1,721,020 research outputs found
Preventing respiratory infection-related cardiovascular disease events in primary care
Get PDFBackground: Cardiovascular disease events (CVD events, comprising coronary and cerebrovascular events) are major causes of morbidity and mortality. CVD can be prevented by medications that target the underlying pathological processes of thrombosis and atherosclerosis. When a patient is diagnosed with a respiratory infection their risk of CVD events is about four times higher than their background risk for the following four weeks. This infection-related CVD event risk is well characterised by epidemiological research, but clinical practice guidelines for primary care do not address it. Prior to this thesis there were no tools for predicting an individual’s risk of an infection-related CVD event and, apart from vaccines, no established interventions for this scenario.
Overall aim: To investigate strategies for preventing infection-related CVD events in primary care.
Approach: 1. Developing statistical models to identify patients with respiratory infections who are at risk of CVD events 2. Validating the prediction models, using them to derive a clinical risk prediction score 3. Estimating the effect of aspirin on infection-related cardiovascular events 4. Estimating the effect of statin use on infection-related cardiovascular events
Methods: Four epidemiological studies using large cohorts from coded UK primary care records held by the Clinical Practice Research Datalink (CPRD). These data were linked to datasets of NHS hospital and Office of National Statistics (ONS) mortality and relative deprivation datasets. The first two studies used prediction modelling methods, and the next two used propensity modelling methods with logistic regression to estimate causal effects.
Results: I developed two statistical models and derived a clinical prediction points-based tool, the DASHI score. DASHI comprises five clinical variables: Diabetes, Age, Smoking status, Heart failure and Infection diagnosis. External validation showed DASHI can predict risk of infection-related CVD events with good calibration and discrimination (both C statistic and observed to expected ratios were 0.85 with IQR 0.85-0.85). This performance was very similar to the regression models. Aspirin and statins were estimated to increase infection-related CVD events; Relative Risk 2.52 (95% CI 2.26 to 2.81) for aspirin and 3.17 (95% CI 2.41 to 4.08) for statins. Aspirin increased bleeding with a relative risk of 1.31 (95% CI 1.06 to 1.16).
Conclusion: The DASHI score can predict risk of primary infection-related CVD events. The absolute risks are low for most people due to the short prediction period. It is unlikely that aspirin and statins increase CVD events given what we know about their effects in other settings. It is more likely the results are inaccurate because of confounding or coding problems in the datasets. In particular, prescriptions are recorded immediately in the clinical record, but there are delays before CVD events enter the datasets. This timing difference may have led to biases exacerbated by the short follow-up period. A definitive answer is likely to require a different approach, and may require different datasets, or a randomised controlled clinical trial
Statin safety in prevention of cardiovascular diseases: causal inference and risk prediction
No full textBackground:
The widespread concerns about statin safety have resulted in low uptake of and poor adherence to statin treatment for prevention of cardiovascular diseases. The use of statins for primary prevention has been particularly challenging due to the controversy about the balance between benefits and harms of treatment. Personalised clinical decision-making and stratified treatment strategies that take into account the risk of adverse events are potential approaches towards better use of statins.
Methods:
A systematic review of randomised controlled trials was conducted, with pair-wise, network, and dose-response meta-analyses, to assess the associations between statins and common adverse events and explore the variations by drug type and dose in primary prevention patients. A prognostic model (StatinMD) was derived and externally validated to predict the personalised risk of serious muscle disorders in individuals eligible for statin treatment, using a competing risk model with data from electronic healthcare records.
Results:
Statins were associated with a small increase in the risk of muscle symptoms, liver dysfunction, renal insufficiency, and eye conditions, but not with muscle disorders or diabetes. There was little evidence of the difference between statin drugs or the dose-response relationships of their adverse effects. The StatinMD model included 22 predictors to predict the risk of serious muscle disorders in 1, 5, and 10 years. The model showed overall good discrimination and calibration in the majority of the population.
Conclusions:
The overall balance between benefits and harms of statins supports their use for primary prevention of cardiovascular diseases. The StatinMD model provides a reliable predicted risk of serious muscle disorders for most individuals to assist clinical decision-making on statin treatment
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Development of clinical prediction rules for reducing delays in the diagnosis of multiple myeloma
Get PDFBackground
Multiple myeloma is a type of blood cancer which starts at the bone marrow. Fifty percent of patients have more than three consultations in primary care before being referred to secondary care. This implies that myeloma patients can experience delays in the diagnosis which could contribute to the relatively poor prognosis. The aim of the thesis was to develop clinical prediction rules that could potentially reduce the time to diagnosis of myeloma patients.
Methods
The thesis comprises three main studies. The first is a systematic review which maps and quantifies the diagnostic pathway of myeloma patients. In the second study, the features of myeloma (symptoms and blood test abnormalities) were examined to identify which present the earliest. The most optimal combinations of blood tests for diagnosing myeloma were also examined. In the third study, a series of clinical prediction rules were developed and validated using the Clinical Research Datalink data that could be used to expedite the diagnosis of myeloma.
Results
Myeloma patients experience substantial delays with 50% experiencing a diagnostic interval greater than three months and 25% more than eight months. Early symptoms of myeloma include back pain, rib pain, chest pain and infections while fractures, weight loss and nausea manifest later in disease progression. For blood tests haemoglobin and inflammatory markers like Erythrocyte sedimentation rate (ESR) and plasma viscosity (PV) can become abnormal up to two years before diagnosis while values in calcium and creatinine manifest later. C-reactive protein is not a useful inflammatory marker for the diagnosis of myeloma. A combination of normal haemoglobin, either ESR or PV and calcium can rule out most myeloma cases. A clinical prediction rule containing demographics (age, gender, BMI), risk factors (MGUS)
symptoms (nosebleeds, back pain, chest pain, rib pain) and the parameters of the full blood count (white cell count, haemoglobin, platelets and mean corpuscular volume) showed good discrimination (AUC: 0.84, 95% CI: 0.82-0.87, R^2: 0.57, 95% CI: 0.53-0.62 and D-statistic: 2.4, 95% CI: 2.2-2.6) and good calibration.
Conclusions
Myeloma patients experience substantial delays in their diagnosis. General practitioners should examine patients that present with myeloma related symptoms using a combination of a full blood count, an inflammatory marker (ESR or PV) and calcium. The clinical prediction rule developed can be useful when myeloma is not suspected and not all tests are ordered. The rule could be applied in the laboratory or on the electronic systems that general practitioners use, but further work is required before implementation.</p
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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