BMI is associated with FEV1 decline in chronic obstructive pulmonary disease: a meta-analysis of clinical trials

Diagnosis and Severity Assessment of COPD Using a Novel Fast-Response Capnometer and Interpretable Machine Learning

INTRODUCTION

Spirometry is the gold standard for COPD diagnosis and severity determination, but is technique-dependent, nonspecific, and requires administration by a trained healthcare professional. There is a need for a fast, reliable, and precise alternative diagnostic test. This study's aim was to use interpretable machine learning to diagnose COPD and assess severity using 75-second carbon dioxide (CO2) breath records captured with TidalSense's N-TidalTM capnometer.

METHOD

For COPD diagnosis, machine learning algorithms were trained and evaluated on 294 COPD (including GOLD stages 1-4) and 705 non-COPD participants. A logistic regression model was also trained to distinguish GOLD 1 from GOLD 4 COPD with the output probability used as an index of severity.

RESULTS

The best diagnostic model achieved an AUROC of 0.890, sensitivity of 0.771, specificity of 0.850 and positive predictive value (PPV) of 0.834. Evaluating performance on all test capnograms that were confidently ruled in or out yielded PPV of 0.930 and NPV of 0.890. The severity determination model yielded an AUROC of 0.980, sensitivity of 0.958, specificity of 0.961 and PPV of 0.958 in distinguishing GOLD 1 from GOLD 4. Output probabilities from the severity determination model produced a correlation of 0.71 with percentage predicted FEV1.

CONCLUSION

The N-TidalTM device could be used alongside interpretable machine learning as an accurate, point-of-care diagnostic test for COPD, particularly in primary care as a rapid rule-in or rule-out test. N-TidalTM also could be effective in monitoring disease progression, providing a possible alternative to spirometry for disease monitoring.

Machine learning-based health environmental-clinical risk scores in European children

BACKGROUND

Early life environmental stressors play an important role in the development of multiple chronic disorders. Previous studies that used environmental risk scores (ERS) to assess the cumulative impact of environmental exposures on health are limited by the diversity of exposures included, especially for early life determinants. We used machine learning methods to build early life exposome risk scores for three health outcomes using environmental, molecular, and clinical data.

METHODS

In this study, we analyzed data from 1622 mother-child pairs from the HELIX European birth cohorts, using over 300 environmental, 100 child peripheral, and 18 mother-child clinical markers to compute environmental-clinical risk scores (ECRS) for child behavioral difficulties, metabolic syndrome, and lung function. ECRS were computed using LASSO, Random Forest and XGBoost. XGBoost ECRS were selected to extract local feature contributions using Shapley values and derive feature importance and interactions.

RESULTS

ECRS captured 13%, 50% and 4% of the variance in mental, cardiometabolic, and respiratory health, respectively. We observed no significant differences in predictive performances between the above-mentioned methods.The most important predictive features were maternal stress, noise, and lifestyle exposures for mental health; proteome (mainly IL1B) and metabolome features for cardiometabolic health; child BMI and urine metabolites for respiratory health.

CONCLUSIONS

Besides their usefulness for epidemiological research, our risk scores show great potential to capture holistic individual level non-hereditary risk associations that can inform practitioners about actionable factors of high-risk children. As in the post-genetic era personalized prevention medicine will focus more and more on modifiable factors, we believe that such integrative approaches will be instrumental in shaping future healthcare paradigms.

Longitudinal BMI change and outcomes in Chronic Obstructive Pulmonary Disease: a nationwide population-based cohort study

BACKGROUND

The association between longitudinal body mass index (BMI) change and clinical outcomes in patients with chronic obstructive pulmonary disease (COPD) has not fully investigated.

METHODS

This retrospective cohort study included 116,463 COPD patients aged ≥ 40, with at least two health examinations, one within 2 years before and another within 3 years after COPD diagnosis (January 1, 2014, to December 31, 2019). Associations between BMI percentage change with all-cause mortality, primary endpoint, and initial severe exacerbation were assessed.

RESULTS

BMI decreased > 5% in 14,728 (12.6%), while maintained in 80,689 (69.2%), and increased > 5% in 21,046 (18.1%) after COPD diagnosis. Compared to maintenance group, adjusted hazard ratio (aHR) for all-cause mortality was 1.70 in BMI decrease group (95% CI:1.61, 1.79) and 1.13 in BMI increase group (95% CI:1.07, 1.20). In subgroup analysis, decrease in BMI showed a stronger effect on mortality as baseline BMI was lower, while an increase in BMI was related to an increase in mortality only in obese COPD patients with aHRs of 1.18 (95% CI: 1.03, 1.36). The aHRs for the risk of severe exacerbation (BMI decrease group and increase group vs. maintenance group) were 1.30 (95% CI:1.24, 1.35) and 1.12 (95% CI:1.07, 1.16), respectively.

CONCLUSIONS

A decrease in BMI was associated with an increased risk of all-cause mortality in a dose-dependent manner in patients with COPD. This was most significant in underweight patients. Regular monitoring for weight loss might be an important component for COPD management.

Analysis of Endocrine and Inflammatory Markers in Preserved Ratio Impaired Spirometry

Chronic Obstructive Pulmonary Disease (COPD) is a disease of the lungs characterized by chronic airflow obstruction. Individuals with preserved ratio impaired spirometry (PRISm) may be at risk for developing COPD. This study aimed to characterize PRISm and COPD patients in terms of their immune response and endocrine profile to identify differences extending beyond lung function. The participants performed the clinical assessment, pulmonary function test, and blood collection to determine serum hormone levels and concentrations of cytokine. Differences were observed in the nutritional status, lung function, and comorbidity. There were no differences in IL-6, IL-8, IL-10, IL-12, and TNF levels between PRISm and COPD groups. Both PRISm and COPD patients have lower dehydroepiandrosterone (DHEA) and dehydroepiandrosterone sulfate (DHEA-S) levels than controls. Correlation analysis of PRISm and COPD patients revealed positive correlations between serum levels of DHEA-S and DHEA, with forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC), which negatively correlated with IL-8 levels. The results indicated that despite differences in lung function parameters, the PRISm and COPD groups exhibited similarities in endocrine profile alterations. This study represents the first attempt to link endocrine with immune markers and lung function in individuals with PRISm.

COPD in Never-Smokers: BOLD Australia Study

Purpose

Tobacco smoking is the major risk factor for COPD, and it is common for other risk factors in never-smokers to be overlooked. We examined the prevalence of COPD among never-smokers in Australia and identified associated risk factors.

Methods

We used data from the Australia Burden of Obstructive Lung Disease (BOLD) study, a cross-section of people aged ≥40 years from six sites. Participants completed interviews and post-bronchodilator spirometry. COPD was primarily defined as an FEV1/FVC ratio <0.70 and secondarily as the ratio less than the lower limit of normal (LLN).

Results

The prevalence of COPD in the 1656 never-smokers who completed the study was 10.5% (95% CI: 9.1-12.1%) [ratio

Conclusion

COPD was prevalent in this population of never-smokers aged 40 years and over. This finding highlights the significance of risk factors other than smoking in the development of COPD.

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Key Words

• BOLD
• LLN
• burden of obstructive lung disease
• lower limit of normal
• non-smokers
• prevalence
• spirometry

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MESH Headings

• Female
• Male
• Humans
• Adult
• Middle Aged
• Child
• Smokers
• Pulmonary Disease, Chronic Obstructive/diagnosis
• Pulmonary Disease, Chronic Obstructive/epidemiology
• Asthma
• Odds Ratio
• Australia/epidemiology

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Grants

• National Health and Medical Research Council (NHMRC) of Australia
• Thoracic Society of Australia and New Zealand
• Robert Pierce Grant-in-Aid for Indigenous Lung Health
• Air Liquide, AstraZeneca; GlaxoSmithKline; and Boehringer Ingelheim

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Affiliation(s)

Marsha A Ivey School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia School of Medicine, Faculty of Medical Sciences, The University of the West Indies, St Augustine, Trinidad and Tobago
Sheree M Smith School of Nursing and Midwifery, Campbelltown Campus, Western Sydney University, Penrith, NSW, 2751, Australia Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
Geza Benke School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
Brett G Toelle Respiratory and Environmental Epidemiology Group, Woolcock Institute of Medical Research, Sydney, NSW, 2037, Australia Sydney Local Health District, Sydney, NSW, 2050, Australia
Michael L Hunter School of Population and Global Health, University of Western Australia, Perth, WA, 6009, Australia
Alan L James Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital and Medical School, University of Western Australia, Perth, WA, 6009, Australia
Graeme P Maguire Curtin Medical School, Curtin University, Perth, WA, 6102, Australia
Richard Wood-Baker School of Medicine, University of Tasmania, Hobart, TAS, 7000, Australia
David P Johns Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
Guy B Marks Respiratory and Environmental Epidemiology Group, Woolcock Institute of Medical Research, Sydney, NSW, 2037, Australia School of Clinical Medicine, University of New South Wales, Sydney, NSW, 2052, Australia
Michael J Abramson School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia

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Construction and validation of nomogram prediction model for risk of acute heart failure in patients with acute exacerbation of chronic obstructive pulmonary disease

To investigate the influencing factors of in-hospital acute heart failure (AHF) in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD), and to construct and validate a risk prediction nomogram model. Three Hundred Thirty patients with AECOPD admitted to our hospital from June 2020 to June 2023 were retrospectively analyzed as a training set for the construction of the model. Three Hundred Twenty-five AECOPD patients admitted to the Second People's Hospital of Hefei from 2006 to June 2023 were also collected as the validation set for the validation of the model. A nomogram model was constructed to predict the risk of nosocomial AHF in patients with AECOPD, and C-index and receiver operating characteristic curve were drawn to assess the predictive predictive efficacy of the model. Model fit was evaluated by Hosmer-Lemeshow test, calibration curve was drawn to evaluate the calibration of the model; decision curve was drawn to analyze the net benefit rate of this nomogram model. Multivariate logistic regression analysis indicated that body mass index, mmRC grade, neutrophils, lymphocytes, hemoglobin, creatinine, PO2, PCO2, and Homocysteine were independent risk factors for in-hospital AHF in patients with AECOPD. To construct a nomogram model for risk prediction of in-hospital AHF in patients with AECOPD. The C-index of the training set was 0.949 (95% CI: 0.91-0.961); the C-index of the validation set was 0.936 (95% CI: 0.911-0.961) suggesting good model discrimination. The receiver operating characteristic curve calculated area under curve for the training set was 0.949 (95% CI: 0.928-0.97); area under curve for the validation set was 0.936 (95% CI: 0.91-0.961) suggesting good model accuracy. The results of Hosmer-Lemeshoe goodness-of-fit test and calibration curve analysis showed that the calibration curve of this nomogram model was close to the ideal curve. The clinical decision curve also showed good clinical net benefit of the nomogram model. Body mass index, mmRC grade, neutrophils, lymphocytes, hemoglobin, creatinine, PO2, PCO2, and Homocysteine are risk factors for in-hospital AHF in AECOPD patients, and nomogram models constructed based on the above factors have some predictive value for in-hospital AHF in AECOPD patients. It is also vital for nursing staff to strengthen nursing care.

BMI trajectory in adulthood in relation to all-cause and cause-specific mortality: A retrospective cohort study in Taiwan

A dynamic change of weight over time has been known as an important factor that impacts mortality risk. The aims of this study were to identify the heterogeneity of BMI trajectory groups and to examine the association of the trajectories of BMI and all-cause and cause-specific mortality. The data for this study were obtained from a large prospective cohort study in Taiwan between 1998 and 2019 that was linked to the National Death Registry for death information. The participants were stratified into four groups by age and gender; self-reported demographics and measured BMI data were used. We used group-based trajectory analysis to identify the distinct trajectories of changes in BMI. A Cox proportional hazards model was used to assess the hazard ratio (HR) of all-cause and cause-specific mortality risk. Data were analyzed in April 2020 and included 89,886 participants. Four trajectory groups were identified by the pattern of BMI change over time. Our study shows that different trajectories were associated with mortality. Our findings suggest that the mortality risk differs in each trajectory group and in each age and gender stratification. It appears that obesity is a protective factor in cancer-related mortality in females but not in males in group of old age participants; low-normal weight is a risk factor in respiratory-related mortality in all participants. Our findings can be used to suggest the appropriate BMI in each age and gender groups and thereby earlier health interventions can be taken to avoid mortality.

A Serological Neoepitope Biomarker of Neutrophil Elastase-Degraded Calprotectin, Associated with Neutrophil Activity, Identifies Idiopathic Pulmonary Fibrosis and Chronic Obstructive Pulmonary Disease More Effectively Than Total Calprotectin

Neutrophil activation can release neutrophil extracellular traps (NETs) in acute inflammation. NETs result in the release of human neutrophil elastase (HNE) and calprotectin, where the former can degrade the latter and generate protein fragments associated with neutrophil activity. We investigated this in chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) using the novel neoepitope biomarker CPa9-HNE, quantifying a specific HNE-mediated fragment of calprotectin in serum. CPa9-HNE was compared to total calprotectin. Initially, CPa9-HNE was measured in healthy (n = 39), COPD (n = 67), and IPF (n = 16) serum using a neoepitope-specific competitive enzyme-linked immunosorbent assay. Then, a head-to-head comparison of CPa9-HNE and total calprotectin, a non-neoepitope, was conducted in healthy (n = 19), COPD (n = 25), and IPF (n = 19) participants. CPa9-HNE levels were significantly increased in COPD (p < 0.0001) and IPF subjects (p = 0.0001) when compared to healthy participants. Additionally, CPa9-HNE distinguished IPF (p < 0.0001) and COPD (p < 0.0001) from healthy participants more effectively than total calprotectin for IPF (p = 0.0051) and COPD (p = 0.0069). Here, CPa9-HNE also distinguished IPF from COPD (p = 0.045) participants, which was not observed for total calprotectin (p = 0.98). Neutrophil activity was significantly higher, as assessed via serum CPa9-HNE, for COPD and IPF compared to healthy participants. Additionally, CPa9-HNE exceeded the ability of non-neoepitope calprotectin serum measurements to separate healthy from lung disease and even COPD from IPF participants, indicating that neutrophil activity is essential for both COPD and IPF.

Efficacy and safety of physical therapy in patients with stage III COPD during ambulatory rehabilitation

This study aimed to determine the efficacy of a combined physical therapy and pharmacological treatment for patients recovering from stage III COPD exacerbation. The efficacy of the rehabilitation program was assessed using anthropological parameters, physical condition, respiratory system function, and functional endurance capacity. Data were collected from 39 patients with stage III COPD who underwent the rehabilitation program. Physical and anthropometric assessments were conducted using the Quetelet Body Mass Index, the Pignet Index, and the Vital Capacity Index (VCI). The functional capacities of the cardiorespiratory system were measured before and after the rehabilitation program using the Ruffier and Ruffier-Dickson tests and the hypoxic Shtange and Genchi tests. Exercise tolerance was evaluated using the Harvard Step Test and the Six-Minute Walk Distance Test (6MWD). Statistical analysis was conducted using the non-parametric Mann-Whitney U test for independent and dependent groups. Participants were randomly divided into two groups for rehabilitation: Group I received standard therapy and a routine physical therapy program, while Group II was given standard therapy along with a modified physical therapy regimen. There was a slight improvement in patient condition during the rehabilitation period for both groups. However, there was a low compliance rate for smoking cessation among the majority of patients, with some reducing their daily cigarette intake. Further long-time research is required to determine the efficacy of the proposed physical therapy program in combination with basic pharmacological therapy. The study suggests incorporating psychotherapeutic sessions and occupational therapy into future rehabilitation programs.

Obesity Paradox in Lung Diseases: What Explains It?

BACKGROUND

Obesity is a globally increasing health problem that impacts multiple organ systems and a potentially modifiable risk factor for many diseases. Obesity has a significant impact on lung function and is strongly linked to the pathophysiology that contributes to lung diseases. On the other hand, reports have emerged that obesity is associated with a better prognosis than for normal weight individuals in some lung diseases, including pneumonia, acute lung injury/acute respiratory distress syndrome, chronic obstructive pulmonary disease, and lung cancer. The lesser mortality and better prognosis in patients with obesity is known as obesity paradox. While obesity paradox is both recognized and disputed in epidemiological studies, recent research has suggested possible mechanisms.

SUMMARY

In this review, we attempted to explain and summarize these factors and mechanisms, including immune response, pulmonary fibrosis, lung function, microbiota, fat and muscle reserves, which are significantly altered by obesity and may contribute to the obesity paradox in lung diseases. We also discuss contrary literature that attributes the "obesity paradox" to confounding.

KEY MESSAGES

The review will illustrate the possible role of obesity in the prognosis or course of lung diseases, leading to a better understanding of the obesity paradox and provide hints for further basic and clinical research in lung diseases.

Analysis of the correlation between BMI and respiratory tract microbiota in acute exacerbation of COPD

Objective

To investigate the distribution differences in the respiratory tract microbiota of AECOPD patients in different BMI groups and explore its guiding value for treatment.

Methods

Sputum samples of thirty-eight AECOPD patients were collected. The patients were divided into low, normal and high BMI group. The sputum microbiota was sequenced by 16S rRNA detection technology, and the distribution of sputum microbiota was compared. Rarefaction curve, α-diversity, principal coordinate analysis (PCoA) and measurement of sputum microbiota abundance in each group were performed and analyzed by bioinformatics methods.

Results

1. The rarefaction curve in each BMI group reached a plateau. No significant differences were observed in the OTU total number or α-diversity index of microbiota in each group. PCoA showed significant differences in the distance matrix of sputum microbiota between the three groups, which was calculated by the Binary Jaccard and the Bray Curtis algorithm. 2. At the phylum level, most of the microbiota were Proteobacteria, Bacteroidetes Firmicutes, Actinobacteria, and Fusobacteria. At the genus level, most were Streptococcus, Prevotella, Haemophilus, Neisseria and Bacteroides. 3. At the phylum level, the abundance of Proteobacteria in the low group was significantly higher than that in normal and high BMI groups, the abundances of Firmicutes in the low and normal groups were significantly lower than that in high BMI groups. At the genus level, the abundance of Haemophilus in the low group was significantly higher than that in high BMI group, and the abundances of Streptococcus in the low and normal BMI groups were significantly lower than that in the high BMI group.

Conclusions

1. The sputum microbiota of AECOPD patients in different BMI groups covered almost all microbiota, and BMI had no significant association with total number of respiratory tract microbiota or α-diversity in AECOPD patients. However, there was a significant difference in the PCoA between different BMI groups. 2. The microbiota structure of AECOPD patients differed in different BMI groups. Gram-negative bacteria (G-) in the respiratory tract of patients predominated in the low BMI group, while gram-positive bacteria (G+) predominated in the high BMI group.

Recent Prevalence of and Factors Associated With Chronic Obstructive Pulmonary Disease in a Rapidly Aging Society: Korea National Health and Nutrition Examination Survey 2015-2019

BACKGROUND

The prevalence of chronic obstructive pulmonary disease (COPD) increases with age, and aging is an important risk factor for COPD development. In the era of global aging, demographic information about the prevalence of and factors associated with COPD are important to establish COPD care plans. However, limited information is available in rapidly aging societies, including Korea.

METHODS

We conducted a cross-sectional observational study using Korea National Health and Nutrition Examination Survey data from 2015-2019. We included 15,613 participants and analyzed trends of and factors associated with COPD.

RESULTS

During the study period, the overall prevalence of COPD was 12.9%. Over five years, the yearly prevalence of COPD was fairly constant, ranging from 11.5% to 13.6%. Among individuals aged ≥ 70 years, nearly one-third met COPD diagnostic criteria. In the multivariable analysis, age 70 years or older was the most strong factor associated with COPD (adjusted odds ratio [aOR], 17.86; 95% confidence interval [CI], 14.16-22.52; compared with age 40-49), followed by asthma (aOR, 3.39; 95% CI, 2.44-4.71), male sex (aOR, 2.64; 95% CI, 2.18-3.19), and current smokers (aOR, 2.60; 95% CI, 2.08-3.25). Additionally, ex-smokers, low income, decreased forced expiratory volume in 1 second %pred, and a history of pulmonary tuberculosis were associated with COPD. On the other hand, body mass index (BMI) ≥ 25 kg/m² (aOR, 0.62; 95% CI, 0.54-0.71; compared with BMI 18.5-24.9 kg/m²) had an inverse association with COPD.

CONCLUSION

Recent trends in the prevalence of COPD in South Korea are relatively stable. Approximately one-third of participants aged 70 years and older had COPD. Aging was the most important factor associated with COPD.

Investigation of time profile of FEV1 across the onset of potential COPD: a retrospective cohort study using medical checkup data in Japan

This study compared the time profile of FEV₁ after COPD diagnosis among rapid decliners, slow decliners, and sustainers in the year of COPD diagnosis. COPD subjects were identified from the annual medical checkup records of Hitachi, Ltd., employees in Japan (April 1998-March 2019). Subjects were categorized into 3 groups (rapid decliner [decrease of FEV₁ ≥ 63 mL/year], slow decliner [< 63 and ≥ 31 mL/year], and sustainer [< 31 mL/year]) for 5 years. The time profile of FEV₁ was compared using mixed-effects model for 5 years after diagnosis; risk factors of rapid decliner were detected using logistic model/gradient boosting decision tree. Of 1294 eligible subjects, 18.6%, 25.7%, and 55.7% were classified as rapid decliners, slow decliners, and sustainers, respectively. The annual rates of FEV₁ decline were similar 3 years before and until COPD diagnosis. The mean FEV₁ in rapid decliners was 2.82 ± 0.04 L in year 0 and 2.41 ± 0.05 L in year 5, and in sustainers, it was 2.67 ± 0.02 L and 2.72 ± 0.02 L (year 0, p = 0.0004). In conclusion, FEV₁ declined yearly before diagnosis and the time profiles of FEV₁ were different in the 3 groups after COPD diagnosis. Therefore, appropriate treatment of the 3 groups with regular lung function tests is necessary to follow FEV₁ decline after COPD onset.

Polycyclic aromatic hydrocarbon exposure burden: Individual and mixture analyses of associations with chronic obstructive pulmonary disease risk

Accumulating data demonstrate that polycyclic aromatic hydrocarbons (PAH) exposure is linked to compromised respiratory diseases. This study aimed to analyze urinary PAH metabolites and their associations with chronic obstructive pulmonary disease (COPD) in a sample size of 3015 subjects from a total population of 50,588 from the National Health and Nutrition Examination Survey (NHANES) in 2007-2016. Results showed that the most predominant metabolite was 1-Hydroxynaphthalene (1-NAP, 84%) with a geometric mean concentration of 50,265 ng/L, followed by its homologue 2-NAP (10%), both of which arose from sources including road emission, smoking and cooking. Multiple logistic regression showed that seven of the ten major PAH metabolites were correlated with increased COPD risk: including 1-NAP (OR: 1.83, 95%CI: 1.25, 2.69), 2-Hydroxyfluorene (2-FLU, OR: 2.29, 95%CI: 1.42, 3.68) and 1-Hydroxyphenanthrene (1-PHE, OR: 2.79, 95%CI: 1.85, 4.21), when compared to the lowest tertile after adjusted for covariates. Total exposure burden per PAH congener sub-group demonstrated persistent positive correlation with COPD for ∑PHE (OR: 1.80, 95%CI: 1.34, 2.43) and ∑FLU (OR: 2.74, 95%CI: 1.77, 4.23) after adjusted for covariates. To address the contribution of PAH exposure as mixture towards COPD, weighted quantile sum (WQS) regression analyses revealed that 1-NAP, 9-Hydroxyfluorene (9-FLU), 3-Hydroxyfluorene (3-FLU) and 1-PHE were among the top contributors in the associations with COPD. Our results demonstrate the contemporary yet ongoing exposure burden of PAH exposure for over a decade, particularly towards NAPs and FLUs that contribute significantly to COPD risk, calling for more timely environmental regulation.

Investigating the Effect of Welding Fume in Pulmonary Function of Welders in an Automobile Industry

Context

Respiratory exposure to welding fumes directly or indirectly, in the long run, can lead to systematic effects among welders.

Aims

This study aimed to investigate respiratory symptoms and pulmonary function parameters among welders working in the automotive industry.

Material and Methods

This cross-sectional study was performed among 2304 workers from two groups in the manufacturing and administrative staff (as exposure and control groups). Pulmonary function parameters and respiratory symptoms were collected through periodic spirometry examinations and a standard respiratory symptoms questionnaire. Exposure to welding fumes was obtained from the annual measurement data based on the NIOSH7300 method. Data were analyzed using SPSS software version 22 and linear and multiple regression statistical tests.

Results

The mean age of the subjects in the case and control groups were 37.5 and 38.5 years, respectively. All the apparent symptoms of respiratory diseases (cough, sputum) in the welder's group were more than in the control group. Also, there was a significant difference between the respiratory symptoms in the two groups (P < 0.001). The mean value of all spirometric parameters (FVC, FEV1, FEV1/FVC, FEF25-75, PEF) in the case group (welders) was significantly lower than the control group.

Conclusion

The results of this study revealed that the variables of age and work experience effectively reduce all spirometric parameters of welders. Also, regarding the effect of metal vapors, a significant relationship has been seen between Cu in welding fume and FEF25-75 and FEV1 spirometric parameters.

CT pectoralis muscle area is associated with DXA lean mass and correlates with emphysema progression in a tobacco-exposed cohort

INTRODUCTION

Muscle loss is an important extrapulmonary manifestation of COPD. Dual energy X-ray absorptiometry (DXA) is the method of choice for body composition measurement but is not widely used for muscle mass evaluation. The pectoralis muscle area (PMA) is quantifiable by CT and predicts cross-sectional COPD-related morbidity. There are no studies that compare PMA with DXA measures or that evaluate longitudinal relationships between PMA and lung disease progression.

METHODS

Participants from our longitudinal tobacco-exposed cohort had baseline and 6-year chest CT (n=259) and DXA (n=164) data. Emphysema was quantified by CT density histogram parenchymal scoring using the 15th percentile technique. Fat-free mass index (FFMI) and appendicular skeletal mass index (ASMI) were calculated from DXA measurements. Linear regression model relationships were reported using standardised coefficient (β) with 95% CI.

RESULTS

PMA was more strongly associated with DXA measures than with body mass index (BMI) in both cross-sectional (FFMI: β=0.76 (95% CI 0.65 to 0.86), p<0.001; ASMI: β=0.76 (95% CI 0.66 to 0.86), p<0.001; BMI: β=0.36 (95% CI 0.25 to 0.47), p<0.001) and longitudinal (ΔFFMI: β=0.43 (95% CI 0.28 to 0.57), p<0.001; ΔASMI: β=0.42 (95% CI 0.27 to 0.57), p<0.001; ΔBMI: β=0.34 (95% CI 0.22 to 0.46), p<0.001) models. Six-year change in PMA was associated with 6-year change in emphysema (β=0.39 (95% CI 0.23 to 0.56), p<0.001) but not with 6-year change in airflow obstruction.

CONCLUSIONS

PMA is an accessible measure of muscle mass and may serve as a useful clinical surrogate for assessing skeletal muscle loss in smokers. Decreased PMA correlated with emphysema progression but not lung function decline, suggesting a difference in the pathophysiology driving emphysema, airflow obstruction and comorbidity risk.

Sex-specific non-linear associations between body mass index and impaired pulmonary ventilation function in a community-based population: Longgang COPD study

Aim: To investigate the prevalence of pulmonary airflow limitation and its association with body mass index (BMI) in a community-based population in Shenzhen, China.

Methods: Study participants were recruited from Nanlian Community in Shenzhen, China, and spirometry was performed to assess lung function including forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), FEV1/FVC ratio, and FEV1 divided by predicted value. Pulmonary airflow limitation was determined by the Chinese Guideline of Pulmonary Function Examination. Multivariable logistic regression models were used to examine the association between BMI and pulmonary airflow limitation. Age, sex, educational attainment, occupation, and current cigarette smoking were used as potential confounders.

Results: Of the 1206 participants, 612 (50.7%) were men and 594 (49.3%) were women with the average age being 53.7 years old. After adjusting for age, sex, educational attainment, occupation, and current cigarette smoking, higher BMI was associated with lower odds (odds ratio: 0.98, 95% confidence interval: 0.97, 0.99) of pulmonary airflow limitation by assuming a linear relationship. Further investigation of the interaction terms, we found that the magnitudes of the associations differed in men and women. A U-shaped relationship was observed in women, while the association was almost linear in men.

Conclusion: The relationship between BMI and pulmonary airflow limitation was U-shaped in women and linear in men.

Mediterranean Diet and Lung Function in Adults Current Smokers: A Cross-Sectional Analysis in the MEDISTAR Project

BACKGROUND

Previous studies have shown that adherence to the Mediterranean Diet (MeDi) has a positive impact on lung function in subjects with lung disease. In subjects free of respiratory diseases, but at risk, this association is not yet well established.

METHODS

Based on the reference data from the MEDISTAR clinical trial (Mediterranean Diet and Smoking in Tarragona and Reus; ISRCTN 03.362.372), an observational study was conducted with 403 middle-aged smokers without lung disease, treated at 20 centres of primary care in Tarragona (Catalonia, Spain). The degree of MeDi adherence was evaluated according to a 14-item questionnaire, and adherence was defined in three groups (low, medium, and high). Lung function were assessed by forced spirometry. Logistic regression and linear regression models were used to analyse the association between adherence to the MeDi and the presence of ventilatory defects.

RESULTS

Globally, the pulmonary alteration prevalence (impaired FEV1 and/or FVC) was 28.8%, although it was lower in participants with medium and high adherence to the MeDi, compared to those with a low score (24.2% and 27.4% vs. 38.5%, p = 0.004). Logistic regression models showed a significant and independent association between medium and high adherence to the MeDi and the presence of altered lung patterns (OR 0.467 [95%CI 0.266, 0.820] and 0.552 [95%CI 0.313, 0.973], respectively).

CONCLUSIONS

MeDi adherence is inversely associated with the risk impaired lung function. These results indicate that healthy diet behaviours can be modifiable risk factors to protect lung function and reinforce the possibility of a nutritional intervention to increase adherence to MeDi, in addition to promoting smoking cessation.

Rapid FEV1/FVC Decline Is Related With Incidence of Obstructive Lung Disease and Mortality in General Population

BACKGROUND

Forced expiratory volume in 1 second (FEV₁)/forced vital capacity (FVC) naturally decreases with age; however, an excessive decline may be related with increased morbidity and mortality. This study aimed to evaluate the FEV₁/FVC decline rate in the Korean general population and to identify whether rapid FEV₁/FVC decline is a risk factor for obstructive lung disease (OLD) and all-cause and respiratory mortality.

METHODS

We evaluated individuals aged 40-69 years who underwent baseline and biannual follow-up spirometric assessments for up to 18 years, excluding those with airflow limitations at baseline. Based on the quartiles of the annual FEV₁/FVC decline rate, the most negative FEV₁/FVC change (1^st quartile of annual FEV₁/FVC decline rate) was classified as rapid FEV₁/FVC decline. We investigated the risk of progression to OLD and all-cause and respiratory mortality in individuals with rapid FEV₁/FVC decline.

RESULTS

The annual FEV₁/FVC decline rate in the eligible 7,768 patients was 0.32 percentage point/year. The incidence rate of OLD was significantly higher in patients with rapid FEV₁/FVC decline than in those with non-rapid FEV₁/FVC decline (adjusted incidence rate, 2.119; 95% confidence interval [CI], 1.932-2.324). Rapid FEV₁/FVC decline was an independent risk factor for all-cause mortality (adjusted hazard [HR], 1.374; 95% CI, 1.105-1.709) and respiratory mortality (adjusted HR, 1.353; 95% CI, 1.089-1.680).

CONCLUSION

The annual FEV₁/FVC decline rate was 0.32%p in the general population in Korea. The incidence rate of OLD and the hazards of all-cause and respiratory mortality were increased in rapid FEV₁/FVC decliners.

Longitudinal association between adiposity changes and lung function deterioration

BACKGROUND

The longitudinal relationship between adiposity and lung function is controversial. We aimed to investigate the long-term association between adiposity changes and lung function in a middle-aged general Asian population.

METHODS

In total, 5011 participants (average age, 54 years; 45% men) were enrolled from a community-based prospective cohort. During the follow-up period (median 8 years), both spirometry and bio-electrical impedance analysis were performed biannually. Individual slopes of the fat mass index (FMI; fat mass divided by the square of height in meters) and waist-to-hip ratio (WHR) were calculated using linear regression analysis. Multivariate linear mixed regression analysis was used to determine the long-term association between adiposity changes and lung function.

RESULTS

The FMI was inversely associated with forced vital capacity (FVC) (estimated: - 31.8 mL in men, - 27.8 mL in women) and forced expiratory volume in 1 s (FEV₁) (estimated: - 38.2 mL in men, - 17.8 mL in women) after adjusting for baseline age, height, residential area, smoking exposure (pack-years, men only), initial adiposity indices, and baseline lung function. The WHR was also inversely associated with FVC (estimated = - 1242.2 mL) and FEV₁ (estimated = - 849.8 mL) in men. The WHR-increased group showed a more rapid decline in lung function than the WHR-decreased group in both the fat-gain and fat-loss groups.

CONCLUSION

Adiposity was associated with the long-term impairment of lung function. Central obesity was the main driver of lung function impairment in the middle-aged general Asian population, regardless of fat mass changes.

Genetic polymorphisms in MIR1208 and MIR5708 are associated with susceptibility to COPD in the Chinese population

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a complex disease characterized by limited airflow and is influenced by genetic and environmental factors. The purpose of this study was to investigate the effects of gene polymorphisms in MIR5708 and MIR1208 on COPD risk.

METHODS

Four single nucleotide polymorphisms (SNPs) in MIR5708 (rs6473227 and rs16907751) and MIR1208 (rs2608029 and rs13280095) were selected and genotyped among 315 COPD patients and 314 healthy controls using the Agena MassARRAY platform. SPSS 18.0 was used for statistical analysis and data processing. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the association between genetic variants of MIR1208 and MIR5708 and COPD risk.

RESULTS

The results suggested that rs16907751 variants in MIR5708 contributed to an increased susceptibility to COPD in the allelic (P = 0.001), co-dominant (homozygous) (P = 0.001), dominant (P = 0.017), recessive (P = 0.002), and additive (P = 0.002) models. The effects of MIR5708 and MIR1208 gene polymorphisms on the risk of COPD were age-, sex-, smoking status-, and BMI-related. Furthermore, the C-A and G-A haplotypes of rs2608029 and rs13280095 in MIR1208 were identified as risk factors for COPD in the population over 70 years (P = 0.029) and in women (P = 0.049), respectively. Finally, significant associations between rs16907751genotypes with pulse rate and forced expiratory volume in 1 s were found among COPD patients.

CONCLUSION

Genetic polymorphisms in MIR5708 and MIR1208 are associated with increased risk of COPD in China.

The Overweight Paradox: Impact of Body Mass Index on Patients Undergoing VATS Lobectomy or Segmentectomy

The aim of this study was to assess the impact of BMI on perioperative outcomes in patients undergoing VATS lobectomy or segmentectomy. Data from 5088 patients undergoing VATS lobectomy or segmentectomy, included in the VATS Group Italian Registry, were collected. BMI (kg/m²) was categorized according to the WHO classes: underweight, normal, overweight, obese. The effects of BMI on outcomes (complications, 30-days mortality, DFS and OS) were evaluated with a linear regression model, and with a logistic regression model for binary endpoints. In overweight and obese patients, operative time increased with BMI value. Operating room time increased by 5.54 minutes (S.E. = 1.57) in overweight patients, and 33.12 minutes (S.E. = 10.26) in obese patients (P < 0.001). Compared to the other BMI classes, overweight patients were at the lowest risk of pulmonary, acute cardiac, surgical, major, and overall postoperative complications. In the overweight range, a BMI increase from 25 to 29.9 did not significantly affect the length of stay, nor the risk of any complications, except for renal complications (OR: 1.55; 95% CI: 1.07-2.24; P = 0.03), and it reduced the risk of prolonged air leak (OR: 0.8; 95% CI: 0.71-0.90; P < 0.001). 30-days mortality is higher in the underweight group compared to the others. We did not find any significant difference in DFS and OS. According to our results, obesity increases operating room time for VATS major lung resection. Overweight patients are at the lowest risk of pulmonary, acute cardiac, surgical, major, and overall postoperative complications following VATS resections. The risk of most postoperative complications progressively increases as the BMI deviates from the point at the lowest risk, towards both extremes of BMI values. Thirty days mortality is higher in the underweight group, with no differences in DFS and OS.

The Overlap Syndrome of Obstructive Sleep Apnea and Chronic Obstructive Pulmonary Disease: A Systematic Review

Chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea (OSA) are common diseases that strongly impact the quality and length of life. Their coexistence is determined by overlap syndrome (OS). This systematic review aims to define the significance of these comorbidities according to the current state of knowledge. For this systematic review, we searched PubMed, Scopus, and Cochrane for studies published between 2018 and 26 October 2022, to find original, observational, human studies published in English, where the diagnosis of COPD was according to the Global Initiative for Obstructive Lung Disease guidelines and the diagnosis of OSA was based on polysomnography. The quality of studies was assessed using the Newcastle-Ottawa quality assessment tool for cohort and case-control studies, as well as its modification for cross-sectional studies. Of the 1548 records identified, 38 were eligible and included in this systematic review. The included studies covered a total population of 27,064 participants. This paper summarizes the most important, up-to-date information regarding OS, including the prevalence, meaning of age/gender/body mass index, polysomnography findings, pulmonary function, comorbidities, predicting OSA among COPD patients, and treatment of this syndrome.

Clustering-based COPD subtypes have distinct longitudinal outcomes and multi-omics biomarkers

Introduction

Chronic obstructive pulmonary disease (COPD) can progress across several domains, complicating the identification of the determinants of disease progression. In our previous work, we applied k-means clustering to spirometric and chest radiological measures to identify four COPD-related subtypes: ‘relatively resistant smokers (RRS)’, ‘mild upper lobe-predominant emphysema (ULE)’, ‘airway-predominant disease (AD)’ and ‘severe emphysema (SE)’. In the current study, we examined the associations of these subtypes to longitudinal COPD-related health measures as well as blood transcriptomic and plasma proteomic biomarkers.

Methods

We included 8266 non-Hispanic white and African-American smokers from the COPDGene study. We used linear regression to investigate cluster associations to 5-year prospective changes in spirometric and radiological measures and to gene expression and protein levels. We used Cox-proportional hazard test to test for cluster associations to prospective exacerbations, comorbidities and mortality.

Results

The RRS, ULE, AD and SE clusters represented 39%, 15%, 26% and 20% of the studied cohort at baseline, respectively. The SE cluster had the greatest 5-year FEV₁ (forced expiratory volume in 1 s) and emphysema progression, and the highest risks of exacerbations, cardiovascular disease and mortality. The AD cluster had the highest diabetes risk. After adjustments, only the SE cluster had an elevated respiratory mortality risk, while the ULE, AD and SE clusters had elevated all-cause mortality risks. These clusters also demonstrated differential protein and gene expression biomarker associations, mostly related to inflammatory and immune processes.

Conclusion

COPD k-means subtypes demonstrate varying rates of disease progression, prospective comorbidities, mortality and associations to transcriptomic and proteomic biomarkers. These findings emphasise the clinical and biological relevance of these subtypes, which call for more study for translation into clinical practice.

Trail registration number

NCT00608764.

Machine Learning Prediction of Progression in Forced Expiratory Volume in 1 Second in the COPDGene® Study

BACKGROUND

The heterogeneous nature of chronic obstructive pulmonary disease (COPD) complicates the identification of the predictors of disease progression. We aimed to improve the prediction of disease progression in COPD by using machine learning and incorporating a rich dataset of phenotypic features.

METHODS

We included 4496 smokers with available data from their enrollment and 5-year follow-up visits in the COPD Genetic Epidemiology (COPDGene^®) study. We constructed linear regression (LR) and supervised random forest models to predict 5-year progression in forced expiratory in 1 second (FEV₁) from 46 baseline features. Using cross-validation, we randomly partitioned participants into training and testing samples. We also validated the results in the COPDGene 10-year follow-up visit.

RESULTS

Predicting the change in FEV₁ over time is more challenging than simply predicting the future absolute FEV₁ level. For random forest, R-squared was 0.15 and the area under the receiver operator characteristic (ROC) curves for the prediction of participants in the top quartile of observed progression was 0.71 (testing) and respectively, 0.10 and 0.70 (validation). Random forest provided slightly better performance than LR. The accuracy was best for Global initiative for chronic Obstructive Lung Disease (GOLD) grades 1-2 participants, and it was harder to achieve accurate prediction in advanced stages of the disease. Predictive variables differed in their relative importance as well as for the predictions by GOLD.

CONCLUSION

Random forest, along with deep phenotyping, predicts FEV₁ progression with reasonable accuracy. There is significant room for improvement in future models. This prediction model facilitates the identification of smokers at increased risk for rapid disease progression. Such findings may be useful in the selection of patient populations for targeted clinical trials.

Predicting COPD Progression in Current and Former Smokers Using a Joint Model for Forced Expiratory Volume in 1 Second and Forced Expiratory Volume in 1 Second to Forced Vital Capacity Ratio

Understanding baseline characteristics that can predict the progression of lung disease such as chronic obstructive pulmonary disease (COPD) for current or former smokers may allow for therapeutic intervention, particularly for individuals at high risk of rapid disease progression or transition from non-COPD to COPD. Classic diagnostic criteria for COPD and disease severity such as the Global Initiative for Chronic Obstructive Lung Disease document are based on forced expiratory volume in 1 second (FEV1) and FEV1 to forced vital capacity (FVC) ratio. Modeling changes in these outcomes jointly is beneficial given that they are correlated, and they are both required for specific disease classifications. Here, linear mixed models were used to model changes in FEV1 and FEV1/FVC jointly for 5- and 10-year intervals, using important baseline predictors to better understand the factors that affect disease progression. Participants with predicted loss of FEV1 and/or FEV1/FVC of at least 5% tended to have more emphysema, higher functional residual capacity, higher airway wall thickness as measured by Pi10, lower FVC to total lung capacity ratio and a lower body mass index at baseline, all relative to overall cohort averages. The model developed can be used to predict progression for any potential COPD individual, based on demographic, symptom, computed tomography, and comorbidity variables.

High-Density Lipoproteins: A Role in Inflammation in COPD

Chronic obstructive pulmonary disease (COPD) is a widespread disease associated with high rates of disability and mortality. COPD is characterized by chronic inflammation in the bronchi as well as systemic inflammation, which contributes significantly to the clinically heterogeneous course of the disease. Lipid metabolism disorders are common in COPD, being a part of its pathogenesis. High-density lipoproteins (HDLs) are not only involved in lipid metabolism, but are also part of the organism’s immune and antioxidant defense. In addition, HDL is a versatile transport system for endogenous regulatory agents and is also involved in the removal of exogenous substances such as lipopolysaccharide. These functions, as well as information about lipoprotein metabolism disorders in COPD, allow a broader assessment of their role in the pathogenesis of heterogeneous and comorbid course of the disease.

Association of geriatric syndromes in older adults with chronic obstructive pulmonary disease

Background

Geriatric syndromes (GS) are multi‐factorial conditions that make older adults vulnerable to morbidities and poor outcomes. The main objective was to observe the frequency of GS in older patients with COPD.

Methods

A case‐control study was conducted in the Geriatric department of a tertiary care hospital in India to evaluate geriatric syndromes including falls, cognitive impairment, frailty, functional impairment, urinary incontinence, malnutrition, and depression in patients with COPD and controls without COPD. The factors having a significant association with the occurrence of these GS in COPD patients were observed.

Results

In this study, 150 cases and 150 controls were included. The mean age of the participant was 65.85±5.54, with 76% males. Functional impairment, cognitive impairment, frailty, urinary incontinence, and malnutrition were significantly higher in COPD patients. The independent variables which increased the odds of geriatric syndromes were dyspnoea (≥2 mMRC grade) (AOR:3.54,95% CI:1.06‐11.8) and low socioeconomic status (AOR: 4.14, 95% CI: 1.03‐16.54), while male gender showed inverse association (AOR: 0.08,95% CI: 0.01‐0.99).

Conclusion

Geriatric syndromes are common in older COPD patients, and assessment for them should be done routinely in these patients.

Decline of Lung Function in Knee and Spine Osteoarthritis in the Korean Population: Cross-Sectional Analysis of Data from the Korea National Health and Nutrition Examination Survey

Background: Evidence on the close association between osteoarthritis (OA) and lung diseases is supported by the shared pathogenesis of the two diseases. We assessed the association between knee and spine OA and chronic obstructive pulmonary disease (COPD) in the Korean population. Methods: Using data from the Korea National Health and Nutrition Examination Survey (KNHANES) 2012, a total of 2006 subjects who underwent both plain radiography for assessment of knee and lumbar spine and spirometry analysis for lung function were analyzed. Radiographic severity grade for OA was assessed using the Kellgren−Lawrence (K-L) grading scale. COPD was defined as a ratio of forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) less than 0.7. Results: Subjects with spine OA had higher prevalence of COPD than controls (p < 0.001), but not knee OA (p = 0.990). FVC (L), FEV1 (L), and FVC/FEV1 (%) were significantly decreased in spine OA compared to in controls (p = 0.003, p < 0.001, and p < 0.001, respectively). FVC (L), FVC (%), FEV1 (L), and FEV1 (%) were significantly different between knee OA and controls. Univariate regression analysis showed that spine OA was significantly associated with COPD (OR 1.581, 95% CI 1.204−2.076, p = 0.001), but not knee OA. Multivariate analysis revealed that spine OA lost statistical significance for COPD. Conclusion: This study found that subjects with knee OA and spine OA had a decline of lung function compared to subjects without OA, although OA was not associated with COPD.

Association of Body Mass Index and Abdominal Obesity with the Risk of Airflow Obstruction: National Health and Nutrition Examination Survey (NHANES) 2007-2012

This study aimed to explore the relationship between body mass index (BMI) and abdominal obesity and the risk of airflow obstruction, based on the data from the 2007-2012 National Health and Nutrition Survey (NHANES). Logistic regression was applied to assess the relationships between BMI or abdominal obesity and the risk of airflow obstruction by the fixed ratio method and the lower limit of normal (LLN) method. We further used the restricted cubic splines with 3 knots located at the 5th, 50th, and 95th percentiles of the distribution to evaluate the dose-response relationship. A total of 12,865 individuals aged 20-80 years old were included. In the fixed ratio method, underweight was positively correlated with the risk of airflow obstruction, and overweight and obesity were negatively correlated with the risk of airflow obstruction. In the LLN method, the results were consistent with the fixed ratio method. Abdominal obesity was positively associated with the risk of airflow obstruction only in the fixed ratio method (OR: 1.41, 95% CI: 1.04-1.90). There was an additive interaction between underweight and smoking on airflow obstruction in both methods. Abdominal obesity and smoking had additive interactions in the LLN method. Dose-response analysis indicated that there was a non-linear trend between BMI and the risk of airflow obstruction (P_{for nonlinearity} < 0.01). Our study suggested that underweight and abdominal obesity were associated with the increased risk of airflow obstruction, and overweight and general obesity were associated with the decreased risk of airflow obstruction.

Reconsidering the Utility of Race-Specific Lung Function Prediction Equations

Rationale: African American individuals have worse outcomes in chronic obstructive pulmonary disease (COPD). Objectives: To assess whether race-specific approaches for estimating lung function contribute to racial inequities by failing to recognize pathological decrements and considering them normal. Methods: In a cohort with and at risk for COPD, we assessed whether lung function prediction equations applied in a race-specific versus universal manner better modeled the relationship between FEV₁, FVC, and other COPD outcomes, including the COPD Assessment Test, St. George's Respiratory Questionnaire, computed tomography percent emphysema, airway wall thickness, and 6-minute-walk test. We related these outcomes to differences in FEV₁ using multiple linear regression and compared predictive performance between fitted models using root mean squared error and Alpaydin's paired F test. Measurements and Main Results: Using race-specific equations, African American individuals were calculated to have better lung function than non-Hispanic White individuals (FEV₁, 76.8% vs. 71.8% predicted; P = 0.02). Using universally applied equations, African American individuals were calculated to have worse lung function. Using Hankinson's Non-Hispanic White equation, FEV₁ was 64.7% versus 71.8% (P < 0.001). Using the Global Lung Initiative's Other race equation, FEV₁ was 70.0% versus 77.9% (P < 0.001). Prediction errors from linear regression were less for universally applied equations compared with race-specific equations when examining FEV₁% predicted with the COPD Assessment Test (P < 0.01), St. George's Respiratory Questionnaire (P < 0.01), and airway wall thickness (P < 0.01). Although African American participants had greater adversity (P < 0.001), less adversity was only associated with better FEV₁ in non-Hispanic White participants (P for interaction = 0.041). Conclusions: Race-specific equations may underestimate COPD severity in African American individuals.Clinical trial registered with www.clinicaltrials.gov (NCT01969344).

Association between body composition, sarcopenia and pulmonary function in chronic obstructive pulmonary disease

Background

Chronic Obstructive Pulmonary Disease (COPD) is characterized by progressive and irreversible airflow limitation. Different factors that modify pulmonary function include age, sex, muscular strength, and a history of exposure to toxic agents. However, the impact of body composition compartments and sarcopenia on pulmonary function is not well-established. This study aimed to evaluate how body composition compartments and sarcopenia affect pulmonary function in COPD patients.

Methods

In a cross-sectional study, patients with a confirmed diagnosis of COPD, > 40 years old, and forced expiratory volume in the first second /forced vital capacity ratio (FEV₁/FVC) < 0.70 post-bronchodilator were included. Patients with cancer, HIV, and asthma were excluded. Body composition was measured with bioelectrical impedance. Sarcopenia was defined according to EWGSOP2, and pulmonary function was assessed by spirometry.

Results

185 patients were studied. The mean age was 72.20 ± 8.39 years; 55.14% were men. A linear regression adjusted model showed associations between body mass index, fat-free mass, skeletal muscle mass index, appendicular skeletal muscle mass index, and phase angle (PhA), and sarcopenia with FEV₁ (%). As regards FVC (%), PhA and exercise tolerance had positive associations.

Conclusion

Body composition, especially PhA, SMMI, ASMMI, and sarcopenia, has a significant impact on pulmonary function. Early detection of disturbances of these indexes enables the early application of such therapeutic strategies in COPD patients.

Respiratory diseases and obesity: special phenotype or independent events: Review

A combination of factors, including Western European eating habits, physical inactivity and genetic predisposition, lead to a dramatic increase in adipose tissue mass. A special place is occupied by abdominal obesity, in which there is an accumulation of adipose tissue in the mesentery of the small intestine and the omentum. Developing in conditions of visceral obesity, insulin resistance, dyslipidemia and systemic inflammation are one of the key components of the pathogenesis of type 2 diabetes mellitus, cardiovascular diseases, non-alcoholic fatty liver and pancreas disease, polycystic ovary disease, some forms of cancer (breast cancer, endometrial cancer, colonic and direct intestines). At the same time, the pathogenetic role of adipose tissue is not limited to its participation in the formation of the cardiometabolic continuum and oncogenesis. The most important role of metabolically active fat in the pathogenesis of many respiratory diseases is known, including bronchial asthma, obstructive sleep apnea and pulmonary hypertension. This paper presents an overview of current data on immunological, pathophysiological and clinical features of the phenotype of the combination of respiratory diseases with overweight and obesity.

Coping With Stress: The Mitokine GDF-15 as a Biomarker of COVID-19 Severity

Growth differentiation factor 15 (GDF-15) is a transforming growth factor (TGF)-β superfamily cytokine that plays a central role in metabolism regulation. Produced in response to mitochondrial stress, tissue damage or hypoxia, this cytokine has emerged as one of the strongest predictors of disease severity during inflammatory conditions, cancers and infections. Reports suggest that GDF-15 plays a tissue protective role via sympathetic and metabolic adaptation in the context of mitochondrial damage, although the exact mechanisms involved remain uncertain. In this review, we discuss the emergence of GDF-15 as a distinctive marker of viral infection severity, especially in the context of COVID-19. We will critically review the role of GDF-15 as an inflammation-induced mediator of disease tolerance, through metabolic and immune reprogramming. Finally, we discuss potential mechanisms of GDF-15 elevation during COVID-19 cytokine storm and its limitations. Altogether, this cytokine seems to be involved in disease tolerance to viral infections including SARS-CoV-2, paving the way for novel therapeutic interventions.

Systemic Inflammatory Biomarkers Define Specific Clusters in Patients with Bronchiectasis: A Large-Cohort Study

Differential phenotypic characteristics using data mining approaches were defined in a large cohort of patients from the Spanish Online Bronchiectasis Registry (RIBRON). Three differential phenotypic clusters (hierarchical clustering, scikit-learn library for Python, and agglomerative methods) according to systemic biomarkers: neutrophil, eosinophil, and lymphocyte counts, C reactive protein, and hemoglobin were obtained in a patient large-cohort (n = 1092). Clusters #1–3 were named as mild, moderate, and severe on the basis of disease severity scores. Patients in cluster #3 were significantly more severe (FEV1, age, colonization, extension, dyspnea (FACED), exacerbation (EFACED), and bronchiectasis severity index (BSI) scores) than patients in clusters #1 and #2. Exacerbation and hospitalization numbers, Charlson index, and blood inflammatory markers were significantly greater in cluster #3 than in clusters #1 and #2. Chronic colonization by Pseudomonas aeruginosa and COPD prevalence were higher in cluster # 3 than in cluster #1. Airflow limitation and diffusion capacity were reduced in cluster #3 compared to clusters #1 and #2. Multivariate ordinal logistic regression analysis further confirmed these results. Similar results were obtained after excluding COPD patients. Clustering analysis offers a powerful tool to better characterize patients with bronchiectasis. These results have clinical implications in the management of the complexity and heterogeneity of bronchiectasis patients.

Deep learning methods may not outperform other machine learning methods on analyzing genomic studies

Deep Learning (DL) has been broadly applied to solve big data problems in biomedical fields, which is most successful in image processing. Recently, many DL methods have been applied to analyze genomic studies. However, genomic data usually has too small a sample size to fit a complex network. They do not have common structural patterns like images to utilize pre-trained networks or take advantage of convolution layers. The concern of overusing DL methods motivates us to evaluate DL methods' performance versus popular non-deep Machine Learning (ML) methods for analyzing genomic data with a wide range of sample sizes. In this paper, we conduct a benchmark study using the UK Biobank data and its many random subsets with different sample sizes. The original UK Biobank data has about 500k participants. Each patient has comprehensive patient characteristics, disease histories, and genomic information, i.e., the genotypes of millions of Single-Nucleotide Polymorphism (SNPs). We are interested in predicting the risk of three lung diseases: asthma, COPD, and lung cancer. There are 205,238 participants have recorded disease outcomes for these three diseases. Five prediction models are investigated in this benchmark study, including three non-deep machine learning methods (Elastic Net, XGBoost, and SVM) and two deep learning methods (DNN and LSTM). Besides the most popular performance metrics, such as the F1-score, we promote the hit curve, a visual tool to describe the performance of predicting rare events. We discovered that DL methods frequently fail to outperform non-deep ML in analyzing genomic data, even in large datasets with over 200k samples. The experiment results suggest not overusing DL methods in genomic studies, even with biobank-level sample sizes. The performance differences between DL and non-deep ML decrease as the sample size of data increases. This suggests when the sample size of data is significant, further increasing sample sizes leads to more performance gain in DL methods. Hence, DL methods could be better if we analyze genomic data bigger than this study.

A retrospective correlative profiling of lung functions, microbiological, radiological, periodontal, hematological parameters in noncystic fibrosis bronchiectasis patients of North India

Introduction:

Noncystic fibrosis bronchiectasis (NCFB) is a neglected debilitating condition with scarce epidemiological literature explaining its geographical heterogeneity, especially in lower and middle-income countries. This study aimed to assess and correlate the functional profile of NCFB patients and evaluate the correlation of body mass index (BMI) with several disease variables.

Methods:

This mixed-method retrospective research study was conducted on 124 radiologically confirmed NCFB patients in terms of various qualitative and quantitative variables.

Results:

Restrictive ventilatory defect was the most common type with the preponderance of male former smokers. Mean platelet lymphocyte ratio (PLR; 104.08 ± 73.59) revealed certain degree of systemic inflammatory burden with a slightly higher mean peripheral leukocyte count (10665.19 ± 4268.81 cell/mm³) and eosinophilia of >2%. Almost all patients had periodontal disease with a higher prevalence of chronic periodontitis (54.83%). Moderately severe and predominantly cystic radiological type was encountered with 61.2% patients positive for Pseudomonas aeruginosa. Bronchiectasis aetiology comorbidity index (BACI) i.e., 2.34 ± 2.37 represented an intermediate mortality risk in our patients. On basis of BMI, majority were young underweights with poor pulmonary functions while PLR skewed toward overweight patients (nonsignificant P > 0.05). Forced expiratory volume/forced vital capacity displayed a negative weak moderately significant correlation with BACI (r = −0.24; P = 0.008). Peripheral lymphocyte count demonstrated a weak negative but significant correlation with modified Reiff score (r = −0.20; P = 0.023) while serum neutrophil count had a weak negative moderately significant correlation with hemoglobin (r = −0.20; P = 0.023).

Conclusions:

NCFB bears great heterogeneity with distinct geographical phenotypes and should be correlated thoroughly in terms of peripheral leukocytes count, pulmonary functions, radiology, BMI, and coexisting comorbidities for adequate management.

Epidemiological evidence relating risk factors to chronic obstructive pulmonary disease in China: A systematic review and meta-analysis

BACKGROUND

Chronic obstructive pulmonary disease (COPD), the most common chronic respiratory disease worldwide, not only leads to the decline of pulmonary function and quality of life consecutively, but also has become a major economic burden on individuals, families, and society in China. The purpose of this meta-analysis was to explore the risk factors for developing COPD in the Chinese population that resides in China and to provide a theoretical basis for the early prevention of COPD.

METHODS

A total of 2457 cross-sectional, case-control, and cohort studies published related to risk factors for COPD in China were searched. Based on the inclusion and exclusion criteria, 20 articles were selected. Stata 11.0 was used for meta-analysis. After merging the data, the pooled effect and 95% confidence intervals (CIs) were calculated to assess the association between risk factors and COPD. Heterogeneity between studies was assessed using I2 and Cochran's Q tests. Begg's test was used to assess publication bias.

RESULTS

Exposure to particulate matter less than 2.5 μm in diameter (PM2.5) (pooled effect = 1.73; 95%CI: 1.16~2.58; P <0.01), smoking history (pooled effect = 2.58; 95%CI: 2.00~3.32; P <0.01), passive smoking history (pooled effect = 1.39; 95%CI: 1.03~1.87; P = 0.03), male sex(pooled effect = 1.70; 95%CI: 1.31~2.22; P <0.01), body mass index (BMI) <18.5 kg/m2 (pooled effect = 1.73; 95%CI: 1.32~2.25; P <0.01), exposure to biomass burning emissions (pooled effect = 1.65; 95%CI: 1.32~2.06; P <0.01), childhood respiratory infections (pooled effect = 3.44; 95%CI: 1.33~8.90; P = 0.01), residence (pooled effect = 1.24; 95%CI: 1.09~1.42; P <0.01), and a family history of respiratory diseases (pooled effect = 2.04; 95%CI: 1.53~2.71; P <0.01) were risk factors for COPD in the Chinese population.

CONCLUSION

Early prevention of COPD could be accomplished by quitting smoking, reducing exposure to air pollutants and biomass burning emissions, maintaining body mass index between 18.5 kg/m2 and 28 kg/m2, protecting children from respiratory infections, adopting active treatments to children with respiratory diseases, and conducting regular screening for those with family history of respiratory diseases.

Effects of Exercise Intervention on Peripheral Skeletal Muscle in Stable Patients With COPD: A Systematic Review and Meta-Analysis

Objectives: Peripheral skeletal muscle dysfunction is an important extrapulmonary manifestation of chronic obstructive pulmonary disease (COPD) that can be counteracted by exercise training. This study aimed to review the effect of three major exercise training modalities, which are used in pulmonary rehabilitation to improve on skeletal muscle mass, function, and exercise capacity in COPD.

Methods: PubMed, Embase, EBSCO, Web of Science, and the PEDro database were searched on April 25, 2020. Only randomized controlled studies published in English evaluating the effects of exercise interventions on peripheral skeletal muscle mass, strength, and exercise capacity in stable COPD patients were included. The quality of included studies was evaluated using the PEDro scale. The mean difference (MD) or the standardized mean difference (SMD) with 95% CI was calculated to summarize the results. Subgroup meta-analysis was used to investigate the effects of different exercise training modalities and different outcome measures. The Grading of Recommendations Assessment, Development, and Evaluation guidelines were used to rate evidence quality.

Results: A total of 30 randomized controlled trials involving 1,317 participants were included. Data from trials investigating endurance exercise (EE), resistance exercise (RE), and combined aerobic and resistance exercise (CE) were pooled into a meta-analysis, and the differences compared with the non-exercising COPD control were improvement in the muscle strength and exercise capacity in stable COPD patients. Subgroup meta-analysis for different exercise training modalities showed that RE significantly improved muscle strength (SMD = 0.6, 95% CI 0.35–0.84, I² = 61%), EE and CE significantly increased VO_2peak (EE: MD = 3.5, 95% CI 1.1–5.91, I² = 92%; CE: MD = 1.66, 95% CI 0.22–3.1, I² = 1%). Subgroup meta-analysis for different outcome measures showed that only isotonic strength was improved after exercise interventions (SMD = 0.89, 95% CI 0.51–1.26, I² = 71%).

Conclusion: Moderate evidence supports that exercise training in stable COPD patients has meaningful and beneficial effects on peripheral skeletal muscle strength and exercise capacity. Peripheral skeletal muscle shows a higher response to RE, and the isotonic test is relatively sensitive in reflecting muscle strength changes. The proportion of aerobic and resistance exercise components in a combined exercise program still needs exploration.

Systematic Review Registration: The review was registered with the PROSPERO: (The website is https://www.crd.york.ac.uk/PROSPERO/, and the ID is CRD42020164868).

Determinants of Pulmonary Emphysema Severity in Taiwanese Patients with Chronic Obstructive Pulmonary Disease: An Integrated Epigenomic and Air Pollutant Analysis

Background: Chronic obstructive pulmonary disease (COPD) continues to pose a therapeutic challenge. This may be connected with its nosological heterogeneity, broad symptomatology spectrum, varying disease course, and therapy response. The last three decades has been characterized by increased understanding of the pathobiology of COPD, with associated advances in diagnostic and therapeutic modalities; however, the identification of pathognomonic biomarkers that determine disease severity, affect disease course, predict clinical outcome, and inform therapeutic strategy remains a work in progress. Objectives: Hypothesizing that a multi-variable model rather than single variable model may be more pathognomonic of COPD emphysema (COPD-E), the present study explored for disease-associated determinants of disease severity, and treatment success in Taiwanese patients with COPD-E. Methods: The present single-center, prospective, non-randomized study enrolled 125 patients with COPD and 43 healthy subjects between March 2015 and February 2021. Adopting a multimodal approach, including bioinformatics-aided analyses and geospatial modeling, we performed an integrated analysis of selected epigenetic, clinicopathological, geospatial, and air pollutant variables, coupled with correlative analyses of time-phased changes in pulmonary function indices and COPD-E severity. Results: Our COPD cohort consisted of 10 non-, 57 current-, and 58 ex-smokers (median age = 69 ± 7.76 years). Based on the percentages of low attenuation area below − 950 Hounsfield units (%LAA_-950insp), 36 had mild or no emphysema (%LAA_-950insp < 6), 22 were moderate emphysema cases (6 ≤ %LAA_-950insp < 14), and 9 presented with severe emphysema (%LAA-950insp ≥ 14). We found that BMI, lnc-IL7R, PM_2.5, PM₁₀, and SO₂ were differentially associated with disease severity, and are highly-specific predictors of COPD progression. Per geospatial levels, areas with high BMI and lnc-IL7R but low PM_2.5, PM₁₀, and SO₂ were associated with fewer and ameliorated COPD cases, while high PM_2.5, PM₁₀, and SO₂ but low BMI and lnc-IL7R characterized places with more COPD cases and indicated exacerbation. The prediction pentad effectively differentiates patients with mild/no COPD from moderate/severe COPD cases, (mean AUC = 0.714) and exhibited very high stratification precision (mean AUC = 0.939). Conclusion: Combined BMI, lnc-IL7R, PM_2.5, PM₁₀, and SO₂ levels are optimal classifiers for accurate patient stratification and management triage for COPD in Taiwan. Low BMI, and lnc-IL7R, with concomitant high PM_2.5, PM₁₀, and SO₂ levels is pathognomonic of exacerbated/aggravated COPD in Taiwan.

Evaluation of the Clinical Effectiveness of the Salmeterol/Fluticasone Fixed-Dose Combination Delivered via the Elpenhaler® Device in Greek Patients with Chronic Obstructive Pulmonary Disease and Comorbidities: The AEOLOS Study

Background: Chronic Obstructive Pulmonary Disease (COPD) is an inflammatory lung disease characterized by airflow limitation that is not completely reversible. The fixed-dose combination of salmeterol and fluticasone propionate (SFC) has been approved as a treatment for COPD patients with a history of recurrent exacerbations and significant symptoms despite regular bronchodilator therapy. In the present study, we evaluated the change in FEV₁, mMRC dyspnea score and satisfaction in COPD patients with at least one comorbidity versus those without comorbidities treated with a fixed-dose SFC via the Elpenhaler^® device for 12 months. Methods: A 12-month multicenter prospective, observational study (NCT02978703) was designed. Data were collected during the enrollment visit (V0) and six (V1) and twelve months (V2) after the initiation of treatment with Elpenhaler^® SFC. The evaluation of the efficacy of the fixed-dose SFC was performed by assessing the change in lung function and dyspnea as expressed by FEV₁ and the mMRC dyspnea scale score in COPD patients with and without comorbidities. Results: In total 1016 patients were enrolled, following usual daily clinical practice. A statistically significant improvement was observed in FEV₁ in the total study population between visits V0, V1 and V2, with a change from the baseline at V1 0.15 ± 0.22 L and at V2 0.21 ± 0.25 L (p < 0.0001 for both comparisons). This improvement was exhibited regardless of the COPD severity at the baseline, being more noticeable in GOLD 2020 groups B and C. Similarly, a significant improvement was observed in mMRC dyspnea scale values between successive visits (p < 0.0001). In patients without comorbidities, there was a significant improvement in FEV₁ of 0.19 ± 0.24 L at V1 and 0.28 ± 0.27 L at V2 (p < 0.0001 for both comparisons), as well as in the mMRC dyspnea score (p < 0.0001). In patients with at least one comorbidity, a corresponding but smaller improvement in FEV₁ was observed (0.11 ± 0.34 L at V1 and 0.20 ± 0.42 L at V2; p < 0.0001 for both comparisons and in the mMRC score (p < 0.0001). In the multiple linear regression analysis BMI, GOLD 2020 groups, mMRC and the presence of comorbidities at the baseline were significant factors for the change of FEV₁ between V0 and V2. Conclusions: COPD patients treated for twelve months with SFC via the Elpenhaler^® device showed significant improvement in lung function and dyspnea at 6 and 12 months, irrespective of the presence of comorbidities.

The Association between Chronic Heroin Smoking and Chronic Obstructive Pulmonary Disease

INTRODUCTION

Little is known about the correlation between chronic obstructive pulmonary disease (COPD) and heroin smoking. Heroin smoking is a recent underinvestigated problem. The goal of this study is to study the impact of heroin smoking among COPD patients.

METHODS

This is a descriptive clinical study. A combination of self-reporting questionnaires and data extraction tools were used to collect information during baseline tests, interviews, and follow-ups. Patients' medical, clinical, and socioeconomic history were recorded. Participants were recruited using random sampling from multiple centers.

RESULTS

Out of 1034 COPD patients, heroin smokers represented the vast majority of addiction cases (n = 133). Heroin smokers were leaner than non-addicts (19.78 ± 4.07 and 24.01 ± 5.6, respectively). The most common type of comorbidities among heroin smokers was emphysema (27%). Both the forced expiratory volume (FEV₁)/forced vital capacity ratio and FEV1% predicted were lower among heroin smokers than non-addicts (52.79 ± 12.71 and 48.54 ± 14.38, respectively). The majority of heroin smokers (55%) had advanced COPD, and at least 15% of heroin smokers suffered from frequent respiratory failure. The mean ± SD for COPD onset age among heroin smokers was 44.23 ± 5.72, and it showed a statistically significant correlation (P < 0.001).

CONCLUSION

Heroin smoking might be linked to the onset of COPD. Heroin smokers showed a significantrespiratory impairment compared to tobacco smokers of the same age group.

COVID-19 infection, progression, and vaccination: Focus on obesity and related metabolic disturbances

Coronaviruses are constantly circulating in humans, causing common colds and mild respiratory infections. In contrast, infection with the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for coronavirus disease-2019 (COVID-19), can cause additional severe complications, particularly in patients with obesity and associated metabolic disturbances. Obesity is a principal causative factor in the development of the metabolic syndrome; a series of physiological, biochemical, clinical, and metabolic factors that increase the risk of obesity-associated diseases. "Metabolically unhealthy" obesity is, in addition to metabolic disturbances, also associated with immunological disturbances. As such, patients with obesity are more prone to develop serious complications from infections, including those from SARS-CoV-2. In this review, we first describe how obesity and related metabolic disturbances increase the risk of SARS-CoV-2 infection. Then, mechanisms contributing to COVID-19 complications and poor prognosis in these patients are discussed. Finally, we discuss how obesity potentially reduces long-term COVID-19 vaccination efficacy. Despite encouraging COVID-19 vaccination results in patients with obesity and related metabolic disturbances in the short-term, it is becoming increasingly evident that long-term COVID-19 vaccination efficacy should be closely monitored in this vulnerable group.

Long-term weight gain in obese COPD patients participating in a disease management program: a risk factor for reduced health-related quality of life

BACKGROUND

Little is known about how long-term weight gain affects the health perception of COPD patients.

OBJECTIVES

The aim is to evaluate the long-term association of BMI change and health-related quality of life (HRQoL) in obese COPD patients.

METHODS

Claims and survey data from a COPD disease management program were used to match two groups of COPD patients with BMI ≥ 30 who have differing weight trajectories over a 5-year timespan via propensity score and genetic matching. EQ-5D-5L, including visual analog scale (VAS) and COPD Assessment Test (CAT), were used as outcomes of interest. Sociodemographic and disease-based variables were matched.

RESULTS

Out of 1202 obese COPD patients, 126 with a weight increase of four or more BMI points were matched separately with 252 (propensity score matching) and 197 (genetic matching) control subjects who had relatively stable BMI. For the EQ-5D-5L, patients with BMI increase reported significantly worse health perception for VAS and all descriptive dimensions except pain/discomfort. For the CAT, especially the perception of ability to complete daily activities and overall energy results were significantly worse. VAS differences reach the range of minimal important differences. Stopping smoking and already being in obesity class II were the most influential risk factors for BMI increase.

CONCLUSION

Obese COPD patients who gain four or more BMI points over 5 years report significantly lower results in different dimensions of generic and disease-specific HRQoL than their peers with stable BMI. To improve real-world outcomes, tracking and preventing specific BMI trajectories could constitute a clinically relevant aspect of managing COPD patients.

Low body mass is associated with reduced left ventricular mass in Chinese elderly with severe COPD

There is limited information on the association of body mass index (BMI) with left ventricular (LV) remodeling corresponding to severity of reduced lung function in patients with chronic obstructive pulmonary disease (COPD). Therefore, we investigated whether BMI is associated with cardiac atrial and ventricular dimensions according to severity of lung functional impairment in Chinese COPD elderly. A total of 563 hospitalized COPD patients with lung function impairment and 184 patients with non-COPD (aged 65–92 years) were collected retrospectively in a cross-sectional study in a university affiliated tertiary hospital in China. BMI and cardiac echocardiographic parameters were compared according to severity of lung functional impairment in COPD patients. BMI was 22.9 ± 3.9 kg/m² in COPD patients, 24.0 ± 4.1 kg/m² in non-COPD patients respectively. Reduced BMI, LV mass index, LV wall thickness and left atrial diameter, and dilated right ventricle (RV) existed in COPD patients with severe lung dysfunction as compared the COPD patients with mild to moderate lung functional reduction and non-COPD patients (P < 0.05), while there were no differences in BMI and echocardiographic parameters between the COPD patients with mild to moderate lung functional decline and non-COPD patients (P > 0.05). Logistic regression analysis showed that low BMI (BMI < 18.5 kg/m²) was correlated with reduced LV mass and wall thickness, dilated RV and reduced lung function in the COPD patients with severe lung dysfunction. In conclusion, this study demonstrates that lower BMI is associated not only with dilated RV and impaired pulmonary function, but also it is related to reduced LV mass in Asian COPD elderly with severe lung dysfunction.

Temporal Associations Among Body Mass Index, Fasting Insulin, and Systemic Inflammation: A Systematic Review and Meta-analysis

IMPORTANCE

Obesity is associated with a number of noncommunicable chronic diseases and is purported to cause premature death.

OBJECTIVE

To summarize evidence on the temporality of the association between higher body mass index (BMI) and 2 potential mediators: chronic inflammation and hyperinsulinemia.

DATA SOURCES

MEDLINE (1946 to August 20, 2019) and Embase (from 1974 to August 19, 2019) were searched, although only studies published in 2018 were included because of a high volume of results. The data analysis was conducted between January 2020 and October 2020.

STUDY SELECTION AND MEASURES

Longitudinal studies and randomized clinical trials that measured fasting insulin level and/or an inflammation marker and BMI with at least 3 commensurate time points were selected.

DATA EXTRACTION AND SYNTHESIS

Slopes of these markers were calculated between time points and standardized. Standardized slopes were meta-regressed in later periods (period 2) with standardized slopes in earlier periods (period 1). Evidence-based items potentially indicating risk of bias were assessed.

RESULTS

Of 1865 records, 60 eligible studies with 112 cohorts of 5603 participants were identified. Most standardized slopes were negative, meaning that participants in most studies experienced decreases in BMI, fasting insulin level, and C-reactive protein level. The association between period 1 fasting insulin level and period 2 BMI was positive and significant (β = 0.26; 95% CI, 0.13-0.38; I2 = 79%): for every unit of SD change in period 1 insulin level, there was an ensuing associated change in 0.26 units of SD in period 2 BMI. The association of period 1 fasting insulin level with period 2 BMI remained significant when period 1 C-reactive protein level was added to the model (β = 0.57; 95% CI, 0.27-0.86). In this bivariable model, period 1 C-reactive protein level was not significantly associated with period 2 BMI (β = -0.07; 95% CI, -0.42 to 0.29; I2 = 81%).

CONCLUSIONS AND RELEVANCE

In this meta-analysis, the finding of temporal sequencing (in which changes in fasting insulin level precede changes in weight) is not consistent with the assertion that obesity causes noncommunicable chronic diseases and premature death by increasing levels of fasting insulin.

Ambient air quality and the risk for Chronic Obstructive Pulmonary Disease among Metro Manila Development Authority traffic enforcers in Metro Manila: An exploratory study

Background

Air pollution and poor ambient air quality are significantly related to multiple health risks. One associated disease is chronic obstructive pulmonary disease (COPD), a preventable disease with several contributing factors and one of the leading causes of morbidity/mortality locally and globally. A potentially high-risk population are traffic enforcers who are constantly exposed to air pollution. In the Philippines, the MMDA has the widest coverage in traffic management. The study determined the risk of COPD among Metro Manila Development Authority (MMDA) traffic enforcers in relation to ambient air quality level, as well as identified other factors that increase the risk of developing COPD.

Methods

Fifty-two MMDA traffic enforcers deployed in PM_2.5 air quality sensor areas in Metro Manila from 2016 to 2018 were recruited through stratified sampling. The International Primary Airways Guidelines (IPAG) questionnaire was utilized to measure risk of COPD. Respiratory health and working history were obtained through questionnaires. Department of environment and natural resources provided PM_2.5 ambient air quality data which aided in the construction of the Exposure-Month Index. Ordinal logistic regression was used to examine the association of PM_2.5 together with the relevant factors and the risk of COPD.

Results

We found statistically significant associations between PM_2.5 and COPD among high risk category [odds risk (OR): 1.24, 95% confidence interval (CI): 1.07-1.44]. Age (Moderate, OR: 1.16, 95% CI: 0.98-1.38 and High, OR: 10.06, 95% CI: 4.02-25.17) and chest pain (Moderate, OR: 68.65, 95% CI: 1.71-2.75 × 10³) were potential risk factors, whereas body mass index (BMI) (OR: 0.05, 95% CI: 0.01-0.53) exhibited protective effect.

Conclusions

Exposure to PM_2.5 was associated with an increased risk of COPD among high-risk category MMDA traffic enforcers. Age and chest pain were potential risk factors to risk of COPD, whereas BMI exhibited a potential protective effect. Results of this study can be used for clinical management of high-risk populations, such that of MMDA traffic enforcers.

Association of Body Mass Index with Risk of Chronic Obstructive Pulmonary Disease: A Systematic Review and Meta-Analysis

The association between body mass index (BMI) and chronic obstructive pulmonary disease (COPD) remains controversial. Therefore, a meta-analysis was conducted to further evaluate the relationship. A comprehensive literature search was performed in PubMed, Web of Science, EMBASE, China National Knowledge Infrastructure (CNKI), and Wanfang databases to identify eligible articles until July 15, 2020. Random effect model (REM) was used to compute the pooled results with 95% confidence intervals (CIs). We conducted meta-regression and subgroup analysis to explore potential sources of heterogeneity. Publication bias was evaluated by funnel plots and Egger's test. Thirty articles with 1,578,449 participants were included in the meta-analysis. The pooled OR of COPD was 1.96 (95% CI: 1.78-2.17) for the underweight group, 0.80 (95% CI: 0.73-0.87) for overweight group, and 0.86 (95% CI: 0.73-1.02) for obesity group. After further excluding 5 studies of high between-study heterogeneity in sensitivity analysis, the pooled OR of COPD was 0.77 (95% CI: 0.68-0.86) for the obesity group. This meta-analysis indicated that BMI was associated with COPD. Specifically, underweight might increase the risk of COPD; overweight and obesity might reduce the risk of COPD.