Treatment of missing data in Bayesian network structure learning : an application to linked biomedical and social survey data

The authors acknowledge the Research/Scientific Computing teams at The James Hutton Institute and NIAB for providing computational resources and technical support for the “UK’s Crop Diversity Bioinformatics HPC” (BBSRC grant BB/S019669/1), use of which has contributed to the results reported within this paper. Access to this was provided via the University of St Andrews Bioinformatics Unit which is funded by a Wellcome Trust ISSF award (grant 105621/Z/14/Z and 204821/Z/16/Z). XK was supported by a World-Leading PhD Scholarship from St Leonard’s Postgraduate School of the University of St Andrews. VAS and KK were partially supported by HATUA, The Holistic Approach to Unravel Antibacterial Resistance in East Africa, a three-year Global Context Consortia Award (MR/S004785/1) funded by the National Institute for Health Research, Medical Research Council and the Department of Health and Social Care. KK is supported by the Academy of Medical Sciences, the Wellcome Trust, the Government Department of Business, Energy and Industrial Strategy, the British Heart Foundation Diabetes UK, and the Global Challenges Research Fund [Grant number SBF004\1093]. KK is additionally supported by the Economic and Social Research Council HIGHLIGHT CPC- Connecting Generations Centre [Grant number ES/W002116/1].Background Availability of linked biomedical and social science data has risen dramatically in past decades, facilitating holistic and systems-based analyses. Among these, Bayesian networks have great potential to tackle complex interdisciplinary problems, because they can easily model inter-relations between variables. They work by encoding conditional independence relationships discovered via advanced inference algorithms. One challenge is dealing with missing data, ubiquitous in survey or biomedical datasets. Missing data is rarely addressed in an advanced way in Bayesian networks; the most common approach is to discard all samples containing missing measurements. This can lead to biased estimates. Here, we examine how Bayesian network structure learning can incorporate missing data. Methods We use a simulation approach to compare a commonly used method in frequentist statistics, multiple imputation by chained equations (MICE), with one specific for Bayesian network learning, structural expectation-maximization (SEM). We simulate multiple incomplete categorical (discrete) data sets with different missingness mechanisms, variable numbers, data amount, and missingness proportions. We evaluate performance of MICE and SEM in capturing network structure. We then apply SEM combined with community analysis to a real-world dataset of linked biomedical and social data to investigate associations between socio-demographic factors and multiple chronic conditions in the US elderly population. Results We find that applying either method (MICE or SEM) provides better structure recovery than doing nothing, and SEM in general outperforms MICE. This finding is robust across missingness mechanisms, variable numbers, data amount and missingness proportions. We also find that imputed data from SEM is more accurate than from MICE. Our real-world application recovers known inter-relationships among socio-demographic factors and common multimorbidities. This network analysis also highlights potential areas of investigation, such as links between cancer and cognitive impairment and disconnect between self-assessed memory decline and standard cognitive impairment measurement. Conclusion Our simulation results suggest taking advantage of the additional information provided by network structure during SEM improves the performance of Bayesian networks; this might be especially useful for social science and other interdisciplinary analyses. Our case study show that comorbidities of different diseases interact with each other and are closely associated with socio-demographic factors.PostprintPublisher PDFPeer reviewe

Effects of adolescent childbearing on maternal depression and problem behaviors: A prospective, population-based study using risk-set propensity scores

Adolescent mothers are reportedly at risk for depression and problem behaviors in the postpartum period, but studies have rarely considered developmental context and have yet to disentangle the effects of childbearing on adolescent functioning from selection effects that are associated with early pregnancy. The current study examined changes in adolescent depression, conduct problems and substance use (alcohol, tobacco and marijuana) across the peripartum period using risk-set propensity scores derived from a population-based, prospective study that began in childhood (the Pittsburgh Girls Study, PGS). Each of 147 childbearing adolescents (ages 12-19) was matched with two same-age, non-childbearing adolescents (n = 294) on pregnancy propensity using 15 time-varying risk variables derived from sociodemographic, psychopathology, substance use, family, peer and neighborhood domains assessed in the PGS wave prior to each pregnancy (T1). Postpartum depression and problem behaviors were assessed within the first 6 months following delivery (T2); data gathered from the non-childbearing adolescent controls spanned the same interval. Within the childbearing group, conduct problems and marijuana use reduced from T1 to T2, but depression severity and frequency of alcohol or tobacco use showed no change. When change was compared across the matched groups, conduct problems showed a greater reduction among childbearing adolescents. Relative to non-childbearing adolescents who reported more frequent substance use with time, childbearing adolescents reported no change in alcohol use and less frequent use of marijuana across the peripartum period. There were no group differences in patterns of change for depression severity and tobacco use. The results do not support the notion that adolescent childbearing represents a period of heightened risk for depression or problem behaviors

Development, validation, qualification, and dissemination of quantitative MR methods: Overview and recommendations by the ISMRM quantitative MR study group

On behalf of the International Society for Magnetic Resonance in Medicine (ISMRM) Quantitative MR Study Group, this article provides an overview of considerations for the development, validation, qualification, and dissemination of quantitative MR (qMR) methods. This process is framed in terms of two central technical performance properties, i.e., bias and precision. Although qMR is confounded by undesired effects, methods with low bias and high precision can be iteratively developed and validated. For illustration, two distinct qMR methods are discussed throughout the manuscript: quantification of liver proton-density fat fraction, and cardiac T1. These examples demonstrate the expansion of qMR methods from research centers toward widespread clinical dissemination. The overall goal of this article is to provide trainees, researchers, and clinicians with essential guidelines for the development and validation of qMR methods, as well as an understanding of necessary steps and potential pitfalls for the dissemination of quantitative MR in research and in the clinic

Predominance of multidrug-resistant bacteria causing urinary tract infections among symptomatic patients in East Africa : a call for action

Background In low- and middle-income countries, antibiotics are often prescribed for patients with symptoms of urinary tract infections (UTIs) without microbiological confirmation. Inappropriate antibiotic use can contribute to antimicrobial resistance (AMR) and the selection of MDR bacteria. Data on antibiotic susceptibility of cultured bacteria are important in drafting empirical treatment guidelines and monitoring resistance trends, which can prevent the spread of AMR. In East Africa, antibiotic susceptibility data are sparse. To fill the gap, this study reports common microorganisms and their susceptibility patterns isolated from patients with UTI-like symptoms in Kenya, Tanzania and Uganda. Within each country, patients were recruited from three sites that were sociodemographically distinct and representative of different populations. Methods UTI was defined by the presence of >104 cfu/mL of one or two uropathogens in mid-stream urine samples. Identification of microorganisms was done using biochemical methods. Antimicrobial susceptibility testing was performed by the Kirby–Bauer disc diffusion assay. MDR bacteria were defined as isolates resistant to at least one agent in three or more classes of antimicrobial agents. Results Microbiologically confirmed UTI was observed in 2653 (35.0%) of the 7583 patients studied. The predominant bacteria were Escherichia coli (37.0%), Staphylococcus spp. (26.3%), Klebsiella spp. (5.8%) and Enterococcus spp. (5.5%). E. coli contributed 982 of the isolates, with an MDR proportion of 52.2%. Staphylococcus spp. contributed 697 of the isolates, with an MDR rate of 60.3%. The overall proportion of MDR bacteria (n = 1153) was 50.9%. Conclusions MDR bacteria are common causes of UTI in patients attending healthcare centres in East African countries, which emphasizes the need for investment in laboratory culture capacity and diagnostic algorithms to improve accuracy of diagnosis that will lead to appropriate antibiotic use to prevent and control AMR.Peer reviewe

Activity pacing: moving beyond taking breaks and slowing down

This brief communication responds to the paper by Jeong and Cho (Qual Life Res 26(4):903–911, 2017) that has described activity pacing in limited terms of adjusting activities through going at a slower rate and taking breaks. Activity pacing was reported as not involving goal setting, in comparison to other strategies for long-term conditions such as Acceptance and Commitment Therapy. This brief communication aims to challenge this limited perception of activity pacing in light of numerous studies that recognise pacing to be a more complex strategy. Pacing is considered to be a multifaceted coping strategy, including broad themes of not only adjusting activities, but also planning activities, having consistent activity levels, acceptance of current abilities and gradually increasing activities, and one that includes goal setting as a key facet. It is essential that pacing is both defined and measured as a multifaceted strategy in order to assess the outcomes of pacing, and for meaningful comparisons with other strategies regarding efficacy for the management of long-term conditions

Wean Earlier and Automatically with New technology (the WEAN study): a protocol of a multicentre, pilot randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Weaning is the process during which mechanical ventilation is withdrawn and the work of breathing is transferred from the ventilator back to the patient. Prolonged weaning is associated with development of ventilator-related complications and longer stays in the Intensive Care Unit (ICU). Computerized or Automated Weaning is a novel weaning strategy that continuously measures and adapts ventilator support (by frequently measuring and averaging three breathing parameters) and automatically conducts Spontaneous Breathing Trials to ascertain whether patients can resume autonomous breathing. Automated Weaning holds promise as a strategy to reduce the time spent on the ventilator, decrease ICU length of stay, and improve clinically important outcomes.</p> <p>Methods/Design</p> <p>A pilot weaning randomized controlled trial (RCT) is underway in the ICUs of 8 Canadian hospitals. We will randomize 90 critically ill adults requiring invasive ventilation for at least 24 hours and identified at an early stage of the weaning process to either Automated Weaning (SmartCare™) or Protocolized Weaning. The results of a National Weaning Survey informed the design of the Protocolized Weaning arm. Both weaning protocols are operationalized in Pressure Support mode, include opportunities for Spontaneous Breathing Trials, and share a common sedation protocol, oxygen titration parameters, and extubation and reintubation criteria. The primary outcome of the WEAN study is to evaluate compliance with the proposed weaning and sedation protocols. A key secondary outcome of the pilot RCT is to evaluate clinician acceptance of the weaning and sedation protocols. Prior to initiating the WEAN Study, we conducted a run-in phase, involving two patients per centre (randomizing the first participant to either weaning strategy and assigning the second patient to the alternate strategy) to ensure that participating centres could implement the weaning and sedation protocols and complete the detailed case report forms.</p> <p>Discussion</p> <p>Mechanical ventilation studies are difficult to implement; requiring protocols to be operationalized continuously and entailing detailed daily data collection. As the first multicentre weaning RCT in Canada, the WEAN Study seeks to determine the feasibility of conducting a large scale future weaning trial and to establish a collaborative network of ICU clinicians dedicated to advancing the science of weaning.</p> <p>Trial Registration Number</p> <p>ISRCTN43760151</p

Classification of the height and flexibility of the medial longitudinal arch of the foot

<p>Abstract</p> <p>Background</p> <p>The risk of developing injuries during standing work may vary between persons with different foot types. High arched and low arched feet, as well as rigid and flexible feet, are considered to have different injury profiles, while those with normal arches may sustain fewer injuries. However, the cut-off values for maximum values (subtalar position during weight-bearing) and range of motion (ROM) values (difference between subtalar neutral and subtalar resting position in a weight-bearing condition) for the medial longitudinal arch (MLA) are largely unknown. The purpose of this study was to identify cut-off values for maximum values and ROM of the MLA of the foot during static tests and to identify factors influencing foot posture.</p> <p>Methods</p> <p>The participants consisted of 254 volunteers from Central and Northern Denmark (198 m/56 f; age 39.0 ± 11.7 years; BMI 27.3 ± 4.7 kg/m²). Navicular height (NH), longitudinal arch angle (LAA) and Feiss line (FL) were measured for either the left or the right foot in a subtalar neutral position and subtalar resting position. Maximum values and ROM were calculated for each test. The 95% and 68% prediction intervals were used as cut-off limits. Multiple regression analysis was used to detect influencing factors on foot posture.</p> <p>Results</p> <p>The 68% cut-off values for maximum MLA values and MLA ROM for NH were 3.6 to 5.5 cm and 0.6 to 1.8 cm, respectively, without taking into account the influence of other variables. Normal maximum LAA values were between 131 and 152° and normal LAA ROM was between -1 and 13°. Normal maximum FL values were between -2.6 and -1.2 cm and normal FL ROM was between -0.1 and 0.9 cm. Results from the multivariate linear regression revealed an association between foot size with FL, LAA, and navicular drop.</p> <p>Conclusions</p> <p>The cut-off values presented in this study can be used to categorize people performing standing work into groups of different foot arch types. The results of this study are important for investigating a possible link between arch height and arch movement and the development of injuries.</p

Treatment seeking behaviours, antibiotic use and relationships to multi-drug resistance : a study of urinary tract infection patients in Kenya, Tanzania and Uganda

Antibacterial resistance (ABR) is a major public health threat. An important accelerating factor is treatment-seeking behaviour, including inappropriate antibiotic (AB) use. In many low- and middle-income countries (LMICs) this includes taking ABs with and without prescription sourced from various providers, including health facilities and community drug sellers. However, investigations of complex treatment-seeking, AB use and drug resistance in LMICs are scarce. The Holistic Approach to Unravel Antibacterial Resistance in East Africa (HATUA) Consortium collected questionnaire and microbiological data from adult outpatients with urinary tract infection (UTI)-like symptoms presenting at healthcare facilities in Kenya, Tanzania and Uganda. Using data from 6,388 patients, we analysed patterns of self-reported treatment seeking behaviours (‘patient pathways’) using process mining and single-channel sequence analysis. Among those with microbiologically confirmed UTI (n = 1,946), we used logistic regression to assess the relationship between treatment seeking behaviour, AB use, and the likelihood of having a multi-drug resistant (MDR) UTI. The most common treatment pathway for UTI-like symptoms in this sample involved attending health facilities, rather than other providers like drug sellers. Patients from sites in Tanzania and Uganda, where over 50% of patients had an MDR UTI, were more likely to report treatment failures, and have repeat visits to providers than those from Kenyan sites, where MDR UTI proportions were lower (33%). There was no strong or consistent relationship between individual AB use and likelihood of MDR UTI, after accounting for country context. The results highlight the hurdles East African patients face in accessing effective UTI care. These challenges are exacerbated by high rates of MDR UTI, suggesting a vicious cycle of failed treatment attempts and sustained selection for drug resistance. Whilst individual AB use may contribute to the risk of MDR UTI, our data show that factors related to context are stronger drivers of variations in ABR.Peer reviewe

Unsettling planning theory

Recent political developments in many parts of the world seem likely to exacerbate rather than ameliorate the planetary-scale challenges of social polarization, inequality and environmental change societies face. In this unconventional multi-authored essay, we therefore seek to explore some of the ways in which planning theory might respond to the deeply unsettling times we live in. Taking the multiple, suggestive possibilities of the theme of unsettlement as a starting point, we aim to create space for reflection and debate about the state of the discipline and practice of planning theory, questioning what it means to produce knowledge capable of acting on the world today. Drawing on exchanges at a workshop attended by a group of emerging scholars in Portland, Oregon in late 2016, the essay begins with an introduction section exploring the contemporary resonances of ‘unsettling’ in, of and for planning theory. This is followed by four, individually authored responses which each connect the idea of unsettlement to key challenges and possible future directions. We end by calling for a reflective practice of theorizing that accepts unsettlement but seeks to act knowingly and compassionately on the uneven terrain that it creates

The importance of interacting climate modes on Australia’s contribution to global carbon cycle extremes

The global carbon cycle is highly sensitive to climate-driven fluctuations of precipitation, especially in the Southern Hemisphere. This was clearly manifested by a 20% increase of the global terrestrial C sink in 2011 during the strongest sustained La Niña since 1917. However, inconsistencies exist between El Niño/La Niña (ENSO) cycles and precipitation in the historical record; for example, significant ENSO-precipitation correlations were present in only 31% of the last 100 years, and often absent in wet years. To resolve these inconsistencies, we used an advanced temporal scaling method for identifying interactions amongst three key climate modes (El Niño, the Indian Ocean dipole, and the southern annular mode). When these climate modes synchronised (1999-2012), drought and extreme precipitation were observed across Australia. The interaction amongst these climate modes, more than the effect of any single mode, was associated with large fluctuations in precipitation and productivity. The long-term exposure of vegetation to this arid environment has favoured a resilient flora capable of large fluctuations in photosynthetic productivity and explains why Australia was a major contributor not only to the 2011 global C sink anomaly but also to global reductions in photosynthetic C uptake during the previous decade of drought