Self-reported smoking status and urinary cotinine levels in patients with asthma

Cigarette Smoke Particle-Induced Lung Injury and Iron Homeostasis

It is proposed that the mechanistic basis for non-neoplastic lung injury with cigarette smoking is a disruption of iron homeostasis in cells after exposure to cigarette smoke particle (CSP). Following the complexation and sequestration of intracellular iron by CSP, the host response (eg, inflammation, mucus production, and fibrosis) attempts to reverse a functional metal deficiency. Clinical manifestations of this response can present as respiratory bronchiolitis, desquamative interstitial pneumonitis, pulmonary Langerhans’ cell histiocytosis, asthma, pulmonary hypertension, chronic bronchitis, and pulmonary fibrosis. If the response is unsuccessful, the functional deficiency of iron progresses to irreversible cell death evident in emphysema and bronchiectasis. The subsequent clinical and pathological presentation is a continuum of lung injuries, which overlap and coexist with one another. Designating these non-neoplastic lung injuries after smoking as distinct disease processes fails to recognize shared relationships to each other and ultimately to CSP, as well as the common mechanistic pathway (ie, disruption of iron homeostasis).

Depression, suicidal motivation and suicidal ideation among individuals with asthma: a cross-sectional study

Background

Asthma is a chronic disease associated with risk of depression and suicidal events. The present study estimated the frequency of depression, suicidal motivation (SM) and suicidal ideation (SI) and identified clinical and psychosocial factors associated with these outcomes among individuals with asthma.

Methods

Cross-sectional study of a non-probabilistic sample of 1,358 adults with asthma and controls without asthma. Asthma severity and asthma control were assessed by a physician according to WHO (2009) and GINA (2012) criteria. Depression, SM and SI were screened by Beck Depression Inventory (BDI). Psychosocial factors were evaluated by a Community Violence Questionnaire, a Social Support Scale, a Stress Perceived Scale and a Resilience Scale. Chi-Square Test, and logistic regression models were performed to evaluate association between variables and outcomes.

Results

Among all participants, 222 (16.30%) had depression, 331 (24.40%) SM and 73 (5.40%) SI. There were 138 (12.10%) individuals with mild depression and SM, and 14 (1.20%) with mild depression and SI. After adjustment, severe asthma (SA) increased the chance of depression by 53.00% whereas mild to moderate asthma (MMA) increased by eleven-fold the likelihood of SI. Perception of low social support increased the chance of depression (OR 3.59; 95% CI, 2.44-5.28) and low resilience by (OR 2.96; 95% CI, 2.00-4.38); distress increased the odds of SM by 37.00%, and low affective support perception raised the likelihood of SI by (OR 6.82; 95% CI, 1.94-2.90).

Conclusions

Asthma, whether mild to moderate or severe, increased the chance of depression and SI. It is noteworthy that individuals with mild depression and MMA are at greater risk for SM and SI. Among the psychosocial variables, perception of low social support and low resilience were the variables associated with depression; distress impacted on SM, and the perception of low affective support raised the chance of SI.

Non-linear dose-response relation between urinary levels of nicotine and its metabolites and cognitive impairment among an elderly population in China

BACKGROUND

Active smoking and exposure to environmental tobacco smoke may be related to cognitive function decline. We assessed the associations of urinary levels of nicotine and its metabolites with cognitive function.

METHODS

A total of 553 elder adults at high risk of cognitive impairment and 2212 gender- and age-matched individuals at low risk of cognitive impairment were selected at a ratio of 1: 4 from the remained individuals (n = 6771) who completed the baseline survey of the Shenzhen Ageing-Related Disorder Cohort, after excluding those with either Alzheimer's disease, Parkinson's syndrome or stroke as well as those with missing data on variables (including active and passive smoking status, Mini-Cog score). Urinary levels of nicotine and its metabolites and cognitive function for all individuals were measured by high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) and assessed using the Mini-Cog test, respectively. Associations of urinary levels of nicotine and its metabolites with cognitive function were analyzed by conditional logistic regression models.

RESULTS

Individuals in the highest tertile of urinary OHCotGluc (OR: 1.52, 95%CI: 1.19-1.93) or NNO (OR: 1.50, 95%CI: 1.16-1.93) levels as well as in the second tertile of urinary ∑Nic level (OR: 1.43, 95%CI: 1.13-1.82) were at higher risk of cognitive impairment compared with those in the corresponding lowest tertile. Restricted cubic spline models revealed the non-linear dose-response relationships between urinary levels of OHCotGluc, NNO or ∑Nic and the risk of cognitive impairment.

CONCLUSIONS

Urinary levels of OHCotGluc, NNO or ∑Nic exhibited a non-linear dose-response relationship with cognitive function in the urban elderly.

The Influence of Smoking Status on Exhaled Breath Profiles in Asthma and COPD Patients

Breath analysis using eNose technology can be used to discriminate between asthma and COPD patients, but it remains unclear whether results are influenced by smoking status. We aim to study whether eNose can discriminate between ever- vs. never-smokers and smoking <24 vs. >24 h before the exhaled breath, and if smoking can be considered a confounder that influences eNose results. We performed a cross-sectional analysis in adults with asthma or chronic obstructive pulmonary disease (COPD), and healthy controls. Ever-smokers were defined as patients with current or past smoking habits. eNose measurements were performed by using the SpiroNose. The principal component (PC) described the eNose signals, and linear discriminant analysis determined if PCs classified ever-smokers vs. never-smokers and smoking <24 vs. >24 h. The area under the receiver–operator characteristic curve (AUC) assessed the accuracy of the models. We selected 593 ever-smokers (167 smoked <24 h before measurement) and 303 never-smokers and measured the exhaled breath profiles of discriminated ever- and never-smokers (AUC: 0.74; 95% CI: 0.66–0.81), and no cigarette consumption <24h (AUC 0.54, 95% CI: 0.43–0.65). In healthy controls, the eNose did not discriminate between ever or never-smokers (AUC 0.54; 95% CI: 0.49–0.60) and recent cigarette consumption (AUC 0.60; 95% CI: 0.50–0.69). The eNose could distinguish between ever and never-smokers in asthma and COPD patients, but not recent smokers. Recent smoking is not a confounding factor of eNose breath profiles.

Smoking status and second-hand smoke biomarkers in COPD, asthma and healthy controls

Introduction

Tobacco smoke worsens COPD and asthma. For healthy individuals, quantifying active and second-hand smoke (SHS) exposure clarifies the epidemiology of tobacco consumption and the efficacy of nonsmoking measures. Identifying tobacco exposure biomarkers and cut-offs might allow the creation of sensitive and specific tests.

Aim

We describe the state-of-the-art serum, urinary cotinine and exhaled carbon monoxide (CO) cut-offs for assessing smoking status and SHS exposure in adult patients with COPD or asthma, and healthy controls.

Methodology

After a keyword research in the PubMed database, we included papers reporting on the cut-offs of the investigated biomarkers in one of the populations of interest. Papers published before 2000, not in English, or reporting only data on nonadult subjects or on pregnant women were excluded from the analysis. 14 papers were included in the final analysis. We summarised diagnostic cut-offs for smoking status or SHS exposure in COPD, asthmatic and healthy control cohorts, reporting sensitivity and specificity when available.

Conclusion

Serum and urinary cotinine and exhaled CO are easy-to-standardise, affordable and objective tests for assessing smoking status and SHS exposure. Evidence on cut-offs with good sensitivity and specificity values is available mainly for healthy controls. For COPD and asthmatic patients, most of the currently available evidence focuses on exhaled CO, while studies on the use of cotinine with definite sensitivity and specificity values are still missing. Solid evidence on SHS exposure is available only for healthy controls. An integrated approach with a combination of these markers still needs evaluation.

Reliable cut-off values for smoking status in COPD and asthmatic adults are only available for exhaled COhttps://bit.ly/34lsHhD

Exposure to secondhand smoke among patients with asthma: a cross-sectional study

Objective

To estimate the frequency of secondhand smoke exposure among patients with asthma.

Methods

A cross-sectional study of asthma patients and non-asthmatic controls using questionnaires to identify secondhand smoke exposure at home, school, work, and public places.

Results

We studied 544 severe asthma patients, 452 mild/moderate asthma patients, and 454 non-asthmatic patients. Among severe patients, the mean age was 51.9 years, 444 (81.6%) were female, 74 (13.6%) were living with a smoker, 383 (71.9%) reported exposure in public spaces and, of the 242 (44.5%) who worked/ studied, 46 (19.1%) reported occupational exposure. Among those with mild/moderate asthma, the mean age was 36.8 years, 351 (77.7%) were female, 50 (11.1%) reported living with a smoker, 381 (84.9%) reported exposure in public settings and, of the 330 (73.0%) who worked/ studied, 58 (17.7%) reported occupational exposure. An association between secondhand smoke exposure and disease control was found among patients with mild/moderate asthma. Among those interviewed, 71% of severe asthma patients and 63% of mild/moderate asthma patients avoided certain places due to fear of secondhand smoke exposure.

Conclusion

Secondhand smoke exposure is a situation frequently reported by a significant proportion of asthma patients. Individuals with asthma are exposed to this agent, which can hamper disease control, exacerbate symptoms and pose unacceptable limitations to their right to come and go in public settings.

Severe asthma: Comparison of different classifications of severity and control

BACKGROUND

Criteria of asthma severity and control lack standardization.

OBJECTIVE

to compare classifications of asthma severity and control, applied to patients from a severe asthma clinic.

METHODS

Cross-sectional study of 473 patients followed up for ≥6 months, reclassified using three criteria: 1) the World Health Organization (WHO) 2010, 2) the American Thoracic Society (ATS) 2000, and 3) the European Respiratory Society (ERS)/ATS 2014. In order to evaluate disease control, the 2012 and 2014 Global Initiative for Asthma (GINA) classifications were compared.

RESULTS

According to the definition of WHO 2010, 429 had Difficult-to-treat severe asthma and only 12 presented Treatment-resistant severe asthma. 114 patients had Refractory asthma by ATS 2000 and 88 had Severe asthma by ERS/ATS 2014. Considering the definitions of WHO 2010, only 9 out of 12 with Treatment-resistant and 64 out of 429 with Difficult-to-treat severe asthma met the criteria of ATS 2000 and ERS/ATS 2014. As for GINA classification of control, 208 (44%) of the 473 subjects were classified as having asthma controlled by the 2014 criteria, whereas only 45 (10%) patients had controlled asthma by the GINA 2012 criteria. The Kappa statistic indicates the highest agreement of the severity classification occurred between the criteria of ATS 2000 and ERS/ATS 2014 (0.64).

CONCLUSION

Good agreement was found between Refractory asthma ATS 2000 and Severe asthma ERS/ATS 2014 classifications. However, poor agreement was observed between the severity rating proposed by the WHO and other classifications. The GINA control classifications of 2012 and 2014 also agreed poorly.