Chest 2009;136 1086-1094

1. Philip Harber, MD, MPH, FCCP,
2. Jessica Levine and
3. Siddharth Bansal, MD

+ Author Affiliations

1. From Occupational-Environmental Preventive Medicine, Department of Family Medicine, David Geffen School of Medicine at the University of California at Los Angeles, Los Angeles, CA.

1. Philip Harber, MD, MPH, FCCP, UCLA Occupational Medicine, 10880 Wilshire Blvd, No. 1800, Los Angeles, CA 90024; e-mail: pharber@mednet.ucla.edu

Abstract

Background: Our objective was to determine how to select the optimal frequency of workplace spirometry screening using diacetyl-exposed workers as an example.

Methods: A Markov model was constructed to assess the likelihood of progressing from healthy status to early or advanced disease, starting from four different exposure levels, and performing longitudinal or cross-sectional interpretation of spirometry results over time. Projected outcomes at 10 years were evaluated to inform the optimal frequency of workplace spirometry testing.

Results: The optimal screening interval depends on the population risk and is highly sensitive to the real-life impact (utility) associated with false-positive results (eg, related to the availability of alternative work). Screening interval is particularly important for high-risk individuals with rapid transition from early to advanced disease, where the 10-year prevalence of advanced disease would be reduced from 5.3 to 2.5% using a 6-month interval rather than a 12-month interval. Longitudinal test interpretation, based on observing trends within each person over time, is marginally preferable to traditional cross-sectional spirometry interpretation.

Conclusions: There is no single best screening interval. For high-risk populations, annual testing may be too infrequent.

Chest 2009;136 1055-1062

1. Akshay Sood, MD, MPH, FCCP,
2. Clifford Qualls, PhD,
3. Alexander Arynchyn, MD, PhD,
4. William S. Beckett, MD, MPH, FCCP,
5. Myron D. Gross, PhD,
6. Michael W. Steffes, MD, PhD,
7. Lewis J. Smith, MD,
8. Paul Holvoet, PhD,
9. Bharat Thyagarajan, MD, PhD and
10. David R. Jacobs, Jr, PhD

+ Author Affiliations

1. From the Department of Medicine (Dr. Sood) and Clinical Translational Sciences Center (Dr. Qualls), University of New Mexico Health Sciences Center, Albuquerque, NM; Department of Preventive Medicine (Dr. Arynchyn), University of Alabama at Birmingham, Birmingham, AL; Department of Medicine (Dr. Beckett), Mount Auburn Hospital, Cambridge, MA; Department of Laboratory Medicine and Pathology (Drs. Gross, Steffes, and Thyagarajan) and Division of Epidemiology (Dr. Jacobs), University of Minnesota, Minneapolis, MN; Department of Medicine (Dr. Smith), Feinberg School of Medicine, Northwestern University, Chicago, IL; Department of Experimental Surgery and Anesthesiology (Dr. Holvoet), Katholieke Universiteit Leuven, Leuven, Belgium; and Institute for Nutrition Research (Dr. Jacobs), University of Oslo, Oslo, Norway.

1. Akshay Sood, MD, MPH, FCCP, Associate Professor of Medicine, University of New Mexico Health Sciences Center School of Medicine, Department of Medicine, 1 University of New Mexico, MSC 10 5550, Albuquerque, NM 87131; e-mail: asood@salud.unm.edu

Abstract

Background: The mechanism for the obesity-asthma association is unknown. This study evaluated the hypothesis that systemic oxidant stress explains this association.

Methods: This cross-sectional study used year-20 follow-up evaluation data of 2,865 eligible participants in the Coronary Artery Risk Development in Young Adults (CARDIA) cohort. Current asthma was self-reported. Oxidant stress primarily was assessed by plasma F2-isoprostane concentrations. Obesity measures included categories of BMI and dual-energy x-ray absorptiometry-assessed fat mass index (FMI) and lean mass index (LMI). Logistic and linear regressions were used for analyses.

Results: Asthma was associated with higher plasma F2-isoprostane concentrations (p = 0.049); however, this association was not significant when adjusted for either gender or BMI. The BMI-asthma association was seen only among women (p = 0.03; gender-specific interaction, p = 0.01), and this association was not explained by plasma F2-isoprostane levels. Similarly, both FMI and LMI were positively associated with asthma in women (p = 0.20 and 0.01, respectively). These associations also were not explained by plasma F2-isoprostane levels. Similar results were obtained when plasma levels of oxidized low-density lipoprotein were used instead of F2-isoprostane levels to study the BMI-asthma association at the year-15 evaluation.

Conclusions: Systemic oxidant stress, primarily assessed by plasma F2-isoprostane concentrations, was not independently associated with asthma and, therefore, may not explain the obesity-asthma association in women. The asthma-oxidant stress association is confounded by gender and obesity. This study is limited by the inability to measure airway oxidant stress. It is possible that another (as yet undetermined) measure of systemic oxidant stress may be more relevant in asthma.

Chest 2009;136 998-1005

1. David S. Hui, MD, FCCP,
2. Benny K. Chow, MPH,
3. Susanna S. Ng, MBChB,
4. Leo C. Y. Chu, MBChB,
5. Stephen D. Hall, PhD,
6. Tony Gin, MD,
7. Joseph J. Y. Sung, MD and
8. Matthew T. V. Chan, MD

+ Author Affiliations

1. From the Department of Medicine and Therapeutics (Drs. Hui, Ng, and Sung, and Mr. Chow), the Center for Housing Innovations (Mr. Chow), Institute of Space and Earth Information Science, and the Department of Anesthesia and Intensive Care (Drs. Chu, Gin, and Chan), The Chinese University of Hong Kong, Hong Kong, People’s Republic of China; and the School of Mechanical Engineering (Dr. Hall), The University of New South Wales, Sydney, NSW, Australia.

1. David S. Hui, MD, FCCP, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, 30-32 Ngan Shing St, Shatin, NT, Hong Kong, People’s Republic of China; e-mail: dschui@cuhk.edu.hk

Abstract

Background: As part of our influenza pandemic preparedness, we studied the exhaled air dispersion distances and directions through two different face masks (Respironics; Murrysville, PA) attached to a human-patient simulator (HPS) during noninvasive positive-pressure ventilation (NPPV) in an isolation room with pressure of −5 Pa.

Methods: The HPS was positioned at 45° on the bed and programmed to mimic mild lung injury (oxygen consumption, 300 mL/min; lung compliance, 35 mL/cm H₂O). Airflow was marked with intrapulmonary smoke for visualization. Inspiratory positive airway pressure (IPAP) started at 10 cm H₂O and gradually increased to 18 cm H₂O, whereas expiratory pressure was maintained at 4 cm H₂O. A leakage jet plume was revealed by a laser light sheet, and images were captured by high definition video. Normalized exhaled air concentration in the plume was estimated from the light scattered by the smoke particles.

Findings: As IPAP increased from 10 to 18 cm H₂O, the exhaled air of a low normalized concentration through the ComfortFull 2 mask (Respironics) increased from 0.65 to 0.85 m at a direction perpendicular to the head of the HPS along the median sagittal plane. When the IPAP of 10 cm H₂O was applied via the Image 3 mask (Respironics) connected to the whisper swivel, the exhaled air dispersed to 0.95 m toward the end of the bed along the median sagittal plane, whereas higher IPAP resulted in wider spread of a higher concentration of smoke.

Conclusions: Substantial exposure to exhaled air occurs within a 1-m region, from patients receiving NPPV via the ComfortFull 2 mask and the Image 3 mask, with more diffuse leakage from the latter, especially at higher IPAP.