jueves, 11 de julio de 2019

Diagnosing COPD | National Institutes of Health (NIH)

Diagnosing COPD | National Institutes of Health (NIH)

National Institutes of Health (NIH) - Turning Discovery into Health



Diagnosing COPD

At a Glance

  • A simple measurement can be used to diagnose clinically significant airflow obstruction, the key characteristic of COPD.
  • The findings validate current guidelines for diagnosing COPD and may help lead to earlier detection and treatment.
Man talking to doctorDiagnosis of COPD remains a major challenge to improving care. DjelicS / iStock / Getty Images Plus
Chronic obstructive pulmonary disease (COPD) is a serious lung disease that makes it hard to breathe. It’s the fourth leading cause of death in the United States, but many people don’t know they have it. Symptoms include shortness of breath, a constant cough, and wheezing. COPD gets worse over time. There is no cure, but treatments and lifestyle changes can help slow its progress and improve quality of life.
COPD lowers the amount of air that flows in and out of the airways. To monitor lung function and gauge the severity of a lung disease, doctors use spirometry. Spirometers measure the air you breathe out. One measure is the forced expiratory volume in one second (FEV1), or the amount of air exhaled forcefully in one second. Forced vital capacity (FVC) is the full amount of air that can be exhaled in a complete breath. When a person’s airflow is obstructed, the ratio of FEV1:FVC is reduced. Experts suggest that a ratio of FEV1:FVC of 0.70 or lower is appropriate for diagnosing COPD. However, this number hasn’t been confirmed by rigorous, large studies.
A team led by Dr. Elizabeth C. Oelsner at Columbia University set out to test different thresholds for diagnosing COPD. The researchers analyzed data from four studies that collected spirometry results from participants and followed up on COPD-related clinical events. The study included more than 24,000 adult participants (54% were women, 69% white, and 24% black). The research was supported in part by NIH’s National Heart, Lung, and Blood Institute (NHLBI). Results were published on June 25, 2019, in the Journal of the American Medical Association.
The team compared how accurately different FEV1:FVC ratios predicted COPD-related hospitalizations and mortality. They assessed ratios ranging from 0.65 to 0.75. They also compared these to another threshold: the lower-limit of normal (LLN). LLN is calculated using population-based data that takes into account age, sex, race, and height.
During about 15 years of follow-up, almost 4,000 participants had a COPD-related event, including about 3,500 hospitalizations and 450 COPD deaths. The optimum FEV1:FVC threshold for predicting these events was 0.71. However, the 0.71 threshold was not significantly different than 0.70. Both were more accurate than using the LLN. No threshold was more statistically accurate than 0.70 across the different subgroups analyzed. This was true regardless of smoking status, gender, and other factors.
“The selection of a threshold for defining airflow obstruction has major implications for patient care and public health, as the prevalence of the condition could vary by more than a third depending on the metric used,” says Oelsner. “Defining ‘normal’ lung function is very challenging in diverse and changing populations, and certain approaches might interpret low levels of lung function as normal in women, non-whites, or the elderly. We were able to show that a simple fixed threshold worked well in our study’s very diverse sample, which improves the generalizability of our results.”
“Diagnosis of airflow obstruction remains a major hurdle to improving care for patients with COPD,” says Dr. James Kiley, director of the NHLBI Division of Lung Diseases. “This validation of a fixed threshold confirms the usefulness of a simple approach for assessment of the disease.”

Related Links

References: Discriminative Accuracy of FEV1:FVC Thresholds for COPD-Related Hospitalization and Mortality. Bhatt SP, Balte PP, Schwartz JE, Cassano PA, Couper D, Jacobs DR Jr, Kalhan R, O'Connor GT, Yende S, Sanders JL, Umans JG, Dransfield MT, Chaves PH, White WB, Oelsner EC. JAMA. 2019 Jun 25;321(24):2438-2447. doi:10.1001/jama.2019.7233. PMID: 31237643.
Funding: NIH’s National Heart, Lung, and Blood Institute (NHLBI), National Institute of Neurological Disorders and Stroke (NINDS), National Institute on Aging (NIA), and National Institute of Nursing Research (NINR); Department of Health and Human Services.

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