Exhaled breath analysis in patients with potentially curative lung cancer undergoing surgery: a longitudinal study.

Exhaled breath analysis has emerged as a non-invasive and promising method for early detection of lung cancer, offering a novel approach for diagnosis through the identification of specific biomarkers present in a patient's breath. For this longitudinal study, 29 treatment-naive patients with lung cancer were evaluated before and after surgery. Secondary electrospray ionization high-resolution mass spectrometry was used for exhaled breath analysis. Volatile organic compounds with absolute log2fold change ⩾1 andq-values ⩾ 0.71 were selected as potentially relevant. Exhaled breath analysis resulted in a total of 3482 features. 515 features showed a substantial difference before and after surgery. The small sample size generated a false positive rate of 0.71, therefore, around 154 of these 515 features were expected to be true changes. Biological identification of the features with the highest consistency (m/z-242.18428 andm/z-117.0539) revealed to potentially be 3-Oxotetradecanoic acid and Indole, respectively. Principal component analysis revealed a primary cluster of patients with a recurrent lung cancer, which remained undetected in the initial diagnostic and surgical procedures. The change of exhaled breath patterns after surgery in lung cancer emphasizes the potential for lung cancer screening and detection.

The effect of longitudinal sleep monitoring on clinician agreement in obstructive sleep apnea diagnosis: The ELSA study.

There is strong evidence for clinically relevant night-to-night variability of respiratory events in patients with suspected obstructive sleep apnea. Sleep experts retrospectively evaluated diagnostic data in 56 patients with suspected obstructive sleep apnea. Experts were blinded to the fact that they were diagnosing the same case twice, once based on a short report of a single in-laboratory respiratory polygraphy and once with the additional information of 14 nights of pulse oximetry at home. All experts (n = 22) were highly qualified, 13 experts (59.1%) treated > 100 patients with suspected obstructive sleep apnea per year. In 12 patients, the apnea-hypopnea index in the respiratory polygraphy was < 5 per hr, but the mean oxygen desaturation index of 14 nights of pulse oximetry was ≥ 5 per hr. The additional information of 14 nights of pulse oximetry helped to diagnose obstructive sleep apnea with a 70% consensus in two of those patients (16.7% [95% confidence interval: 4.7/44.8]). In eight patients, experts could not agree to a 70% consensus regarding continuous positive airway pressure therapy recommendation after respiratory polygraphy. The additional information of multiple-night testing led to a consensus in three of those cases (37.5% [95% confidence interval: 14/69]). Change of obstructive sleep apnea diagnosis and continuous positive airway pressure recommendation was significantly negatively associated with the number of treated obstructive sleep apnea patients > 100 per year compared with 0-29 patients per year (Coef. [95% confidence interval] -0.63 [-1.22/-0.04] and -0.61 [-1.07/-0.15], respectively). Experts found already a high level of consensus regarding obstructive sleep apnea diagnosis, severity and continuous positive airway pressure recommendation after a single respiratory polygraphy. However, longitudinal sleep monitoring could help increase consensus in selected patients with diagnostic uncertainty.

Bedtime to the brain: how infants' sleep behaviours intertwine with non-rapid eye movement sleep electroencephalography features.

Adequate sleep is critical for development and facilitates the maturation of the neurophysiological circuitries at the basis of cognitive and behavioural function. Observational research has associated early life sleep problems with worse later cognitive, psychosocial, and somatic health outcomes. Yet, the extent to which day-to-day sleep behaviours (e.g., duration, regularity) in early life relate to non-rapid eye movement (NREM) neurophysiology-acutely and the long-term-remains to be studied. We measured sleep behaviours in 32 healthy 6-month-olds assessed with actimetry and neurophysiology with high-density electroencephalography (EEG) to investigate the association between NREM sleep and habitual sleep behaviours. Our study revealed four findings: first, daytime sleep behaviours are related to EEG slow-wave activity (SWA). Second, night-time movement and awakenings from sleep are connected with spindle density. Third, habitual sleep timing is linked to neurophysiological connectivity quantified as delta coherence. And lastly, delta coherence at 6 months predicts night-time sleep duration at 12 months. These novel findings widen our understanding that infants' sleep behaviours are closely intertwined with three particular levels of neurophysiology: sleep pressure (determined by SWA), the maturation of the thalamocortical system (spindles), and the maturation of cortical connectivity (coherence). The crucial next step is to extend this concept to clinical groups to objectively characterise infants' sleep behaviours 'at risk' that foster later neurodevelopmental problems.

Clinical characteristics governing treatment adjustment in COPD patients: results from the Swiss COPD cohort study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a widespread chronic disease characterised by irreversible airway obstruction [1]. Features of clinical practice and healthcare systems for COPD patients can vary widely, even within similar healthcare structures. The Global Initiative for Chronic Obstructive Lung Disease (GOLD) strategy is considered the most reliable guidance for the management of COPD and aims to provide treating physicians with appropriate insight into the disease. COPD treatment adaptation typically mirrors the suggestions within the GOLD guidelines, depending on how the patient has been categorised. However, the present study posits that the reasons for adjusting COPD-related treatment are hugely varied. OBJECTIVES: The objective of this study was to assess the clinical symptoms that govern both pharmacological and non-pharmacological treatment changes in COPD patients. Using this insight, the study offers suggestions for optimising COPD management through the implementation of GOLD guidelines. METHODS: In this observational cohort study, 24 general practitioners screened 260 COPD patients for eligibility from 2015-2019. General practitioners were asked to collect general information from patients using a standardised questionnaire to document symptoms. During a follow-up visit, the patient's symptoms and changes in therapy were assessed and entered into a central electronic database. Sixty-five patients were removed from the analysis due to exclusion criteria, and 195 patients with at least one additional visit within one year of the baseline visit were included in the analysis. A change in therapy was defined as a change in either medication or non-medical treatment, such as pulmonary rehabilitation. Multivariable mixed models were used to identify associations between given symptoms and a step up in therapy, a step down, or a step up and a step down at the same time. RESULTS: For the 195 patients included in analyses, a treatment adjustment was made during 28% of visits. In 49% of these adjustments, the change in therapy was a step up, in 33% a step down and in 18% a step up (an increase) of certain treatment factors and a step down (a reduction) of other prescribed treatments at the same time. In the multivariable analysis, we found that the severity of disease was linked to the probability of therapy adjustment: patients in GOLD Group C were more likely to experience an increase in therapy compared to patients in GOLD Group A (odds ratio [OR] 3.43 [95% confidence interval {CI}: 1.02-11.55; p = 0.135]). In addition, compared to patients with mild obstruction, patients with severe (OR 4.24 [95% CI: 1.88-9.56]) to very severe (OR 5.48 [95% CI: 1.31-22.96]) obstruction were more likely to experience a therapy increase (p <0.0001). Patients with comorbidities were less likely to experience a treatment increase than those without (OR 0.42 [95% CI: 0.24-0.73; p = 0.002]). A therapy decrease was associated with both a unit increase in COPD Assessment Test (CAT) score (OR 1.07 [95% CI: 1.01-1.14; p = 0.014]) and having experienced an exacerbation (OR 2.66 [95% CI: 1.01-6.97; p = 0.047]). The combination of steps up as well as steps down in therapy was predicted by exacerbation (OR 8.93 [95% CI: 1.16-68.28; p = 0.035]) and very severe obstruction (OR 589 [95% CI: 2.72 - >999; p = 0.109]). CONCLUSIONS: This cohort study provides insight into the management of patients with COPD in a primary care setting. COPD Group C and airflow limitation GOLD 3-4 were both associated with an increase in COPD treatment. In patients with comorbidities, there were often no treatment changes. Exacerbations did not make therapy increases more probable. The presence of neither cough/sputum nor high CAT scores was associated with a step up in treatment.

Adherence to the GOLD Guidelines in Primary Care: Data from the Swiss COPD Cohort.

(1) Introduction: Chronic obstructive pulmonary disease (COPD) and its associated morbidity and mortality are a global burden on both affected patients and healthcare systems. The Global Initiative for Chronic Obstructive Lung Disease (GOLD) issues guidelines with the aim of improving COPD management. Previous studies reported significant variability in adherence to these recommendations. The objective of this study was to evaluate Swiss primary practitioners' adherence to the GOLD guidelines for the pharmacological treatment of stable COPD. (2) Methods: We studied patients who were included in the Swiss COPD cohort study, an ongoing prospective study in a primary care setting, between 2015 and 2022. The key inclusion criteria are age ≥ 40 years, FEV1/FVC ratio < 70%, and a smoking history of at least 20 pack-years. Adherence to the GOLD guidelines was assessed per visit and over time. (3) Results: The data of 225 COPD patients (mean age 67 ± 9 years, 64% male) and their respective 1163 visits were analyzed. In 65% of visits (726/1121), treatment was prescribed according to the GOLD guidelines. Non-adherence was most common in GOLD groups A and B (64% and 33%) and mainly consisted of over-treatment (two long-acting bronchodilators in group A (98/195, 50%) and ICS in groups A (21/195, 11%) and B (198/808, 25%)). In group D, the prescriptions conformed with the guidelines in 99% of cases (109/108). Guideline adherence was associated with high symptom load (COPD Assessment Test) (OR 1.04, p = 0.002), high number of exacerbations (OR = 2.07, p < 0.001), asthma overlap (OR 3.36, p = 0.049), and diabetes mellitus (OR 2.82, p = 0.045). (4) Conclusion: These results confirm a conflict between the GOLD recommendations and primary practice, mainly concerning over-treatment in GOLD groups A and B. Patients with high symptom load, high exacerbation risk, asthma overlap, and diabetes mellitus are more likely to be treated in conformity with the guidelines. Further research is needed to uncover the reasons for the discrepancies and to design strategies for improvement.

Risk Factors for Recurrent Exacerbations in the General-Practitioner-Based Swiss Chronic Obstructive Pulmonary Disease (COPD) Cohort.

BACKGROUND: Patients with chronic obstructive pulmonary disease (COPD) often suffer from acute exacerbations. Our objective was to describe recurrent exacerbations in a GP-based Swiss COPD cohort and develop a statistical model for predicting exacerbation. METHODS: COPD cohort demographic and medical data were recorded for 24 months, by means of a questionnaire-based COPD cohort. The data were split into training (75%) and validation (25%) datasets. A negative binomial regression model was developed using the training dataset to predict the exacerbation rate within 1 year. An exacerbation prediction model was developed, and its overall performance was validated. A nomogram was created to facilitate the clinical use of the model. RESULTS: Of the 229 COPD patients analyzed, 77% of the patients did not experience exacerbation during the follow-up. The best subset in the training dataset revealed that lower forced expiratory volume, high scores on the MRC dyspnea scale, exacerbation history, and being on a combination therapy of LABA + ICS (long-acting beta-agonists + Inhaled Corticosteroids) or LAMA + LABA (Long-acting muscarinic receptor antagonists + long-acting beta-agonists) at baseline were associated with a higher rate of exacerbation. When validated, the area-under-curve (AUC) value was 0.75 for one or more exacerbations. The calibration was accurate (0.34 predicted exacerbations vs 0.28 observed exacerbations). CONCLUSION: Nomograms built from these models can assist clinicians in the decision-making process of COPD care.

Cardiomyopathy as cause of death in Duchenne muscular dystrophy: a longitudinal observational study.

Background: Cardiomyopathy has become an important life-limiting factor since survival in Duchenne muscular dystrophy (DMD) has greatly increased with long-term ventilation and cough assistance. The aim of this study was to investigate the association between impaired left ventricular ejection fraction (LVEF) and survival. Methods: In a >20-year observational study in patients with DMD (age ≥16 years) with at least three echocardiograms, the association between LVEF and survival and time to cardiac or non-cardiac death was investigated using Kaplan-Meier survival analysis and Cox regression (for LVEF). Results: In 67 DMD patients (430 echocardiograms), the decrease in LVEF over a mean±sd follow-up period of 9.1±5.1 years was -10.0±13.9% absolute, but LVEF progression varied widely. 84% were receiving an angiotensin-converting enzyme inhibitor and 54% a ß-blocker at last follow-up with an LVEF of 37.5±12.4% at that time-point. Median (interquartile range) survival was 33 (25-40) years. 28 out of 67 (42%) of the cohort had died and LVEF was a significant negative predictor of survival (hazard ratio 0.95 (95% CI 0.91-0.99); p<0.007). Those who died of cardiac death (53% of known causes of death) had significantly lower LVEF at the time of death (LVEF -11.0% (95% CI -21.1- -0.9%); p=0.035) compared with non-cardiac death and tended to die at a younger age. Conclusions: Cardiomyopathy with systolic heart failure is the leading cause of death and lower LVEF is an independent predictor of mortality at younger ages in patients with DMD. Patients with DMD appear to be undertreated with respect to heart failure drug therapy.

Effects of continuous positive airway pressure therapy on glucose metabolism in patients with obstructive sleep apnoea and type 2 diabetes: a systematic review and meta-analysis.

Obstructive sleep apnoea is a highly prevalent chronic disorder and has been shown to be associated with disturbed glucose metabolism and type 2 diabetes. However, the evidence from individual clinical trials on the effect of continuous positive airway pressure (CPAP) treatment on glycaemic control in patients with co-existing obstructive sleep apnoea and type 2 diabetes remains controversial. A systematic review of randomised controlled trials assessing the effect of CPAP on glycaemic control in patients with obstructive sleep apnoea and type 2 diabetes was conducted using the databases MEDLINE, Embase, Cochrane and Scopus up to December 2022. Meta-analysis using a random-effect model was performed for outcomes that were reported in at least two randomised controlled trials. From 3031 records screened, 11 RCTs with a total of 964 patients were included for analysis. CPAP treatment led to a significant reduction in haemoglobin A1c (HbA1c) (mean difference -0.24%, 95% CI -0.43- -0.06%, p=0.001) compared to inactive control groups. Meta-regression showed a significant association between reduction in HbA1c and hours of nightly CPAP usage. CPAP therapy seems to significantly improve HbA1c and thus long-term glycaemic control in patients with type 2 diabetes and obstructive sleep apnoea. The amount of improvement is dependent on the hours of usage of CPAP and thus optimal adherence to CPAP should be a primary goal in these patients.

Lack of association between behavioral development and simplified topographical markers of the sleep EEG in infancy.

The sleep EEG mirrors neuronal connectivity, especially during development when the brain undergoes substantial rewiring. As children grow, the slow-wave activity (SWA; 0.75-4.25 Hz) spatial distribution in their sleep EEG changes along a posterior-to-anterior gradient. Topographical SWA markers have been linked to critical neurobehavioral functions, such as motor skills, in school-aged children. However, the relationship between topographical markers in infancy and later behavioral outcomes is still unclear. This study aims to explore reliable indicators of neurodevelopment in infants by analyzing their sleep EEG patterns. Thirty-one 6-month-old infants (15 female) underwent high-density EEG recordings during nighttime sleep. We defined markers based on the topographical distribution of SWA and theta activity, including central/occipital and frontal/occipital ratios and an index derived from local EEG power variability. Linear models were applied to test whether markers relate to concurrent, later, or retrospective behavioral scores, assessed by the parent-reported Ages & Stages Questionnaire at ages 3, 6, 12, and 24 months. Results indicate that the topographical markers of the sleep EEG power in infants were not significantly linked to behavioral development at any age. Further research, such as longitudinal sleep EEG in newborns, is needed to better understand the relationship between these markers and behavioral development and assess their predictive value for individual differences.

Physical Health-Related Quality of Life Improves over Time in Post-COVID-19 Patients: An Exploratory Prospective Study.

(1) Background: Ongoing symptoms after mild or moderate acute coronavirus disease 19 (COVID-19) substantially affect health-related quality of life (HRQoL). However, follow-up data on HRQoL are scarce. We characterized the change in HRQoL over time in post-COVID-19 patients who initially suffered from mild or moderate acute COVID-19 without hospitalization. (2) Methods: Outpatients who visited an interdisciplinary post-COVID-19 consultation at the University Hospital Zurich and suffered from ongoing symptoms after acute COVID-19 were included in this observational study. HRQoL was assessed using established questionnaires. Six months after baseline, the same questionnaires and a self-constructed questionnaire about the COVID-19 vaccination were distributed. (3) Results: In total, 69 patients completed the follow-up, of whom 55 (80%) were female. The mean (SD) age was 44 (12) years and the median (IQR) time from symptom onset to completing the follow-up was 326 (300, 391) days. The majority of patients significantly improved in EQ-5D-5L health dimensions of mobility, usual activities, pain and anxiety. Furthermore, according to the SF-36, patients showed clinically relevant improvements in physical health, whereas no significant change was found regarding mental health. (4) Conclusions: Physical aspects of HRQoL in post-COVID-19 patients relevantly improved over 6 months. Future studies are needed to focus on potential predictors that allow for establishing individual care and early interventions.

Impaired health-related quality of life in long-COVID syndrome after mild to moderate COVID-19.

A growing number of patients with SARS-CoV-2 infections experience long-lasting symptoms. Even patients who suffered from a mild acute infection show a variety of persisting and debilitating neurocognitive, respiratory, or cardiac symptoms (Long-Covid syndrome), consequently leading to limitations in everyday life. Because data on health-related quality of life (HRQoL) is scarce, we aimed to characterize the impact of Long-Covid symptoms after a mild or moderate acute infection on HRQoL. In this observational study, outpatients seeking counseling in the interdisciplinary Post-Covid consultation of the University Hospital Zurich with symptoms persisting for more than 4 weeks were included. Patients who received an alternative diagnosis or suffered from a severe acute Covid-19 infection were excluded. St. George's Respiratory Questionnaire (SGRQ), Euroquol-5D-5L (EQ-5D-5L), and the Short form 36 (SF-36) were distributed to assess HRQoL. 112 patients were included, 86 (76.8%) were female, median (IQR) age was 43 (32.0, 52.5) years with 126 (91, 180) days of symptoms. Patients suffered frequently from fatigue (81%), concentration difficulties (60%), and dyspnea (60%). Patients mostly stated impairment in performing usual activities and having pain/discomfort or anxiety out of the EQ-5D-5L. EQ index value and SGRQ activity score component were significantly lower in females. SF-36 scores showed remarkably lower scores in the physical health domain compared to the Swiss general population before and during the COVID-19 pandemic. Long-Covid syndrome has a substantial impact on HRQoL. Long-term surveillance of patients must provide clarity on the duration of impairments in physical and mental health.Trial registration: The study is registered on www.ClinicalTrials.gov , NCT04793269.

Chest CT Findings after Mild COVID-19 Do Not Explain Persisting Respiratory Symptoms: An Explanatory Study.

(1) Background: Lung tissue involvement is frequently observed in acute COVID-19. However, it is unclear whether CT findings at follow-up are associated with persisting respiratory symptoms after initial mild or moderate infection. (2) Methods: Chest CTs of patients with persisting respiratory symptoms referred to the post-COVID-19 outpatient clinic were reassessed for parenchymal changes, and their potential association was evaluated. (3) Results: A total of 53 patients (31 female) with a mean (SD) age of 46 (13) years were included, of whom 89% had mild COVID-19. Median (quartiles) time from infection to CT was 139 (86, 189) days. Respiratory symptoms were dyspnea (79%), cough (42%), and thoracic pain (64%). Furthermore, 30 of 53 CTs showed very discrete and two CTs showed medium parenchymal abnormalities. No severe findings were observed. Mosaic attenuation (40%), ground glass opacity (2%), and fibrotic-like changes (25%) were recorded. No evidence for an association between persisting respiratory symptoms and chest CT findings was found. (4) Conclusions: More than half of the patients with initially mild or moderate infection showed findings on chest CT at follow-up. Respiratory symptoms, however, were not related to any chest CT finding. We, therefore, do not suggest routine chest CT follow-up in this patient group if no other indications are given.

Online breath analysis with SESI/HRMS for metabolic signatures in children with allergic asthma.

Introduction: There is a need to improve the diagnosis and management of pediatric asthma. Breath analysis aims to address this by non-invasively assessing altered metabolism and disease-associated processes. Our goal was to identify exhaled metabolic signatures that distinguish children with allergic asthma from healthy controls using secondary electrospray ionization high-resolution mass spectrometry (SESI/HRMS) in a cross-sectional observational study. Methods: Breath analysis was performed with SESI/HRMS. Significant differentially expressed mass-to-charge features in breath were extracted using the empirical Bayes moderated t-statistics test. Corresponding molecules were putatively annotated by tandem mass spectrometry database matching and pathway analysis. Results: 48 allergic asthmatics and 56 healthy controls were included in the study. Among 375 significant mass-to-charge features, 134 were putatively identified. Many of these could be grouped to metabolites of common pathways or chemical families. We found several pathways that are well-represented by the significant metabolites, for example, lysine degradation elevated and two arginine pathways downregulated in the asthmatic group. Assessing the ability of breath profiles to classify samples as asthmatic or healthy with supervised machine learning in a 10 times repeated 10-fold cross-validation revealed an area under the receiver operating characteristic curve of 0.83. Discussion: For the first time, a large number of breath-derived metabolites that discriminate children with allergic asthma from healthy controls were identified by online breath analysis. Many are linked to well-described metabolic pathways and chemical families involved in pathophysiological processes of asthma. Furthermore, a subset of these volatile organic compounds showed high potential for clinical diagnostic applications.

An infant sleep electroencephalographic marker of thalamocortical connectivity predicts behavioral outcome in late infancy.

Infancy represents a critical period during which thalamocortical brain connections develop and mature. Deviations in the maturation of thalamocortical connectivity are linked to neurodevelopmental disorders. There is a lack of early biomarkers to detect and localize neuromaturational deviations, which can be overcome with mapping through high-density electroencephalography (hdEEG) assessed in sleep. Specifically, slow waves and spindles in non-rapid eye movement (NREM) sleep are generated by the thalamocortical system, and their characteristics, slow wave slope and spindle density, are closely related to neuroplasticity and learning. Spindles are often subdivided into slow (11.0-13.0 Hz) and fast (13.5-16.0 Hz) frequencies, for which not only different functions have been proposed, but for which also distinctive developmental trajectories have been reported across the first years of life. Recent studies further suggest that information processing during sleep underlying sleep-dependent learning is promoted by the temporal coupling of slow waves and spindles, yet slow wave-spindle coupling remains unexplored in infancy. Thus, we evaluated three potential biomarkers: 1) slow wave slope, 2) spindle density, and 3) the temporal coupling of slow waves with spindles. We use hdEEG to first examine the occurrence and spatial distribution of these three EEG features in healthy infants and second to evaluate a predictive relationship with later behavioral outcomes. We report four key findings: First, infants' EEG features appear locally: slow wave slope is maximal in occipital and frontal areas, whereas slow and fast spindle density is most pronounced frontocentrally. Second, slow waves and spindles are temporally coupled in infancy, with maximal coupling strength in the occipital areas of the brain. Third, slow wave slope, fast spindle density, and slow wave-spindle coupling are not associated with concurrent behavioral status (6 months). Fourth, fast spindle density in central and frontocentral regions at age 6 months predicts overall developmental status at age 12 months, and motor skills at age 12 and 24 months. Neither slow wave slope nor slow wave-spindle coupling predict later behavioral development. We further identified spindle frequency as a determinant of slow and fast spindle density, which accordingly, also predicts motor skills at 24 months. Our results propose fast spindle density, or alternatively spindle frequency, as early EEG biomarker for identifying thalamocortical maturation, which can potentially be used for early diagnosis of neurodevelopmental disorders in infants. These findings are in support of a role of sleep spindles in sensorimotor microcircuitry development. A crucial next step will be to evaluate whether early therapeutic interventions may be effective to reverse deviations in identified individuals at risk.

The sleeping brain's connectivity and family environment: characterizing sleep EEG coherence in an infant cohort.

Brain connectivity closely reflects brain function and behavior. Sleep EEG coherence, a measure of brain's connectivity during sleep, undergoes pronounced changes across development under the influence of environmental factors. Yet, the determinants of the developing brain's sleep EEG coherence from the child's family environment remain unknown. After characterizing high-density sleep EEG coherence in 31 healthy 6-month-old infants by detecting strongly synchronized clusters through a data-driven approach, we examined the association of sleep EEG coherence from these clusters with factors from the infant's family environment. Clusters with greatest coherence were observed over the frontal lobe. Higher delta coherence over the left frontal cortex was found in infants sleeping in their parents' room, while infants sleeping in a room shared with their sibling(s) showed greater delta coherence over the central parts of the frontal cortex, suggesting a link between local brain connectivity and co-sleeping. Finally, lower occipital delta coherence was associated with maternal anxiety regarding their infant's sleep. These interesting links between sleep EEG coherence and family factors have the potential to serve in early health interventions as a new set of targets from the child's immediate environment.

Are Predictors for Overall Mortality in COPD Patients Robust over Time?

(1) Background: Mortality is a major outcome in research on chronic obstructive pulmonary disease (COPD) with various predictors described. However, the dynamic courses of important predictors over time are disregarded. This study evaluates if longitudinal assessment of predictors provides additional information on the mortality risk in COPD when compared with a cross-sectional analysis.; (2) In a longitudinal, prospective, non-interventional cohort study including mild to very severe COPD patients, mortality and its various possible predictors were annually assessed up to seven years.; (3) Results: 297 patients were analysed. Mean (SD) age was 62.5 (7.6) years and 66% males. Mean (SD) FEV1 was 48.8 (21.4)%. A total of 105 events (35.4%) happened with a median (95% CI) survival time of 8.2 (7.2/NA) years. No evidence for a difference between the raw variable and the variable history on the predictive value for all tested variables over each visit was found. There was no evidence for changing effect estimates (coefficients) across the study visits due to the longitudinal assessment; (4) Conclusions: We found no evidence that predictors of mortality in COPD are time dependent. This implies that cross-sectional measured predictors show robust effect estimates over time and multiple assessments seem not to change the predictive value of the measure.

Mammalian Target of Rapamycin Inhibitors and Kidney Function After Thoracic Transplantation: A Systematic Review and Recommendations for Management of Lung Transplant Recipients.

BACKGROUND: Chronic kidney disease (CKD) after lung transplantation is common and limits the survival of transplant recipients. The calcineurin inhibitors (CNI), cyclosporine A, and tacrolimus being the cornerstone of immunosuppression are key mediators of nephrotoxicity. The mammalian target of rapamycin (mTOR) inhibitors, sirolimus and everolimus, are increasingly used in combination with reduced CNI dosage after lung transplantation. METHODS: This systematic review examined the efficacy and safety of mTOR inhibitors after lung transplantation and explored their effect on kidney function. RESULTS: mTOR inhibitors are often introduced to preserve kidney function. Several clinical trials have demonstrated improved kidney function and efficacy of mTOR inhibitors. The potential for kidney function improvement and preservation increases with early initiation of mTOR inhibitors and low target levels for both mTOR inhibitors and CNI. No defined stage of CKD for mTOR inhibitor initiation exists, nor does severe CKD preclude the improvement of kidney function under mTOR inhibitors. Baseline proteinuria may negatively predict the preservation and improvement of kidney function. Discontinuation rates of mTOR inhibitors due to adverse effects increase with higher target levels. CONCLUSIONS: More evidence is needed to define the optimal immunosuppressive regimen incorporating mTOR inhibitors after lung transplantation. Not only the indication criteria for the introduction of mTOR inhibitors are needed, but also the best timing, target levels, and possibly discontinuation criteria must be defined more clearly. Current evidence supports the notion of nephroprotective potential under certain conditions.

Mapping the landscape of lung cancer breath analysis: A scoping review (ELCABA).

Lung cancer is the leading cause of cancer death worldwide due to its late-stage detection. Lung cancer screening, including low-dose computed tomography (low-dose CT), provides an initial clinical solution. Nevertheless, further innovations and refinements would help to alleviate remaining limitations. The non-invasive, gentle, and fast nature of breath analysis (BA) makes this technology highly attractive to supplement low-dose CT for an improved screening algorithm. However, BA has not taken hold in everyday clinical practice. One reason might be the heterogeneity and variety of BA methods. This scoping review is a comprehensive summary of study designs, breath analytical methods, and suggested biomarkers in lung cancer. Furthermore, this synthesis provides a framework with core outcomes for future studies in lung cancer BA. This work supports future research for evidence synthesis, meta-analysis, and translation into clinical routine workflows.

An interoperability framework for multicentric breath metabolomic studies.

Exhaled breath contains valuable information at the molecular level and offers promising potential for precision medicine. However, few breath tests transition to routine clinical practice, partly because of the missing validation in multicenter trials. Therefore, we developed and applied an interoperability framework for standardized multicenter data acquisition and processing for breath analysis with secondary electrospray ionization-high resolution mass spectrometry. We aimed to determine the technical variability and metabolic coverage. Comparison of multicenter data revealed a technical variability of ∼20% and a core signature of the human exhaled metabolome consisting of ∼850 features, corresponding mainly to amino acid, xenobiotic, and carbohydrate metabolic pathways. In addition, we found high inter-subject variability for certain metabolic classes (e.g., amino acids and fatty acids), whereas other regions such as the TCA cycle were relatively stable across subjects. The interoperability framework and overview of metabolic coverage presented here will pave the way for future large-scale multicenter trials.

A gas-phase standard delivery system for direct breath analysis.

Applications for direct breath analysis by mass spectrometry (MS) are rapidly expanding. One of the more recent mass spectrometry-based approaches is secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS). Despite increasing usage, the SESI methodology still lacks standardization procedures for quality control and absolute quantification. In this study, we designed and evaluated a custom-built standard delivery system tailored for direct breath analysis. The system enables the simultaneous introduction of multiple gas-phase standard compounds into ambient MS setups in the lower parts-per-million (ppm) to parts-per-billion (ppb) range. To best mimic exhaled breath, the gas flow can be heated (37 °C-40 °C) and humidified (up to 98% relative humidity). Inter-laboratory comparison of the system included various SESI-HRMS setups, i.e. an Orbitrap and a quadrupole time-of-flight mass spectrometer (QTOF), and using both single- as well as multi-component standards. This revealed highly stable and reproducible performances with between-run variation <19% and within-run variation <20%. Independent calibration runs demonstrated high accuracy (96%-111%) and precision (>95%) for the single-compound standard acetone, while compound-specific performances were obtained for the multi-component standard. Similarly, the sensitivity varied for different compounds within the multi-component standard across all SESI-Orbitrap and -QTOF setups, yielding limits of detections from 3.1 ppb (forp-xylene) to 0.05 ppb (for 1,8-cineol). Routinely applying the standard system throughout several weeks, allowed us to monitor instrument stability and to identify technical outliers in exhaled breath measurements. Such routine deployment of standards would significantly improve data quality and comparability, which is especially important in longitudinal and multi-center studies. Furthermore, performance validation of the system demonstrated its suitability for reliable absolute quantification while it illustrated compound-dependent behavior for SESI.