ABSTRACT
BACKGROUND: Simulation is an important tool for assessing the performance of statistical methods for the analysis of data and for the planning of studies. While methods are available for the simulation of correlated binary random variables, all have significant practical limitations for simulating outcomes from longitudinal cluster randomised trial designs, such as the cluster randomised crossover and the stepped wedge trial designs. For these trial designs as the number of observations in each cluster increases these methods either become computationally infeasible or their range of allowable correlations rapidly shrinks to zero. METHODS: In this paper we present a simple method for simulating binary random variables with a specified vector of prevalences and correlation matrix. This method allows for the outcome prevalence to change due to treatment or over time, and for a 'nested exchangeable' correlation structure, in which observations in the same cluster are more highly correlated if they are measured in the same time period than in different time periods, and where different individuals are measured in each time period. This means that our method is also applicable to more general hierarchical clustered data contexts, such as students within classrooms within schools. The method is demonstrated by simulating 1000 datasets with parameters matching those derived from data from a cluster randomised crossover trial assessing two variants of stress ulcer prophylaxis. RESULTS: Our method is orders of magnitude faster than the most well known general simulation method while also allowing a much wider range of correlations than alternative methods. An implementation of our method is available in an R package NestBin. CONCLUSIONS: This simulation method is the first to allow for practical and efficient simulation of large datasets of binary outcomes with the commonly used nested exchangeable correlation structure. This will allow for much more effective testing of designs and inference methods for longitudinal cluster randomised trials with binary outcomes.
Subject(s)
Computer Simulation , Cross-Over Studies , Randomized Controlled Trials as Topic , Humans , Randomized Controlled Trials as Topic/methods , Randomized Controlled Trials as Topic/statistics & numerical data , Longitudinal Studies , Cluster Analysis , Research Design/statistics & numerical data , Models, Statistical , Data Interpretation, Statistical , AlgorithmsABSTRACT
Dung beetles provide a variety of ecosystem services in both natural and farmed landscapes. Amongst these services, reductions in the abundance of the free-living stages of pests and parasites that develop in faeces is considered to be of great importance. There is evidence from Australia that enhanced dung beetle populations can reduce populations of pest fly species, particularly the bush fly, however, there is little empirical evidence for reductions in the incidence and impact of nematode parasitism in grazing ruminants. There are two main pathways whereby beetles can disrupt worm life-cycles: predaceous species that feed on eggs or larvae can directly reduce populations in dung whereas coprophagous species can affect parasite development, survival and translocation by altering the location, microclimate and infrastructure of dung deposits. In addition, predaceous mites that are phoretic on dung beetles, can also prey on larval stages in the faeces. To date, reductions in both larval survival and the acquisition of gastrointestinal nematode burdens in ruminants on pasture has been reported only in association with the activity of large tunnelers that bury dung 15â¯cm or more below ground. The activity of dwellers, rollers and shallow tunnelers can either limit or enhance larval development and translocation, depending on the influence of other factors, notably rainfall. Currently, the scientific evidence for dung beetles playing a major role in the control of gastrointestinal nematodes in domestic ruminants is very limited and may have been overestimated in assessments of their ecosystem services.
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INTRODUCTION: Despite universal access to government-funded direct-acting antivirals (DAAs) in 2016, the rate of hepatitis C treatment uptake in Australia has declined substantially. Most hepatitis C is related to injecting drug use; reducing the hepatitis C burden among people who inject drugs (PWID) is, therefore, paramount to reach hepatitis C elimination targets. Increasing DAA uptake by PWID is important for interrupting transmission and reducing incidence, as well as reducing morbidity and mortality and improving quality of life of PWID and meeting Australia's hepatitis C elimination targets. METHODS AND ANALYSIS: A cluster randomised cross-over trial will be conducted with three intervention arms and a control arm. Arm A will receive rapid hepatitis C virus (HCV) antibody testing; arm B will receive rapid HCV antibody and rapid RNA testing; arm C will receive rapid HCV antibody testing and same-day treatment initiation for HCV antibody-positive participants; the control arm will receive standard of care. The primary outcomes will be (a) the proportion of participants with HCV commencing treatment and (b) the proportion of participants with HCV achieving cure. Analyses will be conducted on an intention-to-treat basis with mixed-effects logistic regression models. ETHICS AND DISSEMINATION: The study has been approved by the Alfred Ethics Committee (number HREC/64731/Alfred-2020-217547). Each participant will provide written informed consent. Reportable adverse events will be reported to the reviewing ethics committee. The findings will be presented at scientific conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT05016609. TRIAL PROGRESSION: The study commenced recruitment on 9 March 2022 and is expected to complete recruitment in December 2024.
Subject(s)
Antiviral Agents , Cross-Over Studies , Hepatitis C , Substance Abuse, Intravenous , Humans , Antiviral Agents/therapeutic use , Substance Abuse, Intravenous/complications , Hepatitis C/drug therapy , Australia , Randomized Controlled Trials as Topic , Hepatitis C Antibodies/blood , Hepacivirus/geneticsABSTRACT
BACKGROUND: High-dose corticosteroids have been used to attenuate the inflammatory response to cardiac surgery and cardiopulmonary bypass, but patient outcome benefits remain unclear. Our primary aim was to determine whether using dexamethasone was superior to not using dexamethasone to increase the number of home days in the first 30 days after cardiac surgery. Our secondary aim was to evaluate efficiency, value and impact of the novel trial design. METHODS: This pragmatic, international trial incorporating a prerandomized consent design favoring local practice enrolled patients undergoing cardiac surgery across 7 hospitals in Australia and The Netherlands. Patients were randomly assigned to dexamethasone, 1 mg/kg, or not (control). The primary outcome was the number of days alive and at home up to 30 days after surgery ("home days"). Secondary outcomes included prolonged mechanical ventilation (>48 h), sepsis, renal failure, myocardial infarction, stroke and death. RESULTS: Of 2093 patients assessed for eligibility, 1951 were randomized (median age 63 years, 80% male). The median number of home days was 23.0 (IQR, 20.1 to 24.1) in the dexamethasone group and 23.1 (IQR, 20.1 to 24.6) in the no dexamethasone group; median difference 0.1 (95% CI, -0.3 to 0.5), P=0.66. The rates of prolonged mechanical ventilation, RR 0.72 (95% CI, 0.48 to 1.08), sepsis, RR 1.02 (95% CI, 0.57 to 1.82), renal failure, RR 0.94 (95% CI, 0.80 to 1.12), myocardial infarction, RR 1.20 (95% CI, 0.30 to 4.82), stroke, RR 1.06 (95% CI, 0.54 to 2.08), and death, RR 0.72 (95% CI, 0.22 to 2.35), were comparable between groups (all P>0.10). Dexamethasone reduced intensive care unit stay, median 29 (IQR, 22 to 50) h vs. 43 (24 to 72) h, P=0.004. Our novel trial design was highly efficient (89.3% enrolment). CONCLUSIONS: Among patients undergoing cardiac surgery, high-dose dexamethasone decreased intensive care unit stay but did not increase the number of home days after surgery.
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BACKGROUND: The bovine lungworm Dictyocaulus viviparus negatively impacts bovine health and leads to substantial economic losses. Lungworm infections can be difficult to manage due to the unpredictable and severe nature of clinical outbreaks. Despite the widespread use of macrocyclic lactones (MLs) in grazing cattle in the UK, there have been no confirmed reports of resistant lungworms to date, with only one case of anthelmintic-resistant (ML) lungworm confirmed worldwide. METHODS: Lungworm Baermann filtrations were conducted on first-season grazing dairy calves as part of a wider study investigating anthelmintic resistance in gastrointestinal nematodes in Scotland using the faecal egg count reduction test. RESULTS: Clinical signs and significant numbers of lungworm larvae in faeces were observed after treatment with either ivermectin or moxidectin. LIMITATIONS: There are no established guidelines for the diagnosis of resistant lungworms in the field. Currently, resistance can only be diagnosed after a controlled efficacy test has been conducted. This limits the conclusions that can be drawn; however, they are highly suggestive of resistance. CONCLUSION: This short report describes the inefficacy of ivermectin and moxidectin against D. viviparus and is highly suggestive of ML resistance.
Subject(s)
Cattle Diseases , Dictyocaulus Infections , Dictyocaulus , Ivermectin , Macrolides , Animals , Ivermectin/therapeutic use , Ivermectin/pharmacology , Cattle , Macrolides/therapeutic use , Macrolides/pharmacology , Dictyocaulus Infections/drug therapy , Cattle Diseases/drug therapy , Cattle Diseases/parasitology , Dictyocaulus/drug effects , Anthelmintics/therapeutic use , Anthelmintics/pharmacology , Scotland , Drug Resistance , Female , Feces/parasitology , Dairying , Parasite Egg Count/veterinaryABSTRACT
Laser-induced crystallization is a novel alternative to classical methods for crystallizing organic molecules but requires a judicious choice of experimental parameters for the onset of crystallization to be predictable. This study investigated the impact of the laser repetition rate on the time delay from the start of the pulsed laser illumination to the initiation of crystallization, the so-called induction time. A supersaturated urea solution was irradiated with near-infrared (λ = 1030 nm) laser pulses of pulse duration τ = 5 ps at a pulse energy of approximately E = 340 µJ while varying the repetition rate from 10 to 20,000 Hz. The optimal rate discovered ranged from 500 Hz to 1 kHz, quantified by the measured induction time (median 2-5 s) and the mean probability of inducing a successful crystallization event (5 × 10-2%). For higher repetition rates (5-20 kHz), the mean probability dropped to 3 × 10-3%. The reduced efficiency at high repetition rates is likely due to an interaction between an existing thermocavitation bubble and subsequent pulses. These results suggest that an optimized pulse repetition rate can be a means to gain further control over the laser-induced crystallization process.
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Why are some species sexually dimorphic while other closely related species are not? While all females in genus Strauzia share a multiply-banded wing pattern typical of many other true fruit flies, males of four species have noticeably elongated wings with banding patterns "coalesced" into a continuous dark streak across much of the wing. We take an integrative phylogenetic approach to explore the evolution of this dimorphism and develop general hypotheses underlying the evolution of wing dimorphism in flies. We find that the origin of coalesced and other darkened male wing patterns correlate with the inferred origin of host plant sharing in Strauzia. While wing shape among non-host-sharing species tended to be conserved across the phylogeny, shapes of male wings for Strauzia species sharing the same host plant were more different from one another than expected under Brownian models of evolution and overall rates of wing shape change differed between non-host-sharing species and host-sharing species. A survey of North American Tephritidae finds just three other genera with specialist species that share host plants. Host-sharing species in these genera also have wing patterns unusual for each genus. Only genus Eutreta is like Strauzia in having the unusual wing patterns only in males, and of genera that have multiple species sharing hosts, only in Eutreta and Strauzia do males hold territories while females search for mates. We hypothesize that in species that share host plants, those where females actively search for males in the presence of congeners may be more likely to evolve sexually dimorphic wing patterns.
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Linear mixed models are commonly used in analyzing stepped-wedge cluster randomized trials. A key consideration for analyzing a stepped-wedge cluster randomized trial is accounting for the potentially complex correlation structure, which can be achieved by specifying random-effects. The simplest random effects structure is random intercept but more complex structures such as random cluster-by-period, discrete-time decay, and more recently, the random intervention structure, have been proposed. Specifying appropriate random effects in practice can be challenging: assuming more complex correlation structures may be reasonable but they are vulnerable to computational challenges. To circumvent these challenges, robust variance estimators may be applied to linear mixed models to provide consistent estimators of standard errors of fixed effect parameters in the presence of random-effects misspecification. However, there has been no empirical investigation of robust variance estimators for stepped-wedge cluster randomized trials. In this article, we review six robust variance estimators (both standard and small-sample bias-corrected robust variance estimators) that are available for linear mixed models in R, and then describe a comprehensive simulation study to examine the performance of these robust variance estimators for stepped-wedge cluster randomized trials with a continuous outcome under different data generators. For each data generator, we investigate whether the use of a robust variance estimator with either the random intercept model or the random cluster-by-period model is sufficient to provide valid statistical inference for fixed effect parameters, when these working models are subject to random-effect misspecification. Our results indicate that the random intercept and random cluster-by-period models with robust variance estimators performed adequately. The CR3 robust variance estimator (approximate jackknife) estimator, coupled with the number of clusters minus two degrees of freedom correction, consistently gave the best coverage results, but could be slightly conservative when the number of clusters was below 16. We summarize the implications of our results for the linear mixed model analysis of stepped-wedge cluster randomized trials and offer some practical recommendations on the choice of the analytic model.
ABSTRACT
In cluster randomized trials, individuals from the same cluster tend to have more similar outcomes than individuals from different clusters. This correlation must be taken into account in the analysis of every cluster trial to avoid incorrect inferences. In this paper, we describe the principles guiding the analysis of cluster trials including how to correctly account for intra-cluster correlations as well as how to analyze more advanced designs such as stepped-wedge and cluster cross-over trials. We then describe how to handle specific issues such as small sample sizes and missing data.
Subject(s)
Randomized Controlled Trials as Topic , Research Design , Humans , Cluster Analysis , Cross-Over Studies , Sample SizeABSTRACT
The cluster randomized trial allows a randomized evaluation when it is either not possible to randomize the individual or randomizing individuals would put the trial at high risk of contamination across treatment arms. There are many variations of the cluster randomized design, including the parallel design with or without baseline measures, the cluster randomized cross-over design, the stepped-wedge cluster randomized design, and more recently-developed variants such as the batched stepped-wedge design and the staircase design. Once it has been clearly established that there is a need for cluster randomization, one ever important question is which form the cluster design should take. If a design in which time is split into multiple trial periods is to be adopted (e.g. as in a stepped-wedge), researchers must decide whether the same participants should be measured in multiple trial periods (cohort sampling); or if different participants should be measured in each period (continual recruitment or cross-sectional sampling). Here we outline the different possible options and weigh up the pros and cons of the different design choices, which revolve around statistical efficiency, study logistics and the assumptions required.
Subject(s)
Randomized Controlled Trials as Topic , Research Design , Humans , Cross-Sectional Studies , Longitudinal StudiesABSTRACT
Randomized controlled trials can be used to generate evidence on the efficacy and safety of new treatments in eating disorders research. Many of the trials previously conducted in this area have been deemed to be of low quality, in part due to a number of practical constraints. This article provides an overview of established and more innovative clinical trial designs, accompanied by pertinent examples, to highlight how design choices can enhance flexibility and improve efficiency of both resource allocation and participant involvement. Trial designs include individually randomized, cluster randomized, and designs with randomizations at multiple time points and/or addressing several research questions (master protocol studies). Design features include the use of adaptations and considerations for pragmatic or registry-based trials. The appropriate choice of trial design, together with rigorous trial conduct, reporting and analysis, can establish high-quality evidence to advance knowledge in the field. It is anticipated that this article will provide a broad and contemporary introduction to trial designs and will help researchers make informed trial design choices for improved testing of new interventions in eating disorders. PUBLIC SIGNIFICANCE: There is a paucity of high quality randomized controlled trials that have been conducted in eating disorders, highlighting the need to identify where efficiency gains in trial design may be possible to advance the eating disorder research field. We provide an overview of some key trial designs and features which may offer solutions to practical constraints and increase trial efficiency.
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Feeding and Eating Disorders , Randomized Controlled Trials as Topic , Research Design , Humans , Feeding and Eating Disorders/therapyABSTRACT
Structured light offers wider bandwidths and higher security for communication. However, propagation through complex random media, such as the Earth's atmosphere, typically induces intermodal crosstalk. We show numerically and experimentally that coupling of photonic orbital angular momentum modes is governed by a universal function of a single parameter: the ratio between the random medium's and the beam's transverse correlation lengths, even in the regime of pronounced intensity fluctuations.
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BACKGROUND: The Interrupted Time Series (ITS) is a robust design for evaluating public health and policy interventions or exposures when randomisation may be infeasible. Several statistical methods are available for the analysis and meta-analysis of ITS studies. We sought to empirically compare available methods when applied to real-world ITS data. METHODS: We sourced ITS data from published meta-analyses to create an online data repository. Each dataset was re-analysed using two ITS estimation methods. The level- and slope-change effect estimates (and standard errors) were calculated and combined using fixed-effect and four random-effects meta-analysis methods. We examined differences in meta-analytic level- and slope-change estimates, their 95% confidence intervals, p-values, and estimates of heterogeneity across the statistical methods. RESULTS: Of 40 eligible meta-analyses, data from 17 meta-analyses including 282 ITS studies were obtained (predominantly investigating the effects of public health interruptions (88%)) and analysed. We found that on average, the meta-analytic effect estimates, their standard errors and between-study variances were not sensitive to meta-analysis method choice, irrespective of the ITS analysis method. However, across ITS analysis methods, for any given meta-analysis, there could be small to moderate differences in meta-analytic effect estimates, and important differences in the meta-analytic standard errors. Furthermore, the confidence interval widths and p-values for the meta-analytic effect estimates varied depending on the choice of confidence interval method and ITS analysis method. CONCLUSIONS: Our empirical study showed that meta-analysis effect estimates, their standard errors, confidence interval widths and p-values can be affected by statistical method choice. These differences may importantly impact interpretations and conclusions of a meta-analysis and suggest that the statistical methods are not interchangeable in practice.
Subject(s)
Public Health , Humans , Interrupted Time Series AnalysisABSTRACT
We aimed to explore, in a sample of systematic reviews (SRs) with meta-analyses of the association between food/diet and health-related outcomes, whether systematic reviewers selectively included study effect estimates in meta-analyses when multiple effect estimates were available. We randomly selected SRs of food/diet and health-related outcomes published between January 2018 and June 2019. We selected the first presented meta-analysis in each review (index meta-analysis), and extracted from study reports all study effect estimates that were eligible for inclusion in the meta-analysis. We calculated the Potential Bias Index (PBI) to quantify and test for evidence of selective inclusion. The PBI ranges from 0 to 1; values above or below 0.5 suggest selective inclusion of effect estimates more or less favourable to the intervention, respectively. We also compared the index meta-analytic estimate to the median of a randomly constructed distribution of meta-analytic estimates (i.e., the estimate expected when there is no selective inclusion). Thirty-nine SRs with 312 studies were included. The estimated PBI was 0.49 (95% CI 0.42-0.55), suggesting that the selection of study effect estimates from those reported was consistent with a process of random selection. In addition, the index meta-analytic effect estimates were similar, on average, to what we would expect to see in meta-analyses generated when there was no selective inclusion. Despite this, we recommend that systematic reviewers report the methods used to select effect estimates to include in meta-analyses, which can help readers understand the risk of selective inclusion bias in the SRs.
Subject(s)
Bias , Diet , Meta-Analysis as Topic , Research Design , Systematic Reviews as Topic , Humans , Nutritional Sciences , Selection Bias , Reproducibility of Results , Publication Bias , FoodABSTRACT
BACKGROUND: Dexamethasone has been shown to reduce acute pain after surgery, but there is uncertainty as to its effects on chronic postsurgical pain (CPSP). We hypothesised that in patients undergoing major noncardiac surgery, a single intraoperative dose of dexamethasone increases the incidence of CPSP. METHODS: We devised a propensity score-matched analysis of the ENIGMA-II trial CPSP dataset, aiming to compare the incidence of CPSP in patients who had received dexamethasone or not 12 months after major noncardiac surgery. The primary outcome was the incidence of CPSP. We used propensity score matching and inverse probability weighting to balance baseline variables to estimate the average marginal effect of dexamethasone on patient outcomes, accounting for confounding to estimate the average treatment effect on those treated with dexamethasone. RESULTS: We analysed 2999 patients, of whom 116 of 973 (11.9%) receiving dexamethasone reported CPSP, and 380 of 2026 (18.8%) not receiving dexamethasone reported CPSP, unadjusted odds ratio 0.76 (95% confidence interval 0.78-1.00), P=0.052. After propensity score matching, CPSP occurred in 116 of 973 patients (12.2%) receiving dexamethasone and 380 of 2026 patients (13.8%) not receiving dexamethasone, adjusted risk ratio 0.88 (95% confidence interval 0.61-1.27), P=0.493. There was no difference between groups in quality of life or pain interference with daily activities, but 'least pain' (P=0.033) and 'pain right now' (P=0.034) were higher in the dexamethasone group. CONCLUSIONS: Dexamethasone does not increase the risk of chronic postsurgical pain after major noncardiac surgery. CLINICAL TRIAL REGISTRATION: Open Science Framework Registration DOI https://doi.org/10.17605/OSF.IO/ZDVB5.
Subject(s)
Chronic Pain , Dexamethasone , Intraoperative Care , Pain, Postoperative , Propensity Score , Humans , Dexamethasone/therapeutic use , Dexamethasone/administration & dosage , Pain, Postoperative/drug therapy , Pain, Postoperative/prevention & control , Chronic Pain/drug therapy , Male , Female , Middle Aged , Aged , Intraoperative Care/methods , IncidenceABSTRACT
This article introduces the 'staircase' design, derived from the zigzag pattern of steps along the diagonal of a stepped wedge design schematic where clusters switch from control to intervention conditions. Unlike a complete stepped wedge design where all participating clusters must collect and provide data for the entire trial duration, clusters in a staircase design are only required to be involved and collect data for a limited number of pre- and post-switch periods. This could alleviate some of the burden on participating clusters, encouraging involvement in the trial and reducing the likelihood of attrition. Staircase designs are already being implemented, although in the absence of a dedicated methodology, approaches to sample size and power calculations have been inconsistent. We provide expressions for the variance of the treatment effect estimator when a linear mixed model for an outcome is assumed for the analysis of staircase designs in order to enable appropriate sample size and power calculations. These include explicit variance expressions for basic staircase designs with one pre- and one post-switch measurement period. We show how the variance of the treatment effect estimator is related to key design parameters and demonstrate power calculations for examples based on a real trial.
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Randomized Controlled Trials as Topic , Research Design , Cluster Analysis , Linear Models , Probability , Sample SizeABSTRACT
Host shifts to new plant species can drive speciation for plant-feeding insects, but how commonly do host shifts also drive diversification for the parasites of those same insects? Oak gall wasps induce galls on oak trees and shifts to novel tree hosts and new tree organs have been implicated as drivers of oak gall wasp speciation. Gall wasps are themselves attacked by many insect parasites, which must find their hosts on the correct tree species and organ, but also must navigate the morphologically variable galls with which they interact. Thus, we ask whether host shifts to new trees, organs, or gall morphologies correlate with gall parasite diversification. We delimit species and infer phylogenies for two genera of gall kleptoparasites, Synergus and Ceroptres, reared from a variety of North American oak galls. We find that most species were reared from galls induced by just one gall wasp species, and no parasite species was reared from galls of more than four species. Most kleptoparasite divergence events correlate with shifts to non-ancestral galls. These shifts often involved changes in tree habitat, gall location, and gall morphology. Host shifts are thus implicated in driving diversification for both oak gall wasps and their kleptoparasitic associates.
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Quercus , Wasps , Animals , Wasps/genetics , Trees , Phylogeny , EcosystemABSTRACT
Uncertainty relations are core to both classical and quantum physics, and lend themselves to tests across many degrees of freedom, with structured light emerging as a vibrant tool to harness these degrees of freedom. Here, we test Popper's conjecture by replacing the traditional spatial and momentum states with angular position and orbital angular momentum (OAM) states of photons, showing that the OAM spectrum for an entangled photon passing through a virtual slit differs from that of a photon passing through a physical slit. To achieve this, we produce two OAM entangled photons, one of which is sent to a slit encoded as a digital hologram, thereby localising its angular position, all the while measuring the OAM of the other. We show that the measured OAM spectrum is limited to that of the initial SPDC photons, independent of the OAM encoded into the slit, consistent with Popper's viewpoint. Our approach allows us to overcome prior limitations imposed by physical slits and linear momentum, and offers a versatile toolbox for further probes of quantum systems.
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Information exchange between two distant parties, where information is shared without physically transporting it, is a crucial resource in future quantum networks. Doing so with high-dimensional states offers the promise of higher information capacity and improved resilience to noise, but progress to date has been limited. Here we demonstrate how a nonlinear parametric process allows for arbitrary high-dimensional state projections in the spatial degree of freedom, where a strong coherent field enhances the probability of the process. This allows us to experimentally realise quantum transport of high-dimensional spatial information facilitated by a quantum channel with a single entangled pair and a nonlinear spatial mode detector. Using sum frequency generation we upconvert one of the photons from an entangled pair resulting in high-dimensional spatial information transported to the other. We realise a d = 15 quantum channel for arbitrary photonic spatial modes which we demonstrate by faithfully transferring information encoded into orbital angular momentum, Hermite-Gaussian and arbitrary spatial mode superpositions, without requiring knowledge of the state to be sent. Our demonstration merges the nascent fields of nonlinear control of structured light with quantum processes, offering a new approach to harnessing high-dimensional quantum states, and may be extended to other degrees of freedom too.
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Background: Clinical research in perioperative medicine requires the perspectives of patients and caregivers to increase its relevance and quality, benefiting both researchers and the community. Identifying these priorities will enable researchers, funders, and governing bodies to efficiently use scarce funding and resources. We aim to identify the top 10 research priorities in perioperative medical research in Australia. Methods: A mixed-methods, exploratory-sequential design will be conducted. The study will include five phases. Initially, a published open-ended survey gathered responses from the population (researchers, healthcare workers, and consumers) regarding uncertainties/questions relevant to the population about perioperative medical research. We collected 544 questions and quantitatively analysed and grouped them according to the Standardised Endpoints in Perioperative Medicine-Core Outcomes Measures in Perioperative and Anaesthetic Care (StEP-COMPAC) endpoints. Using multicriteria decision-making software, workshops combining the population will be conducted to determine the top 10 priorities for perioperative medicine research for the Australian population. Ethics and dissemination: Ethical approval to conduct the study was obtained from the Alfred Health (Australia) Human Research Ethics Committee (ID: 171/19). The findings will be disseminated in peer review publications, conferences, and dissemination across perioperative research networks. The top 10 priorities will be available to inform research funders, grant submissions, guidelines, and the population.