Fetal alcohol spectrum disorder and attention deficit hyperactivity disorder stimulant trial in children: an N-of-1 pilot trial to compare stimulant to placebo (FASST): protocol.

Introduction: Fetal alcohol spectrum disorder (FASD) is a neurodevelopmental disorder caused by alcohol exposure during pregnancy. FASD is associated with neurodevelopmental deviations, and 50%-94% of children with FASD meet the Diagnostic and Statistical Manual of Mental Disorders-fifth edition diagnostic criteria for attention deficit hyperactivity disorder (ADHD). There is a paucity of evidence around medication efficacy for ADHD symptoms in children with FASD.

Anticoagulation Strategies in Non-Critically Ill Patients with Covid-19.

BACKGROUND: Optimal thromboprophylaxis for hospitalized patients with coronavirus disease 2019 (Covid-19) is uncertain. METHODS: In an open-label, adaptive platform trial, we randomly assigned hospitalized adults with Covid-19 to low-dose low-molecular-weight heparin thromboprophylaxis or intermediate-dose or low-dose plus aspirin. In response to external evidence, the aspirin intervention was discontinued and a therapeutic-dose arm added.

Does the registry speak your language? A case study of the Global Angelman Syndrome Registry.

Global disease registries are critical to capturing common patient related information on rare illnesses, allowing patients and their families to provide information about their condition in a safe, accessible, and engaging manner that enables researchers to undertake critical research aimed at improving outcomes. Typically, English is the default language of choice for these global digital health platforms. Unfortunately, language barriers can significantly inhibit participation from non-English speaking participants.

Managing surgical waiting lists through dynamic priority scoring.

Prioritising elective surgery patients under the Australian three-category system is inherently subjective due to variability in clinician decision making and the potential for extraneous factors to influence category assignment. As a result, waiting time inequities can exist which may lead to adverse health outcomes and increased morbidity, especially for patients deemed to be low priority. This study investigated the use of a dynamic priority scoring (DPS) system to rank elective surgery patients more equitably, based on a combination of waiting time and clinical factors.

Pattern-based assessment of the influence of rainfall characteristics on urban stormwater quality.

Urbanisation increases pollutant generation within catchments and their transport to receiving waters. Changes to rainfall patterns, particularly in the age of climate change, make pollution mitigation a challenging task. Understanding how rainfall characteristics could influence the changes to stormwater pollutant runoff is important for designing effective mitigation strategies.

Being Bayesian in the 2020s: opportunities and challenges in the practice of modern applied Bayesian statistics.

Building on a strong foundation of philosophy, theory, methods and computation over the past three decades, Bayesian approaches are now an integral part of the toolkit for most statisticians and data scientists. Whether they are dedicated Bayesians or opportunistic users, applied professionals can now reap many of the benefits afforded by the Bayesian paradigm. In this paper, we touch on six modern opportunities and challenges in applied Bayesian statistics: intelligent data collection, new data sources, federated analysis, inference for implicit models, model transfer and purposeful software products.

Bayesian design for minimizing prediction uncertainty in bivariate spatial responses with applications to air quality monitoring.

Model-based geostatistical design involves the selection of locations to collect data to minimize an expected loss function over a set of all possible locations. The loss function is specified to reflect the aim of data collection, which, for geostatistical studies, could be to minimize the prediction uncertainty at unobserved locations. In this paper, we propose a new approach to design such studies via a loss function derived through considering the entropy about the model predictions and the parameters of the model.

Angiotensin receptor blockers for the treatment of covid-19: pragmatic, adaptive, multicentre, phase 3, randomised controlled trial.

Objective: To determine whether disrupting the renin angiotensin system with angiotensin receptor blockers will improve clinical outcomes in people with covid-19.

Design: CLARITY was a pragmatic, adaptive, multicentre, phase 3, randomised controlled trial.

Setting: 17 hospital sites in India and Australia.

Adaptive monitoring of coral health at Scott Reef where data exhibit nonlinear and disturbed trends over time.

Time series data are often observed in ecological monitoring. Frequently, such data exhibit nonlinear trends over time potentially due to complex relationships between observed and auxiliary variables, and there may also be sudden declines over time due to major disturbances. This poses substantial challenges for modeling such data and also for adaptive monitoring.

Temperature Sensing and Honey Bee Colony Strength.

Strength auditing of European honey bee (Apis mellifera Linnaeus, 1758 [Hymenoptera: Apidae]) colonies is critical for apiarists to manage colony health and meet pollination contracts conditions. Colony strength assessments used during pollination servicing in Australia typically use a frame-top cluster-count (Number of Frames) inspection. Sensing technology has potential to improve auditing processes, and commercial temperature sensors are widely available.

Comparing pregabalin and gabapentin for persistent neuropathic pain: A protocol for a pilot N-of-1 trial series.

Background: Evidence-based management of neuropathic pain is commonly ineffective due to the large variability in response between cases. Patients often have to trial several drugs before finding one that provides adequate relief, leading to increased costs and worsened outcomes. There is thus a need for tools to guide and streamline prescribing decisions in neuropathic pain.

The impact of functional combined anteversion on hip range of motion: a new optimal zone to reduce risk of impingement in total hip arthroplasty.

Aims: Pelvic tilt (PT) can significantly change the functional orientation of the acetabular component and may differ markedly between patients undergoing total hip arthroplasty (THA). Patients with stiff spines who have little change in PT are considered at high risk for instability following THA. Femoral component position also contributes to the limits of impingement-free range of motion (ROM), but has been less studied.

Protocol for the Controlled evaLuation of Angiotensin Receptor blockers for COVID-19 respIraTorY disease (CLARITY): a randomised controlled trial.

Background: SARS-CoV-2 binds to membrane-bound angiotensin-converting enzyme 2 (ACE2) which may result in downregulation of membrane-bound ACE2. ACE2 is a key regulator of the renin-angiotensin system (RAS) and is responsible for degrading angiotensin II and thereby counteracting its pro-inflammatory, pro-fibrotic effects mediated through the angiotensin II type 1 receptor (AT1R). As AT1R is directly blocked by angiotensin receptor blockers (ARBs), these agents may offer a safe, low-cost solution for reducing COVID-19 respiratory outcomes.

Establishment of an International Collaborative Network for N-of-1 Trials and Single-Case Designs.

In this article we briefly examine the unique features of Single-Case Designs (SCDs) (studies in a single participant), their history and current trends, and real-world clinical applications. The International Collaborative Network for N-of-1 Trials and Single-Case Designs (ICN) is a formal collaborative network for individuals with an interest in SCDs. The ICN was established in 2017 to support the SCD scientific community and provide opportunities for collaboration, a global communication channel, resource sharing and knowledge exchange.

Exploring Symptom Fluctuations and Triggers in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Novel Patient-Centred N-of-1 Observational Designs: A Protocol for a Feasibility and Acceptability Study.

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic condition of unknown aetiology associated with a range of disabling symptoms, including post-exertional malaise, chronic fatigue, musculoskeletal pain, orthostatic intolerance, unrefreshing sleep, and cognitive dysfunction. ME/CFS is a heterogeneous disorder, with significant variation in symptom type and severity between individuals, as well as within individuals over time. The diversity of ME/CFS symptom presentation makes management challenging; treatments supported by data from randomised controlled trials may not work for all individuals due to the variability in experienced symptoms.

A Bayesian approach to model the trends and variability in urban stormwater quality associated with catchment and hydrologic parameters.

Stormwater runoff pollution has become a key environmental issue in urban areas. Reliable estimation of stormwater pollutant discharge is important for implementing robust water quality management strategies. Even though significant attempts have been undertaken to develop water quality models, deterministic approaches have proven inappropriate as they do not address the variability in stormwater quality.

Thermal Impacts of Apicultural Practice and Products on the Honey Bee Colony.

Hive design and apicultural processes have not been fundamentally changed since the design and commercialization of the Langstroth moveable frame hive in 1854. Colonies of Apis mellifera Linnaeus (Hymentoptera: Apidae) (the honey bee) maintain a brood nest temperature within the narrow range of 34.5-35.

Source quantification and risk assessment as a foundation for risk management of metals in urban road deposited solids.

Urban road build-up solids contain toxic metals posing potential risks to human health. Management of human health risks arising from these metals is critical in urban areas. This study collected solids build-up data from 16 study sites with various land use and traffic characteristics.

New conceptualisation of first flush phenomena in urban catchments.

First flush is an important phenomenon commonlyused in stormwater treatment system design where only the highly concentrated initial part of the runoff hydrograph is subject to treatment. Despite the existing methods for estimating the first flush, a robust quantitative definition is difficult to find. This paper discusses a novel approach, where a new parameter is introduced to analyse the variability in the discharge of pollutants at different times throughout a runoff event and thereby enable the identification of first flush.

Catchment based estimation of pollutant event mean concentration (EMC) and implications for first flush assessment.

The Event Mean Concentration (EMC) is considered as a key analytical parameter for assessing the quality of stormwater. The conventional estimation methods to determine EMC do not necessarily address the variability associated with the hydrologic characteristics. Accordingly, this study was conducted to identify the potential hydrologic variables that can influence EMC and thereby to create a mathematical model to determine EMC using the hydrologic variables while incorporating the catchment as an influential factor.

Bayesian adaptive N-of-1 trials for estimating population and individual treatment effects.

This article proposes a novel adaptive design algorithm that can be used to find optimal treatment allocations in N-of-1 clinical trials. This new methodology uses two Laplace approximations to provide a computationally efficient estimate of population and individual random effects within a repeated measures, adaptive design framework. Given the efficiency of this approach, it is also adopted for treatment selection to target the collection of data for the precise estimation of treatment effects.

SSNdesign-An R package for pseudo-Bayesian optimal and adaptive sampling designs on stream networks.

Streams and rivers are biodiverse and provide valuable ecosystem services. Maintaining these ecosystems is an important task, so organisations often monitor the status and trends in stream condition and biodiversity using field sampling and, more recently, autonomous in-situ sensors. However, data collection is often costly, so effective and efficient survey designs are crucial to maximise information while minimising costs.

Relative rate of change in cognitive score network dynamics via Bayesian hierarchical models reveal spatial patterns of neurodegeneration.

The degeneration of the human brain is a complex process, which often affects certain brain regions due to healthy aging or disease. This degeneration can be evaluated on regions of interest (ROI) in the brain through probabilistic networks and morphological estimates. Current approaches for finding such networks are limited to analyses at discrete neuropsychological stages, which cannot appropriately account for connectivity dynamics over the onset of cognitive deterioration, and morphological changes are seldom unified with connectivity networks, despite known dependencies.