191 research outputs found
Tuberculosis in alpaca (Lama pacos) on a farm in Ireland. 1. A clinical report
This case report describes tuberculosis (TB) due to infection with Mycobacterium bovis (M. bovis) in alpaca (Lama pacos) on a farm in Ireland. Two severely debilitated alpaca were presented to the University Veterinary Hospital, University College Dublin in November 2004. Bloods were taken, and haematology and biochemistry results were indicative of chronic infection. Radiological examination showed evidence of diffuse granulomatous pneumonia suggestive of tuberculosis. On necropsy there were granulomatous lesions present throughout many body organs including lung, liver, kidney, intestine as well on peritoneum and mesentery. Culture of acid-fast bacilli from lesions led to a diagnosis of tuberculosis due to M. bovis. The use of intradermal skin testing proved inefficient and unreliable for ante mortem diagnosis of tuberculosis in alpaca. Infection due to M. bovis should be considered among the differential diagnoses of debilitating diseases in alpaca, particularly those farmed in areas known to be traditional black spots for tuberculosis in cattle
Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows
Background: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning prognostic models, most studies use the entire cohort of MCI patients regardless of their disease stages. In this paper, we propose a Time Windows approach to predict conversion to dementia, learning with patients stratified using time windows, thus fine-tuning the prognosis regarding the time to conversion. Methods: In the proposed Time Windows approach, we grouped patients based on the clinical information of whether they converted (converter MCI) or remained MCI (stable MCI) within a specific time window. We tested time windows of 2, 3, 4 and 5 years. We developed a prognostic model for each time window using clinical and neuropsychological data and compared this approach with the commonly used in the literature, where all patients are used to learn the models, named as First Last approach. This enables to move from the traditional question "Will a MCI patient convert to dementia somewhere in the future" to the question "Will a MCI patient convert to dementia in a specific time window". Results: The proposed Time Windows approach outperformed the First Last approach. The results showed that we can predict conversion to dementia as early as 5 years before the event with an AUC of 0.88 in the cross-validation set and 0.76 in an independent validation set. Conclusions: Prognostic models using time windows have higher performance when predicting progression from MCI to dementia, when compared to the prognostic approach commonly used in the literature. Furthermore, the proposed Time Windows approach is more relevant from a clinical point of view, predicting conversion within a temporal interval rather than sometime in the future and allowing clinicians to timely adjust treatments and clinical appointments.FCT under the Neuroclinomics2 project [PTDC/EEI-SII/1937/2014, SFRH/BD/95846/2013]; INESC-ID plurianual [UID/CEC/50021/2013]; LASIGE Research Unit [UID/CEC/00408/2013
Dabigatran in patients with atrial fibrillation: perioperative and periinterventional management
In any type of invasive surgery, the patient’s individual risk of thromboembolism has to be weighed against the risk of bleeding. Based on various everyday situations in clinical routine, the purpose of the present expert recommendations is to provide appropriate perioperative and periinterventional management for patients with atrial fibrillation undergoing long-term treatment with the thrombin inhibitor dabigatran. As we currently have no routine laboratory test to measure therapeutic levels of the substance or the risk of bleeding, general measures such as a standardized documentation of the patient’s history, a sufficient time interval between the last preoperative dose and the procedure, and careful control of local hemostasis should be given special attention
Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer’s disease: a feature selection ensemble combining stability and predictability
Background
Predicting progression from Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) is an utmost open issue in AD-related research. Neuropsychological assessment has proven to be useful in identifying MCI patients who are likely to convert to dementia. However, the large battery of neuropsychological tests (NPTs) performed in clinical practice and the limited number of training examples are challenge to machine learning when learning prognostic models. In this context, it is paramount to pursue approaches that effectively seek for reduced sets of relevant features. Subsets of NPTs from which prognostic models can be learnt should not only be good predictors, but also stable, promoting generalizable and explainable models.
Methods
We propose a feature selection (FS) ensemble combining stability and predictability to choose the most relevant NPTs for prognostic prediction in AD. First, we combine the outcome of multiple (filter and embedded) FS methods. Then, we use a wrapper-based approach optimizing both stability and predictability to compute the number of selected features. We use two large prospective studies (ADNI and the Portuguese Cognitive Complaints Cohort, CCC) to evaluate the approach and assess the predictive value of a large number of NPTs. Results
The best subsets of features include approximately 30 and 20 (from the original 79 and 40) features, for ADNI and CCC data, respectively, yielding stability above 0.89 and 0.95, and AUC above 0.87 and 0.82. Most NPTs learnt using the proposed feature selection ensemble have been identified in the literature as strong predictors of conversion from MCI to AD.
Conclusions
The FS ensemble approach was able to 1) identify subsets of stable and relevant predictors from a consensus of multiple FS methods using baseline NPTs and 2) learn reliable prognostic models of conversion from MCI to AD using these subsets of features. The machine learning models learnt from these features outperformed the models trained without FS and achieved competitive results when compared to commonly used FS algorithms. Furthermore, the selected features are derived from a consensus of methods thus being more robust, while releasing users from choosing the most appropriate FS method to be used in their classification task.PTDC/EEI-SII/1937/2014; SFRH/BD/95846/2013; SFRH/BD/118872/2016info:eu-repo/semantics/publishedVersio
Short-term prediction of threatening and violent behaviour in an Acute Psychiatric Intensive Care Unit based on patient and environment characteristics
<p>Abstract</p> <p>Background</p> <p>The aims of the present study were to investigate clinically relevant patient and environment-related predictive factors for threats and violent incidents the first three days in a PICU population based on evaluations done at admittance.</p> <p>Methods</p> <p>In 2000 and 2001 all 118 consecutive patients were assessed at admittance to a Psychiatric Intensive Care Unit (PICU). Patient-related conditions as actuarial data from present admission, global clinical evaluations by physician at admittance and clinical nurses first day, a single rating with an observer rated scale scoring behaviours that predict short-term violence in psychiatric inpatients (The Brøset Violence Checklist (BVC)) at admittance, and environment-related conditions as use of segregation or not were related to the outcome measure Staff Observation Aggression Scale-Revised (SOAS-R). A multiple logistic regression analysis with SOAS-R as outcome variable was performed.</p> <p>Results</p> <p>The global clinical evaluations and the BVC were effective and more suitable than actuarial data in predicting short-term aggression. The use of segregation reduced the number of SOAS-R incidents.</p> <p>Conclusions</p> <p>In a naturalistic group of patients in a PICU segregation of patients lowers the number of aggressive and threatening incidents. Prediction should be based on clinical global judgment, and instruments designed to predict short-term aggression in psychiatric inpatients.</p> <p>Trial registrations</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT00184119">NCT00184119</a>/<a href="http://www.clinicaltrials.gov/ct2/show/NCT00184132">NCT00184132</a></p
Maintenance N-acetyl cysteine treatment for bipolar disorder : a double-blind randomised placebo controlled trial
Background N-acetyl cysteine (NAC) is a glutathione precursor that has been shown to have antidepressant efficacy in a placebo-controlled trial. The current study aimed to investigate the maintenance effects of NAC following eight weeks of open-label treatment for bipolar disorder.Method The efficacy of a double blind randomized placebo controlled trial of 2 g/day NAC as adjunct maintenance treatment for bipolar disorder was examined. Participants (n = 149) had a Montgomery Asberg Depression Rating Score of [greater than or equal to]12 at trial entry and, after eight weeks of open-label NAC treatment, were randomized to adjunctive NAC or placebo, in addition to treatment as usual. Participants (primarily outpatients) were recruited through public and private services and through newspaper advertisements. Time to intervention for a mood episode was the primary endpoint of the study, and changes in mood symptoms, functionality and quality of life measures were secondary outcomes.Results There was a substantial decrease in symptoms during the eight-week open-label NAC treatment phase. During the subsequent double-blind phase, there was minimal further change in outcome measures with scores remaining low. Consequently, from this low plateau, between-group differences did not emerge on recurrence, clinical functioning or quality of life measures.Conclusions There were no significant between-group differences in recurrence or symptomatic outcomes during the maintenance phase of the trial; however, these findings may be confounded by limitations. Trial Registration The trial was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12607000074493)
Comparison of endothelial progenitor cell function in type 2 diabetes with good and poor glycemic control
<p>Abstract</p> <p>Background</p> <p>Endothelial progenitor cells (EPCs) play an important role in vascular repair and a decrease in the number of EPCs is observed in type 2 diabetes. However, there is no report on the change of EPCs after glycemic control. This study therefore aimed to investigate the EPC number and function in patients with good and poor glycemic control.</p> <p>Methods</p> <p>The number of EPCs was studied using flow cytometry by co-expression of CD34 and VEGFR2. The EPCs were cultured and characterized by the expression of UEA-I, CD34, VEGFR2, vWF and Dil-Ac-LDL engulfment, as well as the ability to form capillary-like structures. An <it>in vitro </it>study on the effect of hyperglycemia on the proliferation and viability of the cultured EPCs was also performed.</p> <p>Results</p> <p>The number of EPCs in type 2 diabetes was significantly decreased compared with healthy controls and there was an inverse correlation between the EPC numbers and plasma glucose, as well as HbA1<sub>C</sub>. The number and function of EPCs in patients with good glycemic control were recovered compared with those with poor glycemic control. When glucose was supplemented in the culture <it>in vitro</it>, there was a negative effect on the proliferation and viability of EPCs, in a dose-dependent manner, whereas the enhancement of apoptosis was observed.</p> <p>Conclusion</p> <p>There was EPC dysfunction in type 2 diabetes which might be improved by strict glycemic control. However, the circulating EPC number and proliferative function in patients with good glycemic control did not reach the level in healthy controls.</p
The Patient Deficit Model Overturned: a qualitative study of patients' perceptions of invitation to participate in a randomized controlled trial comparing selective bladder preservation against surgery in muscle invasive bladder cancer (SPARE, CRUK/07/011)
BACKGROUND: Evidence suggests that poor recruitment into clinical trials rests on a patient ‘deficit’ model – an inability to comprehend trial processes. Poor communication has also been cited as a possible barrier to recruitment. A qualitative patient interview study was included within the feasibility stage of a phase III non-inferiority Randomized Controlled Trial (RCT) (SPARE, CRUK/07/011) in muscle invasive bladder cancer. The aim was to illuminate problems in the context of randomization. METHODS: The qualitative study used a ‘Framework Analysis’ that included ‘constant comparison’ in which semi-structured interviews are transcribed, analyzed, compared and contrasted both between and within transcripts. Three researchers coded and interpreted data. RESULTS: Twenty-four patients agreed to enter the interview study; 10 decliners of randomization and 14 accepters, of whom 2 subsequently declined their allocated treatment. The main theme applying to the majority of the sample was confusion and ambiguity. There was little indication that confusion directly impacted on decisions to enter the SPARE trial. However, confusion did appear to impact on ethical considerations surrounding ‘informed consent’, as well as cause a sense of alienation between patients and health personnel. Sub-optimal communication in many guises accounted for the confusion, together with the logistical elements of a trial that involved treatment options delivered in a number of geographical locations. CONCLUSIONS: These data highlight the difficulty of providing balanced and clear trial information within the UK health system, despite best intentions. Involvement of multiple professionals can impact on communication processes with patients who are considering participation in RCTs. Our results led us to question the ‘deficit’ model of patient behavior. It is suggested that health professionals might consider facilitating a context in which patients feel fully included in the trial enterprise and potentially consider alternatives to randomization where complex interventions are being tested. TRIAL REGISTRATION: ISRCTN6112646
Global trends in milk quality: implications for the Irish dairy industry
The quality of Irish agricultural product will become increasingly important with the ongoing liberalisation of international trade. This paper presents a review of the global and Irish dairy industries; considers the impact of milk quality on farm profitability, food processing and human health, examines global trends in quality; and explores several models that are successfully being used to tackle milk quality concerns. There is a growing global demand for dairy products, fuelled in part by growing consumer wealth in developing countries. Global dairy trade represents only 6.2% of global production and demand currently outstrips supply. Although the Irish dairy industry is small by global standards, approximately 85% of annual production is exported annually. It is also the world's largest producer of powdered infant formula. Milk quality has an impact on human health, milk processing and on-farm profitability. Somatic cell count (SCC) is a key measure of milk quality, with a SCC not exceeding 400,000 cells/ml (the EU milk quality standard) generally accepted as the international export standard. There have been ongoing improvements in milk quality among both established and emerging international suppliers. A number of countries have developed successful industry-led models to tackle milk quality concerns. Based on international experiences, it is likely that problems with effective translation of knowledge to practice, rather than incomplete knowledge per se, are the more important constraints to national progress towards improved milk quality
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