960 resultados para Clinical reasoning


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In order to progress beyond currently available medical devices and implants, the concept of tissue engineering has moved into the centre of biomedical research worldwide. The aim of this approach is not to replace damaged tissue with an implant or device but rather to prompt the patient's own tissue to enact a regenerative response by using a tissue-engineered construct to assemble new functional and healthy tissue. More recently, it has been suggested that the combination of Synthetic Biology and translational tissue-engineering techniques could enhance the field of personalized medicine, not only from a regenerative medicine perspective, but also to provide frontier technologies for building and transforming the research landscape in the field of in vitro and in vivo disease models.

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Summary High bone mineral density on routine dual energy X-ray absorptiometry (DXA) may indicate an underlying skeletal dysplasia. Two hundred fifty-eight individuals with unexplained high bone mass (HBM), 236 relatives (41% with HBM) and 58 spouses were studied. Cases could not float, had mandible enlargement, extra bone, broad frames, larger shoe sizes and increased body mass index (BMI). HBM cases may harbour an underlying genetic disorder. Introduction High bone mineral density is a sporadic incidental finding on routine DXA scanning of apparently asymptomatic individuals. Such individuals may have an underlying skeletal dysplasia, as seen in LRP5 mutations. We aimed to characterize unexplained HBM and determine the potential for an underlying skeletal dysplasia. Methods Two hundred fifty-eight individuals with unexplained HBM (defined as L1 Z-score ≥ +3.2 plus total hip Z-score ≥ +1.2, or total hip Z-score ≥ +3.2) were recruited from 15 UK centres, by screening 335,115 DXA scans. Unexplained HBM affected 0.181% of DXA scans. Next 236 relatives were recruited of whom 94 (41%) had HBM (defined as L1 Z-score + total hip Z-score ≥ +3.2). Fifty-eight spouses were also recruited together with the unaffected relatives as controls. Phenotypes of cases and controls, obtained from clinical assessment, were compared using random-effects linear and logistic regression models, clustered by family, adjusted for confounders, including age and sex. Results Individuals with unexplained HBM had an excess of sinking when swimming (7.11 [3.65, 13.84], p < 0.001; adjusted odds ratio with 95% confidence interval shown), mandible enlargement (4.16 [2.34, 7.39], p < 0.001), extra bone at tendon/ligament insertions (2.07 [1.13, 3.78], p = 0.018) and broad frame (3.55 [2.12, 5.95], p < 0.001). HBM cases also had a larger shoe size (mean difference 0.4 [0.1, 0.7] UK sizes, p = 0.009) and increased BMI (mean difference 2.2 [1.3, 3.1] kg/m 2, p < 0.001). Conclusion Individuals with unexplained HBM have an excess of clinical characteristics associated with skeletal dysplasia and their relatives are commonly affected, suggesting many may harbour an underlying genetic disorder affecting bone mass.

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Objectives. To confirm the association of a functional single-nucleotide polymorphism (SNP), C1858T (rs2476601), in the PTPN22 gene of British Caucasian rheumatoid arthritis (RA) patients and to evaluate its influence on the RA phenotype. Methods. A total of 686 RA patients and 566 healthy volunteers, all of British Caucasian origin, were genotyped for C1858T polymorphism by PCR-restriction fragment length polymorphism assay. Data were analysed using SPSS software and the χ 2 test as applicable. Results. The PTPN22 1858T risk allele was more prevalent in the RA patients (13.9%) compared with the healthy controls (10.3%) (P = 0.008, odds ratio 1.4, 95% confidence interval 1.09-1.79). The association of the T allele was restricted to those with rheumatoid factor (RF)-positive disease (n = 524, 76.4%) (P = 0.004, odds ratio 1.5, 95% confidence interval 1.1-1.9). We found no association between PTPN22 and the presence of the HLA-DRB1 shared epitope or clinical characteristics. Conclusions. We confirmed the previously reported association of PTPN22 with RF-positive RA, which was independent from the HLA-DRB1 genotype.

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Forty-three children with recurrent abdominal pain who had received treatment from a paediatric gastroenterology clinic were reassessed 6 and 12 months after initial presentation. Measures of children's pain included a pain diary (PD) which measured pain intensity, a parent observation record (POR) which assessed pain behaviour and a structured interview to assess the degree to which pain interferes with the child's activities. Pretreatment measures of the child's history of pain, coping strategies in dealing with pain, and their mother's caregiving strategies were examined as predictors of two indices of clinical improvement: the extent of change in pain on the child's pain diary from pre-test to 6 months follow-up, and the degree of interference to the child's activities. All children had shown significant improvement in the level of pain at follow up, with 74.4% being pain free at 12 month follow-up on the PD and 83.7% being pain free on the POR. The amount of change they showed varied, with some showing residual impairment even though they were significantly improved. Regression analyses showed that children with greatest reductions on the child's pain diary at the 6 month follow-up were those with a stress-related mode of onset, whose mothers used more adaptive caregiving strategies, and who received cognitive behavioural family intervention. There was also a non significant trend for younger children to fare better. These data suggest the importance of early diagnosis and routinely assessing parental caregiving behaviour and beliefs about the origins of pain in planning treatment for children with RAP.

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Although there is a plethora of definitions of blended learning, the underlying distinguishing feature is the combination of traditional content delivery and the utilisation of technology. Within Medical Imaging undergraduate education there is evidence of advantages and increased student engagement when utilising a blended learning approach. Although the embedding of technology has been proven to be a useful teaching tool, “Educators should tailor their teaching media to learner’s needs rather than assume that web based learning is intrinsically superior”. This study aims to determine which clinical learning tools are perceived to be the most useful to the student in preparing them for placements.

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The nutritional profiles of 37 children (aged 0.5-14.0 years) with chronic liver disease at the time of acceptance for orthotopic liver transplantation (OLTP) have been evaluated using clinical, biochemical and body composition methods. Nutritional progress while waiting for a donor has been related to outcome, whether transplanted or not. At the time of acceptance, most children were underweight (mean standard deviation (s.d.) weight = -1.4 ± 0.2) and stunted (mean s.d. height = - 2.2 ± 0.4), had low serum albumin (27/35) and had reduced body fat and depleted body cell mass (measured by total body potassium - mean % expected for age = 58 ± 5%, n = 15). Mean ad libitum nutrient intake was 63 ± 5% of recommended daily intake (RDI). Those who died while waiting (n = 8) had significantly lower mean initial s.d. weight compared with those transplanted. The overall actuarial 1 year survival of those who were transplanted (mean waiting time = 75 days) was 81% but those who were initially well nourished (s.d. weight >-1.0) had an actuarial 1 year survival of 100%. There were no significant differences in actuarial survival in relationship to age, type of transplant (whole liver or segmental), liver biochemistry or the presence or absence of ascites. Of the total group accepted for OLTP, whether transplanted or not, the overall 1 year survival for those who were relatively well nourished was 88% and for those undernourished (initial s.d. weight <-1.0) was 38% (P<0.003). Declining nutritional status during the waiting period also adversely affected outcome. We conclude that malnutrition and/or declining nutritional status is a major factor adversely affecting survival in children awaiting OLTP. In transplant units where waiting time is greater than 40 days, earlier referral, prioritization of cases and the use of adult donor livers may reduce this risk and efforts to maintain or improve nutritional status deserve further study.

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Introduction Two symposia on “cardiovascular diseases and vulnerable plaques” Cardiovascular disease (CVD) is the leading cause of death worldwide. Huge effort has been made in many disciplines including medical imaging, computational modeling, bio- mechanics, bioengineering, medical devices, animal and clinical studies, population studies as well as genomic, molecular, cellular and organ-level studies seeking improved methods for early detection, diagnosis, prevention and treatment of these diseases [1-14]. However, the mechanisms governing the initiation, progression and the occurrence of final acute clinical CVD events are still poorly understood. A large number of victims of these dis- eases who are apparently healthy die suddenly without prior symptoms. Available screening and diagnostic methods are insufficient to identify the victims before the event occurs [8,9]. Most cardiovascular diseases are associated with vulnerable plaques. A grand challenge here is to develop new imaging techniques, predictive methods and patient screening tools to identify vulnerable plaques and patients who are more vulnerable to plaque rupture and associated clinical events such as stroke and heart attack, and recommend proper treatment plans to prevent those clinical events from happening. Articles in this special issue came from two symposia held recently focusing on “Cardio-vascular Diseases and Vulnerable Plaques: Data, Modeling, Predictions and Clinical Applications.” One was held at Worcester Polytechnic Institute (WPI), Worcester, MA, USA, July 13-14, 2014, right after the 7th World Congress of Biomechanics. This symposium was endorsed by the World Council of Biomechanics, and partially supported by a grant from NIH-National Institute of Biomedical Image and Bioengineering. The other was held at Southeast University (SEU), Nanjing, China, April 18-20, 2014.

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This study investigates the use of unsupervised features derived from word embedding approaches and novel sequence representation approaches for improving clinical information extraction systems. Our results corroborate previous findings that indicate that the use of word embeddings significantly improve the effectiveness of concept extraction models; however, we further determine the influence that the corpora used to generate such features have. We also demonstrate the promise of sequence-based unsupervised features for further improving concept extraction.

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The goal of this article is to provide a new design framework and its corresponding estimation for phase I trials. Existing phase I designs assign each subject to one dose level based on responses from previous subjects. Yet it is possible that subjects with neither toxicity nor efficacy responses can be treated at higher dose levels, and their subsequent responses to higher doses will provide more information. In addition, for some trials, it might be possible to obtain multiple responses (repeated measures) from a subject at different dose levels. In this article, a nonparametric estimation method is developed for such studies. We also explore how the designs of multiple doses per subject can be implemented to improve design efficiency. The gain of efficiency from "single dose per subject" to "multiple doses per subject" is evaluated for several scenarios. Our numerical study shows that using "multiple doses per subject" and the proposed estimation method together increases the efficiency substantially.

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A decision-theoretic framework is proposed for designing sequential dose-finding trials with multiple outcomes. The optimal strategy is solvable theoretically via backward induction. However, for dose-finding studies involving k doses, the computational complexity is the same as the bandit problem with k-dependent arms, which is computationally prohibitive. We therefore provide two computationally compromised strategies, which is of practical interest as the computational complexity is greatly reduced: one is closely related to the continual reassessment method (CRM), and the other improves CRM and approximates to the optimal strategy better. In particular, we present the framework for phase I/II trials with multiple outcomes. Applications to a pediatric HIV trial and a cancer chemotherapy trial are given to illustrate the proposed approach. Simulation results for the two trials show that the computationally compromised strategy can perform well and appear to be ethical for allocating patients. The proposed framework can provide better approximation to the optimal strategy if more extensive computing is available.

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Prostate cancer is a leading contributor to male cancer-related deaths worldwide. Kallikrein-related peptidases (KLKs) are serine proteases that exhibit deregulated expression in prostate cancer, with KLK3, or prostate specific antigen (PSA), being the widely-employed clinical biomarker for prostate cancer. Other KLKs, such as KLK2, show promise as prostate cancer biomarkers and, additionally, their altered expression has been utilised for the design of KLK-targeted therapies. There is also a large body of in vitro and in vivo evidence supporting their role in cancer-related processes. Here, we review the literature on studies to date investigating the potential of other KLKs, in addition to PSA, as biomarkers and in therapeutic options, as well as their current known functional roles in cancer progression. Increased knowledge of these KLK-mediated functions, including degradation of the extracellular matrix, local invasion, cancer cell proliferation, interactions with fibroblasts, angiogenesis, migration, bone metastasis and tumour growth in vivo, may help define new roles as prognostic biomarkers and novel therapeutic targets for this cancer.

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In Pediatric AIDS Clinical Trials Group 377, antiretroviral therapy-experienced children were randomized to 4 treatment arms that included different combinations of stavudine, lamivudine (3TC), nevirapine (Nvp), nelfinavir (Nfv), and ritonavir (Rtv). Previous treatment with zidovudine (Zdv), didanosine (ddI), or zalcitabine (ddC) was acceptable. Drug resistance ((R)) mutations were assessed before study treatment (baseline) and at virologic failure. Zdv(R), ddI(R), and ddC(R) mutations were detected frequently at baseline but were not associated with virologic failure. Children with drug resistance mutations at baseline had greater reductions in virus load over time than did children who did not. Nvp(R) and 3TC(R) mutations were detected frequently at virologic failure, and Nvp(R) mutations were more common among children receiving 3-drug versus 4-drug Nvp-containing regimens. Children who were maintained on their study regimen after virologic failure accumulated additional Nvp(R) and 3TC(R) mutations plus Rtv(R) and Nfv(R) mutations. However, Rtv(R) and Nfv(R) mutations were detected at unexpectedly low rates.

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Suppose two treatments with binary responses are available for patients with some disease and that each patient will receive one of the two treatments. In this paper we consider the interests of patients both within and outside a trial using a Bayesian bandit approach and conclude that equal allocation is not appropriate for either group of patients. It is suggested that Gittins indices should be used (using an approach called dynamic discounting by choosing the discount rate based on the number of future patients in the trial) if the disease is rare, and the least failures rule if the disease is common. Some analytical and simulation results are provided.

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We explore the use of Gittins indices to search for near optimality in sequential clinical trials. Some adaptive allocation rules are proposed to achieve the following two objectives as far as possible: (i) to reduce the expected successes lost, (ii) to minimize the error probability at the end. Simulation results indicate the merits of the rules based on Gittins indices for small trial sizes. The rules are generalized to the case when neither of the response densities is known. Asymptotic optimality is derived for the constrained rules. A simple allocation rule is recommended for one-stage models. The simulation results indicate that it works better than both equal allocation and Bather's randomized allocation. We conclude with a discussion of possible further developments.

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This paper presents a symbolic navigation system that uses spatial language descriptions to inform goal-directed exploration in unfamiliar office environments. An abstract map is created from a collection of natural language phrases describing the spatial layout of the environment. The spatial representation in the abstract map is controlled by a constraint based interpretation of each natural language phrase. In goal-directed exploration of an unseen office environment, the robot links the information in the abstract map to observed symbolic information and its grounded world representation. This paper demonstrates the ability of the system, in both simulated and real-world trials, to efficiently find target rooms in environments that it has never been to previously. In three unexplored environments, it is shown that on average the system travels only 8.42% further than the optimal path when using only natural language phrases to complete navigation tasks.