Sleep plays a vital role in brain function and systemic physiology across many body systems. Problems with sleep are widely prevalent and include deficits in quantity and quality of sleep; sleep problems that impact the continuity of sleep are collectively referred to as sleep disruptions. Numerous factors contribute to sleep disruption, ranging from lifestyle and environmental factors to sleep disorders and other medical conditions. Sleep disruptions have substantial adverse short- and long-term health consequences. A literature search was conducted to provide a nonsystematic review of these health consequences (this review was designed to be nonsystematic to better focus on the topics of interest due to the myriad parameters affected by sleep). Sleep disruption is associated with increased activity of the sympathetic nervous system and hypothalamic–pituitary–adrenal axis, metabolic effects, changes in circadian rhythms, and proinflammatory responses. In otherwise healthy adults, short-term consequences of sleep disruption include increased stress responsivity, somatic pain, reduced quality of life, emotional distress and mood disorders, and cognitive, memory, and performance deficits. For adolescents, psychosocial health, school performance, and risk-taking behaviors are impacted by sleep disruption. Behavioral problems and cognitive functioning are associated with sleep disruption in children. Long-term consequences of sleep disruption in otherwise healthy individuals include hypertension, dyslipidemia, cardiovascular disease, weight-related issues, metabolic syndrome, type 2 diabetes mellitus, and colorectal cancer. All-cause mortality is also increased in men with sleep disturbances. For those with underlying medical conditions, sleep disruption may diminish the health-related quality of life of children and adolescents and may worsen the severity of common gastrointestinal disorders. As a result of the potential consequences of sleep disruption, health care professionals should be cognizant of how managing underlying medical conditions may help to optimize sleep continuity and consider prescribing interventions that minimize sleep disruption.

Background: Nonadherence to medication is a recognized problem and may be the most challenging aspect of treatment. Methods:We performed a systematic review of factors that influence adherence and the consequences of nonadherence to the patient, healthcare system and society, in patients with schizophrenia. Particular attention was given to the effect of nonadherence on hospitalization rates, as a key driver of increased costs of care. A qualitative systematic literature review was conducted using a broad search strategy using disease and adherence terms. Due to the large number of abstracts identified, article selection was based on studies with larger sample sizes published after 2001. Thirty-seven full papers were included: 15 studies on drivers and 22 on consequences, of which 12 assessed the link between nonadherence and hospitalization. Results: Key drivers of nonadherence included lack of insight, medication beliefs and substance abuse. Key consequences of nonadherence included greater risk of relapse, hospitalization and suicide. Factors positively related to adherence were a good therapeutic relationship with physician and perception of benefits of medication. The most frequently reported driver and consequence were lack of insight and greater risk of hospitalization respectively. Conclusions: Improving adherence in schizophrenia may have a considerable positive impact on patients and society. This can be achieved by focusing on the identified multitude of factors driving nonadherence.

Background and Objective: Orphan drugs have been a highlight of discussions due to their higher prices than non-orphan drugs. There is currently no European consensus on the method of value assessment for orphan drugs. This study assessed the relationship between the prevalence of rare diseases and the annual treatment cost of orphan drugs in France, Germany, Italy, Norway, Spain, Sweden, and UK. Methods: Approved orphan drugs and prevalence data were extracted from the European Medicines Agency website. Annual treatment costs were calculated using ex-factory price. Simple regression was used to analyse the relationship between costs and prevalence. A specific bivariate analysis was performed for the rarest diseases (≤1 per 10,000). Results: 120 drugs were analysed. Prevalence ranged from 0.001 to 5 per 10,000 (mean 1.24, median 1). Annual treatment costs per patient ranged from €755 to €1,051,956 (mean €100,000, median €39,303). Results show a statistically significant inverse correlation between annual treatment cost and disease prevalence in all countries (France: r = −0.370, p = 0.002; Germany: r = −0.365, p = 0.002; Italy: r = −0.340, p = 0.002; Spain: r = −0.316, p = 0.041; UK: r = −0.358, p = 0.0004; Sweden: r = −0.414, p = 0.014; Norway: r = −0.367, p = 0.002). When analysis was focused on the rarest diseases, a stronger correlation exists in all countries (France: r = −0.525, Germany: r = −0.482, Italy: r = −0.497, Spain: r = −0.531, UK: r = −0.436, Sweden: r = −0.455, Norway: r = −0.466; all p < 0.05 except Sweden p = 0.077). Conclusions: This study shows an inverse correlation between annual treatment cost and prevalence with high statistical significance in the studied countries. Although pricing is a complex process where different attributes are assessed, this study supports the idea that payers value rarity in pricing decisions.

Based on this NMA, the analyses for many of the outcomes did not provide significant evidence to indicate that the other approved inhaled antibiotics were more effective than LIS for the treatment of chronic P aeruginosa lung infection in patients with CF. Study withdrawal rates seemed to be comparable among these inhaled antibiotics.