Walking and falling: Using robot simulations to model the role of errors in infant walking

What is the optimal penalty for errors in infant skill learning? Behavioral analyses indicate that errors are frequent but trivial as infants acquire foundational skills. In learning to walk, for example, falling is commonplace but appears to incur only a negligible penalty. Behavioral data, however, cannot reveal whether a low penalty for falling is beneficial for learning to walk. Here, we used a simulated bipedal robot as an embodied model to test the optimal penalty for errors in learning to walk. We trained the robot to walk using 12,500 independent simulations on walking paths produced by infants during free play and systematically varied the penalty for falling-a level of precision, control, and magnitude impossible with real infants. When trained with lower penalties for falling, the robot learned to walk farther and better on familiar, trained paths and better generalized its learning to novel, untrained paths. Indeed, zero penalty for errors led to the best performance for both learning and generalization. Moreover, the beneficial effects of a low penalty were stronger for generalization than for learning. Robot simulations corroborate prior behavioral data and suggest that a low penalty for errors helps infants learn foundational skills (e.g., walking, talking, and social interactions) that require immense flexibility, creativity, and adaptability. RESEARCH HIGHLIGHTS: During infant skill acquisition, errors are commonplace but appear to incur a low penalty; when learning to walk, for example, falls are frequent but trivial. To test the optimal penalty for errors, we trained a simulated robot to walk using real infant paths and systematically manipulated the penalty for falling. Lower penalties in training led to better performance on familiar, trained paths and on novel untrained paths, and zero penalty was most beneficial. Benefits of a low penalty were stronger for untrained than for trained paths, suggesting that discounting errors facilitates acquiring skills that require immense flexibility and generalization.

Maternal Cardiovascular Responses to Position Change in Pregnancy

The maternal cardiovascular-circulatory system undergoes profound changes almost from the conception of a pregnancy until the postpartum period to support the maternal adaptions required for pregnancy and lactation. Maintenance of cardiovascular homeostasis requires changes in the cardiovascular autonomic responses. Here, we present a longitudinal study of the maternal cardiovascular autonomic responses to pregnancy and maternal position. Over a normal gestation, in the left lateral position there are significant changes in both time and frequency domain parameters reflecting heart rate variability. We show that cardiovascular autonomic responses to physiological stressors (standing and supine positions in late pregnancy) became significantly different with advancing gestation. In the third trimester, 60% of the subjects had an unstable heart rate response on standing, and these subjects had a significantly reduced sample entropy evident in their heart rate variability data. By 6 weeks, postpartum function returned to near the non-pregnant state, but there were consistent differences in high-frequency power when compared to nulligravid cases. Finally, we review complementary evidence, in particular from magnetic resonance imaging, that provides insights into the maternal and fetal impacts of positioning in pregnancy. This demonstrates a clear relationship between supine position and maternal hemodynamic parameters, which relates to compression of the inferior vena cava (p = 0.05). Together, these studies demonstrate new understanding of the physiology of physiological stressors related to position.

Improving artificial intelligence with games

Games continue to drive progress in the development of artifi cial intelligence.

Kinematic coordinations capture learning during human-exoskeleton interaction

Human-exoskeleton interactions have the potential to bring about changes in human behavior for physical rehabilitation or skill augmentation. Despite significant advances in the design and control of these robots, their application to human training remains limited. The key obstacles to the design of such training paradigms are the prediction of human-exoskeleton interaction effects and the selection of interaction control to affect human behavior. In this article, we present a method to elucidate behavioral changes in the human-exoskeleton system and identify expert behaviors correlated with a task goal. Specifically, we observe the joint coordinations of the robot, also referred to as kinematic coordination behaviors, that emerge from human-exoskeleton interaction during learning. We demonstrate the use of kinematic coordination behaviors with two task domains through a set of three human-subject studies. We find that participants (1) learn novel tasks within the exoskeleton environment, (2) demonstrate similarity of coordination during successful movements within participants, (3) learn to leverage these coordination behaviors to maximize success within participants, and (4) tend to converge to similar coordinations for a given task strategy across participants. At a high level, we identify task-specific joint coordinations that are used by different experts for a given task goal. These coordinations can be quantified by observing experts and the similarity to these coordinations can act as a measure of learning over the course of training for novices. The observed expert coordinations may further be used in the design of adaptive robot interactions aimed at teaching a participant the expert behaviors.

Accuracy of clinical predictions of prognosis at the end-of-life: evidence from routinely collected data in urgent care records

BACKGROUND

The accuracy of prognostication has important implications for patients, families, and health services since it may be linked to clinical decision-making, patient experience and outcomes and resource allocation. Study aim is to evaluate the accuracy of temporal predictions of survival in patients with cancer, dementia, heart, or respiratory disease.

METHODS

Accuracy of clinical prediction was evaluated using retrospective, observational cohort study of 98,187 individuals with a Coordinate My Care record, the Electronic Palliative Care Coordination System serving London, 2010-2020. The survival times of patients were summarised using median and interquartile ranges. Kaplan Meier survival curves were created to describe and compare survival across prognostic categories and disease trajectories. The extent of agreement between estimated and actual prognosis was quantified using linear weighted Kappa statistic.

RESULTS

Overall, 3% were predicted to live "days"; 13% "weeks"; 28% "months"; and 56% "year/years". The agreement between estimated and actual prognosis using linear weighted Kappa statistic was highest for patients with dementia/frailty (0.75) and cancer (0.73). Clinicians' estimates were able to discriminate (log-rank p < 0.001) between groups of patients with differing survival prospects. Across all disease groups, the accuracy of survival estimates was high for patients who were likely to live for fewer than 14 days (74% accuracy) or for more than one year (83% accuracy), but less accurate at predicting survival of "weeks" or "months" (32% accuracy).

CONCLUSION

Clinicians are good at identifying individuals who will die imminently and those who will live for much longer. The accuracy of prognostication for these time frames differs across major disease categories, but remains acceptable even in non-cancer patients, including patients with dementia. Advance Care Planning and timely access to palliative care based on individual patient needs may be beneficial for those where there is significant prognostic uncertainty; those who are neither imminently dying nor expected to live for "years".

Prognostic evaluation in patients with advanced cancer in the last months of life: ESMO Clinical Practice Guideline

•This ESMO Clinical Practice Guideline provides key recommendations for using prognostic estimates in advanced cancer. •The guideline covers recommendations for patients with cancer and an expected survival of months or less. •An algorithm for use of clinical predictions, prognostic factors and multivariable risk prediction models is presented. •The author group encompasses a multidisciplinary group of experts from different institutions in Europe, USA and Asia. •Recommendations are based on available scientific data and the authors’ collective expert opinion.

A domain-agnostic approach for characterization of lifelong learning systems

Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to "real world" events, where the input distributions and tasks encountered by the deployed systems will not be limited to the original training context, and systems will instead need to adapt to novel distributions and tasks while deployed. This critical gap may be addressed through the development of "Lifelong Learning" systems that are capable of (1) Continuous Learning, (2) Transfer and Adaptation, and (3) Scalability. Unfortunately, efforts to improve these capabilities are typically treated as distinct areas of research that are assessed independently, without regard to the impact of each separate capability on other aspects of the system. We instead propose a holistic approach, using a suite of metrics and an evaluation framework to assess Lifelong Learning in a principled way that is agnostic to specific domains or system techniques. Through five case studies, we show that this suite of metrics can inform the development of varied and complex Lifelong Learning systems. We highlight how the proposed suite of metrics quantifies performance trade-offs present during Lifelong Learning system development - both the widely discussed Stability-Plasticity dilemma and the newly proposed relationship between Sample Efficient and Robust Learning. Further, we make recommendations for the formulation and use of metrics to guide the continuing development of Lifelong Learning systems and assess their progress in the future.

Comparison of the effects on maternal endothelial cell activation: an in vitro study of anti-hypertensive drugs clinically used in pre-eclampsia

Endothelial cell dysfunction in pregnancy, which can be induced by placental factors, is the fundamental component of the pathogenesis of pre-eclampsia. The dysfunctional vascular endothelium disrupts the balance of vasodilatory and vasoconstrictive factors, resulting in increasing blood pressure. There is currently no effective treatment for pre-eclampsia and effective control of hypertension may reduce neonatal morbidity and mortality by prolonging gestation, especially in cases of early onset disease. To date methyldopa, labetalol, nifedipine and metoprolol are recommended for controlling blood pressure in pre-eclampsia. All of these drugs have different mechanisms of action. In this in vitro study we investigated whether different types of anti-hypertensive drugs could have different effects on improving maternal endothelial cell dysfunction. Endothelial cells (HMEC-1) were exposed to phorbol-12-myristate-13-acetate (PMA) or pre-eclamptic sera or extracellular vesicles (EVs) derived from pre-eclamptic placentae, in the presence of each of the studied anti-hypertensive drugs (methyldopa, labetalol, nifedipine and metoprolol) or placebo for 24 h. Endothelial cell-surface adhesion molecule (ICAM-1) and monocyte adhesion were measured. The expression of cell-face ICAM-1 by HMEC-1 cells and THP-1 monocyte adherent to HMEC-1 that were exposed to three separate well-known activators of endothelial cells in the presence of four anti-hypertensive drugs was significantly reduced regardless of the dose. However, the effect on the reduction of ICAM-1 expression and monocyte adhesion was not significantly different between the four medications. Our data suggest that the beneficial effect on improving endothelial cell function by these commonly prescribed anti-hypertensive drugs is seemingly independent of the anti-hypertensive mechanisms of the medication.

Outracing champion Gran Turismo drivers with deep reinforcement learning

Many potential applications of artificial intelligence involve making real-time decisions in physical systems while interacting with humans. Automobile racing represents an extreme example of these conditions; drivers must execute complex tactical manoeuvres to pass or block opponents while operating their vehicles at their traction limits¹. Racing simulations, such as the PlayStation game Gran Turismo, faithfully reproduce the non-linear control challenges of real race cars while also encapsulating the complex multi-agent interactions. Here we describe how we trained agents for Gran Turismo that can compete with the world's best e-sports drivers. We combine state-of-the-art, model-free, deep reinforcement learning algorithms with mixed-scenario training to learn an integrated control policy that combines exceptional speed with impressive tactics. In addition, we construct a reward function that enables the agent to be competitive while adhering to racing's important, but under-specified, sportsmanship rules. We demonstrate the capabilities of our agent, Gran Turismo Sophy, by winning a head-to-head competition against four of the world's best Gran Turismo drivers. By describing how we trained championship-level racers, we demonstrate the possibilities and challenges of using these techniques to control complex dynamical systems in domains where agents must respect imprecisely defined human norms.

Antiphospholipid antibodies do not cause retargeting of placental extracellular vesicles in the maternal body

Antiphospholipid antibodies (aPL) are autoantibodies that cause pregnancy disorders by a poorly defined mechanism that involves the placenta. The human placenta is covered by a single multinucleated cell, the syncytiotrophoblast, which extrudes vast numbers of extracellular vesicles (EVs) into the maternal blood. Extracellular vesicles are tiny packages of cellular material used by cells for remote signalling. In normal pregnancy, placental EVs assist maternal adaptations to pregnancy. We have previously shown that aPL alter the cargo of placental EVs, increasing the load of danger signals. These changes in EV cargo may explain how aPL contribute to the increased risk of recurrent miscarriage, preeclampsia and stillbirths observed in aPL-affected pregnancies. An additional possibility, that aPL alters the targeting of placental EVs to maternal organs to cause maternal maladaptation to pregnancy was investigated in this study.

Agent-Based Markov Modeling for Improved COVID-19 Mitigation Policies

The year 2020 saw the covid-19 virus lead to one of the worst global pandemics in history. As a result, governments around the world have been faced with the challenge of protecting public health while keeping the economy running to the greatest extent possible. Epidemiological models provide insight into the spread of these types of diseases and predict the effects of possible intervention policies. However, to date, even the most data-driven intervention policies rely on heuristics. In this paper, we study how reinforcement learning (RL) and Bayesian inference can be used to optimize mitigation policies that minimize economic impact without overwhelming hospital capacity. Our main contributions are (1) a novel agent-based pandemic simulator which, unlike traditional models, is able to model fine-grained interactions among people at specific locations in a community; (2) an RLbased methodology for optimizing fine-grained mitigation policies within this simulator; and (3) a Hidden Markov Model for predicting infected individuals based on partial observations regarding test results, presence of symptoms, and past physical contacts. This article is part of the special track on AI and COVID-19.

Examining the potential preventability of adverse fetal/neonatal outcomes associated with severe maternal morbidity

BACKGROUND

Severe maternal morbidity (SMM) occurs in 1-2% of pregnancies. Despite the knowledge that a SMM event can contribute to poor fetal/neonatal outcomes, little is known about the preventability of these adverse outcomes.

AIMS

To examine adverse fetal/neonatal outcomes associated with SMM to determine if these outcomes were potentially preventable.

MATERIALS AND METHODS

A New Zealand national retrospective cohort study examining cases of SMM with an adverse fetal/neonatal outcome. Maternity and initial neonatal care were explored by multidisciplinary panels utilising a preventability tool to assess whether the fetal/neonatal harm was potentially preventable. Adverse fetal/neonatal outcomes were defined as fetal or early neonatal death, Apgar score <7 at five minutes, admission to neonatal intensive care unit or special care baby unit and neonatal encephalopathy.

RESULTS

Of 85 cases reviewed, adverse fetal/neonatal outcome was deemed potentially preventable in 55.3% of cases (n = 47/85). Preventability was related to maternal antenatal/peripartum care (in utero) in 39% (n = 33/85), to initial neonatal care (ex utero) in 36% (n = 29/80), and to both maternal and neonatal care in 20% (16/80) of cases. Main contributors to potential preventability were factors related to healthcare providers, particularly lack of recognition of high risk, delayed or failure to diagnose, and delayed or inappropriate treatment.

CONCLUSIONS

Multidisciplinary panels found that over half of adverse fetal/neonatal harm associated with SMM was potentially preventable. The novel approach of examining both maternal and neonatal care identifies opportunities to improve fetal/neonatal outcomes associated with SMM at multiple points on the perinatal continuum of care.

Importance sampling in reinforcement learning with an estimated behavior policy

In reinforcement learning, importance sampling is a widely used method for evaluating an expectation under the distribution of data of one policy when the data has in fact been generated by a different policy. Importance sampling requires computing the likelihood ratio between the action probabilities of a target policy and those of the data-producing behavior policy. In this article, we study importance sampling where the behavior policy action probabilities are replaced by their maximum likelihood estimate of these probabilities under the observed data. We show this general technique reduces variance due to sampling error in Monte Carlo style estimators. We introduce two novel estimators that use this technique to estimate expected values that arise in the RL literature. We find that these general estimators reduce the variance of Monte Carlo sampling methods, leading to faster learning for policy gradient algorithms and more accurate off-policy policy evaluation. We also provide theoretical analysis showing that our new estimators are consistent and have asymptotically lower variance than Monte Carlo estimators.

Prognostic tools or clinical predictions: Which are better in palliative care?

PURPOSE

The Palliative Prognostic (PaP) score; Palliative Prognostic Index (PPI); Feliu Prognostic Nomogram (FPN) and Palliative Performance Scale (PPS) have all been proposed as prognostic tools for palliative cancer care. However, clinical judgement remains the principal way by which palliative care professionals determine prognoses and it is important that the performance of prognostic tools is compared against clinical predictions of survival (CPS).

METHODS

This was a multi-centre, cohort validation study of prognostic tools. Study participants were adults with advanced cancer receiving palliative care, with or without capacity to consent. Key prognostic data were collected at baseline, shortly after referral to palliative care services. CPS were obtained independently from a doctor and a nurse.

RESULTS

Prognostic data were collected on 1833 participants. All prognostic tools showed acceptable discrimination and calibration, but none showed superiority to CPS. Both PaP and CPS were equally able to accurately categorise patients according to their risk of dying within 30 days. There was no difference in performance between CPS and FPN at stratifying patients according to their risk of dying at 15, 30 or 60 days. PPI was significantly (p<0.001) worse than CPS at predicting which patients would survive for 3 or 6 weeks. PPS and CPS were both able to discriminate palliative care patients into multiple iso-prognostic groups.

CONCLUSIONS

Although four commonly used prognostic algorithms for palliative care generally showed good discrimination and calibration, none of them demonstrated superiority to CPS. Prognostic tools which are less accurate than CPS are of no clinical use. However, prognostic tools which perform similarly to CPS may have other advantages to recommend them for use in clinical practice (e.g. being more objective, more reproducible, acting as a second opinion or as an educational tool). Future studies should therefore assess the impact of prognostic tools on clinical practice and decision-making.

Awareness in severe Alzheimer's disease: a systematic review

Objective: There is limited understanding about how people in the severe stages of Alzheimer's disease (AD) experience and demonstrate awareness. We synthesised all available evidence with the aim of understanding how awareness is preserved or impaired in severe AD and what evidence there is for different levels of awareness according to the levels of awareness framework.Method: A systematic search of the following databases: Embase, PsycINFO, MEDLINE and Web of Science was carried out. A narrative synthesis and analysis was conducted of all included studies. All studies were assessed for quality using the AXIS and CASP tools.Results: Our findings suggest that lower level sensory awareness is relatively maintained in severe AD. Findings for higher level awareness are variable and this may be related to the diversity of methods that have been used to explore awareness in these circumstances.Conclusion: Awareness is complex, heterogeneous and varies significantly between individuals. Environmental and contextual factors have a significant impact on whether awareness is observed in people with severe AD. Adaptation of the environment has the potential to facilitate the expression of awareness while education of caregivers may increase understanding of people with severe AD and potentially improve the quality of care that is received.

Arterial stiffness and microvascular disease in type 2 diabetes

BACKGROUND

The clustering of arterial stiffness with microvascular disease (MD) and their effects on the clinical outcome of patients with type 2 diabetes (T2D) remains not fully clarified.

METHODS

In a prospective study of 414 patients with T2D, we investigated the prognostic value of arterial stiffness and MD for clinical outcomes. Participants were assessed for the presence of MD (ie diabetic retinopathy, nephropathy and neuropathy) and arterial stiffness by pulse wave velocity (PWV) and followed-up for a median of 30 (range 1-60) months. The primary endpoint of the study was the composite endpoint of major adverse cardiovascular events, that is, cardiovascular and non-cardiovascular mortality and non-fatal myocardial infarction/stroke.

RESULTS

A total of 146 (35.3%) patients had evidence of MD at baseline. In cox regression models, MD and PWV were independently associated with the composite clinical endpoint; for MD hazard ratio (HR), 3.24, 95%CI, 1.10-9.54, P=.032, and for PWV HR, 1.20, 95%CI, 1.06-1.36, P=.004) after adjustment for traditional risk factors, and enhanced risk discrimination and reclassification. The subgroup of patients with MD and high PWV was associated with increased incidence of the composite clinical endpoint (20.9% vs 1.8% in those with no MD & low PWV, P=.001). Importantly, absence of MD at baseline was associated with no mortality events during the follow-up period. PWV at baseline was not associated with MD progression during follow-up.

CONCLUSIONS

These findings support that screening for arterial stiffness and MD in the routine clinical assessment of patients with T2D may enhance prognostication and cardiovascular risk reclassification.

Progression of whole-heart Atherosclerosis by coronary CT and major adverse cardiovascular events

BACKGROUND

The current study aimed to examine the independent prognostic value of whole-heart atherosclerosis progression by serial coronary computed tomography angiography (CCTA) for major adverse cardiovascular events (MACE).

METHODS

The multi-center PARADIGM study includes patients undergoing serial CCTA for symptomatic reasons, ≥2 years apart. Whole-heart atherosclerosis was characterized on a segmental level, with co-registration of baseline and follow-up CCTA, and summed to per-patient level. The independent prognostic significance of atherosclerosis progression for MACE (non-fatal myocardial infarction [MI], death, unplanned coronary revascularization) was examined. Patients experiencing interval MACE were not omitted.

RESULTS

The study population comprised 1166 patients (age 60.5 ​± ​9.5 years, 54.7% male) who experienced 139 MACE events during 8.2 (IQR 6.2, 9.5) years of follow up (15 death, 5 non-fatal MI, 119 unplanned revascularizations). Whole-heart percent atheroma volume (PAV) increased from 2.32% at baseline to 4.04% at follow-up. Adjusted for baseline PAV, the annualized increase in PAV was independently associated with MACE: OR 1.23 (95% CI 1.08, 1.39) per 1 standard deviation increase, which was consistent in multiple subpopulations. When categorized by composition, only non-calcified plaque progression associated independently with MACE, while calcified plaque did not. Restricting to patients without events before follow-up CCTA, those with future MACE showed an annualized increase in PAV of 0.93% (IQR 0.34, 1.96) vs 0.32% (IQR 0.02, 0.90), P ​< ​0.001.

CONCLUSIONS

Whole-heart atherosclerosis progression examined by serial CCTA is independently associated with MACE, with a prognostic threshold of 1.0% increase in PAV per year.

Uncovering social structures and informational prejudices to reduce inequity in delivery and uptake of new molecular technologies

Advances in molecular technologies have the potential to help remedy health inequities through earlier detection and prevention; if, however, their delivery and uptake (and therefore any benefits associated with such testing) are not more carefully considered, there is a very real risk that existing inequities in access and use will be further exacerbated. We argue this risk relates to the way that information and knowledge about the technology is both acquired and shared, or not, between health practitioners and their patients.A healthcare system can be viewed as a complex social network comprising individuals with different worldviews, hierarchies, professional cultures and subcultures and personal beliefs, both for those giving and receiving care. When healthcare practitioners are not perceived as knowledge equals, they would experience informational prejudices, and the result is that knowledge dissemination across and between them would be impeded. The uptake and delivery of a new technology may be inequitable as a result. Patients would also experience informational prejudice when they are viewed as not being able to understand the information that is presented to them, and information may be withheld.Informational prejudices driven by social relations and structures have thus far been underexplored in considering (in)equitable implementation and uptake of new molecular technologies. Every healthcare interaction represents an opportunity for experiencing informational prejudice, and with it the risk of being inappropriately informed for undertaking (or offering) such screening or testing. Making knowledge acquisition and information dissemination, and experiences of informational prejudice, explicit through sociologically framed investigations would extend our understandings of (in)equity, and offer ways to affect network relationships and structures that support equity in delivery and uptake.

The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation

Intelligent mobile robots have recently become able to operate autonomously in large-scale indoor environments for extended periods of time. In this process, mobile robots need the capabilities of both task and motion planning. Task planning in such environments involves sequencing the robot’s high-level goals and subgoals, and typically requires reasoning about the locations of people, rooms, and objects in the environment, and their interactions to achieve a goal. One of the prerequisites for optimal task planning that is often overlooked is having an accurate estimate of the actual distance (or time) a robot needs to navigate from one location to another. State-of-the-art motion planning algorithms, though often computationally complex, are designed exactly for this purpose of finding routes through constrained spaces. In this article, we focus on integrating task and motion planning (TMP) to achieve task-level-optimal planning for robot navigation while maintaining manageable computational efficiency. To this end, we introduce TMP algorithm PETLON (Planning Efficiently for Task-Level-Optimal Navigation), including two configurations with different trade-offs over computational expenses between task and motion planning, for everyday service tasks using a mobile robot. Experiments have been conducted both in simulation and on a mobile robot using object delivery tasks in an indoor office environment. The key observation from the results is that PETLON is more efficient than a baseline approach that pre-computes motion costs of all possible navigation actions, while still producing plans that are optimal at the task level. We provide results with two different task planning paradigms in the implementation of PETLON, and offer TMP practitioners guidelines for the selection of task planners from an engineering perspective.

Making equal rights to health an election issue in NZ local body elections

In New Zealand there are 20 district health boards (DHBs) with local elections every 3 years. There is low voter turnout for these, we suspect because the public has low cognizance of the role DHBs have in governing their health and disability system. Good governance ensures everyone whatever ethnicity, gender or sexual proclivity, from birth to old age, able or disabled, mentally well or unwell, drugfree or addicted, has equal rights of dignified access to healthcare. Without public engagement in DHB elections, the community risks having candidates elected that also don't understand their role through a preventative public health framework or human rights lens. The United Community Action Network (UCAN) developed a human rights framework and Health Charter for people driven into poverty by the costs of staying well in NZ. The framework outlines 6 social determinants of health needing protection through policy, to ensure all enjoy their rights to health. UCAN and the Public Health Association of New Zealand (PHA) partnered to raise public and the candidates' awareness during 2019 elections, of these social determinants causing inequity in health outcomes. A series of short explainer-videos were created for sharing through social media during the election build-up period, helping to promote PHA Branches' public Meet the Candidates events. Post-election, a longer film was produced to send to the elected DHB members. Our theory of change centred on spotlighting health inequity for voters, so that they would elect DHB members who had the greatest understanding and commitment to addressing this issue. With shareable videos we aimed to attract audience, raise awareness and debate the policy solutions to health inequity with candidates, enabling more informed choice amongst the voting public. Post-election, we maintain supportive relationships with the elected DHB members that promised their commitment to our Health Charter during their campaigns.

Key messages

Using videos and social media, local body elections provide an opportunity to promote everyone’s right to affordable healthcare, supporting and informing voter decision-making. UCAN's Health Charter is an advocacy resource for raising awareness of the social determinants of health inequity and poverty for people with mental illness, addiction and disability.

A scorecard for local body election candidates in New Zealand

Local elections are held every 3 years in NZ for District Health Boards (DHB). The public has low capability to scrutinise candidates for their knowledge/experience in public health governance. As a result, there is low voting turn-out for elections. So, 3 PHA branches developed scorecards for 2019 candidates. Our aims addressed 3 problems: 1. How to raise public awareness about local DHB elections 2. How to engage voters and provide them with information about candidates from a public health perspective 3.Can we encourage candidates to discuss public health issues/ preventative measures publicly. We hoped to promote democracy by increasing informed voter turnout. Scorecards were based on candidates' responses to a survey with 3 dimensions: alignment with public health values; health sector governance experience; views on a specific public health issue (water fluoridation). Survey responses were scored by panels of branch members. Southern branch sent the survey to 28 DHB candidates across 2 DHBs, and 24 replied in time. Wellington branch sent it to 23 CCDHB candidates and 16 replied in time. Canterbury's response rate was just over 50%, 11 of 21 surveys were returned.

We produced scorecards for results in formats for printing and sharing online. We shared them on PHA's website, social media and featured them in the e-newsletter. Each branch launched them at local Meet the DHB Candidate events where hundreds of paper copies were distributed. There was good online interest in the scorecards: 3453 previews, 287 downloads for further printing/distribution. Many candidates committed, if elected, to policy solutions presented them at our events. There was significant increase (684 in Southern, 698 in Wellington, 2006 in Canterbury) in DHB voter turnout in 2019, compared to last election with no scorecards. Not all top-scoring candidates were subsequently elected onto respective DHBs, but for Wellington and Southland all elected had high scores.

Key messages

PHANZ plays a role in supporting NZ democracy by filling a gap in public information about election candidates, whether they are fit for purpose when scrutinised through the public health lens. Election Scorecard are effective for raising public awareness, providing scrutiny of the candidates from a public health perspective, encouraging candidates to consider public health issues.

Association of Cardiovascular Disease Risk Factor Burden With Progression of Coronary Atherosclerosis Assessed by Serial Coronary Computed Tomographic Angiography

IMPORTANCE

Several studies have reported that the progression of coronary atherosclerosis, as measured by serial coronary computed tomographic (CT) angiography, is associated with the risk of future cardiovascular events. However, the cumulative consequences of multiple risk factors for plaque progression and the development of adverse plaque characteristics have not been well characterized.

OBJECTIVES

To examine the association of cardiovascular risk factor burden, as assessed by atherosclerotic cardiovascular disease (ASCVD) risk score, with the progression of coronary atherosclerosis and the development of adverse plaque characteristics.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study is a subgroup analysis of participant data from the prospective observational Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging (PARADIGM) study, which evaluated the association between serial coronary CT angiography findings and clinical presentation. The PARADIGM international multicenter registry, which includes 13 centers in 7 countries (Brazil, Canada, Germany, Italy, Portugal, South Korea, and the US), was used to identify 1005 adult patients without known coronary artery disease who underwent serial coronary CT angiography scans (median interscan interval, 3.3 years; interquartile range [IQR], 2.6-4.8 years) between December 24, 2003, and December 16, 2015. Based on the 10-year ASCVD risk score, the cardiovascular risk factor burden was classified as low (<7.5%), intermediate (7.5%-20.0%), or high (>20.0%). Data were analyzed from February 8, 2019, to April 17, 2020.

EXPOSURES

Association of baseline ASCVD risk burden with plaque progression.

MAIN OUTCOMES AND MEASURES

Noncalcified plaque, calcified plaque, and total plaque volumes (mm3) were measured. Noncalcified plaque was subclassified using predefined Hounsfield unit thresholds for fibrous, fibrofatty, and low-attenuation plaque. The percent atheroma volume (PAV) was defined as plaque volume divided by vessel volume. Adverse plaque characteristics were defined as the presence of positive remodeling, low-attenuation plaque, or spotty calcification.

RESULTS

In total, 1005 patients (mean [SD] age, 60 [8] years; 575 men [57.2%]) were included in the analysis. Of those, 463 patients (46.1%) had a low 10-year ASCVD risk score (low-risk group), 373 patients (37.1%) had an intermediate ASCVD risk score (intermediate-risk group), and 169 patients (16.8%) had a high ASCVD risk score (high-risk group). The annualized progression rate of PAV for total plaque, calcified plaque, and noncalcified plaque was associated with increasing ASCVD risk (r = 0.26 for total plaque, r = 0.23 for calcified plaque, and r = 0.11 for noncalcified plaque; P < .001). The annualized PAV progression of total plaque, calcified plaque, and noncalcified plaque was significantly greater in the high-risk group compared with the low-risk and intermediate-risk groups (for total plaque, 0.99% vs 0.45% and 0.58%, respectively; P < .001; for calcified plaque, 0.61% vs 0.23% and 0.36%; P < .001; and for noncalcified plaque, 0.38%vs 0.22% and 0.23%; P = .01). When further subclassified by noncalcified plaque type, the annualized PAV progression of fibrofatty and low-attenuation plaque was greater in the high-risk group (0.09% and 0.02%, respectively) compared with the low- to intermediate-risk group (n = 836; 0.02% [P = .02] and 0.001% [P = .008], respectively). The interval development of adverse plaque characteristics was greater in the high-risk group compared with the low-risk and intermediate-risk groups (for new positive remodeling, 73 patients [43.2%] vs 151 patients [32.6%] and 133 patients [35.7%], respectively; P = .02; for new low-attenuation plaque, 26 patients [15.4%] vs 44 patients [9.5%] and 35 patients [9.4%]; P = .02; and for new spotty calcification, 37 patients [21.9%] vs 52 patients [11.2%] and 54 patients [14.5%]; P = .002). The progression of noncalcified plaque subclasses and the interval development of adverse plaque characteristics did not significantly differ between the low-risk and intermediate-risk groups.

CONCLUSIONS AND RELEVANCE

Progression of coronary atherosclerosis occurred across all ASCVD risk groups and was associated with an increase in 10-year ASCVD risk. The progression of fibrofatty and low-attenuation plaques and the development of adverse plaque characteristics was greater in patients with a high risk of ASCVD.

Predictive value of the QFR in detecting vulnerable plaques in non-flow limiting lesions: a combined analysis of the PROSPECT and IBIS-4 study

Studies have shown that the quantitative flow ratio (QFR), recently introduced to assess lesion severity from coronary angiography, provides useful prognostic information; however the additive value of this technique over intravascular imaging in detecting lesions that are likely to cause events is yet unclear. We analysed data acquired in the PROSPECT and IBIS-4 studies, in particular the baseline virtual histology-intravascular ultrasound (VH-IVUS) and angiographic data from 17 non-culprit lesions with a presumable vulnerable phenotype (i.e., thin or thick cap fibroatheroma) that caused major adverse cardiac events or required revascularization (MACE) at 5-year follow-up and from a group of 78 vulnerable plaques that remained quiescent. The segments studied by VH-IVUS were identified in coronary angiography and the QFR was estimated. The additive value of 3-dimensional quantitative coronary angiography (3D-QCA) and of the QFR in predicting MACE at 5 year follow-up beyond plaque characteristics was examined. It was found that MACE lesions had a greater plaque burden (PB) and smaller minimum lumen area (MLA) on VH-IVUS, a longer length and a smaller minimum lumen diameter (MLD) on 3D-QCA and a lower QFR compared with lesions that remained quiescent. By univariate analysis MLA, PB, MLD, lesion length on 3D-QCA and QFR were predictors of MACE. In multivariate analysis a low but normal QFR (> 0.80 to < 0.97) was the only independent prediction of MACE (HR 3.53, 95% CI 1.16-10.75; P = 0.027). In non-flow limiting lesions with a vulnerable phenotype, QFR may provide additional prognostic information beyond plaque morphology for predicting MACE throughout 5 years.

The effect of positioning on maternal anatomy and hemodynamics during late pregnancy

INTRODUCTION

Supine positioning during late pregnancy causes dramatic compression of maternal abdominal vasculature and is a risk factor for stillbirth. The azygos vein has been shown to provide collateral circulation in this scenario. There are many well-known anatomical differences in abdominal vasculature between the left and right sides of the body. However, the effect of left and right positioning in pregnancy has not been well studied.

MATERIALS AND METHODS

After obtaining ethics approval, 10 women with uncomplicated pregnancies between 34 and 38 weeks gestation underwent magnetic resonance imaging in the left and right lateral positions. Phase contrast images were evaluated to measure blood flow through the abdominal aorta, inferior vena cava, and azygos vein.

RESULTS

No significant differences between left and right lateral positions were found in blood flow through the IVC at its formation (mean difference -0.15 L/min [CI -0.47, 0.18], p = .34) or through the azygos vein (mean difference 0.02 L/min [CI -0.22, 0.26], p = .87). Blood flow through the IVC just above the level of the renal veins was found to be reduced by 35% in the right lateral position when compared to the left (mean difference 1.01 L/min [CI 0.25, 1.43], p = .03). There were no significant differences in cardiac output or blood flow through the abdominal aorta.

CONCLUSIONS

While it was noted that blood flow through the IVC immediately above the level of the renal veins was reduced in the right lateral position, this did not appear to impact significantly on maternal cardiac output or blood flow through the azygos vein.

Examining adverse fetal/neonatal outcomes associated with severe maternal morbidity

BACKGROUND

While there is a global focus on severe maternal morbidity (SMM), less is known about the impact of SMM on fetal and neonatal outcomes.

AIMS

To examine fetal/neonatal outcomes associated with SMM.

MATERIALS AND METHODS

A national New Zealand (NZ) retrospective cohort study describing fetal/neonatal outcomes of all women with SMM admitted to a NZ Intensive Care Unit (ICU) or High Dependency Unit (HDU) in 2014. Adverse fetal/neonatal outcomes were defined as one or more of the following: fetal or early neonatal death, hypoxic ischaemic encephalopathy, Apgar score less than seven at five minutes, admission to Neonatal Intensive Care Unit or Special Care Baby Unit.

RESULTS

There were 400 women with SMM admitted to NZ ICU/HDU units in 2014, and 395 (98.8%) had complete birth/pregnancy outcome information. Of these, 49.4% (195/395) were associated with an adverse fetal/neonatal outcome. Indigenous Māori women had a 30% higher rate of adverse fetal/neonatal outcome compared to NZ European women (63.7% and 48.9% respectively; relative risk = 1.30, 95% CI 1.04-1.64). Pre-eclampsia was associated with an adverse fetal/neonatal outcome in 67% (81/120). Perinatal-related mortality rate was 53.1 per 1000 total births compared to NZ perinatal mortality of 11.2 per 1000 total births for 2014.

CONCLUSION

SMM events are associated with high rates of adverse fetal/neonatal outcomes with a higher burden of adverse events for Māori. Further research is needed to explore opportunities in maternal and neonatal care pathways to improve fetal/neonatal outcomes and address inequities.

Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog

In this work, we present methods for using human-robot dialog to improve language understanding for a mobile robot agent. The agent parses natural language to underlying semantic meanings and uses robotic sensors to create multi-modal models of perceptual concepts like red and heavy. The agent can be used for showing navigation routes, delivering objects to people, and relocating objects from one location to another. We use dialog clari_cation questions both to understand commands and to generate additional parsing training data. The agent employs opportunistic active learning to select questions about how words relate to objects, improving its understanding of perceptual concepts. We evaluated this agent on Amazon Mechanical Turk. After training on data induced from conversations, the agent reduced the number of dialog questions it asked while receiving higher usability ratings. Additionally, we demonstrated the agent on a robotic platform, where it learned new perceptual concepts on the y while completing a real-world task.

Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry

Background

Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography–determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP.

Methods and Results

Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume ≥1.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher‐ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78–0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52–0.67]; Duke coronary artery disease score, 0.74 [0.68–0.79]; ML model 1, 0.62 [0.55–0.69]; ML model 2, 0.73 [0.67–0.80]; all P<0.001; statistical model, 0.81 [0.75–0.87], P=0.128).

Conclusions

Based on a ML framework, quantitative atherosclerosis characterization has been shown to be the most important feature when compared with clinical, laboratory, and qualitative measures in identifying patients at risk of RPP.

Hemodynamic changes in women with symptoms of supine hypotensive syndrome

INTRODUCTION

Supine positioning during late pregnancy causes the gravid uterus to compress the inferior vena cava, resulting in dramatic hemodynamic changes. The maintenance of placental perfusion requires maternal circulatory and autonomic adaptations. Women with supine hypotensive syndrome (defined as a drop in systolic blood pressure of anything between 15 and 30 mmHg or an increase in heart rate of 20 bpm, with or without symptoms) may have reduced ability to compensate for the effects of supine positioning.

MATERIAL AND METHODS

Twelve women with uncomplicated pregnancies and no symptoms of supine hypotension (normal) and 10 women with uncomplicated pregnancies who reported symptoms of supine hypotension between 34 and 38 weeks' gestation underwent magnetic resonance imaging in the supine and left lateral positions. Phase contrast images were evaluated to measure blood flow through the aorta, inferior vena cava, superior vena cava and azygos vein.

RESULTS

Women with symptoms of supine hypotension showed significant reductions in azygos venous flow rate compared with the normal group (-0.15 (-0.30 to -0.01) L/min). Those with symptoms showed no statistically significant compensatory changes in heart rate compared with the normal group (heart rate change 4.5 (-3.1 to 12.1) bpm). Hemodynamic changes in response to positioning were similar across both groups including: a reduction in inferior vena cava blood flow, reduction in cardiac output and an increase in azygos blood flow.

CONCLUSIONS

Maternal hemodynamic adaptations were found to be consistent across groups irrespective of whether the women had symptoms of supine hypotension. In both groups a reduction in blood flow through the inferior vena cava occurred in the supine position with a subsequent reduction in cardiac output. Both groups showed a compensatory increase in blood flow through the azygos vein in order to partially compensate for this. Taking into account the effect of maternal position, women with symptoms were found to have reduced azygos flow compared with asymptomatic women. There was a significant increase in heart rate when the women were supine than when they were in the left lateral position.

New screen on the block: non-invasive prenatal testing for fetal chromosomal abnormalities

Non-invasive prenatal testing (NIPT) is a new screen for fetal chromosomal abnormalities. It is a screening test based on technology that involves the analysis of feto-placental DNA that is present in maternal blood. This DNA is then analysed for abnormalities of specific chromosomes (eg 13, 18, 21, X, Y). NIPT has a much higher screening capability for chromosomal abnormalities than current combined first trimester screening, with ~99% sensitivity for trisomy 21 (Down syndrome) and at least a 10-fold higher positive predictive value. The low false-positive rate (1-3%) is one of the most advertised advantages of NIPT. In practice, this could lead to a significant reduction in the number of false-positive tests and the need for invasive diagnostic procedures. NIPT is now suitable for singleton and twin pregnancies and can be performed from ~10 weeks in a pregnancy. NIPT is not currently publicly funded in most countries. However, the increasing availability of NIPT commercially will likely lead to an increase in demand for this as a screening option. Given the high numbers of women who visit a general practitioner (GP) in their first trimester, GPs are well-placed to also offer NIPT as a screening option. A GP's role in facilitating access to this service will likely be crucial in ensuring equity in access to this technology, and it is important to ensure that they are well supported to do so.

Expressive writing as a therapeutic intervention for people with advanced disease: a systematic review

Background

Expressive writing involves writing about stressful or traumatic experiences. Despite trials in people with advanced disease, no systematic review to date has critiqued the evidence on expressive writing in this population. To synthesise the evidence of the effects of expressive writing on pain, sleep, depression and anxiety in people with advanced disease.

Methods

A systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. CINAHL, CENTRAL, PsycINFO and PubMed were searched from January 1986 to March 2018. Other sources included clinical data registers and conference proceedings. Studies were included if they were randomised controlled trials that assessed the impact of an intervention involving expressive writing for adults with advanced disease and/or studies involving linguistic analysis on the expressive writing output. Methodological quality was assessed using the Cochrane risk of bias tool and the Mixed Methods Appraisal Tool. The Grading of Recommendations Assessment, Development and Evaluation tool was used to assess the level of evidence for the outcomes of interest. The protocol of this systematic review has been registered on PROSPERO (CRD42017058193).

Results

Six eligible studies with a total of 288 participants were identified, including four randomised controlled trials. All of the trials were in cancer and recruited predominantly women. None of the interventions were tailored to the population. Studies had methodological shortcomings and evidence was generally of low quality. Combined analysis of the four trials, involving 214 participants in total, showed no clear difference in the effect of expressive writing on sleep, anxiety or depression compared to an active control. Pain was not evaluated in the trials. In contrast, analysis of the four studies that included linguistic analysis alluded to linguistic mechanisms for potential effects.

Conclusion

Although the trial results suggest there is no benefit in expressive writing for people with advanced disease, the current evidence is limited. There is a need for more rigorous trials. It would be of benefit first to undertake exploratory research in trial design including how best to measure impact and in tailoring of the intervention to address the specific needs of people with advanced disease.

Trial registration

The protocol of this systematic review has been registered on PROSPERO, which can be accessed here (registration number: CRD42017058193).

Electronic supplementary material

The online version of this article (10.1186/s12904-019-0449-y) contains supplementary material, which is available to authorized users.

Polysomnographic Heart Rate Variability Indices and Atrial Ectopy Associated with Incident Atrial Fibrillation Risk in Older Community-dwelling Men

BACKGROUND

Autonomic dysfunction contributes to atrial fibrillation (AF).

OBJECTIVE

We hypothesized that polysomnogram (PSG)-based heart rate variability (HRV) autonomic function biomarkers are associated with incident AF and these associations are modified by measures of sleep disordered breathing (SDB).

METHODS

2350 participants of a multi-center prospective study (Outcomes of Sleep Disorders in Older Men Study) without baseline AF underwent sleep studies with incident adjudicated AF follow up (8.0 ± 2.6 years). Cox proportional hazard models were used to analyze sleep study-ECG spectral HRV indices [low and high frequency power (LF, HF), LF/HF] and time domain indices [mean of normal to normal beats (MNN), short and long term variability (STV, LTV) and STV/LTV] and premature atrial contractions (PACs) and incident AF (HR and 95% CI). Statistical interactions between HRV and SDB were examined. Models were adjusted for age, race, body mass index, waist circumference, cardiac medications, co-morbid diseases, alcohol use and study site.

RESULTS

Lower LF/HF and lower LF were associated with higher AF incidence (LF/HF Q1 vs. Q4: 1.46, 1.02-2.08, LF Q1 vs. Q4: 1.46, 1.02-2.10). Higher STV/LTV was associated with an increased risk of AF (p-trend= 0.028). The highest PAC quartile had a 3-fold increased AF risk (2.99, 1.94-4.62) compared to the lowest quartile. A significant interaction of obstructive apnea was observed in the LF-AF relationship (0.045).

CONCLUSIONS

Sleep-related reduced sympathovagal balance (LF/HF) and increased atrial ectopy are independently associated with future AF; a relationship modified by obstructive apnea.