Expert review of respiratory medicine最新文献

Background: Underrepresentation of minority groups in clinical trials may hinder the potential benefits of pulmonary rehabilitation (PR) programs for individuals with chronic obstructive pulmonary disease (COPD). The aim of this work was to determine whether participants in PR randomized control trials (RCTs) conducted in the U.S.A., Canada, the UK, and Australia are representative of ethnicity, sex, gender, and sociodemographic characteristics.

Research design: A systematic search was performed for relevant literature from inception to December 2022. Titles and abstracts were screened before undergoing a full article review. Relevant data on reporting of age, sex, gender, ethnicity, and sociodemographic characteristics of participants was extracted.

Results: Thirty-six RCTs met the inclusion criteria. Only 6% of publications reported on ethnicity, with ≥90% of participants reported as 'White.' All 36 papers reported on age, with the mean between 60 and 69 years old. Thirty-five studies reported on sex (97%), with the majority (67%) reporting more male than female participants. There was no mention of different genders in any paper. Other sociodemographic factors were reported in 7 (19%) papers.

Conclusions: Inclusivity and representation in clinical trials are essential to ensure that research findings are generalizable. Clinical trialists need to consider the demographics of today's society during recruitment.

Introduction: Hypercapnia is developed in patients with acute and/or chronic respiratory conditions. Clinical data concerning hypercapnia and respiratory infections interaction is limited.

Areas covered: Currently, the relationship between hypercapnia and respiratory infections remains unclear. In this review, we summarize studies on the effects of hypercapnia on models of pulmonary infections to clarify the role of elevated CO2 in these pulmonary pathologies. Hypercapnia affects different cell types in the alveoli, leading to changes in the immune response. In vitro studies show that hypercapnia downregulates the NF-κβ pathway, reduces inflammation and impairs epithelial wound healing. While in vivo models show a dual role between short- and long-term effects of hypercapnia on lung infection. However, it is still controversial whether the effects observed under hypercapnia are pH dependent or not.

Expert opinion: The role of hypercapnia is still a controversial debate. Hypercapnia could play a beneficial role in mechanically ventilated models, by lowering the inflammation produced by the stretch condition. But it could be detrimental in infectious scenarios, causing phagocyte dysfunction and lack of infection control. Further data concerning hypercapnia on respiratory infections is needed to elucidate this interaction.

Introduction: Home noninvasive ventilation (HNIV) has expanded globally, with a greater evidence base for its use. HNIV improves multiple patient related outcomes in patients with chronic hypercapnic respiratory failure. Obesity hypoventilation syndrome (OHS) is rapidly taking over as the primary indication for HNIV and COPD patients who overlap with obstructive sleep apnea hypoventilation syndromes (OSAHS) and are increasingly recognized but add to the complexity of HNIV prescribing. Optimal settings vary for differing diseases, with higher inspiratory pressures often required in those with OHS and COPD, yet which settings translate into greatest patient benefit remains unknown.

Areas covered: We cover the evidence base underpinning the common indications for HNIV in COPD, OHS, neuromuscular disease (NMD), and chest wall disease (CWD) and highlight common HNIV modes used.

Expert opinion: Active screening for nocturnal hypoventilation in OHS and COPD may be important to guide earlier ventilation. Further research on which HNIV modalities best improve patient related outcomes and the right time for initiation in different patient phenotypes is rapidly needed. Worldwide, clinical research trials should aim to bridge the gap by reporting on patient-related outcomes and cost effectiveness in real-world populations to best understand the true benefit of HNIV amongst heterogenous patient populations.

Introduction: Immunotherapy (IO) has established a new milestone in lung cancer treatment. Several registrational studies have approved immune checkpoint inhibitors (ICIs) in different settings, including the metastatic nonsmall cell lung cancer (NSCLC). As well known, responders are just a certain proportion of patients; therefore, their selection by using predictive factors has stood out as a crucial issue to address in tailoring a patient-centered care.

Areas covered: In our review we propose a detailed yet handy cross section on ICIs as first-line treatment in metastatic NSCLC, regarding indications, histological, clinical, and blood-based biomarkers, other than their mechanisms of resistance and new immunological actionable targets. We performed a literature search through PubMed entering keywords complying with crucial features of immunotherapy.

Expert opinion: IO represents the backbone of lung cancer treatment. Trials are currently testing novel immune blockade agents assessing combinatorial approaches with standard ICIs, or antibody drug conjugates (ADC), harboring immunological targets. Perfecting patients' selection is an ongoing challenge and a more and more urgent need in order to best predict responders who will consistently benefit from it.

Introduction: Extracorporeal membrane oxygenation (ECMO) facilitated resuscitation was first described in the 1960s, but only recently garnered increased attention with large observational studies and randomized trials evaluating its use.

Areas covered: In this comprehensive review of extracorporeal cardiopulmonary resuscitation (ECPR), we report the history of resuscitative ECMO, terminology, circuit configuration and cannulation considerations, complications, selection criteria, implementation and management, and important considerations for the provider. We review the relevant guidelines, different approaches to cannulation, postresuscitation management, and expected outcomes, including neurologic, cardiac, and hospital survival. Finally, we advocate for the participation in national/international Registries in order to facilitate continuous quality improvement and support scientific discovery in this evolving area.

Expert opinion: ECPR is the most disruptive technology in cardiac arrest resuscitation since high-quality CPR itself. ECPR has demonstrated that it can provide up to 30% increased odds of survival for refractory cardiac arrest, in tightly restricted systems and for select patients. It is also clear, though, from recent trials that ECPR will not confer this high survival when implemented in less tightly protocoled settings and within lower volume environments. Over the next 10 years, ECPR research will explore the optimal initiation thresholds, best practices for implementation, and postresuscitation care.

Objectives: Single-inhaler triple therapies (SITTs) have never been directly compared in randomized controlled trials (RCTs) in chronic obstructive pulmonary disease (COPD). Cochrane recommends the Bayesian approach for indirect comparisons but a frequentist network meta-analysis (NMA) reported superiority of fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI) over other SITT. We assessed the most appropriate inference method for NMA characterized by between-study heterogeneity on SITT in COPD.

Methods: Bayesian and frequentist NMA were performed on RCTs investigating the effect of SITT on exacerbations and trough forced expiratory volume in the 1^st second (FEV₁) in COPD.

Results: The included RCTs (ETHOS, FULFIL, IMPACT, KRONOS 200812) reported significant between-study heterogeneity (I² > 99%, p < 0.001). The Bayesian random-effect NMA provided unbiased evidence that FF/UMEC/VI was not superior to other SITT on exacerbations and trough FEV₁. The frequentist fixed-effect NMA indicated that FF/UMEC/VI was significantly (p < 0.05) more effective than other SITT, although results were affected by dispersion, asymmetry, and significant risk of bias. Frequentist random-effect NMA provided effect estimates rather similar but not equal to those of Bayesian approach.

Conclusion: Indirect comparison should be performed via Bayesian approach instead of frequentist inference with a fixed-effect model. Claiming the superiority of a specific medication over other therapies should be confirmed by findings originating from well-designed RCTs.

Introduction: Asthma and chronic obstructive pulmonary disease (COPD) are leading causes of morbidity and mortality worldwide. Despite all available diagnostics and treatments, these conditions pose a significant individual, economic and social burden. Artificial intelligence (AI) promises to support clinical decision-making processes by optimizing diagnosis and treatment strategies of these heterogeneous and complex chronic respiratory diseases. Its capabilities extend to predicting exacerbation risk, disease progression and mortality, providing healthcare professionals with valuable insights for more effective care. Nevertheless, the knowledge gap between respiratory clinicians and data scientists remains a major constraint for wide application of AI and may hinder future progress. This narrative review aims to bridge this gap and encourage AI deployment by explaining its methodology and added value in asthma and COPD diagnosis and treatment.

Areas covered: This review offers an overview of the fundamental concepts of AI and machine learning, outlines the key steps in building a model, provides examples of their applicability in asthma and COPD care, and discusses barriers to their implementation.

Expert opinion: Machine learning can advance our understanding of asthma and COPD, enabling personalized therapy and better outcomes. Further research and validation are needed to ensure the development of clinically meaningful and generalizable models.

Background: The disorder of circadian rhythm could be a key factor mediating fibrotic lung disease Therefore, our study aims to determine the diagnostic value of circadian rhythm-related genes (CRRGs) in IPF.

Methods: We retrieved the data on CRRGs from previous studies and the GSE150910 dataset. The participants from the GSE150910 dataset were divided into training and internal validation sets. Next, we used several various bioinformatics methods and machine learning algorithms to screen genes. Next, we identified SEMA5A, COL7A1, and TUBB3, which were included in the random forest (RF) diagnostic model. Finally, external validation was conducted on data retrieved from the GSE184316 datasets.

Results: The results revealed that the RF diagnostic model could diagnose patients with IPF in the internal validation set with the area under the ROC curve (AUC) value of 0.905 and in the external validation with the AUC value of 0.767. Furthermore, real-time quantitative PCR and western blotting results revealed a significant decrease in SEMA5A (p < 0.05) expression level and an increase in COL7A1 and TUBB3 expression levels in TGF-β1-treated normal human lung fibroblasts.

Conclusion: We constructed an RF diagnostic model based on SEMA5A, COL7A1, and TUBB3 expression in lung tissue for diagnosing patients with IPF.