Prevalence and burden of comorbidities in Chronic Obstructive Pulmonary Disease

The classical definition of Chronic Obstructive Pulmonary Disease (COPD) as a lung condition characterized by irreversible airway obstruction is outdated. The systemic involvement in patients with COPD, as well as the interactions between COPD and its comorbidities, justify the description of chronic systemic inflammatory syndrome. The pathogenesis of COPD is closely linked with aging, as well as with cardiovascular, endocrine, musculoskeletal, renal, and gastrointestinal pathologies, decreasing the quality of life of patients with COPD and, furthermore, complicating the management of the disease. The most frequently described comorbidities include skeletal muscle wasting, cachexia (loss of fat-free mass), lung cancer (small cell or non-small cell), pulmonary hypertension, ischemic heart disease, hyperlipidemia, congestive heart failure, normocytic anemia, diabetes, metabolic syndrome, osteoporosis, obstructive sleep apnea, depression, and arthritis. These complex interactions are based on chronic low-grade systemic inflammation, chronic hypoxia, and multiple common predisposing factors, and are currently under intense research. This review article is an overview of the comorbidities of COPD, as well as their interaction and influence on mutual disease progression, prognosis, and quality of life.

"Chronic obstructive pulmonary disease and phenotypes: a state-of-the-art."

Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous and multisystemic disease with progressive increasing morbidity and mortality. COPD is now widely accepted as a heterogeneous condition with multiple phenotypes and endotypes. This review will discuss the old and new concepts for the different types of COPD phenotypes, as well as the inclusion of them in current guidelines. Phenotypical approach to COPD is having huge impact on everyday practice and changed nonpharmacological and pharmacological management of COPD in last decade. However, phenotypical approach is small step to precision medicine in COPD management in the absence of big, specific and well-designed COPD trials with exact identification of phenotypes for more personalization of the treatment of COPD.

Chronic Obstructive Pulmonary Disease and Stroke

Chronic obstructive pulmonary disease (COPD) is currently the fourth leading cause of death in the world and its incidence and prevalence is on the rise. It is evident that COPD is linked to cardiovascular disease. In the last years, several studies demonstrated that COPD may also be a risk factor for stroke, another major cause of death worldwide. Taking in consideration that COPD has multiple comorbidities it is hard to say whether COPD is an independent risk factor for stroke or it is due to confounding effect. This review is aimed to discuss current data on COPD and stroke, potential links, therapy, and prevention. Current data suggest that COPD may increase the risk of hemorrhagic stroke. The incidence of other stroke subtypes may also be increased in COPD or may be due to confounding effect. However, COPD patients who have stroke are at risk for pulmonary and extrapulmonary complications. We conclude that more studies are needed to further clarify the links between COPD and stroke. The management of COPD as well as the use of prevention therapy is essential to decrease the risk for stroke and should be at special attention in pulmonary medicine and neurology.

Predicting Health-Related Quality of Life in Patients with Chronic Obstructive Pulmonary Disease: The Impact of Age

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity in the elderly population. COPD leads to a reduced health-related quality of life (HRQL), but the factors which contribute to this are not well understood. A better understanding of the factors which determine HRQL should lead to an improved care for such patients.

OBJECTIVES

The purpose of this study was to investigate possible age-related differences in HRQL in a population of patients with a similar severity of obstruction.

METHODS

A total of 180 consecutive COPD patients were enrolled into the study. We analyzed spirometric data, BODE index and its components, and comorbidities were assessed by the Charlson index. HRQL was assessed by the Clinical COPD Questionnaire (CCQ) and St. George's Respiratory Questionnaire (SGRQ).

RESULTS

The cohort consisted of 93 'younger' patients (mean age 54.8 ± 3.1 years) and 87 older patients (mean age 73.1 ± 5.5 years). Patients in both groups had a similar severity of obstruction: FEV1 (% from predicted) was 39.9 ± 13.2% in the elderly group compared to 41.7 ± 11.7% in the younger group (p > 0.05). The forward stepwise regression analysis shows that the BODE index, the Charlson index, and the rate of exacerbations are important predictors of deterioration of HRQL in elderly COPD patients, which explains 29% of the total SGRQ score. In the younger COPD patients, the coefficient of determination R2 was 0.27, but the predictors were the BODE index and the rate of exacerbations.

CONCLUSIONS

The BODE index, the Charlson index, and the rate of exacerbations were found to be the major determinants of HRQL in elderly COPD patients, while in younger COPD patients, the BODE index and the rate of exacerbations were influential factors.

Multidimensional indices in the assessment of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD), a very common disease, is the third leading cause of death worldwide. Due to the significant heterogeneity of clinical phenotypes of COPD there is no single method suitable for predicting patients' health status and outcomes, and therefore multidimensional indices, assessing different components of the disease, were developed and are recommended for clinical practice by international guidelines. Several indices have been widely accepted: BODE and its modifications, ADO, DOSE, CODEX, COTE. They differ in their composition and aim, while they are more accurate and better validated in specific settings and populations. We review the characteristics, strengths and limitations of these indices, and we discuss their role in routine management of patients with COPD, as well as in specific clinical scenarios, such as resuscitation and ceiling of care, or decisions to offer more invasive treatments. This analysis may help clinicians to use those indexes in a more practical and appropriate way.

To sleep, or not to sleep - that is the question, for polysomnography

Have we reached the point where respiratory polygraphy can replace polysomnography in the assessment of OSAS? http://ow.ly/UxCU30bNopq.

Predictors of daytime sleepiness in patients with obstructive sleep apnea

BACKGROUND

The main symptomatic criterion to diagnose obstructive sleep apnea (OSA) is the level of daytime sleepiness. The Epworth Sleepiness Scale is a simple, self-administered questionnaire which provides a measurement of the subject's general level of daytime sleepiness. The aim of this study was to investigate the factors that can predict daytime sleepiness in patients with sleep apnea.

METHODS

50 consecutive patients with obstructive sleep apnea were enrolled into the study. Age, gender, anthropometric and polygraphic data were thoroughly analyzed. In all subjects daily sleepiness was assessed by Epworth Sleepiness Scale.

RESULTS

The mean age of the subjects was 54.7 ± 12.8 years, 82% males. The mean BMI was 31.9 ± 6 kg/m2. Pearson correlation coefficient analysis demonstrates a significant positive correlation between the Epworth Sleepiness Scale and the desaturation index (r = 0.31, p < 0.01) and arterial hypertension (r = 0.32, p < 0.01). The forward stepwise regression analysis shows that the apnea hypopnea index and desaturation index are important predictors of daytime sleepiness in patients with obstructive sleep apnea which explains 40% of the Epworth Sleepiness Scale score.

CONCLUSION

The desaturation index showed the strongest correlation with the Epworth scale. According to the results of the backward stepwise multiple regression and logistic regression, the predictors for the level of daytime sleepiness are oAHI and index of desaturation. According to the analysis of the ROC curve, desaturation index is a predictor of a high specificity.