66 resultados para Play-Based Intervention
em BORIS: Bern Open Repository and Information System - Berna - Suiça
Resumo:
Screening people without symptoms of disease is an attractive idea. Screening allows early detection of disease or elevated risk of disease, and has the potential for improved treatment and reduction of mortality. The list of future screening opportunities is set to grow because of the refinement of screening techniques, the increasing frequency of degenerative and chronic diseases, and the steadily growing body of evidence on genetic predispositions for various diseases. But how should we decide on the diseases for which screening should be done and on recommendations for how it should be implemented? We use the examples of prostate cancer and genetic screening to show the importance of considering screening as an ongoing population-based intervention with beneficial and harmful effects, and not simply the use of a test. Assessing whether screening should be recommended and implemented for any named disease is therefore a multi-dimensional task in health technology assessment. There are several countries that already use established processes and criteria to assess the appropriateness of screening. We argue that the Swiss healthcare system needs a nationwide screening commission mandated to conduct appropriate evidence-based evaluation of the impact of proposed screening interventions, to issue evidence-based recommendations, and to monitor the performance of screening programmes introduced. Without explicit processes there is a danger that beneficial screening programmes could be neglected and that ineffective, and potentially harmful, screening procedures could be introduced.
Resumo:
The WHO fracture risk assessment tool FRAX® is a computer based algorithm that provides models for the assessment of fracture probability in men and women. The approach uses easily obtained clinical risk factors (CRFs) to estimate 10-year probability of a major osteoporotic fracture (hip, clinical spine, humerus or wrist fracture) and the 10-year probability of a hip fracture. The estimate can be used alone or with femoral neck bone mineral density (BMD) to enhance fracture risk prediction. FRAX® is the only risk engine which takes into account the hazard of death as well as that of fracture. Probability of fracture is calculated in men and women from age, body mass index, and dichotomized variables that comprise a prior fragility fracture, parental history of hip fracture, current tobacco smoking, ever long-term use of oral glucocorticoids, rheumatoid arthritis, other causes of secondary osteoporosis, daily alcohol consumption of 3 or more units daily. The relationship between risk factors and fracture probability was constructed using information of nine population-based cohorts from around the world. CRFs for fracture had been identified that provided independent information on fracture risk based on a series of meta-analyses. The FRAX® algorithm was validated in 11 independent cohorts with in excess of 1 million patient-years, including the Swiss SEMOF cohort. Since fracture risk varies markedly in different regions of the world, FRAX® models need to be calibrated to those countries where the epidemiology of fracture and death is known. Models are currently available for 31 countries across the world. The Swiss-specific FRAX® model was developed very soon after the first release of FRAX® in 2008 and was published in 2009, using Swiss epidemiological data, integrating fracture risk and death hazard of our country. Two FRAX®-based approaches may be used to explore intervention thresholds. They have recently been investigated in the Swiss setting. In the first approach the guideline that individuals with a fracture probability equal to or exceeding that of women with a prior fragility fracture should be considered for treatment is translated into thresholds using 10-year fracture probabilities. In that case the threshold is age-dependent and increases from 16 % at the age of 60 ys to 40 % at the age of 80 ys. The second approach is a cost-effectiveness approach. Using a FRAX®-based intervention threshold of 15 % for both, women and men 50 years and older, should permit cost-effective access to therapy to patients at high fracture probability in our country and thereby contribute to further reduce the growing burden of osteoporotic fractures.
Resumo:
FRAX-based cost-effective intervention thresholds in the Swiss setting were determined. Assuming a willingness to pay at 2× Gross Domestic Product per capita, an intervention aimed at reducing fracture risk in women and men with a 10-year probability for a major osteoporotic fracture at or above 15% is cost-effective.
Resumo:
BACKGROUND: Depressive disorders are among the leading causes of worldwide disability with mild to moderate forms of depression being particularly common. Low-intensity treatments such as online psychological treatments may be an effective way to treat mild to moderate depressive symptoms and prevent the emergence or relapse of major depression. METHODS/DESIGN: This study is a currently recruiting multicentre parallel-groups pragmatic randomized-controlled single-blind trial. A total of 1000 participants with mild to moderate symptoms of depression from various settings including in- and outpatient services will be randomized to an online psychological treatment or care as usual (CAU). We hypothesize that the intervention will be superior to CAU in reducing depressive symptoms assessed with the Personal Health Questionnaire (PHQ-9, primary outcome measure) following the intervention (12 wks) and at follow-up (24 and 48 wks). Further outcome parameters include quality of life, use of health care resources and attitude towards online psychological treatments. DISCUSSION: The study will yield meaningful answers to the question of whether online psychological treatment can contribute to the effective and efficient prevention and treatment of mild to moderate depression on a population level with a low barrier to entry. TRIAL REGISTRATION: Trial Registration Number: NCT01636752.
Resumo:
OBJECTIVES This study aimed to update the Logistic Clinical SYNTAX score to predict 3-year survival after percutaneous coronary intervention (PCI) and compare the performance with the SYNTAX score alone. BACKGROUND The SYNTAX score is a well-established angiographic tool to predict long-term outcomes after PCI. The Logistic Clinical SYNTAX score, developed by combining clinical variables with the anatomic SYNTAX score, has been shown to perform better than the SYNTAX score alone in predicting 1-year outcomes after PCI. However, the ability of this score to predict long-term survival is unknown. METHODS Patient-level data (N = 6,304, 399 deaths within 3 years) from 7 contemporary PCI trials were analyzed. We revised the overall risk and the predictor effects in the core model (SYNTAX score, age, creatinine clearance, and left ventricular ejection fraction) using Cox regression analysis to predict mortality at 3 years. We also updated the extended model by combining the core model with additional independent predictors of 3-year mortality (i.e., diabetes mellitus, peripheral vascular disease, and body mass index). RESULTS The revised Logistic Clinical SYNTAX models showed better discriminative ability than the anatomic SYNTAX score for the prediction of 3-year mortality after PCI (c-index: SYNTAX score, 0.61; core model, 0.71; and extended model, 0.73 in a cross-validation procedure). The extended model in particular performed better in differentiating low- and intermediate-risk groups. CONCLUSIONS Risk scores combining clinical characteristics with the anatomic SYNTAX score substantially better predict 3-year mortality than the SYNTAX score alone and should be used for long-term risk stratification of patients undergoing PCI.
Resumo:
Telomeres and telomerase play essential roles in the regulation of the lifespan of human cells. While normal human somatic cells do not or only transiently express telomerase and therefore shorten their telomeres with each cell division, most human cancer cells typically express high levels of telomerase and show unlimited cell proliferation. High telomerase expression allows cells to proliferate and expand long-term and therefore supports tumor growth. Owing to the high expression and its role, telomerase has become an attractive diagnostic and therapeutic cancer target. Imetelstat (GRN163L) is a potent and specific telomerase inhibitor and so far the only drug of its class in clinical trials. Here, we report on the structure and the mechanism of action of imetelstat as well as about the preclinical and clinical data and future prospects using imetelstat in cancer therapy.
Resumo:
Background: Medication-related problems are common in the growing population of older adults and inappropriate prescribing is a preventable risk factor. Explicit criteria such as the Beers criteria provide a valid instrument for describing the rate of inappropriate medication (IM) prescriptions among older adults. Objective: To reduce IM prescriptions based on explicit Beers criteria using a nurse-led intervention in a nursing-home (NH) setting. Study Design: The pre/post-design included IM assessment at study start (pre-intervention), a 4-month intervention period, IM assessment after the intervention period (post-intervention) and a further IM assessment at 1-year follow-up. Setting: 204-bed inpatient NH in Bern, Switzerland. Participants: NH residents aged ≥60 years. Intervention: The intervention included four key intervention elements: (i) adaptation of Beers criteria to the Swiss setting; (ii) IM identification; (iii) IM discontinuation; and (iv) staff training. Main Outcome Measure: IM prescription at study start, after the 4-month intervention period and at 1-year follow-up. Results: The mean±SD resident age was 80.3±8.8 years. Residents were prescribed a mean±SD 7.8±4.0 medications. The prescription rate of IMs decreased from 14.5% pre-intervention to 2.8% post-intervention (relative risk [RR] = 0.2; 95% CI 0.06, 0.5). The risk of IM prescription increased nonstatistically significantly in the 1-year follow-up period compared with post-intervention (RR = 1.6; 95% CI 0.5, 6.1). Conclusions: This intervention to reduce IM prescriptions based on explicit Beers criteria was feasible, easy to implement in an NH setting, and resulted in a substantial decrease in IMs. These results underscore the importance of involving nursing staff in the medication prescription process in a long-term care setting.
Resumo:
Reperfusion of an organ following prolonged ischemia instigates the pro-inflammatory and pro-coagulant response of ischemia / reperfusion (IR) injury. IR injury is a wide-spread pathology, observed in many clinically relevant situations, including myocardial infarction, stroke, organ transplantation, sepsis and shock, and cardiovascular surgery on cardiopulmonary bypass. Activation of the classical, alternative, and lectin complement pathways and the generation of the anaphylatoxins C3a and C5a lead to recruitment of polymorphonuclear leukocytes, generation of radical oxygen species, up-regulation of adhesion molecules on the endothelium and platelets, and induction of cytokine release. Generalized or pathway-specific complement inhibition using protein-based drugs or low-molecular-weight inhibitors has been shown to significantly reduce tissue injury and improve outcome in numerous in-vitro, ex-vivo, and in-vivo models. Despite the obvious benefits in experimental research, only few complement inhibitors, including C1-esterase inhibitor, anti-C5 antibody, and soluble complement receptor 1, have made it into clinical trials of IR injury. The results are mixed, and the next objectives should be to combine knowledge and experience obtained in the past from animal models and channel future work to translate this into clinical trials in surgical and interventional reperfusion therapy as well as organ transplantation.
Resumo:
In schizophrenia, nonverbal behavior, including body movement, is of theoretical and clinical importance. Although reduced nonverbal expressiveness is a major component of the negative symptoms encountered in schizophrenia, few studies have objectively assessed body movement during social interaction. In the present study, 378 brief, videotaped role-play scenes involving 27 stabilized outpatients diagnosed with paranoid-type schizophrenia were analyzed using Motion Energy Analysis (MEA). This method enables the objective measuring of body movement in conjunction with ordinary video recordings. Correlations between movement parameters (percentage of time in movement, movement speed) and symptom ratings from independent PANSS interviews were calculated. Movement parameters proved to be highly reliable. In keeping with predictions, reduced movement and movement speed correlated with negative symptoms. Accordingly, in patients who exhibited noticeable movement for less than 20% of the observation time, prominent negative symptoms were highly probable. As a control measure, the percentage of movement exhibited by the patients during role-play scenes was compared to that of their normal interactants. Patients with negative symptoms differed from normal interactants by showing significantly reduced head and body movement. Two specific positive symptoms were possibly related to movement parameters: suspiciousness tended to correlate with reduced head movement, and the expression of unusual thought content tended to relate to increased movement. Overall, a close and theoretically meaningful association between the objective movement parameters and the symptom profiles was found. MEA appears to be an objective, reliable and valid method for quantifying nonverbal behavior, an aspect which may furnish new insights into the processes related to reduced expressiveness in schizophrenia.
Resumo:
In this paper we present a new population-based method for the design of bone fixation plates. Standard pre-contoured plates are designed based on the mean shape of a certain population. We propose a computational process to design implants while reducing the amount of required intra-operative shaping, thus reducing the mechanical stresses applied to the plate. A bending and torsion model was used to measure and minimize the necessary intra-operative deformation. The method was applied and validated on a population of 200 femurs that was further augmented with a statistical shape model. The obtained results showed substantial reduction in the bending and torsion needed to shape the new design into any bone in the population when compared to the standard mean-based plates.
Resumo:
Non-linear image registration is an important tool in many areas of image analysis. For instance, in morphometric studies of a population of brains, free-form deformations between images are analyzed to describe the structural anatomical variability. Such a simple deformation model is justified by the absence of an easy expressible prior about the shape changes. Applying the same algorithms used in brain imaging to orthopedic images might not be optimal due to the difference in the underlying prior on the inter-subject deformations. In particular, using an un-informed deformation prior often leads to local minima far from the expected solution. To improve robustness and promote anatomically meaningful deformations, we propose a locally affine and geometry-aware registration algorithm that automatically adapts to the data. We build upon the log-domain demons algorithm and introduce a new type of OBBTree-based regularization in the registration with a natural multiscale structure. The regularization model is composed of a hierarchy of locally affine transformations via their logarithms. Experiments on mandibles show improved accuracy and robustness when used to initialize the demons, and even similar performance by direct comparison to the demons, with a significantly lower degree of freedom. This closes the gap between polyaffine and non-rigid registration and opens new ways to statistically analyze the registration results.
Resumo:
This paper presents a new approach for reconstructing a patient-specific shape model and internal relative intensity distribution of the proximal femur from a limited number (e.g., 2) of calibrated C-arm images or X-ray radiographs. Our approach uses independent shape and appearance models that are learned from a set of training data to encode the a priori information about the proximal femur. An intensity-based non-rigid 2D-3D registration algorithm is then proposed to deformably fit the learned models to the input images. The fitting is conducted iteratively by minimizing the dissimilarity between the input images and the associated digitally reconstructed radiographs of the learned models together with regularization terms encoding the strain energy of the forward deformation and the smoothness of the inverse deformation. Comprehensive experiments conducted on images of cadaveric femurs and on clinical datasets demonstrate the efficacy of the present approach.