Lung function impairment and risk of incident heart failure: the NHLBI Pooled Cohorts Study.

AIMS: The aim is to evaluate associations of lung function impairment with risk of incident heart failure (HF). METHODS AND RESULTS: Data were pooled across eight US population-based cohorts that enrolled participants from 1987 to 2004. Participants with self-reported baseline cardiovascular disease were excluded. Spirometry was used to define obstructive [forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) <0.70] or restrictive (FEV1/FVC ≥0.70, FVC <80%) lung physiology. The incident HF was defined as hospitalization or death caused by HF. In a sub-set, HF events were sub-classified as HF with reduced ejection fraction (HFrEF; EF <50%) or preserved EF (HFpEF; EF ≥50%). The Fine-Gray proportional sub-distribution hazards models were adjusted for sociodemographic factors, smoking, and cardiovascular risk factors. In models of incident HF sub-types, HFrEF, HFpEF, and non-HF mortality were treated as competing risks. Among 31 677 adults, there were 3344 incident HF events over a median follow-up of 21.0 years. Of 2066 classifiable HF events, 1030 were classified as HFrEF and 1036 as HFpEF. Obstructive [adjusted hazard ratio (HR) 1.17, 95% confidence interval (CI) 1.07-1.27] and restrictive physiology (adjusted HR 1.43, 95% CI 1.27-1.62) were associated with incident HF. Obstructive and restrictive ventilatory defects were associated with HFpEF but not HFrEF. The magnitude of the association between restrictive physiology and HFpEF was similar to associations with hypertension, diabetes, and smoking. CONCLUSION: Lung function impairment was associated with increased risk of incident HF, and particularly incident HFpEF, independent of and to a similar extent as major known cardiovascular risk factors.

Establishing normal reference values in quantitative computed tomography of emphysema.

Quantitative computed tomography (QCT) can provide reliable and valid measures of lung structure and volumes. Similar to lung function measured by spirometry, lung measures obtained by QCT vary by demographic and anthropomorphic factors including sex, race/ethnicity, and height in asymptomatic nonsmokers. Hence, accounting for these factors is necessary to define abnormal from normal QCT values. Prediction equations for QCT may be derived from a sample of asymptomatic individuals to estimate reference values. This review article describes the methodology of reference equation development using, as an example, quantitative densitometry to detect pulmonary emphysema. The process described is generalizable to other QCT measures, including lung volumes, airway dimensions, and gas-trapping. Pulmonary emphysema is defined morphologically by airspace enlargement with alveolar wall destruction and has been shown to correlate with low lung attenuation estimated by QCT. Deriving reference values for a normal quantity of low lung attenuation requires 3 steps. First, criteria that define normal must be established. Second, variables for inclusion must be selected on the basis of an understanding of subject-specific, scanner-specific, and protocol-specific factors that influence lung attenuation. Finally, a reference sample of normal individuals must be selected that is representative of the population in which QCT will be used to detect pulmonary emphysema. Sources of bias and confounding inherent to reference values are also discussed. Reference equation development is a multistep process that can define normal values for QCT measures such as lung attenuation. Normative reference values will increase the utility of QCT in both research and clinical practice.