Comorbidities, Patient Knowledge, and Disease Management in a National Sample of Patients with COPD

Objective

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States but is often undertreated. COPD often overlaps with other conditions such as hypertension and osteoporosis, which are less morbid but may be treated more aggressively. We evaluated the prevalence of these comorbid conditions and compared testing, patient knowledge, and management in a national sample of patients with COPD.

Methods

A survey was administered by telephone in 2006 to 1003 patients with COPD to evaluate the prevalence of comorbid conditions, diagnostic testing, knowledge, and management using standardized instruments. The completion rate was 87%.

Results

Among 1003 patients with COPD, 61% reported moderate or severe dyspnea and 41% reported a prior hospitalization for COPD. The most prevalent comorbid diagnoses were hypertension (55%), hypercholesterolemia (52%), depression (37%), cataracts (31%), and osteoporosis (28%). Only 10% of respondents knew their forced expiratory volume in 1 second (95% confidence interval [CI], 8-12) compared with 79% who knew their blood pressure (95% CI, 76-83). Seventy-two percent (95% CI, 69-75) reported taking any medication for COPD, usually a short-acting bronchodilator, whereas 87% (95% CI, 84-90) of patients with COPD and hypertension were taking an antihypertensive medication and 72% (95% CI, 68-75) of patients with COPD and hypercholesterolemia were taking a statin.

Conclusion

Although most patients with COPD in this national sample were symptomatic and many had been hospitalized for COPD, COPD self-knowledge was low and COPD was undertreated compared with generally asymptomatic, less morbid conditions such as hypertension.     

α1-抗胰蛋白酶缺乏症误诊一例并文献复习

目的分析α1-抗胰蛋白酶（alpha-1 antitrypsin,α1-AT）缺乏症的误诊原因及诊治经过,以提高对本病的认识。方法对我院收治1例α1-AT缺乏症的临床资料进行回顾性分析并结合相关文献进行复习。结果本例因反复乏力、食欲缺乏、尿黄伴胸闷、气促3年,再发2个月就诊,外院曾误诊为不明原因肝硬化、气胸、肺大泡,多次予护肝、抗感染等综合治疗,病情反复。后结合胸部CT、肝脏CT及肝脏穿刺活检,明确诊断为α1-AT缺乏症,予护肝、抗感染、利尿、提高白蛋白含量、补充血浆等综合治疗,病情好转出院。结论α1-AT缺乏症比较罕见,对临床出现不明原因的肝脏损害和（或）肺气肿患者应想到本病可能,及时行肝脏穿刺活检及光学显微镜、电子显微镜、高碘酸希夫（PAS）染色等检查,以及早诊断并治疗。     

Alternatives to lung transplantation: lung volume reduction for COPD

Emphysema is disabling and progressive and hallmarked by decreased exercise tolerance and impaired quality of life. Surgical interventions that reduce lung volume have been the focus of multiple interventions for decades; however, until recently, limited evidence has documented their effectiveness. Lung volume reduction surgery (LVRS) underwent rigorous study in the National Emphysema Treatment Trial (NETT), which demonstrated its short-term and long-term effectiveness, associated morbidity and mortality, and the essential factors that predict LVRS success or failure. This article summarizes the major results of the NETT and briefly reviews newer bronchoscopic lung volume reduction techniques that show promise as alternative treatments for select patients with COPD undergoing consideration for lung transplantation.     

Exhaled nitric oxide measure using multiple flows in clinically relevant subgroups of COPD

Although there is widespread interest in fractional exhaled nitric oxide (FeNO) as a non-invasive, time and cost effective biomarker for assessing airway inflammation in chronic obstructive pulmonary disease (COPD), its usefulness is still controversial. We examined the FeNO levels in clinically meaningful subgroups of COPD in a group of 91 COPD patients with FEV(1) 17-77% of predicted. Multiple flow rates FeNO at 10, 30, 50, 100 and 200 mL/s were measured and a two-compartment model was used to estimate the diffusion Capacity (D), alveolar NO concentration (Calv) and airway wall NO concentration (Caw). All patients had spirometry, assessment of symptoms with questionnaires and low-dose CT scan as well as assessment of weight and body composition. We examined the following subgroups of COPD: Patients with 1) Severe emphysema, 2) Chronic bronchitis, 3) Frequent exacerbations, 4) Loss of lean body mass and 5) Low fat-free mass index. We used advanced non-linear mixed model adjusted for age and gender. The modelled differences in D, Calv or Caw among COPD subgroups were small and not statistically significant. The analysis showed significant effects of current smoking on Caw and of gender on D and Calv. The results were the same if the advanced non-linear mixed model was substituted by more standard analysis techniques. This study questions the relevance of using FeNO as a biomarker to evaluate local inflammation in COPD and points to a need for developing novel non-invasive biomarkers for research laboratory work and daily clinical practice.     

DNA repair as an emerging target for COPD-lung cancer overlap

Cigarette smoking is the leading cause of lung cancer and chronic obstructive pulmonary disease (COPD). Many of the detrimental effects of cigarette smoke have been attributed to the development of DNA damage, either directly from chemicals contained in cigarette smoke or as a product of cigarette smoke-induced inflammation and oxidative stress. In this review, we discuss the environmental, epidemiological, and physiological links between COPD and lung cancer and the likely role of DNA damage and repair in COPD and lung cancer development. We explore alterations in DNA damage repair by DNA repair proteins and pathways. We discuss emerging data supporting a key role for the DNA repair protein, xeroderma pigmentosum group C (XPC), in cigarette smoke-induced COPD and early lung cancer development. Understanding the interplay between cigarette smoke, DNA damage repair, COPD, and lung cancer may lead to prognostic tools and new, potentially targetable, pathways for lung cancer prevention and treatment.     

Active Relearning for Robust Supervised Training of Emphysema Patterns

Radiologists are adept at recognizing the character and extent of lung parenchymal abnormalities in computed tomography (CT) scans. However, the inconsistent differential diagnosis due to subjective aggregation necessitates the exploration of automated classification based on supervised or unsupervised learning. The robustness of supervised learning depends on the training samples. Towards optimizing emphysema classification, we introduce a physician-in-the-loop feedback approach to minimize ambiguity in the selected training samples. An experienced thoracic radiologist selected 412 regions of interest (ROIs) across 15 datasets to represent 124, 129, 139 and 20 training samples of mild, moderate, severe emphysema and normal appearance, respectively. Using multi-view (multiple metrics to capture complementary features) inductive learning, an ensemble of seven un-optimized support vector models (SVM) each based on a specific metric was constructed in less than 6 s. The training samples were classified using seven SVM models and consensus labels were created using majority voting. In the active relearning phase, the ensemble-expert label conflicts were resolved by the expert. The efficacy and generality of active relearning feedback was assessed in the optimized parameter space of six general purpose classifiers across the seven dissimilarity metrics. The proposed just-in-time active relearning feedback with un-optimized SVMs yielded 15 % increase in classification accuracy and 25 % reduction in the number of support vectors. The average improvement in accuracy of six classifiers in their optimized parameter space was 21 %. The proposed cooperative feedback method enhances the quality of training samples used to construct automated classification of emphysematous CT scans. Such an approach could lead to substantial improvement in quantification of emphysema.