Zhuleth2867

There was little theoretical development in included studies, with little insight into the contextual factors or underlying mechanism required to support the implementation of integrated care initiatives. This review identified a set of inter-related barriers and facilitators which, if addressed, can improve the implementation and sustainability of truly integrated care.

To investigate the relationship between arteriovenous fistula (AVF) arterial diameter (AD) and AVF aneurysm development and progression.

This study identified all patients who underwent fistulograms which demonstrated AVF aneurysms meeting criteria and requiring surgical intervention between 01/01/2014 and 7/30/2016. Patient demographics were collected and AVF dimensions were measured on fistulograms. A control group with nonaneurysmal AVFs who had undergone serial fistulograms between 2013 and 2016 were identified and identical datasets collected. Statistical analysis was performed with STATA 14.0 using student's

-test, Chi square tests and linear regression.

45 eligible patients were identified in the AVF aneurysm study group and 24 in the control group, with the mean age of AVF creation being older in the control group (61.8 vs 53 years,

 = 0.03). The mean interval between AVF creation and first fistulogram in the study group was 1464 ± 282 days, compared to an interval of 263 ± 101 days in the control group (

 = 0.003). The AD on the first fistulogram in those study group patients with aneurysms evident on first fistulogram was greater than in the control group (6.5±1.8 mm vs 5.0 ± 1.8 mm,

 = 0.003). The AD on first fistulogram of the study group predicted maximum aneurysm diameter on last fistulogram (

 = 0.6,

 = 0.03) as well as the interval between first fistulogram and surgical revision (

 = -0.33,

 = 0.03).

AVF aneurysms are a later complication in access natural history and AD may help to predict their progression.

AVF aneurysms are a later complication in access natural history and AD may help to predict their progression.We report three cases where the connector/sleeve, which helps fix the flexible catheter section to a port injection chamber, was inadvertently left in scar tissue during port removal. Concerned patients presented months later with a palpable subcutaneous nodule, near the port site. The nodules were variably imaged with plain X-rays, mammography or ultrasound with the diagnosis correctly made by a surgeon familiar with devices. Two connectors were removed, and one was left in place following discussions with the patient. Prevention, recognition and management of this problem are discussed.Radiation damage of healthy tissues represents one of the complications of radiotherapy effectiveness. This study is focused on the screening of potentially effective drugs routinely used in medical practice and involved in the mechanism of radiation injury, namely for radiation-induced production of free radicals in the body. Experiments in rats revealed significant reduction of oxidative stress (malondialdehyde) and inflammatory marker (tumor necrosis factor α) in 10 Gy irradiated groups after administration of atorvastatin and a slight decrease after tadalafil administration, which indicates that one of the possible mechanisms for mitigation of radiation-induced cardiac damage could be the modulation of nitric oxide (NO) in endothelium and phosphodiesterase 5. In addition, miRNAs were analyzed as potential markers and therapeutically effective molecules. Expression of miRNA-21 and miRNA-15b showed the most significant changes after irradiation. Atorvastatin and tadalafil normalized changes of miRNA (miRNA-1, miRNA-15b, miRNA-21) expression levels in irradiated hearts. selleck chemicals This screening study concludes that administration of specific drugs could mitigate the negative impact of radiation on the heart, but more detailed experiments oriented to other aspects of drug effectiveness and their exact mechanisms are still needed.Measuring the effectiveness of interprofessional education (IPE) experiences is essential but challenging. Surveying learners before (pretest) and after (posttest) an IPE experience may result in minimal change due to response shift bias. Retrospective pretest/posttest assessment may ameliorate response shift bias but may also result in inflated change scores due to social desirability bias. We studied a cohort of 675 students from 12 health professions who completed the Interprofessional Attitudes Scale (IPAS) within the 4 weeks before (pretest) and the 3 weeks after (posttest) an IPE forum and completed the Interprofessional Collaborative Competency Attainment Survey (ICCAS) within the 3 weeks after the forum as a retrospective pretest/posttest. We found higher scores on the pretest IPAS than the retrospective pretest ICCAS and greater change in scores on the ICCAS than the IPAS, indicating potential response shift and social desirability biases. Furthermore, we found few significant correlations between change scores in subscales of the two tests, but a high number of strong and significant correlation among the ICCAS subscale change scores. Our results indicate the timing of pretest administration may impact change scores or that subscales of IPAS may be more unique than those of ICCAS. These findings suggest that educators should consider the potential impact of response shift and social desirability biases when interpreting results of the IPAS and ICCAS in response to an IPE learning experience.Palliative care is referred to a set of programs for patients that suffer life-limiting illnesses. These programs aim to maximize the quality of life (QoL) for the last stage of life. They are currently based on clinical evaluation of the risk of 1-year mortality. The main aim of this work is to develop and validate machine-learning-based models to predict the exitus of a patient within the next year using data gathered at hospital admission. Five machine-learning techniques were applied using a retrospective dataset. The evaluation was performed with five metrics computed by a resampling strategy Accuracy, the area under the ROC curve, Specificity, Sensitivity, and the Balanced Error Rate. All models reported an AUC ROC from 0.857 to 0.91. Specifically, Gradient Boosting Classifier was the best model, producing an AUC ROC of 0.91, a sensitivity of 0.858, a specificity of 0.808, and a BER of 0.1687. Information from standard procedures at hospital admission combined with machine learning techniques produced models with competitive discriminative power.