Differentiating responses to obstructive sleep apnoea using pulse transit time

Conventional overnight polysomnography (PSG) used to determine the respiratory behaviour during sleep can be a complex and expensive procedure. Pulse transit time analysis (PTT) has shown potential to detect obstructive apnoeic and hypopnoeic events in adults. This study was undertaken to determine the potential of PTT to differentiate responses to upper airway obstruction. 103 obstructive respiratory events occurred in PSG studies performed on 11 children (10 male and 1 female, mean age 7.5years). PTT measurements were evaluated against the corresponding PSG results pre-scored by 2 blinded observers. Broadly, there were 2 types of responses. They can be either short period of rapid PTT decreases (Type 1) or prolonged but gradual PTT decreases (Type 2). Type 1 obstructive events showed a mean change of 51.77% (p

Classification of oximetry signals using Bayesian neural networks to assist in the detection of obstructive sleep apnoea syndrome

In the present study, multilayer perceptron (MLP) neural networks were applied to help in the diagnosis of obstructive sleep apnoea syndrome (OSAS). Oxygen saturation (SaO2) recordings from nocturnal pulse oximetry were used for this purpose. We performed time and spectral analysis of these signals to extract 14 features related to OSAS. The performance of two different MLP classifiers was compared: maximum likelihood (ML) and Bayesian (BY) MLP networks. A total of 187 subjects suspected of suffering from OSAS took part in the study. Their SaO2 signals were divided into a training set with 74 recordings and a test set with 113 recordings. BY-MLP networks achieved the best performance on the test set with 85.58% accuracy (87.76% sensitivity and 82.39% specificity). These results were substantially better than those provided by ML-MLP networks, which were affected by overfitting and achieved an accuracy of 76.81% (86.42% sensitivity and 62.83% specificity). Our results suggest that the Bayesian framework is preferred to implement our MLP classifiers. The proposed BY-MLP networks could be used for early OSAS detection. They could contribute to overcome the difficulties of nocturnal polysomnography (PSG) and thus reduce the demand for these studies.

Health promotion for chronic obstructive pulmonary disease

Peter, a 45 year old male, enters the pharmacy and asks, 'do you have something to stop a cough?' On questioning you find out that Peter has an irritating cough that has been off and on for the past few weeks since winter started. He coughs up phlegm every now and then, mostly upon waking. He has tried some cough mixture that he bought at the supermarket but is looking for something stronger. He states that he does not have any medical history or allergies and does not take any medication. He does feel that he can't exercise as much as he used to as he gets more breathless these days.

Potential risk factors for medication non-adherence in patients with chronic obstructive pulmonary disease (COPD)

Aims - To investigate the effect of a range of demographic and psychosocial variables on medication adherence in chronic obstructive pulmonary disease (COPD) patients managed in a secondary care setting. Methods - A total of 173 patients with a confirmed diagnosis of COPD, recruited from an outpatient clinic in Northern Ireland, participated in the study. Data collection was carried out via face-to-face interviews and through review of patients’ medical charts. Social and demographic variables, co-morbidity, self-reported drug adherence (Morisky scale), Hospital Anxiety and Depression (HAD) scale, COPD knowledge, Health Belief Model (HBM) and self-efficacy scales were determined for each patient. Results - Participants were aged 67 ± 9.7 (mean ± SD) years, 56 % female and took a mean (SD) of 8.2 ± 3.4 drugs. Low adherence with medications was present in 29.5 % of the patients. Demographic variables (gender, age, marital status, living arrangements and occupation) were not associated with adherence. A range of clinical and psychosocial variables, on the other hand, were found to be associated with medication adherence, i.e. beliefs regarding medication effectiveness, severity of COPD, smoking status, presence of co-morbid illness, depressed mood, self-efficacy, perceived susceptibility and perceived barriers within the HBM (p < 0.05). Logistic regression analysis showed that perceived ineffectiveness of medication, presence of co-morbid illness, depressed mood and perceived barriers were independently associated with medication non-adherence in the study (P < 0.05). Conclusions - Adherence in COPD patients is influenced more by patients’ perception of their health and medication effectiveness, the presence of depressed mood and co-morbid illness than by demographic factors or disease severity.

Obstructive sleep apnoea is associated with sight threatening retinopathy and predicts the developement of preproliferative and proliferative retinopathy in patients with type 2 diabetes:a longitudinal analysis

troduct I on . An observational longitudinal study. P ur P ose . Assess the relationship between obstructive sleep apnoea (OSA) and DR cross-sectionally and longitudinally. M ethods . Adults with Type 2 diabetes mellitus (T2DM), who were re - cruited from a hospital-based diabetes clinic in the UK. Patients with pre-existing OSA, end-stage renal disease and non-diabetic retinopa - thy were excluded. OSA (apnoea hypopnea index ≥ 5 events/hour) was assessed by a single overnight home-based cardio-respiratory study (Alice PDX, Philips Respironics, USA). DR was assessed us - ing retinal images between 2007 and 2012. Sight threatening diabetic retinopathy (STDR) was defined as presence of pre-proliferative or proliferative DR, maculopathy or photocoagulation. Advanced DR was defined as pre-proliferative or proliferative DR. r esults . 199 patients were included (57.3% (n=114) men, 47.7% (n=95) White Europeans). STDR and OSA prevalence were 38.7% (n=77) and 62.8% respectively. A t b A sel I ne . STR prevalence was higher in patients with OSA (OSA+) compared to those without OSA (OSA-) [48.8% n=61 vs. 21.6% n=16, p<0.001]. After adjustment for confounders, OSA remained independently associated with STR (OR 3.7, 95% CI 1.6-8.9, p=0.006), maculopathy (OR 4.5, 95% CI 1.8-11.4, p=0.002) and advanced DR (OR 3.9, 95% CI 1.02-15.3, p=0.047). Mild and moderate to severe OSA were independently associated with STR and maculopathy and only moderate to severe OSA was associated with advanced DR following adjustment for con - founders. l ong I tud I n A lly . Over the follow-up period of (4.4±1 years), more OSA+ patients progressed from no or background DR to advanced DR (15.3% (n=17) vs. 3% (n=2), p=0.01). OSA was an independent pre - dictor of advanced DR development after adjustment for confounders (OR 6.6, 95% CI 1.2-35.1, p=0.03). OSA did not predict the develop - ment of maculopathy. c onclus I ons . OSA is independently associated with STR and predicts the development of preproliferative and proliferative DR. Intervention - al studies are needed to assess the impact of OSA treatment on DR.

Obstructive sleep apnoea predicts the development of preproliferative and proliferative retinopathy in patients with type 2 diabetes:a longitudinal analysis

Background and aims: Diabetic Retinopathy (DR) is a leading cause of blindness. OSA is associated with increased oxidative and nitrosative stress and endothelial dysfunction in patients with type 2 diabetes (T2DM). Hence, it is plausible that OSA can promote the development and progression of DR. Materials and methods: An observational longitudinal study in adults with T2DM. Patients with pre-existing OSA, end-stage renal disease and non-diabetic retinopathy were excluded. OSA (apnoea hypopnea index ≥ 5 events/hour) was assessed by a single overnight home-based cardio-respiratory monitoring (Alice PDX, etc.). DR was assesses using retinal images between 2007 and 2012. Sight threatening retinopathy (STR) was defined as pre-proliferative or proliferative DR, maculopathy or photocoagulation. Advanced DR was defined as pre-proliferative or proliferative DR. Results: 199 patients were included (57.3% men, 47.7% White Europeans). STR and OSA prevalence were 38.7 % and 62.8% respectively. STR preva-lence was higher in patients with OSA (OSA+) compared to those with-out (OSA-) [48.8% vs. 21.6%, p <0.001]. After adjustment for confounders, OSA remained independently associated with STR (OR 3.7, 95%CI 1.6-8.9, p=0.006, maculopathy (OR 4.5, 1.8-11.4, p=0.002) and advanced DR (OR 3.9, 1.02-15.3, p=0.047). Over 4.4±1 years, more OSA+ patients progressed from no or background DR to advanced DR (15.3% vs. 3%, p=0.01). OSA was an independent predictor of advanced DR development after adjustment (OR 6.6, 95%CI 1.2-35.1, p=0.03). OSA did not predict the development of maculopathy. Patients received continuous positive airway pressure treatment were less likely to develop advanced DR. Conclusion: OSA is independently associated with STR and predicts the development of preproliferative and proliferative DR. Interventional studies are needed to assess the impact of OSA treatment on DR.Supported by: NIHR (UK) and The UK Novo Nordisk Research Foundation.

Identifying the scope for savings at inpatient episode level:an illustration applying DEA to chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is characterized by a largely irreversible obstruction of the airways, and is one of the leading causes of chronic morbidity and mortality worldwide. This paper illustrates the use of Data Envelopment Analysis (DEA) to assess the potential for cost savings at COPD inpatient episode level. The analysis uses the length of stay of each episode as a surrogate for expenditure on that episode while allowing for the medical condition of the patient and the quality of care received. We find substantial possible reductions in length of stay which would translate to cost savings. The paper also explores differences both between hospitals and between care teams within hospitals so that cost efficient protocols of treatment can be identified and disseminated.

An Analytical Workflow for Metagenomic Data and its Application to the Study of Chronic Obstructive Pulmonary Disease (COPD)

Metagenomics is the culture-independent study of genetic material obtained directly from environmental samples. It has become a realistic approach to understanding microbial communities thanks to advances in high-throughput DNA sequencing technologies over the past decade. Current research has shown that different sites of the human body house varied bacterial communities. There is a strong correlation between an individual’s microbial community profile at a given site and disease. Metagenomics is being applied more often as a means of comparing microbial profiles in biomedical studies. The analysis of the data collected using metagenomics can be quite challenging and there exist a plethora of tools for interpreting the results. An automatic analytical workflow for metagenomic analyses has been implemented and tested using synthetic datasets of varying quality. It is able to accurately classify bacteria by taxa and correctly estimate the richness and diversity of each set. The workflow was then applied to the study of the airways microbiome in Chronic Obstructive Pulmonary Disease (COPD). COPD is a progressive lung disease resulting in narrowing of the airways and restricted airflow. Despite being the third leading cause of death in the United States, little is known about the differences in the lung microbial community profiles of healthy individuals and COPD patients. Bronchoalveolar lavage (BAL) samples were collected from COPD patients, active or ex-smokers, and never smokers and sequenced by 454 pyrosequencing. A total of 56 individuals were recruited for the study. Substantial colonization of the lungs was found in all subjects and differentially abundant genera in each group were identified. These discoveries are promising and may further our understanding of how the structure of the lung microbiome is modified as COPD progresses. It is also anticipated that the results will eventually lead to improved treatments for COPD.