Cough in patients with lung cancer: a longitudinal observational study of characterisation and clinical associations.
Chest. 2018 Oct 12;:
Authors: Amélie Harle AS, Blackhall FH, Molassiotis A, Yorke J, Dockry R, Holt K, Yuill D, Baker K, Smith JA
BACKGROUND: Cough is common in patients with lung cancer and current antitussive treatments are suboptimal. There is little published data describing cough in patients with lung cancer or work assessing clinical associations; the aim of the current is study is to fill that gap.
METHODS: Longitudinal prospective observational single-cohort study over 60 days. Patients were assessed through self-reported validated scales and, in a subsample, ambulatory cough monitoring, at study entry (day 0), day 30 and day 60.
RESULTS: At study entry, 177 patients were included and 153 provided data at day 60. The median duration of cough was 52 weeks (IQR 8.5-260). Cough was described as severe enough to warrant treatment in 62% of the patients. Depending on the scale used, performance status was associated with both cough severity and cough impact (p<0.001) at study entry, while higher cough severity at study entry was associated with female sex (p=0.02), asthma (p=0.035), and reflux disease (p<0.001); cough impact at study entry was additionally associated with experiencing nausea (p=0.018). Cancer characteristics (i.e. cancer stage, histology) were not associated with cough severity nor cough impact; neither was smoking or COPD.
CONCLUSIONS: This is the first study to describe characteristics of cough in patients with lung cancer and identify clinical associations that may be relevant for its treatment. Our data suggest that cough is a frequent and distressing symptom, and an unmet clinical need. Its associationwith gastro-intestinal symptoms in this study may improve our understanding of pathophysiology and therapeutic options for cough occurring in patients with lung cancer.
PMID: 30321508 [PubMed - as supplied by publisher]
Severe Pertussis Infections in the United States, 2011-2015.
Clin Infect Dis. 2018 Oct 15;:
Authors: Mbayei SA, Faulkner A, Miner C, Edge K, Cruz V, Peña SA, Kudish K, Coleman J, Pradhan E, Thomas S, Martin S, Skoff TH
Background: The incidence of pertussis in the United States has increased in recent years. While characteristics of severe pertussis infection have been described in infants, fewer data are available in older children and adults. In this analysis, we characterize pertussis infections in hospitalized patients of all ages.
Methods: Cases of pertussis with cough onset from January 1, 2011 through December 31, 2015 from 7 U.S. Emerging Infections Program Network states were reviewed. Additional information on hospitalized patients was obtained through abstraction of the inpatient medical record. Descriptive and multivariable analyses were conducted to characterize severe pertussis infection and identify potential risk factors.
Results: Among 15,942 cases of pertussis reported, 515 (3.2%) were hospitalized. Three hospitalized patients died. Infants aged <2 months accounted for 1.6% of all pertussis cases but 29.3% of hospitalizations. Infants aged 2-11 months and adults aged ≥65 years also had high rates of hospitalization. Infants aged <2 months whose mothers received Tdap during the 3 rd trimester and children aged 2 months to 11 years who were up to date on pertussis-containing vaccines had a 43-66% reduced risk of hospitalization. Among adolescents aged 12-20 years, 43.5% had a history of asthma and among adults and ≥65 years, 26.8% had a history of chronic obstructive pulmonary disease.
Conclusions: Individuals at the extreme ends of life may be the most vulnerable to severe pertussis infections, though hospitalization was reported across all age groups. Continued monitoring of severe pertussis infections will be important to help guide prevention, control, and treatment options.
PMID: 30321305 [PubMed - as supplied by publisher]
Automatic emphysema detection using weakly labeled HRCT lung images.
PLoS One. 2018;13(10):e0205397
Authors: Pino Peña I, Cheplygina V, Paschaloudi S, Vuust M, Carl J, Weinreich UM, Østergaard LR, de Bruijne M
PURPOSE: A method for automatically quantifying emphysema regions using High-Resolution Computed Tomography (HRCT) scans of patients with chronic obstructive pulmonary disease (COPD) that does not require manually annotated scans for training is presented.
METHODS: HRCT scans of controls and of COPD patients with diverse disease severity are acquired at two different centers. Textural features from co-occurrence matrices and Gaussian filter banks are used to characterize the lung parenchyma in the scans. Two robust versions of multiple instance learning (MIL) classifiers that can handle weakly labeled data, miSVM and MILES, are investigated. Weak labels give information relative to the emphysema without indicating the location of the lesions. The classifiers are trained with the weak labels extracted from the forced expiratory volume in one minute (FEV1) and diffusing capacity of the lungs for carbon monoxide (DLCO). At test time, the classifiers output a patient label indicating overall COPD diagnosis and local labels indicating the presence of emphysema. The classifier performance is compared with manual annotations made by two radiologists, a classical density based method, and pulmonary function tests (PFTs).
RESULTS: The miSVM classifier performed better than MILES on both patient and emphysema classification. The classifier has a stronger correlation with PFT than the density based method, the percentage of emphysema in the intersection of annotations from both radiologists, and the percentage of emphysema annotated by one of the radiologists. The correlation between the classifier and the PFT is only outperformed by the second radiologist.
CONCLUSIONS: The presented method uses MIL classifiers to automatically identify emphysema regions in HRCT scans. Furthermore, this approach has been demonstrated to correlate better with DLCO than a classical density based method or a radiologist, which is known to be affected in emphysema. Therefore, it is relevant to facilitate assessment of emphysema and to reduce inter-observer variability.
PMID: 30321206 [PubMed - in process]
The Impact of Chronic Diseases on the Quality of Life of Primary Care Patients in Cambodia, Myanmar and Vietnam.
Iran J Public Health. 2018 Sep;47(9):1308-1316
Authors: Pengpid S, Peltzer K
Background: Quality of life is a key measure in estimating the burden of disease, especially of chronic diseases. This study investigated the impact of a variety of chronic diseases on quality of life (QoL) in primary health care patients in three Southeast Asian countries (Cambodia, Myanmar, and Vietnam).
Methods: This cross-sectional survey was conducted on 4803 adult chronic disease patients (mean age 49.3 yr; SD=16.5) recruited systematically from primary health care centers in rural and urban areas in Cambodia, Myanmar and Vietnam in 2015.
Results: In ANCOVA analysis, adjusted for age, sex, marital status, geo locality, education, income and country, the poorest summative QoL was found among patients with cancer (49.8 mean score), followed by Parkinson's disease (50.7), mental disorder (53.2), epilepsy (53.3), asthma (54.3), kidney disease (54.3), chronic obstructive pulmonary disease (COPD) (54.5) and cardiovascular diseases (CVD) (55.1). Patients having three or more chronic conditions had a significantly lower summative QoL than patients with two chronic conditions (56.4) and one chronic condition (58.0). In multivariable linear regression analysis, younger age, being married or cohabitating, better education, living in an urban area, having only one chronic condition, not experiencing chronic disease stigma and good medication adherence was associated with better QoL in two or three of the study countries.
Conclusion: Major chronic diseases were found to have poor QoL. The determined QoL of chronic disease patients in this study provides information to improve the management of chronic diseases.
PMID: 30320005 [PubMed]
Established and Emerging Environmental Contributors to Disparities in Asthma and Chronic Obstructive Pulmonary Disease.
Curr Epidemiol Rep. 2018 Jun;5(2):114-124
Authors: Levy JI, Quirós-Alcalá L, Fabian MP, Basra K, Hansel NN
Purpose of review: Multiple respiratory diseases, including asthma and chronic obstructive pulmonary disease (COPD), display significant socioeconomic and racial/ethnic disparities. The objective of this review is to evaluate the evidence supporting a link between disproportionate environmental exposures and these health disparities.
Recent findings: Studies suggest that various co-occurring factors related to the home environment, neighborhood environment, non-modifiable individual factors, and individual behaviors and attributes can increase or modify the risk of adverse respiratory outcomes among socioeconomically-disadvantaged and racially/ethnically diverse populations. Pollutants in the home environment, including particulate matter, nitrogen dioxide, and pesticides, are elevated among lower socioeconomic status populations and have been implicated in the development or exacerbation of respiratory-related conditions. Neighborhood crime and green space are socioeconomically patterned and linked with asthma outcomes through psychosocial pathways. Non-modifiable individual factors such as genetic predisposition cannot explain environmental health disparities but can increase susceptibility to air pollution and other stressors. Individual behaviors and attributes, including obesity and physical activity, contribute to worse outcomes among those with asthma or COPD.
Summary: The root causes of these multifactorial exposures are complex, but many likely stem from economic forces and racial/ethnic and economic segregation that influence the home environment, neighborhood environment, and access to healthy foods and consumer products. Critical research needs include investigations that characterize exposure to and health implications of numerous stressors simultaneously, both to guard against potential confounding in epidemiological investigations and to consider the cumulative impact of multiple elevated environmental exposures and sociodemographic stressors on health disparities.
PMID: 30319934 [PubMed]