) in the study population. ConclusionPatients with idiopathic pulmonary fibrosis participating in a yoga program demonstrated significant improvement in quality of life assessed by the cough and total scores of L-IPF and the cough score of R-scale-PF than those receiving usual care. SummaryWe examine if the implementation of a modified yoga program improves patient-reported outcomes in patients with idiopathic pulmonary fibrosis. Our study reveals significant post-yoga improvements in the yoga group compared to the control group across different patient-reported outcomes. Such outcomes are meaningful endpoints in patients with idiopathic pulmonary fibrosis and serve as a critical endpoint in related clinical trials.

We present our Stage-1 Registered Report as a full clinical trial article with all methods in past tense and including mock results, table and figures for the primary analysis. To remind the reader that this Stage-1 article is written before data collection, we highlight in color that these mock results are only for illustrative purposes and will be replaced by the actual results in the Stage-2 Registered Report. Background In patients experiencing out-of-hospital cardiac arrest, optimization of oxygen delivery during cardiopulmonary resuscitation is a critical. Although both positive end-expiratory pressure (PEEP) and zero end-expiratory pressure (ZEEP) are employed during CPR, their respective impacts on clinically relevant outcomes is yet to be clearly established. Methods This investigator-initiated, pragmatic, registry-based, multicenter, triple-blind randomized controlled superiority trial evaluates whether applying 8 cm H2O PEEP during cardiopulmonary resuscitation improves outcomes compared with ZEEP in adults with non-traumatic, non-drowning out-of-hospital cardiac arrest. Pre-randomized CPR kits (1:1 PEEP vs. sham) were used by ambulance sites during manual ventilation throughout the resuscitation process. The primary analysis was conducted in the principal stratum of patients who received either a supraglottic airway or endotracheal tube. The primary outcome was neurological status at hospital discharge measured by a utility-weighted score on the modified Rankin Scale. Secondary outcomes included prehospital return of spontaneous circulation, 30-day survival, and 6-month quality of life. The primary safety outcome was clinically significant pneumothorax.

In pharmacoepidemiologic studies of COVID-19, there were concerns about bias from residual confounding. We applied high-dimensional propensity scores (HDPS) to a case study investigating the role of inhaled corticosteroids (ICS) in COVID-19 to adjust for unmeasured confounding. We selected patients with chronic obstructive pulmonary disease on 01 March 2020 from Clinical Practice Research Datalink (CPRD) Aurum, comparing ICS/LABA/(+-LAMA) and LABA/LAMA users. ICS effects on the outcomes COVID-19 hospitalisation and death were assessed through weighted and unweighted Cox proportional hazards models. HDPS were estimated from primary care clinical records, prescriptions and hospitalisations. SNOMED-CT codes and dictionary of medicines and devices codes from CPRD Aurum were mapped to International Classification of Disease 10th revision codes and British National Formulary paragraphs respectively. We estimated propensity scores (PS) combining prespecified and HDPS covariates, selecting the top 100, 250, 500, 750 and 1000 covariates ranked by confounding potential. When excluding triple therapy users, the conventional PS-weighted estimates showed weak evidence of increased risk of COVID-19 hospitalisation among ICS users (HR 1.19 (95% CI 0.92-1.54)). Results varied slightly based on the number of covariates included in HDPS (HR using 100 HDPS covariates 1.01 (95% CI 0.76-1.33), HR using 250 HDPS covariates 1.24 (95% CI 0.83-1.87)). For COVID-19 death, conventional PS-weighted models showed weak evidence of harm of ICS when excluding triple therapy users (HR 1.24 (95% CI 0.87-1.75)). HDPS-weighting moved estimates toward the null, suggesting no effect of ICS (HR using 250 HDPS covariates excluding triple therapy 1.08 (95% CI 0.73- 1.59)). HDPS may have provided better confounding control for COVID-19 deaths and may be able to partially compensate for suboptimal comparison groups. HDPS results can be sensitive to the number of covariates included, highlighting the importance of sensitivity analyses. Key pointsO_LIResidual confounding, including residual confounding by indication, is a major concern in pharmacoepidemiologic studies of COVID-19 outcomes. C_LIO_LIWe apply high-dimensional propensity scores (HDPS) to adjust for residual confounding in a case study of inhaled corticosteroids (ICS) on COVID-19 hospitalisation and death in CPRD Aurum. C_LIO_LIConventional PS-weighted analyses suggested harmful effects of ICS on COVID-19 hospitalisation and, to a lesser extent, deaths. C_LIO_LIHDPS weighted analyses of COVID-19 hospitalisations were sensitive to the number of covariates included, with results moving towards the null for smaller number of covariates and away from the null when including more covariates, while for deaths, estimates moved towards the null consistently. C_LIO_LIHDPS demonstrated promise in addressing confounding even when comparison groups are suboptimal, but its performance depends on the careful selection and ranking of covariates. C_LI Plain Language SummaryA key challenge when researching the effects of medications using electronic health records is accounting for the fact that people who receive different medications often differ in important ways. Such differences, called confounding, is typically accounted for using statistical methods which require researchers to pre-specify all important confounders. A newer method, called high-dimensional propensity scores (HDPS), uses a data-driven approach to select what confounders to account for instead. These methods have not yet been applied to studies of inhaled corticosteroids and COVID-19 outcomes, an area where studies have found conflicting findings. We used electronic health records from the UK to compare the risk of COVID-19 hospitalisation and death among patients with chronic obstructive pulmonary disease taking two different treatments (ICS/LABA and LABA/LAMA) using both conventional and HDPS methods. Our findings showed that HDPS can reduce important differences between patients (confounding), but that the results can be sensitive to the number of covariates included. This demonstrates the value of HDPS and the need for researchers to run their analysis using several different assumptions.

ABSTRACT Background: Corticosteroids reduce mortality in severe COVID-19 requiring oxygen or invasive mechanical ventilation, yet emerging data suggest that SARS-CoV-2-associated acute lung injury is biologically heterogeneous and that treatment response may vary across molecularly defined disease states. Lung-derived molecular endotypes of severe COVID-19-associated acute lung injury have been described, but direct molecular profiling is not routinely available at the bedside. We evaluated whether a clinical predictor of previously defined lung molecular endotype identifies heterogeneity in corticosteroid treatment effect among mechanically ventilated patients with COVID-19. Methods: We utilized a single-center cohort of 5,000 patients with COVID-19 treated at the University of North Carolina Hospital between January 1, 2020, and December 31, 2022, to emulate a target trial assessing the effect of corticosteroid receipt on mortality, length of stay, and incident organ support. Confounding was addressed through inverse probability of treatment weighting (IPTW). Outcomes for severely ill patients requiring mechanical ventilation were compared to the RECOVERY trial results, with subsequent moderation analysis and stratified analysis by clinically predicted lung molecular endotype and vaccination status. The primary outcome was 28-day mortality. Secondary Outcomes were time to discharge alive and progression to additional organ support. Results: This emulated target trial showed a directionally favorable but non-statistically significant association between corticosteroid treatment and reduced 28-day mortality in patients requiring mechanical ventilation for SARS-CoV-2 infection. A clinical predictor of lung molecular endotype moderated the effect of corticosteroids on 28-day mortality (p-value for interaction 0.038) and identified distinct predicted endotype-specific treatment effect. Corticosteroid treatment was associated with lower 28-day mortality in the predicted Hyper-Inflammatory endotype (OR 0.62, 95% CI 0.39, 0.99) but not in the predicted Metabolic Dysregulation endotype (OR 1.15, 95% CI 0.82, 1.61). We did not detect significant effect modification by vaccination status (p-value for interaction 0.65), although inference was limited by the small, vaccinated subgroup (28-mortality OR 0.78, 95% CI 0.37, 1.65 in vaccinated vs 0.94, 95% CI 0.70, 1.26 in unvaccinated). Conclusions: In this target trial emulation of mechanically ventilated patients with severe COVID-19, corticosteroid treatment showed a directionally favorable but non-statistically significant association with reduced 28-day mortality in the overall cohort. However, a clinical predictor of lung molecular endotype identified significant heterogeneity in treatment effect, with benefit concentrated in the predicted Hyper-Inflammatory endotype and no apparent benefit in the predicted Metabolic Dysregulation endotype. These findings support prospective validation of clinically deployable endotype-guided corticosteroid treatment strategies in acute lung injury and ARDS.