Evaluating Patient Preferences of Maintenance Therapy for the Treatment of Chronic Obstructive Pulmonary Disease: A Discrete Choice Experiment in the UK, USA and Germany.

Introduction: With increasing availability of different treatments for chronic obstructive pulmonary disease (COPD), we sought to understand patient preferences for COPD treatment in the UK, USA, and Germany using a discrete choice experiment (DCE). Methods: Qualitative research identified six attributes associated with COPD maintenance treatments: ease of inhaler use, exacerbation frequency, frequency of inhaler use, number of different inhalers used, side effect frequency, and out-of-pocket costs. A DCE using these attributes, with three levels each, was designed and tested through cognitive interviews and piloting. It comprised 18 choice sets, selected using a D-efficient experimental design. Demographics and disease history were collected and the final DCE survey was completed online by participants recruited from panels in the UK, USA and Germany. Responses were analyzed using mixed logit models, with results expressed as odds ratios (ORs). Results: Overall, 450 participants (150 per country) completed the DCE; most (UK and Germany, 97.3%; USA, 98.0%) were included in the final analysis. Based on relative attribute importance, avoidance of side effects was found to be most important (UK: OR 11.65; USA: OR 7.17; Germany: OR 11.45; all p<0.0001), followed by the likelihood of fewer exacerbations (UK: OR 2.22; USA: OR 1.63; Germany: OR 2.54; all p<0.0001) and increased ease of use (UK: OR 1.84; USA: OR 1.84; Germany: OR 1.60; all p<0.0001). Number of inhalers, out-of-pocket costs, and frequency of inhaler use were found to be less important. Preferences were relatively consistent across the three countries. All participants required a reduction in exacerbations to accept more frequent inhaler use or use of more inhalers. Conclusion: When selecting COPD treatment, individuals assigned the highest value to the avoidance of side effects, experiencing fewer exacerbations, and ease of inhaler use. Ensuring that patients' preferences are considered may encourage treatment compliance

LayoutLM: Pre-training of Text and Layout for Document Image Understanding

Pre-training techniques have been verified successfully in a variety of NLP tasks in recent years. Despite the widespread use of pre-training models for NLP applications, they almost exclusively focus on text-level manipulation, while neglecting layout and style information that is vital for document image understanding. In this paper, we propose the \textbf{LayoutLM} to jointly model interactions between text and layout information across scanned document images, which is beneficial for a great number of real-world document image understanding tasks such as information extraction from scanned documents. Furthermore, we also leverage image features to incorporate words' visual information into LayoutLM. To the best of our knowledge, this is the first time that text and layout are jointly learned in a single framework for document-level pre-training. It achieves new state-of-the-art results in several downstream tasks, including form understanding (from 70.72 to 79.27), receipt understanding (from 94.02 to 95.24) and document image classification (from 93.07 to 94.42). The code and pre-trained LayoutLM models are publicly available at \url{https://aka.ms/layoutlm}.Comment: KDD 202

Dimensions of Children's Health Beliefs

Health beliefs interviews were conducted with 250 children aged 6-17 years. A factor analysis of the items resulted in six correlated fac tors which were interpreted as 1) specific health concerns, 2)general health concerns, 3) perceived parental concern, 4) perceived general susceptibility, 5) perceived susceptibility to specific conditions, and 6) perceived seriousness of and susceptibility to disease. Factor scores were computed and two-way analyses of variance (by age and sex of child) were conducted on six sets of factor scores. No significant sex differences or sex by age in teraction effects were noted. Younger children scored significantly higher on "specific health concerns"and "perceived general susceptibility,"while older children scored significantly higher on "perceived parental concern. " Tests of differences among variances showed a tendency for the variability to be greater among younger children. The results are interpreted as pro viding partial support for a model of children's health beliefs and as a basis for further operationalization of concepts which are central to an understand ing of motivated health behavior. Implications for practice are discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66657/2/10.1177_109019818000700304.pd

Testing Newtonian Gravity with AAOmega: Mass-to-Light Profiles of Four Globular Clusters

Testing Newtonian gravity in the weak-acceleration regime is vital to our understanding of the nature of the gravitational interaction. It has recently been claimed that the velocity dispersion profiles of several globular clusters flatten out at large radii, reminiscent of galaxy rotation curves, even though globular clusters are thought to contain little or no dark matter. We investigate this claim, using AAOmega observations of four globular clusters, namely M22, M30, M53 and M68. M30, one such cluster that has had this claim made for its velocity dispersion, was included for comparison with previous studies. We find no statistically significant flattening of the velocity dispersion at large radii for any of our target clusters and therefore we infer the observed dynamics do not require that globular clusters are dark matter dominated, or a modification of gravity. Furthermore, by applying a simple dynamical model we determine the radial mass-to-light profiles for each cluster. The isothermal rotations of each cluster are also measured, with M22 exhibiting clear rotation, M68 possible rotation and M30 and M53 lacking any rotation, within the uncertainties.Comment: 7 pages, 4 figures and two tables. Accepted by MNRA

Effects of local hypothermia-rewarming on physiology, metabolism and inflammation of acutely injured human spinal cord.

In five patients with acute, severe thoracic traumatic spinal cord injuries (TSCIs), American spinal injuries association Impairment Scale (AIS) grades A-C, we induced cord hypothermia (33 °C) then rewarming (37 °C). A pressure probe and a microdialysis catheter were placed intradurally at the injury site to monitor intraspinal pressure (ISP), spinal cord perfusion pressure (SCPP), tissue metabolism and inflammation. Cord hypothermia-rewarming, applied to awake patients, did not cause discomfort or neurological deterioration. Cooling did not affect cord physiology (ISP, SCPP), but markedly altered cord metabolism (increased glucose, lactate, lactate/pyruvate ratio (LPR), glutamate; decreased glycerol) and markedly reduced cord inflammation (reduced IL1β, IL8, MCP, MIP1α, MIP1β). Compared with pre-cooling baseline, rewarming was associated with significantly worse cord physiology (increased ICP, decreased SCPP), cord metabolism (increased lactate, LPR; decreased glucose, glycerol) and cord inflammation (increased IL1β, IL8, IL4, IL10, MCP, MIP1α). The study was terminated because three patients developed delayed wound infections. At 18-months, two patients improved and three stayed the same. We conclude that, after TSCI, hypothermia is potentially beneficial by reducing cord inflammation, though after rewarming these benefits are lost due to increases in cord swelling, ischemia and inflammation. We thus urge caution when using hypothermia-rewarming therapeutically in TSCI

Ribosome profiling-guided depletion of an mRNA increases cell growth rate and protein secretion

Recombinant protein production coopts the host cell machinery to provide high protein yields of industrial enzymes or biotherapeutics. However, since protein translation is energetically expensive and tightly controlled, it is unclear if highly expressed recombinant genes are translated as efficiently as host genes. Furthermore, it is unclear how the high expression impacts global translation. Here, we present the first genome-wide view of protein translation in an IgG-producing CHO cell line, measured with ribosome profiling. Through this we found that our recombinant mRNAs were translated as efficiently as the host cell transcriptome, and sequestered up to 15% of the total ribosome occupancy. During cell culture, changes in recombinant mRNA translation were consistent with changes in transcription, demonstrating that transcript levels influence specific productivity. Using this information, we identified the unnecessary resistance marker NeoR to be a highly transcribed and translated gene. Through siRNA knock-down of NeoR, we improved the production- and growth capacity of the host cell. Thus, ribosomal profiling provides valuable insights into translation in CHO cells and can guide efforts to enhance protein production

Dealing with missing standard deviation and mean values in meta-analysis of continuous outcomes: a systematic review

Background: Rigorous, informative meta-analyses rely on availability of appropriate summary statistics or individual participant data. For continuous outcomes, especially those with naturally skewed distributions, summary information on the mean or variability often goes unreported. While full reporting of original trial data is the ideal, we sought to identify methods for handling unreported mean or variability summary statistics in meta-analysis. Methods: We undertook two systematic literature reviews to identify methodological approaches used to deal with missing mean or variability summary statistics. Five electronic databases were searched, in addition to the Cochrane Colloquium abstract books and the Cochrane Statistics Methods Group mailing list archive. We also conducted cited reference searching and emailed topic experts to identify recent methodological developments. Details recorded included the description of the method, the information required to implement the method, any underlying assumptions and whether the method could be readily applied in standard statistical software. We provided a summary description of the methods identified, illustrating selected methods in example meta-analysis scenarios. Results: For missing standard deviations (SDs), following screening of 503 articles, fifteen methods were identified in addition to those reported in a previous review. These included Bayesian hierarchical modelling at the meta-analysis level; summary statistic level imputation based on observed SD values from other trials in the meta-analysis; a practical approximation based on the range; and algebraic estimation of the SD based on other summary statistics. Following screening of 1124 articles for methods estimating the mean, one approximate Bayesian computation approach and three papers based on alternative summary statistics were identified. Illustrative meta-analyses showed that when replacing a missing SD the approximation using the range minimised loss of precision and generally performed better than omitting trials. When estimating missing means, a formula using the median, lower quartile and upper quartile performed best in preserving the precision of the meta-analysis findings, although in some scenarios, omitting trials gave superior results. Conclusions: Methods based on summary statistics (minimum, maximum, lower quartile, upper quartile, median) reported in the literature facilitate more comprehensive inclusion of randomised controlled trials with missing mean or variability summary statistics within meta-analyses

Effective Feedback to Improve Primary Care Prescribing Safety (EFIPPS) a pragmatic three-arm cluster randomised trial:designing the intervention (ClinicalTrials.gov registration NCT01602705)

Peer reviewedPublisher PD