ERS International Congress 2023: highlights from the Allied Respiratory Professionals Assembly.

This article summarises some of the outstanding sessions that were (co)organised by the Allied Respiratory Professionals Assembly during the 2023 European Respiratory Society International Congress. Two sessions from each Assembly group are outlined, covering the following topics: Group 9.01 focuses on respiratory physiology techniques, specifically on predicted values and reference equations, device development and novel applications of cardiopulmonary exercise tests; Group 9.02 presents an overview of the talks given at the mini-symposium on exercise training, physical activity and self-management at home and outlines some of the best abstracts in respiratory physiotherapy; Group 9.03 highlights the nursing role in global respiratory health and presents nursing interventions and outcomes; and Group 9.04 provides an overview of the best abstracts and recent advances in behavioural science and health psychology. This Highlights article provides valuable insight into the latest scientific data and emerging areas affecting the clinical practice of Allied Respiratory Professionals.

Multidisciplinary Development and Initial Validation of a Clinical Knowledge Base on Chronic Respiratory Diseases for mHealth Decision Support Systems.

Most mobile health (mHealth) decision support systems currently available for chronic obstructive respiratory diseases (CORDs) are not supported by clinical evidence or lack clinical validation. The development of the knowledge base that will feed the clinical decision support system is a crucial step that involves the collection and systematization of clinical knowledge from relevant scientific sources and its representation in a human-understandable and computer-interpretable way. This work describes the development and initial validation of a clinical knowledge base that can be integrated into mHealth decision support systems developed for patients with CORDs. A multidisciplinary team of health care professionals with clinical experience in respiratory diseases, together with data science and IT professionals, defined a new framework that can be used in other evidence-based systems. The knowledge base development began with a thorough review of the relevant scientific sources (eg, disease guidelines) to identify the recommendations to be implemented in the decision support system based on a consensus process. Recommendations were selected according to predefined inclusion criteria: (1) applicable to individuals with CORDs or to prevent CORDs, (2) directed toward patient self-management, (3) targeting adults, and (4) within the scope of the knowledge domains and subdomains defined. Then, the selected recommendations were prioritized according to (1) a harmonized level of evidence (reconciled from different sources); (2) the scope of the source document (international was preferred); (3) the entity that issued the source document; (4) the operability of the recommendation; and (5) health care professionals' perceptions of the relevance, potential impact, and reach of the recommendation. A total of 358 recommendations were selected. Next, the variables required to trigger those recommendations were defined (n=116) and operationalized into logical rules using Boolean logical operators (n=405). Finally, the knowledge base was implemented in an intelligent individualized coaching component and pretested with an asthma use case. Initial validation of the knowledge base was conducted internally using data from a population-based observational study of individuals with or without asthma or rhinitis. External validation of the appropriateness of the recommendations with the highest priority level was conducted independently by 4 physicians. In addition, a strategy for knowledge base updates, including an easy-to-use rules editor, was defined. Using this process, based on consensus and iterative improvement, we developed and conducted preliminary validation of a clinical knowledge base for CORDs that translates disease guidelines into personalized patient recommendations. The knowledge base can be used as part of mHealth decision support systems. This process could be replicated in other clinical areas.

Relationship between longitudinal changes in type-2 inflammation, immunoglobulin E sensitization, and clinical outcomes in young asthmatics.

BACKGROUND: Asthma is a heterogeneous condition where biomarkers may be of considerable advantage in diagnosis and therapy monitoring. However, the changes in asthma biomarkers and immunoglobulin E (IgE) over the course of life has not been extensively investigated. OBJECTIVE: To study longitudinal changes in type-2 inflammatory biomarkers, IgE, and clinical outcomes, and the association between these changes, in young asthmatics. METHODS: Asthmatics (age 10-35 years, n = 253) were examined at baseline and at a follow-up visit, 43 [23-65] (median [range]) months later. Subjects were analyzed using the multi-allergen tests Phadiatop and fx5 (ImmunoCAP) and grouped based on the baseline allergen-specific IgE antibody (sIgE) concentration: <0.10, 0.10-0.34, and ≥0.35 kUA /L. The relationship between changes (Δ values) in type-2 biomarkers (individualized fraction of exhaled nitric oxide [FeNO%], blood eosinophil [B-Eos] count, total IgE [tIgE] and sIgE, lung function [% predicted forced expiratory volume in 1 second (FEV1 ) and FEV1 /forced vital capacity (FVC)], and Asthma Control Test [ACT]) score were determined. RESULTS: At follow up, FEV1 and FEV1 /FVC had decreased (93.6% vs. 95.8%, and 93.4% vs. 94.7% of predicted, respectively [p < 0.001 both]), whereas ACT score had increased (21.6 vs. 20.6, p = 0.001). A significant decline in lung function was seen in subjects with sIgE ≥ 0.10 kUA/L, but not in those with undetectable sIgE (<0.10 kUA /L). Furthermore, tIgE and sIgE declined over time (p < 0.001 all) whereas FeNO% and B-Eos count were not significantly changed. In univariate analysis, significant negative correlations between ∆B-Eos count and ∆FeNO%, on one hand, and changes in lung function, on the other hand, were seen, and multivariate analysis showed an independent relationship between ΔFeNO%, and ΔFEV1 (p < 0.05) and ΔFEV1 /FVC% (p < 0.01). Sex-specific analysis showed that the independent association between ΔFeNO%, and ΔFEV1 remained only in females (p = 0.005), and there was a significant interaction with sex (p = 0.02). CONCLUSION: In young asthmatics, IgE levels declined over 43 months, whereas FeNO and B-Eos remained unchanged. In spite of improved asthma control, an accelerated lung function decline was seen in patients with detectable sIgE at baseline, and the decline correlated with changes in type-2 biomarkers. Particularly, the increase in individualized FeNO associated independently with decline in FEV1 in females.

The influence of individual characteristics and non-respiratory diseases on blood eosinophil count.

BACKGROUND: Blood eosinophil (B-Eos) count is an emerging biomarker in the management of respiratory disease but determinants of B-Eos count besides respiratory disease are poorly described. Therefore, we aimed to evaluate the influence of non-respiratory diseases on B-Eos count, in comparison to the effect on two other biomarkers: fraction of exhaled nitric oxide (FeNO) and C-reactive protein (CRP), and to identify individual characteristics associated with B-Eos count in healthy controls. METHODS: Children/adolescents (<18 years) and adults with complete B-Eos data from the US National Health and Nutritional Examination Surveys 2005-2016 were included, and they were divided into having respiratory diseases (n = 3333 and n = 7,894, respectively) or not having respiratory disease (n = 8944 and n = 15,010, respectively). After excluding any respiratory disease, the association between B-Eos count, FeNO or CRP, and non-respiratory diseases was analyzed in multivariate models and multicollinearity was tested. After excluding also non-respiratory diseases independently associated with B-Eos count (giving healthy controls; 8944 children/adolescents and 5667 adults), the independent association between individual characteristics and B-Eos count was analyzed. RESULTS: In adults, metabolic syndrome, heart disease or stroke was independently associated with higher B-Eos count (12%, 13%, and 15%, respectively), whereas no associations were found with FeNO or CRP. In healthy controls, male sex or being obese was associated with higher B-Eos counts, both in children/adolescents (15% and 3% higher, respectively) and adults (14% and 19% higher, respectively) (p < 0.01 all). A significant influence of race/ethnicity was also noted, and current smokers had 17% higher B-Eos count than never smokers (p < 0.001). CONCLUSIONS: Non-respiratory diseases influence B-Eos count but not FeNO or CRP. Male sex, obesity, certain races/ethnicities, and current smoking are individual characteristics or exposures that are associated with higher B-Eos counts. All these factors should be considered when using B-Eos count in the management of respiratory disease.

A Systematic Review of Asthma Phenotypes Derived by Data-Driven Methods.

Classification of asthma phenotypes has a potentially relevant impact on the clinical management of the disease. Methods for statistical classification without a priori assumptions (data-driven approaches) may contribute to developing a better comprehension of trait heterogeneity in disease phenotyping. This study aimed to summarize and characterize asthma phenotypes derived by data-driven methods. We performed a systematic review using three scientific databases, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. We included studies reporting adult asthma phenotypes derived by data-driven methods using easily accessible variables in clinical practice. Two independent reviewers assessed studies. The methodological quality of included primary studies was assessed using the ROBINS-I tool. We retrieved 7446 results and included 68 studies of which 65% (n = 44) used data from specialized centers and 53% (n = 36) evaluated the consistency of phenotypes. The most frequent data-driven method was hierarchical cluster analysis (n = 19). Three major asthma-related domains of easily measurable clinical variables used for phenotyping were identified: personal (n = 49), functional (n = 48) and clinical (n = 47). The identified asthma phenotypes varied according to the sample's characteristics, variables included in the model, and data availability. Overall, the most frequent phenotypes were related to atopy, gender, and severe disease. This review shows a large variability of asthma phenotypes derived from data-driven methods. Further research should include more population-based samples and assess longitudinal consistency of data-driven phenotypes.

InspirerMundi-Remote Monitoring of Inhaled Medication Adherence through Objective Verification Based on Combined Image Processing Techniques.

BACKGROUND: The adherence to inhaled controller medications is of critical importance for achieving good clinical results in patients with chronic respiratory diseases. Self-management strategies can result in improved health outcomes and reduce unscheduled care and improve disease control. However, adherence assessment suffers from difficulties on attaining a high grade of trustworthiness given that patient self-reports of high-adherence rates are known to be unreliable. OBJECTIVE: Aiming to increase patient adherence to medication and allow for remote monitoring by health professionals, a mobile gamified application was developed where a therapeutic plan provides insight for creating a patient-oriented self-management system. To allow a reliable adherence measurement, the application includes a novel approach for objective verification of inhaler usage based on real-time video capture of the inhaler's dosage counters. METHODS: This approach uses template matching image processing techniques, an off-the-shelf machine learning framework, and was developed to be reusable within other applications. The proposed approach was validated by 24 participants with a set of 12 inhalers models. RESULTS: Performed tests resulted in the correct value identification for the dosage counter in 79% of the registration events with all inhalers and over 90% for the three most widely used inhalers in Portugal. These results show the potential of exploring mobile-embedded capabilities for acquiring additional evidence regarding inhaler adherence. CONCLUSION: This system helps to bridge the gap between the patient and the health professional. By empowering the first with a tool for disease self-management and medication adherence and providing the later with additional relevant data, it paves the way to a better-informed disease management decision.

Inflammatory patterns in fixed airflow obstruction are dependent on the presence of asthma.

RATIONALE: Fixed airflow obstruction (FAO) can complicate asthma. Inflammation is a proposed underlying mechanism. OBJECTIVE: Our aim in this cross-sectional investigation was to evaluate the blood leucocyte pattern and level of exhaled nitric oxide in asthmatics and non-asthmatics with or without FAO. METHODS: A total of 11,579 individuals aged ≥20 years from the US National Health and Nutrition Examination Survey were included. They were grouped as: controls without asthma and FAO (n = 9,935), asthmatics without FAO (n = 674), asthmatics with FAO (n = 180) and non-asthmatics with FAO (n = 790). FAO was defined as post-bronchodilator FEV1/FVC < lower limit of normal. Exhaled nitric oxide ≥ 25ppb, blood eosinophil levels ≥300 cells/µL, and blood neutrophil levels ≥5100 cells/µL were defined as elevated. Stratified analyses for smoking and smoking history were performed. RESULTS: Elevated blood eosinophil levels were more common in all groups compared to the controls, with the highest prevalence in the group with asthma and fixed airflow obstruction (p<0.01). In a multiple logistic regression model adjusted for potential confounders including smoking, the asthma groups had significantly higher odds ratios for elevated B-Eos levels compared to the control group (odds ratio 1.4, (confidence interval: 1.1-1.7) for the asthma group without fixed airflow obstruction and 2.5 (1.4-4.2) for the asthma group with fixed airflow obstruction). The group with fixed airflow obstruction without asthma had higher odds ratio for elevated blood neutrophil levels compared to the controls: 1.4 (1.1-1.8). Smoking and a history of smoking were associated to elevated B-Neu levels. CONCLUSION: Fixed airflow obstruction in asthma was associated with elevated blood eosinophil levels, whereas fixed airflow obstruction without asthma was associated with elevated blood neutrophil levels.

Predictors of Acute Kidney Injury Associated with Cardiopulmonary Bypass.

OBJECTIVES: To study the incidence of acute kidney injury (AKI) in the postoperative period of cardiac surgery in patients without preoperative renal insufficiency who underwent cardiac surgery with cardiopulmonary bypass (CPB), and to explore the association between the incidence of AKI and predictors related to CPB. METHODS: Observational, cross-sectional study. Participants were divided in two groups, those who developed AKI in the postoperative period and those who did not develop AKI. Kidney Disease: Improving Global Outcomes - Clinical Practice Guideline for Acute Kidney Injury (KDIGO) classification was used to characterize AKI. The analysis included preoperative variables (anthropometric data, cardiovascular risk factors and blood parameters), as well as the type of surgery, intraoperative variables related to CPB, and postoperative creatinine variation. Association between variables was studied with binary logistic regression. RESULTS: We have included 329 patients, of which 62 (19%), developed AKI. There were statistically significant differences between the groups in age (p<0.001; OR (95%)-1.075 (1.037-1.114)), duration of CPB (p=0.011; 1.008 (1.002-1.014)), urine output during CPB (p=0.038; 0.998 (0.996-0.999)), mannitol and furosemide administration during CPB, (respectively, p=0.032; 2.293 (1.075-4.890) and p=0.013; 2.535 (1.214-5.296)). CONCLUSIONS: A significant number of patients developed AKI in the postoperative period of cardiac surgery and this incidence was influenced by factors related to CPB, namely: age, duration of CPB, urine output during CPB, mannitol and furosemide administration during CPB.

Comparison of hypothesis- and data-driven asthma phenotypes in NHANES 2007-2012: the importance of comprehensive data availability.

BACKGROUND: Half of the adults with current asthma among the US National Health and Nutrition Examination Survey (NHANES) participants could be classified in more than one hypothesis-driven phenotype. A data-driven approach applied to the same subjects may allow a more useful classification compared to the hypothesis-driven one. AIM: To compare previously defined hypothesis-driven with newly derived data-driven asthma phenotypes, identified by latent class analysis (LCA), in adults with current asthma from NHANES 2007-2012. METHODS: Adults (≥ 18 years) with current asthma from the NHANES were included (n = 1059). LCA included variables commonly used to subdivide asthma. LCA models were derived independently according to age groups: < 40 and ≥ 40 years old. RESULTS: Two data-driven phenotypes were identified among adults with current asthma, for both age groups. The proportions of the hypothesis-driven phenotypes were similar among the two data-driven phenotypes (p > 0.05). Class A < 40 years (n = 285; 75%) and Class A ≥ 40 years (n = 462; 73%), respectively, were characterized by a predominance of highly symptomatic asthma subjects with poor lung function, compared to Class B < 40 years (n = 94; 25%) and Class B ≥ 40 years (n = 170; 27%). Inflammatory biomarkers, smoking status, presence of obesity and hay fever did not markedly differ between the phenotypes. CONCLUSION: Both data- and hypothesis-driven approaches using clinical and physiological variables commonly used to characterize asthma are suboptimal to identify asthma phenotypes among adults from the general population. Further studies based on more comprehensive disease features are required to identify asthma phenotypes in population-based studies.

Adult Asthma Scores-Development and Validation of Multivariable Scores to Identify Asthma in Surveys.

BACKGROUND: One of the questions in epidemiology is the identification of adult asthma in studies. OBJECTIVE: To develop and validate multivariable scores for adult asthma identification in epidemiological studies and to explore cutoffs to rule in/rule out asthma, compared with asthma diagnosed by a physician after clinical examination and diagnostic tests, blinded to the self-administered questions. METHODS: We analyzed data (n = 711 adults) from a nationwide population-based study. The predictors were self-administered questions identified in a literature review (the Adult Asthma Epidemiological Score [A2 score]) and from the Global Allergy and Asthma Network of Excellence (GA2LEN) questionnaire (the GA2LEN Asthma Epidemiological Score [GA2LEN score]). Scores were developed using exploratory factor analysis. Internal consistency, discriminative power, and diagnostic accuracy were assessed. RESULTS: The A2 score comprises 8 questions (including "Did a physician confirm you had asthma?") and the GA2LEN score comprises 6 questions (including "Have you ever had asthma?"). Both had high Cronbach α (0.89 and 0.85, respectively, for the A2 score and the GA2LEN score) and good area under the receiver-operating characteristic curve (90.4% and 89.0%). The scoring is the sum of positive answers. Asthma is present (rule in) for scores of 4 or more (specificity, 99.2%; PPV, 93.3% and 91.7%; accuracy, 89.4% and 87.4%, respectively, for the A2 score and the GA2LEN score). Asthma is excluded (rule out) for A2 scores of 0 to 1 and a GA2LEN score of 0 (sensitivity, 93.1%; NPV, 98.2% and 98.0%; accuracy 89.4% and 82.8%, respectively, for the A2 score and the GA2LEN score). CONCLUSIONS: These practical scores can be used to rule in/rule out asthma in epidemiological studies and clinical screening/triage settings. They may help physicians in primary care or other specialties to screen patients with asthma using a simple score with a high level of discrimination and to identify the best candidates to be referred for a diagnostic workup. Moreover, their use may contribute to reducing the inconsistencies of operational definitions of asthma across studies and surveys.

Disentangling the heterogeneity of allergic respiratory diseases by latent class analysis reveals novel phenotypes.

BACKGROUND: Refined phenotyping of allergic diseases may unravel novel phenotypes. Conjunctivitis as an independent disorder has never been approached. AIM: To identify distinct classes of allergic respiratory diseases using latent class analysis (LCA) and distinguish each class using classification and regression tree (CART) analysis. METHODS: Seven hundred and twenty-eight adults from the Portuguese general population study ICAR had a structured medical interview combined with blood collection, skin prick tests, spirometry with bronchodilation, and exhaled nitric oxide. LCA was applied to 19 variables. The CART algorithm selected the most likely variables distinguishing LCA-classes. RESULTS: A six-class model was obtained. Class 1 (25%): nonallergic participants without bronchial or ocular symptoms. Classes 2 (22%) and 3 (11%): nasal and ocular (low levels) symptoms without nasal impairment, monosensitized (Class 2) or polysensitized (Class 3). Class 4 (13%): polysensitized participants with high levels of nasal and ocular symptoms, and nasal impairment. Classes 5 (16%) and 6 (14%): high level of nasal, bronchial and ocular symptoms with nasal impairment (non-allergic or polysensitized, respectively). Participants in classes 5 and 6 had more bronchial exacerbations and unscheduled medical visits (P < 0.001). Ocular symptoms were significantly higher in classes with nasal impairment, compared to those without impairment (P < 0.001) or no nasal symptom (P < 0.001). CART highlighted ocular symptoms as the most relevant variable in distinguishing LCA-classes. CONCLUSION: Novel severe phenotypes of participants with co-occurrence of ocular, nasal and bronchial symptoms, and exacerbation-prone were identified. The tree algorithm showed the importance of the ocular symptoms in the expression of allergic diseases phenotypes.

Systemic inflammatory markers in relation to lung function in NHANES. 2007-2010.

BACKGROUND: Low-grade systemic inflammation, mainly assessed by C-reactive protein (CRP), has been associated with impaired lung function. Few studies have studied if CRP, blood eosinophils, and blood neutrophils offer additive information in relation to lung function. OBJECTIVES: To analyse associations between lung function and CRP, blood eosinophils, and blood neutrophils, with special regard to additive information of combining the inflammatory markers. METHODS: Cross-sectional study on 7753 participants, 20-80 years of age, in the National Health and Nutrition Examination Survey. Gender-based tertiles for CRP, blood eosinophils, and blood neutrophils were analysed in relation to the following lung function parameters: forced expiratory volume in 1 s (FEV1% predicted), forced vital capacity (FVC % predicted), and FEV1/FVC ratio. RESULTS: CRP, blood eosinophils, and blood neutrophils levels were inversely related to FEV1 and FVC. Only blood eosinophils and blood neutrophils were inversely related to FEV1/FVC ratio. Further, lower lung function was found with increased number of elevated inflammatory markers in the highest tertile (one, two or three vs. non elevated) for FEV1 (ß-coeff., -2.20, -4.43, and -6.43, p < 0.001) and FVC (ß-coeff., -1.70, -3.15 and -5.33, p < 0.001), respectively. CONCLUSIONS & CLINICAL RELEVANCE: CRP, blood eosinophils, and blood neutrophils offer independent and additive information in relation to lower FEV1 and FVC in the general population. This indicates that a combination of biomarkers yields more information than the biomarkers assessed individually.

Exhaled NO reference limits in a large population-based sample using the Lambda-Mu-Sigma method.

Absolute values are used in the interpretation of the fraction of exhaled nitric oxide (FeNO), but it has been suggested that equations to calculate reference values may be a practical and clinically useful approach. We hypothesize that the application of the Lambda-Mu-Sigma (LMS) method may improve FeNO reference equations and their interpretation. Our aims were to develop FeNO reference equations with the LMS method and to describe the difference between this method and the absolute fixed cut-offs of the current recommendations. We utilized the United States National Health and Nutrition Examination Surveys 2007-2012 and included healthy individuals with no respiratory diseases and blood eosinophils <300/mm3 ( n = 8,340). Natural log-transformed FeNO was modeled using the LMS method, imbedded in the generalized additive models for location, scale, and shape models. A set of FeNO reference equations was developed. The explanatory variables were sex, age, height, smoking habits, and race/ethnicity. A significant proportion of individuals with normal FeNO given by the equations were classified as having intermediate levels by the current recommendations. Further lower predicted FeNO compared with previous linear models was seen. In conclusion, we suggest a novel model for the prediction of reference FeNO values that can contribute to the interpretation of FeNO in clinical practice. This approach should be further validated in large samples with an objective measurement of atopy and a medical diagnosis of asthma and rhinitis. NEW & NOTEWORTHY Novel reference equations and fraction of exhaled nitric oxide (FeNO)-predicted values to improve interpretation of FeNO in clinical practice are presented. These may increase the accuracy of ruling out airway inflammation in patients with asthma or suspected asthma.

Does lung microbiome play a causal or casual role in asthma?

Asthma is the most common chronic disease in childhood. The pathogenesis of asthma is multifactorial and is thought to include environmental factors interacting with genetics during pregnancy and in the first years of life. In the last decades, a possible role of gut microbiota in allergic disease pathogenesis has been demonstrated. Next generation sequencing techniques have allowed the identification of a distinct microbiome in the healthy lungs. The lung microbiome is characterized by the prevalence of bacteria belonging to the phylum Bacteroidetes (mostly Prevotella and Veilonella spp) in healthy subjects and to the phylum Proteobacteria in asthmatics (mostly Haemophilus, Moraxella, and Neisseria spp). In asthma, as well as in other diseases, the lung microbiome composition changes due to a disruption of the delicate balance between immigration and elimination of bacteria. The lung microbiome can interact with the immune system, thus influencing inflammation. Early infections with viruses, such as respiratory syncytial virus, may alter lung microbiome composition favoring the emergence of Proteobacteria, a phylum which is also linked to severity of asthma and bronchial hyperreactivity. Lastly, antibiotics may alter the gut and lung microbiota and potentially disturb the relationship between microbiota and host. Therefore, antibiotics should be prescribed with increasing awareness of their potential harmful effect on the microbiota in young children with and without asthma. The potential effects of probiotics and prebiotics on lung microbiome are unknown.

Having concomitant asthma phenotypes is common and independently relates to poor lung function in NHANES 2007-2012.

BACKGROUND: Evidence for distinct asthma phenotypes and their overlap is becoming increasingly relevant to identify personalized and targeted therapeutic strategies. In this study, we aimed to describe the overlap of five commonly reported asthma phenotypes in US adults with current asthma and assess its association with asthma outcomes. METHODS: Data from the National Health and Nutrition Examination Surveys (NHANES) 2007-2012 were used (n = 30,442). Adults with current asthma were selected. Asthma phenotypes were: B-Eos-high [if blood eosinophils (B-Eos) ≥ 300/mm3]; FeNO-high (FeNO ≥ 35 ppb); B-Eos&FeNO-low (B-Eos < 150/mm3 and FeNO < 20 ppb); asthma with obesity (AwObesity) (BMI ≥ 30 kg/m2); and asthma with concurrent COPD. Data were weighted for the US population and analyses were stratified by age (< 40 and ≥ 40 years old). RESULTS: Of the 18,619 adults included, 1059 (5.6% [95% CI 5.1-5.9]) had current asthma. A substantial overlap was observed both in subjects aged < 40 years (44%) and ≥ 40 years (54%). The more prevalent specific overlaps in both age groups were AwObesity associated with either B-Eos-high (15 and 12%, respectively) or B-Eos&FeNO-low asthma (13 and 11%, respectively). About 14% of the current asthma patients were "non-classified". Regardless of phenotype classification, having concomitant phenotypes was significantly associated with (adjusted OR, 95% CI) ≥ 2 controller medications (2.03, 1.16-3.57), and FEV1 < LLN (3.21, 1.74-5.94), adjusted for confounding variables. CONCLUSIONS: A prevalent overlap of commonly reported asthma phenotypes was observed among asthma patients from the general population, with implications for objective asthma outcomes. A broader approach may be required to better characterize asthma patients and prevent poor asthma outcomes.

The treatment of acute bronchiolitis: past, present and future.

Acute bronchiolitis treatment: little has changed from late 19th century to nowadays, promising strategies incoming http://ow.ly/BmH230aWoXr.

Differential effect of cigarette smoke exposure on exhaled nitric oxide and blood eosinophils in healthy and asthmatic individuals.

BACKGROUND: Tobacco smoking affects both the fraction of exhaled nitric oxide (FeNO) and blood eosinophil (B-Eos) count, two clinically useful biomarkers in respiratory disease that represent local and systemic type-2 inflammation, respectively. OBJECTIVE: We aimed to study the influence of objectively measured smoke exposure on FeNO and B-Eos in a large population of subjects with and without asthma. METHODS: We utilized the US National Health and Nutrition Examination Surveys 2007-2012 and included 10 669 subjects aged 6-80 years: 9869 controls and 800 asthmatics. Controls were defined as having no respiratory disease, no hay fever in the past year, and B-Eos count ≤0.3 × 109 l-1. Asthma was defined as self-reported current asthma and at least one episode of wheezing or an asthma attack in the past year, but no emphysema or chronic bronchitis. Tobacco use was collected via questionnaires and serum cotinine was measured with mass spectrometry. RESULTS: Increasing cotinine levels were associated with a progressive reduction in FeNO in both controls and asthmatics. FeNO remained significantly higher in asthmatics than controls except in the highest cotinine decile, equivalent to an average reported consumption of 13 cigarettes/day. B-Eos count increased with cotinine in controls, but was unchanging in asthmatics. Interestingly, B-Eos count was significantly higher in presently non-exposed (cotinine below detection limit) former smokers than never smokers. CONCLUSION: Smoke exposure decreases FeNO and increases B-Eos count. These effects should be considered in the development of normalized values and their interpretation in clinical practice. The persistence of elevated B-Eos in former smokers warrants further studies.

Predictors of Acute Kidney Injury in the Postoperative Period of Cardiac Surgery Associated with Cardiopulmonary Bypass.

INTRODUCTION: Acute kidney injury (AKI) in the postoperative period of cardiac surgery occurs in 1 to 30% of the patients, mainly caused by ischemia secondary to renal hypoperfusion. Cardiopulmonary bypass (CPB) has a deleterious effect on renal function, constituting an aggression to the patient's homeostasis. AIM: To evaluate the incidence of AKI in the postoperative period of cardiac surgery in patients without preoperative renal insufficiency who underwent cardiac surgery with CPB, and explore the association between incidence of AKI and predictors related to CPB. METHODS: Observational, retrospective, cross-sectional study. Participants were divided in two groups, those who developed AKI in the postoperative period and those who did not develop AKI. KDIGO Clinical Practice Guideline for Acute Kidney Injury classification was used to characterize AKI. The preoperative variables analysed were anthropometric data, cardiovascular risk factors and blood parameters. The type of surgery, intraoperative variables related to CPB and postoperative creatinine variation were also analysed. The association between variables was studied using binary logistic regression. RESULTS: Of the 329 patients included, 62 (18.8%), developed AKI. There were statistically significant differences between the groups in age (p<0.001), CPB time (p=0.011), diuresis during CPB (p=0.038) and mannitol and furosemide administration during CPB (respectively, p=0.032 and p=0.013). Odds ratio showed a significant positive association between AKI and age (OR (95%)- 1.08 (1.04-1.11)), CPB time (OR (95%)-1.01 (1.00-1.01)), mannitol and furosemide administration during CPB (respectively, OR (95%)-2.29 (1.08-4.89) and OR (95%)-2.54 (1.21-5.30)). CONCLUSIONS: This study shows that a significant number of patients developed AKI in the postoperative period of cardiac surgery and this incidence was influenced by factors related to CPB.

Targeted therapies for lung cancer: how did the game begin?

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Doing science: How to submit a successful funding application.

How to submit a successful funding application: "You never get a second chance to make a first impression!" http://ow.ly/XgmbJ.