Occurrence of refeeding syndrome in adults started on artificial nutrition support: prospective cohort study

This final article is available for use under the terms of the Creative Commons Attribution Non-Commercial 2.0 Licence; see http://bmjopen.bmj.comRefeeding syndrome is a potentially life-threatening condition characterised by severe intracellular electrolyte shifts, acute circulatory fluid overload and organ failure. The initial symptoms are non-specific but early clinical features are severely low-serum electrolyte concentrations of potassium, phosphate or magnesium. Risk factors for the syndrome include starvation, chronic alcoholism, anorexia nervosa and surgical interventions that require lengthy periods of fasting. The causes of the refeeding syndrome are excess or unbalanced enteral, parenteral or oral nutritional intake. Prevention of the syndrome includes identification of individuals at risk, controlled hypocaloric nutritional intake and supplementary electrolyte replacementPeer reviewedFinal Published versio

Analysis of the pancreato-biliary system from MRCP

We present a preprocessing and segmentation scheme designed to address the particular difficulties encountered in the analysis of magnetic resonance cholangiopancreatography (MRCP) data, as a precursor to the application of computer assisted diagnosis (CAD) techniques. MRCP generates noisy, low resolution, non-isometric data which often exhibits significant greylevel inhomogeneities. This combination of characteristics results in data volumes in which reliable segmentation and analysis are difficult to achieve. In this paper we describe a data processing approach developed to overcome these difficulties and allow for the effective application of automated CAD procedures in the analysis of the biliary tree and pancreatic duct in MRCP examinations

Dietary guidelines for irritable bowel syndrome are important for gastroenterologists, dietitians and people with irritable bowel syndrome

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134108/1/jhn12413_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134108/2/jhn12413.pd

Adverse Selection and Incentives in an Early Retirement Program

We evaluate potential determinants of enrollment in an early retirement incentive program for non-tenure-track employees at a large university. Using administrative records on the eligible population of employees not covered by collective bargaining agreements, historical employee count and layoff data by budget units, and public information on unit budgets, we find dips in per-employee finances in a budget unit during the application year and higher recent per employee layoffs were associated with increased probabilities of eligible employee program enrollment. Our results also suggest that, on average, employees whose salaries are lower than we would predict given their personal characteristics and job titles were more likely to enroll in the early retirement program. To the extent that employees' compensation reflect their productivity, as it should under a pay system in which annual salary increases are based on merit, this finding suggests that adverse selection was not a problem with the program. That is, we find no evidence that on average the "most productive" employees took the incentive.retirement incentive program, adverse selection, layoff threat, university

Adverse Selection and Incentives in an Early Retirement Program

We evaluate potential determinants of enrollment in an early retirement incentive program for non-tenure-track employees of a large university. Using administrative record on the eligible population of employees not covered by collective bargaining agreements, historical employee count and layoff data by budget units, and public information on unit budgets, we find dips in per-employee finance in a budget unit during the application year and higher recent per employee layoffs were associated with increased probabiliites of eligible employee program enrollment. Our results also suggest, on average, that employees whose salaries are lower than we would predict given their personal characteristics and job titles were more likely to enroll in the early retirement program. To the extent that employees' compensation reflects their productivity, as it should under a pay system in which annual salary increases are based on merit, this finidng suggests that adverse selection was not a problem with the program. That is, we find no evidence that on average the "most productive" employees took the incentive.

Volumetric reconstruction: matching and merging in DICOM data

Evolving protocols in Whole Body MRI (WB-MRI) present new challenges in the application of automated image processing and analysis procedures. We address two issues relating to sectionally acquired coronal WBMRI: greyscale non-uniformity correction and accurate data merging. The body is scanned in a number of slightly overlapping coronal sections, each containing 32 eight mm thick slices. Adjacent coronal sub-section often demonstrate a significant greyscale mismatch resulting in sharp discontinuities within homogeneous tissue regions in the body. This presents problems for automatic segmentation and classification approaches. Similarly a simplistic reconstruction procedure can lead to inaccuracies in the relative alignment of the data from each DICOM image in the reconstructed volume, resulting in the dislocation of small structure

Intensity non-uniformity correction in multi-section whole body MRI

As whole body MRI (WB-MRI) gains currency, the data this class of technique generates presents new challenges for the imaging community. One acquisition protocol currently being applied with considerable success entails imaging the subject in a number of successive coronal sections, resulting in a high resolution, gap free, full body acquisition. However this technique often results in considerable greylevel offsets between adjacent coronal sections. To make the images suitable for the application of automated image analysis procedures these discontinuities in the grey data must be alleviated. We examine the issues related to this problem, and present a solution based on histogram rescaling, which is designed to correct for the non-uniformities while preserving the integrity of the data histogram so that it can be used robustly in later processing steps. The final datasets reconstructed from the resampled coronal sections exhibit superior greyscale homogeneity, visually and in statistical measures, and the image segmentation results achieved using this corrected data are consistently more robust and more accurate than those arrived at using the original raw data. The approach has been tested and successfully validated on a database of sixty two WB-MRI datasets

Identification of body fat tissues in MRI data

In recent years non-invasive medical diagnostic techniques have been used widely in medical investigations. Among the various imaging modalities available, Magnetic Resonance Imaging is very attractive as it produces multi-slice images where the contrast between various types of body tissues such as muscle, ligaments and fat is well defined. The aim of this paper is to describe the implementation of an unsupervised image analysis algorithm able to identify the body fat tissues from a sequence of MR images encoded in DICOM format. The developed algorithm consists of three main steps. The first step pre-processes the MR images in order to reduce the level of noise. The second step extracts the image areas representing fat tissues by using an unsupervised clustering algorithm. Finally, image refinements are applied to reclassify the pixels adjacent to the initial fat estimate and to eliminate outliers. The experimental data indicates that the proposed implementation returns accurate results and furthermore is robust to noise and to greyscale in-homogeneity

The effect of communicating the genetic risk of cardiometabolic disorders on motivation and actual engagement in preventative lifestyle modification and clinical outcome: a systematic review and meta-analysis of randomised controlled trials.

Genetic risk prediction of chronic conditions including obesity, diabetes and CVD currently has limited predictive power but its potential to engage healthy behaviour change has been of immense research interest. We aimed to understand whether the latter is indeed true by conducting a systematic review and meta-analysis investigating whether genetic risk communication affects motivation and actual behaviour change towards preventative lifestyle modification. We included all randomised controlled trials (RCT) since 2003 investigating the impact of genetic risk communication on health behaviour to prevent cardiometabolic disease, without restrictions on age, duration of intervention or language. We conducted random-effects meta-analyses for perceived motivation for behaviour change and clinical changes (weight loss) and a narrative analysis for other outcomes. Within the thirteen studies reviewed, five were vignette studies (hypothetical RCT) and seven were clinical RCT. There was no consistent effect of genetic risk on actual motivation for weight loss, perceived motivation for dietary change (control v. genetic risk group standardised mean difference (smd) -0·15; 95 % CI -1·03, 0·73, P=0·74) or actual change in dietary behaviour. Similar results were observed for actual weight loss (control v. high genetic risk SMD 0·29 kg; 95 % CI -0·74, 1·31, P=0·58). This review found no clear or consistent evidence that genetic risk communication alone either raises motivation or translates into actual change in dietary intake or physical activity to reduce the risk of cardiometabolic disorders in adults. Of thirteen studies, eight were at high or unclear risk of bias. Additional larger-scale, high-quality clinical RCT are warranted.Medical Research CouncilThis is the final version of the article. It first appeared from Cambridge University Press via https://doi.org/10.1017/S0007114516002488