Sleep Disorders and Adherence to Inhalation Therapy in Patients with Chronic Obstructive Pulmonary Disease

Evaluation of daytime sleepiness and insomnia symptoms in OSA patients with a characterization of symptom-defined phenotypes and their involvement in depression comorbidity-a cross-sectional clinical study

Introduction

Recent research highlights the significance of insomnia and sleepiness, shifting from obstructive sleep apnea (OSA) severity and sleep structure, in defining OSA phenotypes.

Objectives

This study aimed to characterize insomnia and sleepiness associated with OSA phenotypes and assess their involvement in depression symptoms (DS) in OSA.

Materials and methods

This cross-sectional, clinical study included 181 participants who underwent polysomnography (PSG) and filled out questionnaires, including the Epworth Sleepiness Scale (ESS), Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), and Beck Depression Index (BDI). They were categorized into phenotypes: insomnia-sleepiness (I + S; ESS ≥ 11; ISI ≥ 15; n = 20), sleepiness (S; ESS ≥ 11; ISI < 15; n = 22), insomnia (I; ESS < 11; ISI ≥ 15), and asymptomatic (A; ESS < 11; ISI<15; n=55).

Results

A linear regression model for the BDI score (R2 = 0.357, p < 0.001) included ISI score and subjective-to-objective sleep latency ratio. The ISI score was a predictive factor for mild and moderate DS [OR = 1.23 (95% CI: 1.09-1.38), p < 0.001 and OR = 1.39 (95% CI: 1.13-1.72), p = 0.002]. The I and I + S phenotypes are characterized by higher BDI scores (p < 0.001 and p = 0.02), longer subjective sleep latency (p = 0.008 and p = 0.04), and shorter subjective total sleep time (TST; p = 0.049 and p = 0.006) compared to A. Furthermore, the I and I + S groups had shorter subjective TST than S (p = 0.03 and p = 0.047). The I and I + S had higher BDI scores than A (p < 0.001 and p = 0.02, respectively) and S (p < 0.001 and p = 0.02, respectively). The I phenotype was associated with the risk of mild and moderate DS (OR = 5.61 (95% CI: 1.91-16.53), p < 0.001 and OR = 9.55 (95% CI: 1.81-50.48), p = 0.008 respectively). Moreover, the I + S phenotype presented an even greater risk for mild DS (OR = 10.29 (95% CI: 2.95-35.85), p < 0.001).

Conclusion

Using clinical features for OSA phenotyping holds promise for finding OSA individuals with increased risk for DS occurrence.

BDNF and proBDNF Serum Protein Levels in Obstructive Sleep Apnea Patients and Their Involvement in Insomnia and Depression Symptoms

Introduction: Obstructive sleep apnea (OSA) is a disorder that, apart from somatic sequelae, increases the risk of developing psychiatric conditions. Brain-derived neurotrophic factor (BDNF) signaling pathway is involved in the pathophysiology of depression and insomnia. Therefore, the study aimed to investigate differences in concentrations of BDNF and proBDNF in patients with OSA and healthy individuals, to evaluate diurnal changes of these proteins, and to assess the correlations with psychiatric symptoms. Methods: Sixty individuals following polysomnography (PSG) were divided into two groups based on the apnea-hypopnea index (AHI): OSA patients (AHI ≥ 30; n = 30) and control group (AHI < 5; n = 30). Participants filled out questionnaires: Beck Depression Inventory (BDI), Athens Insomnia Scale (AIS), and Pittsburgh Sleep Quality Index (PSQI). Peripheral blood was collected before and after PSG. Protein concentrations were measured using ELISA. OSA group was divided into subgroups: AIS (−)/AIS (+) (AIS > 5), PSQI (−)/PSQI (+) (PSQI > 5), and BDI (−)/BDI (+) (BDI > 19). Results: No differences in BDNF and proBDNF protein levels were observed between OSA and the control groups. However, BDNF and proBDNF evening protein concentrations were higher in the AIS (+) and PSQI (+) groups (p < 0.001 for all). The BDI (+) group was characterized by lower morning levels of both proteins (p = 0.047 and p = 0.003, respectively). Conclusions: BDNF signaling pathway might be involved in the pathophysiology of depression and insomnia in patients with OSA. BDNF and proBDNF protein levels might be useful in defining OSA phenotypes.

Status of and strategies for improving adherence to COPD treatment

Despite the wide application of adherence as a concept, the definition, evaluation and improvement of the adherence to treatment by patients with chronic obstructive pulmonary disease (COPD) still present some challenges. First, it is necessary to clearly define the concepts of treatment adherence, compliance and persistence. Second, it is critical to consider the various methods of evaluating and quantifying adherence when interpreting adherence studies. In addition, the advantages and disadvantages of the different ways of measuring treatment adherence should be taken into account. Another subject of some debate is the number of variables associated with COPD treatment adherence. Adherence is a complex concept that goes beyond the dosage or the use of inhalation devices, and a number of variables are involved in determining adherence, from the clinical aspects of the disease to the patient's confidence in the doctor's expertise and the level of social support experienced by the patient. Notably, despite these challenges, the importance of adherence has been well established by clinical trials and routine clinical practice. The available evidence consistently shows the substantial impact that a lack of adherence has on the control of the disease and its long-term prognosis. For these reasons, the correct evaluation of therapeutic adherence should be a key objective in clinical interviews of patients. In recent years, various initiatives for improving adherence have been explored. All these initiatives have been based on patient education. Therefore, health care professionals should be aware of the issues pertaining to adherence and take the opportunity to educate patients each time they contact the health care system.