Management of allergic conjunctivitis and dry eye

Ocular allergy is a common eye condition encountered in clinical practice. However, little is known how seasonal allergic conjunctivitis (SAC), the most common subtype, is managed in clinical practice. Further, dry eye, another common eye condition, may be misdiagnosed as SAC and vice-versa as they share similar signs and symptoms. In addition, despite the frequent recommendation of non-pharmacological treatments for SAC, evidenceto support their use has not been identified in the scientific literature. The aim of this thesis was therefore to determine the actual diagnosis and management of SAC and dry eye in clinical practice and investigate the efficacy of non-pharmacological treatments for these conditions. The diagnostic and management strategies for SAC and dry eye employed by pharmacy staff are found to be inconsistent with current guidelines and scientific evidence based upon a mystery shopper design. Cluster analysis of tear film metrics in normal and dry eye patients identified several clinically relevant groups of patients that may allow for targeted treatment recommendations. Using a novel environmental chamber model of SAC, the use of artificial tears and cold compresses, either alone or combined is an effective treatment modality for acute and symptomatic SAC, on a par with topical anti-allergic medication, and has been demonstrated for the first time. In addition, eyelid warming therapy with a simple, readily available, seed filled device is an effective method of treating meibomian gland dysfunction (MGD) related evaporative dry eye, perhaps the most common dry eye subtype. A greater focus on ophthalmology must be implemented as part of the formal education and training of pharmacy staff, while greater professional communication between community pharmacists, optometrists and the population they serve is required. Artificial tears and cold compresses may be considered as front line agents for acute SAC by pharmacy staff and optometrists, to whom pharmacological treatment options are limited.

Corticobasal degeneration and dementia

Corticobasal degeneration is a rare, progressive neurodegenerative disorder which significantly impairs movement. The most common initial symptom is asymmetric limb clumsiness with or without accompanying rigidity or tremor. Subsequently, the disease progresses to affect gait and there is a slow progression to influence ipsilateral arms and legs. Apraxia and dementia are the most common cortical signs. Clinical diagnosis of the disorder is difficult as the symptoms resemble those of related neurodegenerative disorders. Histopathologically, there is widespread neuronal and glial pathology including tau-immunoreactive neuronal cytoplasmic inclusions, neuropil threads, oligodendroglial inclusions, astrocytic plaques, together with abnormally enlarged ‘ballooned’ neurons. Corticobasal degeneration has affinities both with the parkinsonian syndromes including Parkinson’s disease, progressive supranuclear palsy, and multiple system atrophy and with the fronto-temporal dementias. Treatment of corticobasal degeneration involves managing and reducing the effect of symptoms.

Use of Google as a tool to aid diagnosis by optometry students

Background: Previous work has shown that medical problems can be diagnosed by practitioners using Google. The aim of this study was to determine whether optometry students would benefit from using Google when diagnosing eye diseases. Methods: Participants were given symptoms and signs and instructed to list three key words and use them to search Aston University e-Library and Google UK. Results: Aston University e-Library only search resulted in correct diagnosis in 16 of 60 simulated cases. Aston e-Library plus Google search resulted in correct diagnosis in 31 of 60 simulated cases. Conclusion: Google is a useful aid to help optometry students improve their success rate when diagnosing eye conditions.

Machine learning for large-scale wearable sensor data in Parkinson disease:concepts, promises, pitfalls, and futures

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, “wearable,” sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that “learn” from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society.

Is pregnancy a teachable moment for diet and physical activity behaviour change? An interpretative phenomenological analysis of the experiences of women during their first pregnancy

OBJECTIVES: Pregnancy may provide a 'teachable moment' for positive health behaviour change, as a time when women are both motivated towards health and in regular contact with health care professionals. This study aimed to investigate whether women's experiences of pregnancy indicate that they would be receptive to behaviour change during this period. DESIGN: Qualitative interview study. METHODS: Using interpretative phenomenological analysis, this study details how seven women made decisions about their physical activity and dietary behaviour during their first pregnancy. RESULTS: Two women had required fertility treatment to conceive. Their behaviour was driven by anxiety and a drive to minimize potential risks to the pregnancy. This included detailed information seeking and strict adherence to diet and physical activity recommendations. However, the majority of women described behaviour change as 'automatic', adopting a new lifestyle immediately upon discovering their pregnancy. Diet and physical activity were influenced by what these women perceived to be normal or acceptable during pregnancy (largely based on observations of others) and internal drivers, including bodily signals and a desire to retain some of their pre-pregnancy self-identity. More reasoned assessments regarding benefits for them and their baby were less prevalent and influential. CONCLUSIONS: Findings suggest that for women who conceived relatively easily, diet and physical activity behaviour during pregnancy is primarily based upon a combination of automatic judgements, physical sensations, and perceptions of what pregnant women are supposed to do. Health professionals and other credible sources appear to exert less influence. As such, pregnancy alone may not create a 'teachable moment'. Statement of contribution What is already known on this subject? Significant life events can be cues to action with relation to health behaviour change. However, much of the empirical research in this area has focused on negative health experiences such as receiving a false-positive screening result and hospitalization, and in relation to unequivocally negative behaviours such as smoking. It is often suggested that pregnancy, as a major life event, is a 'teachable moment' (TM) for lifestyle behaviour change due to an increase in motivation towards health and regular contact with health professionals. However, there is limited evidence for the utility of the TM model in predicting or promoting behaviour change. What does this study add? Two groups of women emerged from our study: the women who had experienced difficulties in conceiving and had received fertility treatment, and those who had conceived without intervention. The former group's experience of pregnancy was characterized by a sense of vulnerability and anxiety over sustaining the pregnancy which influenced every choice they made about their diet and physical activity. For the latter group, decisions about diet and physical activity were made immediately upon discovering their pregnancy, based upon a combination of automatic judgements, physical sensations, and perceptions of what is normal or 'good' for pregnancy. Among women with relatively trouble-free conception and pregnancy experiences, the necessary conditions may not be present to create a 'teachable moment'. This is due to a combination of a reliance on non-reflective decision-making, perception of low risk, and little change in affective response or self-concept.