Risk factors for hospitalization among adults with asthma: the influence of sociodemographic factors and asthma severity

BACKGROUND: The morbidity and mortality from asthma have markedly increased since the late 1970s. The hospitalization rate, an important marker of asthma severity, remains substantial. METHODS: In adults with health care access, we prospectively studied 242 with asthma, aged 18–50 years, recruited from a random sample of allergy and pulmonary physician practices in Northern California to identify risk factors for subsequent hospitalization. RESULTS: Thirty-nine subjects (16%) reported hospitalization for asthma during the 18-month follow-up period. On controlling for asthma severity in multiple logistic regression analysis, non-white race (odds ratio [OR], 3.1; 95% confidence interval [CI], 1.1–8.8) and lower income (OR, 1.1 per $10,000 decrement; 95$10,000 decrement; 95% CI, 1.02–1.4). CONCLUSION: In adult asthmatics with access to health care, non-white race, low income, and greater asthma severity were associated with a higher risk of hospitalization. Targeted interventions applied to high-risk asthma patients may reduce asthma morbidity and mortality

Impact of comorbid conditions on asthmatic adults and children

Comorbid conditions (comorbidities) can complicate the diagnosis and management of asthma. In different age groups, comorbid conditions can present varying challenges, including diagnostic confusion due to mimicking asthma symptoms, exacerbation of asthma symptoms, therapy for comorbid conditions affecting asthma or therapy for asthma affecting these conditions. This review aims to summarise some common comorbid conditions with asthma, such as rhinitis, vocal cord dysfunction, gastro-oesophageal reflux, psychiatric disorders, obesity and obstructive sleep apnoea, and discuss their prevalence, symptoms, diagnosis and treatment, highlighting any differences in how they impact children and adults. Overall, there is a lack of data on the impact of treating comorbid conditions on asthma outcomes and further studies are needed to guide age-appropriate asthma management in the presence of these conditions.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.A.K. reports personal fees from AstraZeneca, Behring, Boehringer Ingelheim, GlaxoSmithKline, Griffols, Teva, Novartis, Novo Nordisk, Paladdin, Pfizer, Purdue, Sanofi and Trudel, outside the submitted work. D.M.G.H. reports personal fees from AstraZeneca, Chiesi and Pfizer and grants and personal fees from Boehringer Ingelheim, GlaxoSmithKline and Novartis, outside the submitted work. S.J.S. reports fees from AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Novartis, Propeller Health, Regeneron and Sanofi, outside the submitted work all paid to the University of Colorado School of Medicinepublished version, accepted version, submitted versio

Architecture for mixed criticality resource management in Internet of Things

We believe that the next big step in the field of Internet of Things (IoT) is to realize a virtual computing platform that provides access to heterogeneous group of device resources present in our living environments. By enabling 3rd party developers to access sensor and actuator resources present in a given environment in a same way they can access resources of a single mobile phone, the virtual computing platform would open a new market for the 3rd party IoT applications like the smart phones have done for mobile apps. To accomplish this vision, the virtual computing platform must be able to manage resource sharing between applications with differing criticality requirements for ensuring that the whole IoT system runs optimally. The main challenge is that the approach should be generic and extendable for future needs. To tackle this issue, we propose a two-level resource management architecture, where the necessary information about applications and resources are represented with machine-interpretable semantic descriptions based on the Semantic Web technologies. At the system level, these descriptions are used by the global resource manager for allocating resources to the applications based on their criticality and needs. At local level, each device is assigned with a local resource manager that schedules the access to resources provided by the device so that the performance of the more critical applications could be optimized at the expense of the less critical ones. To evaluate our approach in practice, we have implemented a reference implementation of the proposed architecture and demonstrated it through several applications with differing criticality levels. The results are very promising for managing mixed criticality applications in IoT

Application development for the Internet of Things: A context-aware mixed criticality systems development platform

The Internet of Things (IoT) is gaining momentum and may positively influence the automation of energy-efficiency management of smart buildings. However, the development of IoT-enabled applications still takes tremendous efforts due to the lack of proper tools. Many software components have to be developed from scratch, thus requiring huge amounts of effort, as developers must have a deep understanding of the technologies, the new application domain, and the interplay with legacy systems. In this paper we introduce the IMPReSS Systems Development Platform (SDP) that aims at reducing the complexity of developing IoT-enabled applications for supporting sensor data collection in buildings, managing automated system changes according to the context, and real-time prioritization of devices for controlling energy usage. The effectiveness of the SDP for the development of IoT-based context-aware and mixed-criticality applications was assessed by using it in four scenarios involving energy efficiency management in public buildings. Qualitative studies were undertaken with application developers in order to evaluate their perception of five key components of the SDP with regard to usability. The study revealed significant and encouraging results. Further, a quantitative performance analysis explored the scalability limits of the IMPReSS communication components