230 research outputs found
Investigation of the association of Apgar score with maternal socio-economic and biological factors: an analysis of German perinatal statistics
PURPOSE: To examine the relationship of 5-min Apgar score with maternal socio-economic and biological factors. METHODS: We analyzed data from 465,964 singleton pregnancies (37–41 weeks’ gestation) from the German perinatal statistics of 1998–2000. Using a logistic regression model we analyzed the incidence of low (0–6) 5-min Apgar scores in relation to these maternal factors: body mass index (BMI), age, previous live births, country of origin, occupation, single mother status, working during pregnancy, and smoking. RESULTS: A low Apgar score was more common in overweight [adjusted odds ratio (OR) 1.24; 95% confidence interval (CI) 1.10–1.40; P < 0.001] and obese [OR 1.92 (95% CI 1.67–2.20); P < 0.001] compared to normal weight women. A low Apgar score was also more common for women aged >35 years compared to those aged 20–35 years [OR 1.35 (95% CI 1.16–1.58); P < 0.001]. Furthermore, odds of a low Apgar score were higher for women with no previous live births compared to those with one or more previous live births [OR 1.52 (95% CI 1.37–1.70); P < 0.001]. Socio-economic factors did not convincingly influence Apgar scores. CONCLUSIONS: There was an influence of the biological maternal factors age, BMI, and parity on the 5-min Apgar score. There was no convincing effect of socio-economic factors on Apgar score in our study population. Possible reasons for this are discussed
Reader and author gender and genre in Goodreads
This is an accepted manuscript of an article published by SAGE Publishing in Journal of Librarianship & Information Science on 01/05/2017, available online: https://doi.org/10.1177/0961000617709061
The accepted version of the publication may differ from the final published version.There are known gender differences in book preferences in terms of both genre and author gender but their extent and causes are not well understood. It is unclear whether reader preferences for author genders occur within any or all genres and whether readers evaluate books differently based on author genders within specific genres. This article exploits a major source of informal book reviews, the Goodreads.com website, to assess the influence of reader and author genders on book evaluations within genres. It uses a quantitative analysis of 201,560 books and their reviews, focusing on the top 50 user-specified genres. The results show strong gender differences in the ratings given by reviewers to books within genres, such as female reviewers rating contemporary romance more highly, with males preferring short stories. For most common book genres, reviewers give higher ratings to books authored by their own gender, confirming that gender bias is not confined to the literary elite. The main exception is the comic book, for which male reviewers prefer female authors, despite their scarcity. A word frequency analysis suggested that authors wrote, and reviewers valued, gendered aspects of books within a genre. For example, relationships and romance were disproportionately mentioned by women in mystery and fantasy novels. These results show that, perhaps for the first time, it is possible to get large scale evidence about the reception of books by typical readers, if they post reviews online
A Survey on Continuous Time Computations
We provide an overview of theories of continuous time computation. These
theories allow us to understand both the hardness of questions related to
continuous time dynamical systems and the computational power of continuous
time analog models. We survey the existing models, summarizing results, and
point to relevant references in the literature
Uncovering treatment burden as a key concept for stroke care: a systematic review of qualitative research
<b>Background</b> Patients with chronic disease may experience complicated management plans requiring significant personal investment. This has been termed ‘treatment burden’ and has been associated with unfavourable outcomes. The aim of this systematic review is to examine the qualitative literature on treatment burden in stroke from the patient perspective.<p></p>
<b>Methods and findings</b> The search strategy centred on: stroke, treatment burden, patient experience, and qualitative methods. We searched: Scopus, CINAHL, Embase, Medline, and PsycINFO. We tracked references, footnotes, and citations. Restrictions included: English language, date of publication January 2000 until February 2013. Two reviewers independently carried out the following: paper screening, data extraction, and data analysis. Data were analysed using framework synthesis, as informed by Normalization Process Theory. Sixty-nine papers were included. Treatment burden includes: (1) making sense of stroke management and planning care, (2) interacting with others, (3) enacting management strategies, and (4) reflecting on management. Health care is fragmented, with poor communication between patient and health care providers. Patients report inadequate information provision. Inpatient care is unsatisfactory, with a perceived lack of empathy from professionals and a shortage of stimulating activities on the ward. Discharge services are poorly coordinated, and accessing health and social care in the community is difficult. The study has potential limitations because it was restricted to studies published in English only and data from low-income countries were scarce.<p></p>
<b>Conclusions</b> Stroke management is extremely demanding for patients, and treatment burden is influenced by micro and macro organisation of health services. Knowledge deficits mean patients are ill equipped to organise their care and develop coping strategies, making adherence less likely. There is a need to transform the approach to care provision so that services are configured to prioritise patient needs rather than those of health care systems
Creatine ingestion augments dietary carbohydrate mediated muscle glycogen supercomposition during the initial 24 hrs of recovery following prolonged exhaustive exercise in humans
Muscle glycogen availability can limit endurance exercise performance. We previously demonstrated 5 days of creatine (Cr) and carbohydrate (CHO) ingestion augmented post-exercise muscle glycogen storage compared to CHO feeding alone in healthy volunteers. Here we aimed to characterise the time-course of this Cr-induced response under more stringent and controlled experimental conditions and identify potential mechanisms underpinning this phenomenon. Fourteen healthy, male volunteers cycled to exhaustion at 70% VO2peak. Muscle biopsies were obtained at rest immediately post-exercise and after 1, 3 and 6 days of recovery, during which Cr or placebo supplements (20g.day-1) were ingested along with a prescribed high CHO diet (37.5 kcal.kg body mass-1.day-1, >80% calories CHO). Oral-glucose tolerance tests (oral-GTT) were performed pre-exercise and after 1, 3 and 6 days of Cr and placebo supplementation. Exercise depleted muscle glycogen content to the same extent in both treatment groups. Creatine supplementation increased muscle total-Cr, free-Cr and phosphocreatine (PCr) content above placebo following 1, 3 and 6 days of supplementation (all P<0.05). Creatine supplementation also increased muscle glycogen content noticeably above placebo after 1 day of supplementation (P<0.05), which was sustained thereafter. This study confirmed dietary Cr augments post-exercise muscle glycogen super-compensation, and demonstrates this occurred during the initial 24 h of post-exercise recovery (when muscle total-Cr had increased by <10%). This marked response ensued without apparent treatment differences in muscle insulin sensitivity (oral-GTT, muscle GLUT4 mRNA), osmotic stress (muscle c-fos and HSP72 mRNA) or muscle cell volume (muscle water content) responses, such that another mechanism must be causative
Landmarking the brain for geometric morphometric analysis: An error study
Neuroanatomic phenotypes are often assessed using volumetric analysis. Although powerful and versatile, this approach is limited in that it is unable to quantify changes in shape, to describe how regions are interrelated, or to determine whether changes in size are global or local. Statistical shape analysis using coordinate data from biologically relevant landmarks is the preferred method for testing these aspects of phenotype. To date, approximately fifty landmarks have been used to study brain shape. Of the studies that have used landmark-based statistical shape analysis of the brain, most have not published protocols for landmark identification or the results of reliability studies on these landmarks. The primary aims of this study were two-fold: (1) to collaboratively develop detailed data collection protocols for a set of brain landmarks, and (2) to complete an intra- and inter-observer validation study of the set of landmarks. Detailed protocols were developed for 29 cortical and subcortical landmarks using a sample of 10 boys aged 12 years old. Average intra-observer error for the final set of landmarks was 1.9 mm with a range of 0.72 mm-5.6 mm. Average inter-observer error was 1.1 mm with a range of 0.40 mm-3.4 mm. This study successfully establishes landmark protocols with a minimal level of error that can be used by other researchers in the assessment of neuroanatomic phenotypes. © 2014 Chollet et al
Machine learning-based prediction of breast cancer growth rate in-vivo
BackgroundDetermining the rate of breast cancer (BC) growth in vivo, which can predict prognosis, has remained elusive despite its relevance for treatment, screening recommendations and medicolegal practice. We developed a model that predicts the rate of in vivo tumour growth using a unique study cohort of BC patients who had two serial mammograms wherein the tumour, visible in the diagnostic mammogram, was missed in the first screen.MethodsA serial mammography-derived in vivo growth rate (SM-INVIGOR) index was developed using tumour volumes from two serial mammograms and time interval between measurements. We then developed a machine learning-based surrogate model called Surr-INVIGOR using routinely assessed biomarkers to predict in vivo rate of tumour growth and extend the utility of this approach to a larger patient population. Surr-INVIGOR was validated using an independent cohort.ResultsSM-INVIGOR stratified discovery cohort patients into fast-growing versus slow-growing tumour subgroups, wherein patients with fast-growing tumours experienced poorer BC-specific survival. Our clinically relevant Surr-INVIGOR stratified tumours in the discovery cohort and was concordant with SM-INVIGOR. In the validation cohort, Surr-INVIGOR uncovered significant survival differences between patients with fast-growing and slow-growing tumours.ConclusionOur Surr-INVIGOR model predicts in vivo BC growth rate during the pre-diagnostic stage and offers several useful applications
Using formative research to develop CHANGE! : a curriculum-based physical activity promoting intervention
Background : Low childhood physical activity levels are currently one of the most pressing public health concerns. Numerous school-based physical activity interventions have been conducted with varied success. Identifying effective child-based physical activity interventions are warranted. The purpose of this formative study was to elicit subjective views of children, their parents, and teachers about physical activity to inform the design of the CHANGE! (Children\u27s Health, Activity, and Nutrition: Get Educated!) intervention programme. Methods : Semi-structured mixed-gender interviews (group and individual) were conducted in 11 primary schools, stratified by socioeconomic status, with 60 children aged 9-10 years (24 boys, 36 girls), 33 parents (4 male, 29 female) and 10 teachers (4 male, 6 female). Questions for interviews were structured around the PRECEDE stage of the PRECEDE-PROCEDE model and addressed knowledge, attitudes and beliefs towards physical activity, as well as views on barriers to participation. All data were transcribed verbatim. Pen profiles were constructed from the transcripts in a deductive manner using the Youth Physical Activity Promotion Model framework. The profiles represented analysis outcomes via a diagram of key emergent themes. Results : Analyses revealed an understanding of the relationship between physical activity and health, although some children had limited understanding of what constitutes physical activity. Views elicited by children and parents were generally consistent. Fun, enjoyment and social support were important predictors of physical activity participation, though several barriers such as lack of parental support were identified across all group interviews. The perception of family invested time was positively linked to physical activity engagement. Conclusions : Families have a powerful and important role in promoting health-enhancing behaviours. Involvement of parents and the whole family is a strategy that could be significant to increase children\u27s physical activity levels. Addressing various perceived barriers to such behaviours therefore, remains imperative. <br /
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