Bayesian data analysis for newcomers

The relationship between radiological OA severity or body weight and outcomes following a structured education and exercise therapy program (GLA:D®) for people with knee osteoarthritis

BACKGROUND

Clinicians may presume people with higher bodyweight or greater OA severity do not respond to exercise therapy for knee osteoarthritis (OA), but few studies have examined this.

OBJECTIVE

To examine the relationship between radiographical OA severity or bodyweight and pain and functional outcomes following a structured education and exercise therapy program (Good Life with OsteoArthritis from Denmark: GLA:D®).

METHODS

33 participants with knee OA were assessed at baseline and week 8 following GLA:D®. Outcomes were pain (Visual analogue scale (VAS) 0-100), Knee Injury and Osteoarthritis Outcome Score-12 (KOOS-12 total), 40 m-fast-paced walk and 30-s chair stand. Multilevel models were used to define the severity of OA in medial, lateral and patellofemoral compartments using the Kellgren-Lawrence (KL) system and to examine the relationship between compartment severity, bodyweight and outcomes.

RESULTS

No meaningful relationships between bodyweight and response to GLA:D® were found for any outcome measures. Greater medial OA compartment severity was related to less improvement in pain, KOOS-12 and chair stand repetitions. However, all levels of lateral compartment severity had similar improvements, and greater patellofemoral compartment severity was related to more improvement for KOOS-12 and pain.

CONCLUSION

Bodyweight may have little influence on a person's response to a structured education and exercise therapy program. While people with greater medial compartment severity were less likely to improve following the program, OA severity in the PF and lateral compartments was not a barrier to improvement.

The "good is up" metaphoric effects on recognition: True for source guessing but false for item memory

The "good is up" metaphor, which links valence and verticality was found to influence affective judgement and to direct attention, but its effects on memory remain unclear with contradictory research findings. To provide a more accurate assessment of memory components involved in recognition, such as item memory and source-guessing biases, a standard source monitoring paradigm was applied in this research. A series of three experiments provided a conceptual replication and extension of Experiment 2 by Crawford et al., (2014) and yielded a consistent result pattern suggesting that the "good is up" metaphor biases participants' guessing of source location. That is, when source memory failed, participants were more inclined to guess the "up" location versus "down" location for positive items (and vice versa for negative items). It did, however, not affect source memory or item memory for valenced stimuli learned from metaphor-congruent versus incongruent locations (i.e., no metaphor-(in)congruent effects in memory). We suggest that the "good is up" metaphor may affect cognitive processes in a more subtle way than originally suggested.

The impact of subtle contextual information on remembering to complete academic goals

Remembering to complete goals-termed prospective memory (PM)-is critical for success in everyday life, yet minimal empirical work has been dedicated to examining PM within an educational setting. The main goal of this study was to investigate students' ability to complete numerous future-oriented academic intentions (PM tasks) while simultaneously paying attention to a lecture and to see if working memory (WM) capacity and adding subtle contextual information would support the students' likelihood of completing their PM tasks. Participants took part in a 2-hr session of college course-like activities. Throughout the session, there was occasionally the opportunity to complete one of several naturalistic PM tasks. The following findings are based on the results of our Bayesian models. Providing subtle contextual clues about when PM tasks could be completed was found to likely increase performance. The number of PM intentions to be remembered (i.e., load) produced no discernable effect on ongoing task performance or PM performance. Furthermore, individual differences in WM capacity were likely to be predictive of a near-zero change in PM performance. The current findings hold meaningful implications for educators, wherein providing context, even at a subtle level, can enhance students' ability to remember to complete tasks, without altering their ability to focus on the tasks at hand. Moreover, it appears that asking students to remember to complete multiple, prospective in-class tasks is not likely to hinder task completion or their ability to focus on other ongoing tasks.

Data-driven prior elicitation for Bayes factors in Cox regression for nine subfields in biomedicine

Biomedical research often utilizes Cox regression for the analysis of time-to-event data. The pervasive use of frequentist inference for these analyses implicates that the evidence for or against the presence (or absence) of an effect cannot be directly compared and that researchers must adhere to a predefined sampling plan. As an alternative, the use of Bayes factors improves upon these limitations, which is especially important for costly and time-consuming biomedical studies. However, Bayes factors involve their own difficulty of specifying priors for the parameters of the statistical model. In this article, we develop data-driven priors centered around zero for Cox regression tailored to nine subfields in biomedicine. To this end, we extracted hazard ratios and associated [Formula: see text] confidence intervals from the abstracts of large corpora of already existing studies within the nine biomedical subfields. We used these extracted data to inform priors for the nine subfields. All of our suggested priors are Normal distributions with means of 0 and standard deviations closely scattered around 1. We propose that researchers use these priors as reasonable starting points for their analyses.

A systematic analysis on global epidemiology and burden of foot fracture over three decades

PURPOSE

To comprehensively analyze the geographic and temporal trends of foot fracture, understand its health burden by age, sex, and sociodemographic index (SDI), and explore its leading causes from 1990 to 2019.

METHODS

The datasets in the present study were generated from the Global Burden of Diseases Study 2019, which included foot fracture data from 1990 to 2019. We extracted estimates along with the 95% uncertainty interval (UI) for the incidence and years lived with disability (YLDs) of foot fracture by location, age, gender, and cause. The epidemiology and burden of foot fracture at the global, regional, and national level was exhibited. Next, we presented the age and sex patterns of foot fracture. The leading cause of foot fracture was another focus of this study from the viewpoint of age, sex, and location. Then, Pearson's correlations between age-standardized rate (ASR), SDI, and estimated annual percentage change were calculated.

RESULTS

The age-standardized incidence rate was 138.68 (95% UI: 104.88 - 182.53) per 100,000 persons for both sexes, 174.24 (95% UI: 134.35 - 222.49) per 100,000 persons for males, and 102.19 (95% UI: 73.28 - 138.00) per 100,000 persons for females in 2019. The age-standardized YLDs rate was 5.91 (95% UI: 3.58 - 9.25) per 100,000 persons for both genders, 7.35 (95% UI: 4.45 - 11.50) per 100,000 persons for males, and 4.51 (95% UI: 2.75 - 7.03) per 100,000 persons for females in 2019. The global incidence and YLDs of foot fracture increased in number and decreased in ASR from 1990 to 2019. The global geographical distribution of foot fracture is uneven. The incidence rate for males peaked at the age group of 20 - 24 years, while that for females increased with advancing age. The incidence rate of older people was rising, as younger age incidence rate declined from 1990 to 2019. Falls, exposure to mechanical forces, and road traffic injuries were the 3 leading causes of foot fracture. Correlations were observed between ASR, estimated annual percentage change, and SDI.

CONCLUSIONS

The burden of foot fracture remains high globally, and it poses an enormous public health challenge, with population aging. It is necessary to allocate more resources to the high-risk populations. Targeted realistic intervention policies and strategies are warranted.

Brain oxygenation monitoring during neonatal stabilization and resuscitation and its potential for improving preterm infant outcomes: a systematic review and meta-analysis with Bayesian analysis

Neonatal stabilization and resuscitation in preterm infants are critical interventions. Cerebral tissue oxygen saturation (CrSO2) measured with near-infrared spectroscopy monitoring offers potential benefits by providing real-time information on brain oxygenation. This systematic review aimed to determine if CrSO2-monitoring to guide neonatal resuscitation after birth can improve survival without cerebral injury. A systematic search of MEDLINE, Google Scholar, EMBASE, the Cumulative Index of Nursing and Allied Health Literature, Clinical Trials.gov, and the Cochrane Central Register of Controlled Trials was performed through December 2024. We included only human studies that investigated CrSO2-guided interventions during neonatal resuscitation after birth in preterm infants. A meta-analysis was performed using individual patient data and the Bayesian method. The main outcome assessed was survival without cerebral injury (Study registration:PROSPERO CRD42024512148). Two studies were identified, including a total of 667 preterm infants with less than 34 weeks of gestation, describing CrSO2-guided interventions during neonatal resuscitation. The meta-analysis revealed a high probability of treatment superiority for NIRS-guided interventions that demonstrated improved outcomes compared to standard care, with a 4.5% increase in the rate of survival without cerebral injury (93% probability) and 4.2% reduction of IVH of any grade (94% probability). The risk of bias can be described as low.

CONCLUSION

This meta-analysis suggests that CrSO2-guided interventions may offer a meaningful advantage in preterm infant resuscitation after birth, improving survival without brain injury. The analysis indicates a high probability of a clinically important benefit. This warrants consideration in clinical practice.

WHAT IS KNOWN

• Studies have shown that near-infrared spectroscopy can monitor brain oxygenation in preterm infants immediately after birth.

WHAT IS NEW

• This is the first meta-analysis to examine the impact of near-infrared spectroscopy based interventions on neonatal resuscitation outcomes. • Interventions based on monitoring preterm infants' cerebral oxygenation may improve their chances of surviving without severe brain injury, compared to standard care.

Comparative Effectiveness of Active and Reactive Mattresses in Pressure Injury Healing for Older People in Their Own Homes: A Pragmatic Equivalence Randomised-Controlled Study

Background: Pressure injuries are an ongoing problem commonly managed with the prescription of pressure mattresses. There is conflicting research about the comparable effectiveness of the two types of pressure mattresses, active and reactive. This, coupled with technological advances and an updated understanding of pressure aetiology, means decision-making when prescribing pressure mattresses is complicated. Objective/Design: A pragmatic approach was used to design an equivalence randomised-controlled trial investigating the comparative effectiveness of active and reactive pressure mattresses in a community setting from a wound healing perspective as well as from a user acceptability perspective. Methods: Participants with an existing pressure injury were provided with an active or reactive mattress for wound healing, with wound stages assessed using photography. Usual clinical care was provided based on the protocols of the health care service, including nursing and occupational therapy input. Participants were monitored for the healing of their existing pressure injuries, using the Revised Photographic Wound Assessment Tool. User acceptability feedback was provided through surveys, including impact on comfort, pain levels and bed mobility. An equivalence design was used for data analysis to determine if the surfaces were comparable. Results: Twelve participants completed the study, which found that people on active mattresses healed 11.71 days (95% CI -55.97-31.78 days) quicker than people on reactive mattresses; however, the small sample size meant that a definitive determination could not be made. Users found bed mobility more challenging, and pain levels decreased, regardless of mattress type. Conclusions: A pragmatic methodology is imperative for research in this field due to the complexity of pressure injury healing. Researchers exploring multi-faceted conditions should consider a pragmatic design to ensure transferability of results to the clinical setting. The results from this study were inconclusive when determining the equivalence of active and reactive mattresses due to the small sample size. When choosing a mattress, prescribers need to consider user preferences and mattress features to ensure user acceptability.

Assessing the effectiveness of metaHelper: a randomized controlled trial of a web application for statistical transformations in meta-analysis

OBJECTIVES

To test whether the use of a web application (www.metaHelper.eu) can reduce errors and time needed for statistical transformations commonly performed for meta-analysis.

STUDY DESIGN AND SETTING

We developed an R package and a corresponding web application to streamline statistical transformations in meta-analysis. A parallel randomized controlled trial following the Consolidated Standards of Reporting Trials guidelines was conducted. The trial was preregistered, and ethical approval was obtained from the University of Krems' ethics committee. We conducted a parallel randomized controlled trial with 26 participants, including researchers and students with varying levels of statistical expertise. Participants performed six statistical calculations commonly used in meta-analysis: computing pooled standard deviations, converting standard errors, and calculating standardized mean differences for both 2-group and 3-arm studies. Performance was evaluated based on accuracy and time taken to complete each task. A Bayesian mixed-effects model was used to analyze the results. Participants were randomly assigned to either the experimental group (metaHelper) or the control group (allowed to use internet sources, the Cochrane Handbook, or any other sources chosen by the participant).

RESULTS

Main outcomes were correctness of calculations and time taken to complete tasks. The metaHelper group had a higher probability of providing correct answers (85%) compared to the control group (31%). Additionally, the metaHelper group completed an average of 133 seconds per task faster (95% credibility interval: 83-180).

CONCLUSION

MetaHelper effectively enhances the accuracy and efficiency of statistical transformations required for meta-analysis.

PLAIN LANGUAGE SUMMARY

Meta-analysis, a method for combining research results, often requires researchers to transform statistical data, like converting standard errors to standard deviations. These transformations are critical can be prone to errors, especially when done manually or with limited guidance. To address this, we developed metaHelper (www.metahelper.eu), a user-friendly web application and R package designed to assist researchers with these calculations. In our study, we conducted a randomized controlled trial to compare metaHelper with traditional methods like handbook instructions and freely available online tools (whatever our participants wanted to use). Twenty-six researchers and students participated, performing 6 common statistical calculations. We measured their accuracy and the time they took to complete each task. Results statistical model: Probability of achieving a correct answer. Results statistical model: Average time needed per task for both groups.

Daily and Half-yearly Associations between Boundary Diffusion and Parent-adolescent Relationship Quality after Divorce

Boundary diffusion is a particular risk after divorce and has been associated with adolescents' adjustment problems. Yet, its potential impact on parent-adolescent relationship quality is less straightforward, as previous findings support both an alienation and conflict perspective. Therefore these associations (daily and half-yearly) were examined in recently divorced families, addressing both within-dyad changes and between-dyad differences. Data were collected among a sample of N = 133 (pre)adolescents (Mage = 11.76; 51.5% boys) from 76 divorced families, using a measurement burst design: Every six months, 14 consecutive days of daily diaries were collected, for 5 waves. Between dyads, adolescents who experienced more boundary diffusion than others, also reported more conflict with both their parents. Within dyads, when adolescents experienced more boundary diffusion than usual by one of their parents (actor), warmth decreased and conflict increased between this parent and the adolescent, that same and the following day. Adolescents also engaged in more conflict with the other parent that day. These findings mostly supported the conflict perspective: Post-divorce boundary diffusion appears to be a general risk factor for parent-adolescent conflict with both parents, and from day-to-day boundary diffusion was linked to a deteriorated parent-adolescent relationship quality, especially with the parent that triangulated or parentified them. There were no significant long-term associations, nor did any moderator (age, gender, living arrangement) explain heterogeneity in effects.

The importance of change communication and state motivation when adapting to changes

Employees often work in dynamic environments requiring adaptive performance (e.g., emergencies, clients from other cultures). To optimize change management, employee training, and personnel selection in organizations, researchers have focused on trait-like predictors of adaption to change, such as personality traits or cognitive ability. The study (N = 300) shifts the focus to more proximal performance predictors - change communication and task-related state motivation. Adaptive performance was modeled using latent growth models. Providing two change-related hints, one at the beginning of the task and another directly after the change, mitigated performance impairment observed directly after the change. Moreover, this advantage largely persisted throughout the later stages of the task. In contrast, a single hint at the beginning of the task did not substantially facilitate adaption. Finally, task-related state motivation was linked to better performance on the subsequent measurement occasion. Organizations might minimize change-induced losses by deploying adequate change communication and maintaining employee motivation.

Focus on Opportunities and Adaptive Performance: The Importance of Distinguishing Between Subjective and Objective Performance Measures

People who perceive more opportunities in their occupational future often report better well-being and motivation. A positive correlation with performance has also been reported, but until now, only the relationship with two broad performance dimensions, task and contextual performance, has been examined extensively. Furthermore, performance ratings often rely on self-reports, which can be biased. The present study (N = 258) helps close these research gaps. First, it examines the relationship between focus on opportunities and a specific performance facet (i.e., adaptive performance). Second, performance is assessed both subjectively and objectively. The distinction proved critical. After adjusting for education, focus on opportunities was related to self-reported adaption to change, but there was no substantial evidence that focus on opportunities promotes objective adaptive performance. Thus, it cannot yet be recommended to use focus on opportunities in organizational and educational contexts for selecting and training highly adaptable employees or students.

Concentration toward the mode: Estimating changes in the shape of a distribution of student data

When making comparisons between groups of students, a common technique is to analyze whether there are statistically significant differences between the means of each group. This convention, however, is problematic when data are negatively skewed and bounded against a performance ceiling, features that are typical of data in education settings. In such a situation, we might be particularly interested to observe group differences in the left tail, specifically among students who have room to improve, and conventional analyses of group means have limitations for detecting such differences. In this article, an alternative to these conventions is presented. Rather than comparing the means of two groups, we can instead compare how closely student data are concentrated toward the modes of each group. Bayesian methods provide an ideal framework for this kind of analysis because they enable us to make flexible comparisons between parameter estimates in custom analytical models. A Bayesian approach for examining concentration toward the mode is outlined and then demonstrated using public data from a previously reported classroom experiment. Using only the outcome data from this prior experiment, the proposed method observes a credible difference in concentration between groups, whereas conventional tests show no significant overall differences between group means. The present article underscores the limitations of conventional statistical assumptions and hypotheses, especially in school psychology and related fields, and offers a method for making more flexible comparisons in the concentration of data between groups.

Prediction of methylphenidate treatment response for ADHD using conventional and radiomics T1 and DTI features: Secondary analysis of a randomized clinical trial

BACKGROUND

Attention-Deficit/Hyperactivity Disorder (ADHD) is commonly treated with methylphenidate (MPH). Although highly effective, MPH treatment still has a relatively high non-response rate of around 30%, highlighting the need for a better understanding of treatment response. Radiomics of T1-weighted images and Diffusion Tensor Imaging (DTI) combined with machine learning approaches could offer a novel method for assessing MPH treatment response.

PURPOSE

To evaluate the accuracy of both conventional and radiomics approaches in predicting treatment response based on baseline T1 and DTI data in stimulant-naive ADHD participants.

METHODS

We performed a secondary analysis of a randomized clinical trial (ePOD-MPH), involving 47 stimulant-naive ADHD participants (23 boys aged 11.4 ± 0.4 years, 24 men aged 28.1 ± 4.3 years) who underwent 16 weeks of treatment with MPH. Baseline T1-weighted and DTI MRI scans were acquired. Treatment response was assessed at 8 weeks (during treatment) and one week after cessation of 16-week treatment (post-treatment) using the Clinical Global Impressions - Improvement scale as our primary outcome. We compared prediction accuracy using a conventional model and a radiomics model. The conventional approach included the volume of bilateral caudate, putamen, pallidum, accumbens, and hippocampus, and for DTI the mean fractional anisotropy (FA) of the entire brain white matter, bilateral Anterior Thalamic Radiation (ATR), and the splenium of the corpus callosum, totaling 14 regional features. For the radiomics approach, 380 features (shape-based and first-order statistics) were extracted from these 14 regions. XGBoost models with nested cross-validation were used and constructed for the total cohort (n = 47), as well as children (n = 23) and adults (n = 24) separately. Exact binomial tests were employed to compare model performance.

RESULTS

For the conventional model, balanced accuracy (bAcc) in predicting treatment response during treatment was 63 % for the total cohort, 32 % for children, and 36 % for adults (Area Under the Receiver Operating Characteristic Curve (AUC-ROC): 0.69, 0.33, 0.41 respectively). Radiomics models demonstrated bAcc's of 68 %, 64 %, and 64 % during treatment (AUC-ROCs of 0.73, 0.62, 0.69 respectively). These predictions were better than chance for both conventional and radiomics models in the total cohort (p = 0.04, p = 0.003 respectively). The radiomics models outperformed the conventional models during treatment in children only (p = 0.02). At post-treatment, performance was markedly reduced.

CONCLUSION

While conventional and radiomics models performed equally well in predicting clinical improvement across children and adults during treatment, radiomics features offered enhanced structural information beyond conventional region-based volume and FA averages in children. Prediction of symptom improvement one week after treatment cessation was poor, potentially due to the transient effects of stimulant treatment on symptom improvement.

Using Bayesian Hypothesis-testing to Reanalyze Randomized Controlled Trials: Does it Always Tell the Truth, the Whole Truth and Nothing but the Truth?

Adequately powered randomized controlled trials (RCTs) are considered the highest level of evidence in guiding clinical practice. Reports using Bayesian hypothesis-testing to reanalyze RCTs are increasing. One distinct advantage of Bayesian analysis is that we can obtain a range of numerical probabilities that reflect how likely a study intervention is more effective than the alternative after considering both pre-existing available evidence and the alternate hypotheses. A recent analysis of critical care trials showed that some trials with an indeterminate result according to the frequentist analysis could have a high probability of being effective when reinterpreted by Bayesian analysis. In this perspective article, we will discuss the caveats in interpreting the results of Bayesian reanalysis of RCTs before we change clinical practice. When overoptimistic hypothesis prior probabilities are used, it carries a risk to translate noises into false signals. Using Bayes factors (BFs) to quantify evidence contained in data (by the ratio of the probability of data under each hypothesis) is thus more preferable than using a single prior probability, such that the BF approach becomes the mainstream in Bayesian hypothesis-testing. Still, BFs are dependent on the prior parameter distributions; comparing different hypotheses would invariably result in different results.

How to cite this article

Ho KM, Lee A. Using Bayesian Hypothesis-testing to Reanalyze Randomized Controlled Trials: Does it Always Tell the Truth, the Whole Truth and Nothing but the Truth? Indian J Crit Care Med 2024;28(11):1005-1008.

Unravelling the object-based nature of visual working memory: insight from pointers

Visual working memory (VWM) plays a crucial role in temporarily storing and processing visual information, but the nature of stored representations and their interaction with new inputs has long been unclear. The pointer system refers to how VWM links new sensory inputs to stored information using specific cues. This study aimed to investigate whether the pointer system is based on spatial, feature-based, or object-based cues by employing the repetition benefit effect, where memory performance improves with repeated memory items. Across three experiments, we manipulated spatial positions, shapes, and colors as pointer cues to determine how these features affect VWM consolidation and updating. The results showed that while spatial location serves as a strong pointer cue, shape and color features can also effectively reestablish object correspondence in VWM. These findings support the view that the pointer system in VWM is flexible and object-based, utilizing various feature cues to maintain memory continuity. This study provides new insights into how VWM connects new inputs with stored information through the pointer system.

Beyond 'statistical significance': A nontechnical primer of Bayesian statistics and Bayes factors for health researchers

RATIONALE

Hypothesis testing is integral to health research and is commonly completed through frequentist statistics focused on computing p values. p Values have been long criticized for offering limited information about the relationship of variables and strength of evidence concerning the plausibility, presence and certainty of associations among variables. Bayesian statistics is a potential alternative for inference-making. Despite emerging discussion on Bayesian statistics across various disciplines, the uptake of Bayesian statistics in health research is still limited.

AIM

To offer a primer on Bayesian statistics and Bayes factors for health researchers to gain preliminary knowledge of its use, application and interpretation in health research.

METHODS

Theoretical and empirical literature on Bayesian statistics and methods were used to develop this methodological primer.

CONCLUSIONS

Using Bayesian statistics in health research without a careful and complete understanding of its underlying philosophy and differences from frequentist testing, estimation and interpretation methods can result in similar ritualistic use as done for p values.

IMPLICATIONS

Health researchers should supplement frequentists statistics with Bayesian statistics when analysing research data. The overreliance on p values for clinical decisions making should be avoided. Bayes factors offer a more intuitive measure of assessing the strength of evidence for null and alternative hypothesis.

A longitudinal study of the probability of developing malocclusion in children using a Bayesian analysis

INTRODUCTION

This study evaluated the probability of developing malocclusions in mixed dentition.

METHODS

A longitudinal study was conducted with 598 children (aged 5 years) in deciduous dentition. The children were followed for 3 years until mixed dentition (aged 8 years). Overjet, overbite, and transversal relations were evaluated. Bayesian models were used to analyze the data and estimate the parameters.

RESULTS

The parameter θ was used for the distributions, indicating the probability of presenting a given condition with a credibility index (ICr) of 95%. After 3 years of follow-up, 121 children were reevaluated. The results showed that children have a high probability of malocclusion in mixed dentition. There was a higher probability of developing an increased overjet in the mixed dentition of 20.5% (ICr 95%, 13.6-28.4) to 48.3% (ICr 95%, 39.1-57.7) and a higher probability of having a normal overbite in the deciduous dentition and a lower probability in the mixed dentition (ICr 95%, 9.2-21.3).

CONCLUSIONS

Considering the probabilistic model of Bayesian analysis, children with normal overjet in the deciduous dentition may show an increased overjet in the mixed dentition. Concerning overbite, children may present an anterior open bite during the transition between deciduous and mixed dentition, as well as self-correction of deep overbite in mixed dentition. Furthermore, they may present a posterior crossbite during the mixed dentition when there is a normal transverse relationship in the deciduous dentition.

Nicotinic acid improves mitochondrial function and associated transcriptional pathways in older inactive males

Objectives

To examine the effect of the NAD+ precursor, nicotinic acid (NA), for improving skeletal muscle status in sedentary older people.

Methods

In a double-blind, randomised, placebo-controlled design, 18 sedentary yet otherwise healthy older (65-75 y) males were assigned to 2-weeks of NA (acipimox; 250 mg × 3 daily, n=8) or placebo (PLA, n=10) supplementation. At baseline, and after week 1 and week 2 of supplementation, a battery of functional, metabolic, and molecular readouts were measured.

Results

Resting and submaximal respiratory exchange ratio was lower (p<0.05) after 2 weeks in the NA group only, but maximal aerobic and anaerobic function and glucose handling were unchanged (p>0.05). Bayesian statistical modelling identified that leak, maximal coupled and maximal uncoupled mitochondrial respiratory states, increased over the 2-week supplemental period in the NA group (probability for a positive change (pd) 85.2, 90.8 and 95.9 %, respectively) but not in PLA. Citrate synthase and protein content of complex II (SDHB) and V (ATP5A) electron transport chain (ETC) components increased over the 2-week period in the NA group only (pd 95.1, 74.5 and 82.3 %, respectively). Mitochondrial and myofibrillar protein synthetic rates remained unchanged in both groups. NA intake altered the muscle transcriptome by increasing the expression of gene pathways related to cell adhesion/cytoskeleton organisation and inflammation/immunity and decreasing pathway expression of ETC and aerobic respiration processes. NAD+-specific pathways (e.g., de novo NAD+ biosynthetic processes) and genes (e.g., NADSYN1) were uniquely regulated by NA.

Conclusions

NA might be an effective strategy for improving ageing muscle mitochondrial health.

Dissecting glial scar formation by spatial point pattern and topological data analysis

Glial scar formation represents a fundamental response to central nervous system (CNS) injuries. It is mainly characterized by a well-defined spatial rearrangement of reactive astrocytes and microglia. The mechanisms underlying glial scar formation have been extensively studied, yet quantitative descriptors of the spatial arrangement of reactive glial cells remain limited. Here, we present a novel approach using point pattern analysis (PPA) and topological data analysis (TDA) to quantify spatial patterns of reactive glial cells after experimental ischemic stroke in mice. We provide open and reproducible tools using R and Julia to quantify spatial intensity, cell covariance and conditional distribution, cell-to-cell interactions, and short/long-scale arrangement, which collectively disentangle the arrangement patterns of the glial scar. This approach unravels a substantial divergence in the distribution of GFAP+ and IBA1+ cells after injury that conventional analysis methods cannot fully characterize. PPA and TDA are valuable tools for studying the complex spatial arrangement of reactive glia and other nervous cells following CNS injuries and have potential applications for evaluating glial-targeted restorative therapies.

Artificial intelligence and machine learning: Definition of terms and current concepts in critical care research

With increasing computing power, artificial intelligence (AI) and machine learning (ML) have prospered, which facilitate the analysis of large datasets, especially those found in critical care. It is important to define these terminologies, to inform a standardized approach to critical care research. This manuscript hopes to clarify these terms with examples from medical literature. Three major components that are required for a successful ML implementation: (i) reliable dataset, (ii) ML algorithm, and (iii) unbiased model evaluation, are discussed. A reliable dataset can be structured or unstructured with limited noise, outliers, and missing values. ML, a subset of AI, is typically focused on supervised or unsupervised learning tasks in which the output is based on inputs and derived from iterative pattern recognition algorithms, while AI is the overall ability of a machine to "think" or mimic human behavior; and to analyze data free from human influence. Even with successful implementation, advanced AI and ML algorithms have faced challenges in adoption into practice, mainly due to their lack of interpretability, which hinders trust, buy-in, and engagement from clinicians. Consequently, traditional algorithms, such as linear and logistic regression, that may have reduced predictive power but are highly interpretable, continue to be widely used.

No evidence that belief in conspiracy theories is negatively related to attitudes toward transhumanism

Transhumanism is a movement that emphasizes the improvement of the human condition by developing technologies and making them widely available. Conspiracy theories regularly refer to the allegedly transhumanist agenda of elites. We hypothesized that belief in conspiracy theories would be related to more unfavorable attitudes toward the transhumanist movement. We examined this association through two pre-registered studies (based on two French samples, total N after exclusion = 550). We found no evidence of a negative relationship between belief in conspiracy theories and attitudes toward transhumanism. This null result was further corroborated by Bayesian analysis, an equivalence test, and an internal mini meta-analysis. This work plays a precursory role in understanding attitudes toward an international cultural and intellectual movement that continues to grow in popularity and influence.

Effectiveness and Safety of Measures to Prevent Infections and Other Complications Associated With Peripheral Intravenous Catheters: A Systematic Review and Meta-analysis

BACKGROUND

Peripheral intravenous catheters (PIVCs) contribute substantially to the global burden of infections. This systematic review assessed 24 infection prevention and control (IPC) interventions to prevent PIVC-associated infections and other complications.

METHODS

We searched Ovid MEDLINE, Embase, Cochrane Library, WHO Global Index Medicus, CINAHL, and reference lists for controlled studies from 1 January 1980-16 March 2023. We dually selected studies, assessed risk of bias, extracted data, and rated the certainty of evidence (COE). For outcomes with 3 or more trials, we conducted Bayesian random-effects meta-analyses.

RESULTS

105 studies met our prespecified eligibility criteria, addressing 16 of the 24 research questions; no studies were identified for 8 research questions. Based on findings of low to high COE, wearing gloves reduced the risk of overall adverse events related to insertion compared with no gloves (1 non-randomized controlled trial [non-RCT]; adjusted risk ratio [RR], .52; 95% CI, .33-.85), and catheter removal based on defined schedules potentially resulted in a lower phlebitis/thrombophlebitis incidence (10 RCTs; RR, 0.74, 95% credible interval, .49-1.01) compared with clinically indicated removal in adults. In neonates, chlorhexidine reduced the phlebitis score compared with non-chlorhexidine-containing disinfection (1 RCT; 0.14 vs 0.68; P = .003). No statistically significant differences were found for other measures.

CONCLUSIONS

Despite their frequent use and concern about PIVC-associated complications, this review underscores the urgent need for more high-quality studies on effective IPC methods regarding safe PIVC management. In the absence of valid evidence, adherence to standard precaution measures and documentation remain the most important principles to curb PIVC complications.

CLINICAL TRIALS REGISTRATION

The protocol was registered in the Open Science Framework (https://osf.io/exdb4).

A 5-Year Analysis of Age, Stature and Armspan in Mixed Martial Arts

Purpose: Athlete stature and armspan is anecdotally assumed to provide an advantage in mixed martial arts (MMA), despite an absence of supporting data. In contrast, winners of MMA bouts have been shown to be younger than bouts losers. Whilst absolute measurements of stature, armspan and armspan:stature scale (A:S) have been shown to not distinguish between winners and losers of MMA bouts, relative differences between competitors have not been analysed. This study aimed to analyse 5 years of athlete age and morphological data to replicate and expand previous studies to determine whether absolute and/or relative age and morphological variables effect winning and losing in MMA. Methods and Results: Bayes factor (BF>3) inferential analyses conducted on the cohort overall (n = 2,229 professional bouts), each year sampled and each individual body mass division found that only absolute (winners = 29.8 ± 4 years; losers = 30.7 ± 4.2 years) and relative age (winners = 0.82 ± 5.3 years younger than losers) differentiates between winners and losers across the whole cohort, in 4 of the 5 years, and in 4 of the 13 divisions sampled. Armspan appears to provide an advantage in heavyweight only (winners = 198.4 ± 6.6cm; losers = 196.1 ± 7.7cm), with greater A:S being a disadvantage (winners = 1.003 ± 0.022cm∙cm-1; losers = 1.010 ± 0.023 cm∙cm-1) in women's strawweight only. No variables had any effect on how bouts were won. Conclusions: These results confirm previous reports that the effect of athlete morphology is greatly overstated in MMA, appearing to be irrelevant in most divisions. Bout winners tend to be younger than losers, particularly in divisions displaying more diverse skill requirements.

Longitudinal Meta-Analysis of Peak Height Velocity in Young Female Athletes

Growth patterns and biological milestones in youth sports are key to interpreting the development of young athletes. However, there is no analysis of longitudinal meta-analysis describing the growth of young female athletes. This longitudinal meta-analysis estimated growth curves and age at peak height velocity (PHV) in young female athletes based on anthropometric data from longitudinal studies found in the literature. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, studies with repeated measurements in young female athletes were identified from searches of four databases (MEDLINE, Web of Science, SCOPUS, and SPORTDiscus) without date restrictions through August 2023. We adapted our bias assessment criteria using the Cochrane risk of bias tool for randomized controlled trials as a reference. Bayesian multilevel modeling was used to perform a longitudinal meta-analysis to extract stature growth curves and age at PHV. Fourteen studies met our eligibility criteria. Twenty-one independent samples could be included in the analysis. Conditional on the data and models, the predicted mean age at PHV for female athletes was 11.18 years (90% CI: 8.62; 12.94). When studies were aggregated by sport in the models, the models could not capture sport-specific growth curves for stature and estimate a corresponding age at PHV. We provide the first longitudinal meta-analytic summary of pubertal growth and derive age at PHV in young female athletes. The meta-analysis predicted that age at PHV occurs at similar ages to those in the general pediatric population. The data pool was limited in sports and geographic distribution, emphasizing the need to promote longitudinal research in females across different youth sports contexts.

Association Between Betrayal Trauma and the PAI Traumatic Stress Scale

The Personality Assessment Inventory (PAI) is among the most commonly used broadband inventories of psychological functioning. For the purposes of assessing trauma specifically, the most relevant aspect of the PAI is the Traumatic Stress subscale of the Anxiety-Related Disorders scale (ARD-T), which measures the degree to which a person feels wounded by something in their past. Research suggests that ARD-T is associated with exposure to a variety of different traumatic stressors. However, there is little research on the degree to which traumatic stressors that entail a component of interpersonal betrayal (i.e. betrayal trauma) are associated with higher scores on ARD-T relative to other stressors. In this study, we evaluated the relative associations between traumas with varying degrees of betrayal and scores on ARD-T in a secondary analysis of two non-clinical samples (college sample N = 494; crowdsourced sample N = 364) using a Bayesian approach to multiple regression. In both samples, traumas with both high and medium (but not low) degrees of betrayal were associated with elevated ARD-T scores. Findings suggest that ARD-T scores are associated with interpersonal trauma regardless of betrayal, which has implications for interpretation of the ARD-T scale in practice.

Enabling identification of component processes in perceptual learning with nonparametric hierarchical Bayesian modeling

Perceptual learning is a multifaceted process, encompassing general learning, between-session forgetting or consolidation, and within-session fast relearning and deterioration. The learning curve constructed from threshold estimates in blocks or sessions, based on tens or hundreds of trials, may obscure component processes; high temporal resolution is necessary. We developed two nonparametric inference procedures: a Bayesian inference procedure (BIP) to estimate the posterior distribution of contrast threshold in each learning block for each learner independently and a hierarchical Bayesian model (HBM) that computes the joint posterior distribution of contrast threshold across all learning blocks at the population, subject, and test levels via the covariance of contrast thresholds across blocks. We applied the procedures to the data from two studies that investigated the interaction between feedback and training accuracy in Gabor orientation identification over 1920 trials across six sessions and estimated learning curve with block sizes L = 10, 20, 40, 80, 160, and 320 trials. The HBM generated significantly better fits to the data, smaller standard deviations, and more precise estimates, compared to the BIP across all block sizes. In addition, the HBM generated unbiased estimates, whereas the BIP only generated unbiased estimates with large block sizes but exhibited increased bias with small block sizes. With L = 10, 20, and 40, we were able to consistently identify general learning, between-session forgetting, and rapid relearning and adaptation within sessions. The nonparametric HBM provides a general framework for fine-grained assessment of the learning curve and enables identification of component processes in perceptual learning.

Self-truncated sampling produces more moderate covariation judgment and related decision than descriptive frequency information: The role of regressive frequency estimation

Covariation judgment underlies a diversity of psychological theories and influences various everyday decisions. Information about covariation can be learned from either a summary description of frequencies (i.e., contingency tables) or trial-by-trial experience (i.e., sampling individual instances). Two studies were conducted to investigate the impact of information learning mode (i.e., description vs. self-truncated sampling) on covariation judgment and related decision. In each trial under the description condition, participants were presented with a contingency table with explicit cell frequencies, whereas in each trial under the self-truncated sampling condition, participants were allowed to determine when to stop sampling instances and thus the actual sample size. To eliminate sampling error, an other-yoked (i.e., between-subject) design was used in this research so that cell frequencies shown in a trial under the description condition were matched with those experienced in a trial under the self-truncated sampling condition. Experiment 1 showed that the self-truncated sampling condition led to more moderate covariation judgments than the description condition (i.e., a description-experience gap). Experiment 2 demonstrated further that the same gap extended to covariation-related decisions in terms of relative contingent preference (RCP). Regressive frequency estimation under self-truncated sampling appeared to underlie the consistent gaps found in the two studies, whereas the impact of regressive diagnosticity (i.e., the same sample of instances was viewed as less diagnostic under description than under self-truncated sampling) or simultaneous overestimation and underweighting of rare instances under experience was not supported by the observed data. Future research might examine alternative accounts of the observed gaps, such as the impacts of belief updating and stopping rule under self-truncated sampling.

Remotely prescribed and monitored home-based gait-and-balance therapeutic exergaming using augmented reality (AR) glasses: protocol for a clinical feasibility study in people with Parkinson's disease

BACKGROUND

Clinical guidelines for people with Parkinson's disease (pwPD) stress that, complementary to pharmacological treatment, exercise and physiotherapy should be given a central role in disease management. Adhering to regular exercise of the right type, and with high repetition, remains a challenge for pwPD. Exergaming has the potential to increase adherence through play and personalised interventions, both in clinic and at home. Reality DTx® is an augmented-reality (AR) home-based gait-and-balance exergaming intervention specifically designed for pwPD as an extension of supervised physiotherapy. The primary objective of this study is to evaluate the feasibility and potential efficacy of Reality DTx®.

METHODS

Twenty-four pwPD (Hoehn and Yahr stages 2-4) with self-reported gait and/or balance impairments will participate in this study. The study comprises a 6-week waitlist-controlled AR home-based therapeutic gait-and-balance exergaming intervention. Reality DTx® will initially be prescribed remotely for a minimum of 5 days a week for 30 min per day. We will remotely set and adjust the frequency, difficulty, type of games, and/or duration weekly, based on objective and subjective data from the AR glasses and participant, respectively. In addition to the home-based gait-and-balance exergaming intervention, the study comprises three laboratory visits: before the 6-week waitlist period (t0; baseline), before the 6-week intervention period (t1; pre-intervention), and after the 6-week intervention period (t2; post-intervention). The primary study parameters are feasibility (in terms of safety, adherence, and user experience) and potential efficacy for improving gait and balance (using standard clinical gait-and-balance tests and a targeted walking-related fall-risk assessment). Recruitment started in December 2022 and the final post-intervention assessment will be according to planning in July 2023.

CONCLUSIONS

This clinical feasibility trial is the first remotely prescribed and monitored home-based AR gait-and-balance exergaming intervention for pwPD. The results in terms of clinical feasibility (i.e. safety, adherence, and user experience) and potential efficacy (gait, balance, and fall-risk outcomes) form the basis for future randomised controlled studies on the effectiveness of home-based AR gait-and-balance exergaming interventions for pwPD.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT05605249 . Registered on 4 November 2022.

Positive skill transfer in balance and speed control from balance bike to pedal bike in adults: A multiphase intervention study

BACKGROUND

Learning to cycle can be challenging for adults who did not acquire the necessary skills during childhood. Balance bikes have been used to teach children how to cycle, but it was unclear whether this approach could also be effective for adults.

PURPOSE

To address this, a multi-phase intervention study was conducted to investigate whether healthy adults could be taught to cycle independently through the use of a balance bike.

METHODS

In Phase 1, a case-control observational study was conducted in which 13 cyclists and 8 non-cyclists completed balance bike tests. Based on the findings, an 8-session intervention pre- and post-test study was conducted in Phase 2, using an 8 × 20-minute balance bike training programme to improve cycling postural stability and control. Another 11 non-cyclists completed the novel programme. The time taken to complete the balance bike tests was compared before and after the program, while their cycling confidence was recorded in each session. To assess the effectiveness of the programme, participants were invited to cycle on a pedal bike to evaluate their ability to cycle independently.

RESULTS

The results in Phase 1 showed that cyclists performed better on the balance bike than non-cyclists, with Bayes factor analyses providing evidence of this difference, BF01 = 0.228 in the 15 m sprint test and BF01 = 0.138 in the two-turn curved sprint test. The novel training programme in Phase 2 demonstrated remarkable effectiveness in improving their balance bike riding performance, as evidenced by the Bayes factor for completion times in the repeated measures being BF01 < 0.001. All participants were able to cycle independently with confidence after the programme.

CONCLUSIONS

This study sheds light on the idea that it's never too late for adults to learn how to ride a bike. It provides evidence that healthy adults can learn to ride independently with the help of a balance bike, a tool that's commonly used for teaching children. The study identifies five key principles for effective balance bike training in adults, including focusing on riding speed, gliding to turn, building cycling confidence, engaging high motor skills, and using a dual-task approach. Our evidence-based training programme offers a safe, enjoyable, and effective way for adults to develop the skills and confidence they need to ride, even if they've never ridden before.

Bias in estimated short sprint profiles using timing gates due to the flying start: simulation study and proposed solutions

Short sprints are most frequently evaluated and modeled using timing gates. Flying start distance is often recommended to avoid premature timing system triggering by lifting knees or swinging arms. This results in timing system initiation not being aligned with the initial force application, which yields bias in estimated short sprint parameters. This simulation study aims to explore the effects of the flying start distance on bias and sensitivity to detect changes in short sprint parameters using three models: the contemporary No Correction model and two proposed Estimated time correction (Estimated TC), and Estimated flying distance (Estimated FD) models. In conclusion, both the Estimated TC and Estimated FD models provided more precise parameter estimates, but surprisingly, the No correction model provided higher sensitivity for specific parameter changes. Besides standardizing the sprint starting technique for the short sprint performance monitoring, practitioners are recommended to utilize and track the results of all three models.

Sharing imagery and analysis tools in a simulated submarine control room

We examined the impact of sharing periscope imagery and analysis tools in eighteen five-member teams (Sonar, Periscope, 2xTrack Motion Analysts, Track Manager) who undertook simulated submarine patrol tasks. Compared to a baseline condition, sharing imagery to team members increased perceived individual workload, with no improvement to team performance (tactical picture accuracy). When both imagery and analysis tools were shared, perceived workload increased and tactical picture compilation was more accurate. Despite this improved tactical picture for the imagery and analysis tools condition, there was no advantage to mission completion (rendezvous/close contact detection) or situation awareness. In contrast to the increased subjective workload, individuals in teams provided with shared imagery (with or without tools) had a lower physiological response (heart rate, electrodermal) to task demands compared to the baseline condition. Sharing imagery and analysis tools likely benefited tactical picture compilation by enabling dynamic task redistribution and multiple streams of concurrent data analysis.

Frailty's influence on 30-day mortality in old critically ill ICU patients: a bayesian analysis evaluating the clinical frailty scale

INTRODUCTION

Frailty is widely acknowledged as influencing health outcomes among critically ill old patients. Yet, the traditional understanding of its impact has predominantly been through frequentist statistics. We endeavored to explore this association using Bayesian statistics aiming to provide a more nuanced understanding of this multifaceted relationship.

METHODS

Our analysis incorporated a cohort of 10,363 older (median age 82 years) patients from three international prospective studies, with 30-day all-cause mortality as the primary outcome. We defined frailty as Clinical Frailty Scale ≥ 5. A hierarchical Bayesian logistic regression model was employed, adjusting for covariables, using a range of priors. An international steering committee of registry members reached a consensus on a minimal clinically important difference (MCID).

RESULTS

In our study, the 30-day mortality was 43%, with rates of 38% in non-frail and 51% in frail groups. Post-adjustment, the median odds ratio (OR) for frailty was 1.60 (95% CI 1.45-1.76). Frailty was invariably linked to adverse outcomes (OR > 1) with 100% probability and had a 90% chance of exceeding the minimal clinically important difference (MCID) (OR > 1.5). For the Clinical Frailty Scale (CFS) as a continuous variable, the median OR was 1.19 (1.16-1.22), with over 99% probability of the effect being more significant than 1.5 times the MCID. Frailty remained outside the region of practical equivalence (ROPE) in all analyses, underscoring its clinical importance regardless of how it is measured.

CONCLUSIONS

This research demonstrates the significant impact of frailty on short-term mortality in critically ill elderly patients, particularly when the Clinical Frailty Scale (CFS) is used as a continuous measure. This approach, which views frailty as a spectrum, enables more effective, personalized care for this vulnerable group. Significantly, frailty was consistently outside the region of practical equivalence (ROPE) in our analysis, highlighting its clinical importance.

Does the liner material influence pulpal vitality in deep carious cavities submitted to selective caries removal? A network meta-analysis review

OBJECTIVES

To evaluate whether the restorative material in direct contact with the dentin influences pulp vitality in primary and permanent teeth with deep carious lesions restored after selective caries removal (SCR).

MATERIAL AND METHODS

Systematic searches of databases MEDLINE via PubMed, Scopus and ISI Web of Science were performed for primary and permanent teeth. Inclusion criteria were applied for title and abstract reading of databases search results. After full texts review of included studies, those that did not meet exclusion criteria were excluded from meta-analysis.

RESULTS

For meta-analysis, 2 studies were included for permanent teeth and 6 for primary teeth. The failure events reported were meta-analyzed using two statistical methods: standard pairwise meta-analysis (SPMA) and network meta-analysis (NMA). The SPMA identified similar failure occurrence of restorations performed with calcium hydroxide (CH) and other liner materials (RR 0.84, 95% CI 0.41, 1.74; p = 0.64), no significant difference between the use of alternative liners or CH regardless deciduous or permanent teeth (RR 0.79, 95% CI 0.36, 1.71; p = 0.55) and similar risk of failing at different follow-ups for all liner materials tested (RR 0.77, 95% CI 0.35, 1.70; p = 0.52). Probabilistic analysis indicated GIC as liner material with the highest probability of clinical success (SUCRA = 72.76%), and CH ranked as the worst liner material (SUCRA = 21.81%).

CONCLUSION

Pulpal vitality was not affected by material used as liner after selective caries removal in deep carious cavities.

CLINICAL RELEVANCE

Current clinical evidence supports the weak recommendation to not use calcium hydroxide as liner after SCR.

baymedr: an R package and web application for the calculation of Bayes factors for superiority, equivalence, and non-inferiority designs

BACKGROUND

Clinical trials often seek to determine the superiority, equivalence, or non-inferiority of an experimental condition (e.g., a new drug) compared to a control condition (e.g., a placebo or an already existing drug). The use of frequentist statistical methods to analyze data for these types of designs is ubiquitous even though they have several limitations. Bayesian inference remedies many of these shortcomings and allows for intuitive interpretations, but are currently difficult to implement for the applied researcher.

RESULTS

We outline the frequentist conceptualization of superiority, equivalence, and non-inferiority designs and discuss its disadvantages. Subsequently, we explain how Bayes factors can be used to compare the relative plausibility of competing hypotheses. We present baymedr, an R package and web application, that provides user-friendly tools for the computation of Bayes factors for superiority, equivalence, and non-inferiority designs. Instructions on how to use baymedr are provided and an example illustrates how existing results can be reanalyzed with baymedr.

CONCLUSIONS

Our baymedr R package and web application enable researchers to conduct Bayesian superiority, equivalence, and non-inferiority tests. baymedr is characterized by a user-friendly implementation, making it convenient for researchers who are not statistical experts. Using baymedr, it is possible to calculate Bayes factors based on raw data and summary statistics.

Estimating the Trial-by-Trial Learning Curve in Perceptual Learning with Hierarchical Bayesian Modeling

The learning curve serves as a crucial metric for assessing human performance in perceptual learning. It may encompass various component processes, including general learning, between-session forgetting or consolidation, and within-session rapid relearning and adaptation or deterioration. Typically, empirical learning curves are constructed by aggregating tens or hundreds of trials of data in blocks or sessions. Here, we devised three inference procedures for estimating the trial-by-trial learning curve based on the multi-component functional form identified in Zhao et al. (submitted): general learning, between-session forgetting, and within-session rapid relearning and adaptation. These procedures include a Bayesian inference procedure (BIP) estimating the posterior distribution of parameters for each learner independently, and two hierarchical Bayesian models (HBMv and HBMc) computing the joint posterior distribution of parameters and hyperparameters at the population, subject, and test levels. The HBMv and HBMc incorporate variance and covariance hyperparameters, respectively, between and within subjects. We applied these procedures to data from two studies investigating the interaction between feedback and training accuracy in Gabor orientation identification across about 2000 trials spanning six sessions (Liu et al., 2010, 2012) and estimated the trial-by-trial learning curves at both the subject and population levels. The HBMc generated best fits to the data and the smallest half width of 68.2% credible interval of the learning curves compared to the BIP and HBMv. The parametric HBMc with the multi-component functional form provides a general framework for trial-by-trial analysis of the component processes in perceptual learning and for predicting the learning curve in unmeasured time points.

Bayesian learning from multi-way EEG feedback for robot navigation and target identification

Many brain-computer interfaces require a high mental workload. Recent research has shown that this could be greatly alleviated through machine learning, inferring user intentions via reactive brain responses. These signals are generated spontaneously while users merely observe assistive robots performing tasks. Using reactive brain signals, existing studies have addressed robot navigation tasks with a very limited number of potential target locations. Moreover, they use only binary, error-vs-correct classification of robot actions, leaving more detailed information unutilised. In this study a virtual robot had to navigate towards, and identify, target locations in both small and large grids, wherein any location could be the target. For the first time, we apply a system utilising detailed EEG information: 4-way classification of movements is performed, including specific information regarding when the target is reached. Additionally, we classify whether targets are correctly identified. Our proposed Bayesian strategy infers the most likely target location from the brain's responses. The experimental results show that our novel use of detailed information facilitates a more efficient and robust system than the state-of-the-art. Furthermore, unlike state-of-the-art approaches, we show scalability of our proposed approach: By tuning parameters appropriately, our strategy correctly identifies 98% of targets, even in large search spaces.

A Classification Bias and an Exclusion Bias Jointly Overinflated the Estimation of Publication Biases in Bilingualism Research

A publication bias has been argued to affect the fate of results in bilingualism research. It was repeatedly suggested that studies presenting evidence for bilingual advantages are more likely to be published compared to studies that do not report results in favor of the bilingual advantage hypothesis. This work goes back to the original claim and re-examines both the dataset and the classification of the studies that were employed. We find that the exclusion of published works such as doctoral dissertations, book chapters, and conference proceedings from the original dataset significantly inflated the presumed publication bias. Moreover, the estimation of the publication bias was affected by a classification bias that uses a mega-category that consists of both null and negative outcomes. Yet finding evidence for a bilingual disadvantage is not synonymous with obtaining a result indistinguishable from zero. Consequently, grouping together null and negative findings in a mega-category has various ramifications, not only for the estimation of the presumed publication bias but also for the field's ability to appreciate the insofar hidden correlations between bilingual advantages and disadvantages. Tracking biases that inflate scientific results is important, but it is not enough. The next step is recognizing the nested Matryoshka doll effect of bias-within-bias, and this entails raising awareness for one's own bias blind spots in science.

Bayesian Statistics Improves Biological Interpretability of Metabolomics Data from Human Cohorts

Univariate analyses of metabolomics data currently follow a frequentist approach, using p-values to reject a null hypothesis. We here propose the use of Bayesian statistics to quantify evidence supporting different hypotheses and discriminate between the null hypothesis versus the lack of statistical power. We used metabolomics data from three independent human cohorts that studied the plasma signatures of subjects with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The data are publicly available, covering 84-197 subjects in each study with 562-888 identified metabolites of which 777 were common between the two studies and 93 were compounds reported in all three studies. We show how Bayesian statistics incorporates results from one study as "prior information" into the next study, thereby improving the overall assessment of the likelihood of finding specific differences between plasma metabolite levels. Using classic statistics and Benjamini-Hochberg FDR-corrections, Study 1 detected 18 metabolic differences and Study 2 detected no differences. Using Bayesian statistics on the same data, we found a high likelihood that 97 compounds were altered in concentration in Study 2, after using the results of Study 1 as the prior distributions. These findings included lower levels of peroxisome-produced ether-lipids, higher levels of long-chain unsaturated triacylglycerides, and the presence of exposome compounds that are explained by the difference in diet and medication between healthy subjects and ME/CFS patients. Although Study 3 reported only 92 compounds in common with the other two studies, these major differences were confirmed. We also found that prostaglandin F2alpha, a lipid mediator of physiological relevance, was reduced in ME/CFS patients across all three studies. The use of Bayesian statistics led to biological conclusions from metabolomic data that were not found through frequentist approaches. We propose that Bayesian statistics is highly useful for studies with similar research designs if similar metabolomic assays are used.

When not responding to food changes food value: The role of timing

Establishing behavior change toward appetitive foods can be crucial to improve people's health. Food go/no-go training (GNG), in which people respond to some food items and not to other food items depending on the presentation of a go or no-go cue, is a means to establish behavior change. GNG changes the perceived value of food items and food consumption. After GNG, no-go items are rated as less attractive than go and/or untrained items, an empirical phenomenon called the NoGo-devaluation-effect. This effect is not always found, however. One theory-based explanation for these inconsistent results may be found in the timing of the go and no-go cues, which is also inconsistent across studies. Hence, in the present work we conducted two experiments to examine the possible role of go and no-go cue presentation timing in eliciting the NoGo-devaluation-effect. In Experiment 1, we presented the food items before the presentation of go/no-go cues, whereas we reversed this order in Experiment 2. As predicted, the NoGo-devaluation-effect was obtained in Experiment 1. This effect was absent in Experiment 2. Moreover, recognition memory for stimulus-action contingencies moderated the devaluation effect in Experiment 1, but not in Experiment 2. These results show that NoGo devaluation is dependent on the timing of the NoGo cue, which has theoretical and applied implications for understanding how and when go/no-go training influences food consumption. We propose that the value of food items is updated during go/no-go training to minimize prediction errors, and that this updating process is boosted by attention.

Remote Blood Oxygen Estimation From Videos Using Neural Networks

Peripheral blood oxygen saturation (SpO 2) is an essential indicator of respiratory functionality and received increasing attention during the COVID-19 pandemic. Clinical findings show that COVID-19 patients can have significantly low SpO 2 before any obvious symptoms. Measuring an individual's SpO 2 without having to come into contact with the person can lower the risk of cross contamination and blood circulation problems. The prevalence of smartphones has motivated researchers to investigate methods for monitoring SpO 2 using smartphone cameras. Most prior schemes involving smartphones are contact-based: They require using a fingertip to cover the phone's camera and the nearby light source to capture reemitted light from the illuminated tissue. In this paper, we propose the first convolutional neural network based noncontact SpO 2 estimation scheme using smartphone cameras. The scheme analyzes the videos of an individual's hand for physiological sensing, which is convenient and comfortable for users and can protect their privacy and allow for keeping face masks on. We design explainable neural network architectures inspired by the optophysiological models for SpO 2 measurement and demonstrate the explainability by visualizing the weights for channel combination. Our proposed models outperform the state-of-the-art model that is designed for contact-based SpO 2 measurement, showing the potential of the proposed method to contribute to public health. We also analyze the impact of skin type and the side of a hand on SpO 2 estimation performance.

Beyond statistical significance: nuanced interpretations of statistically nonsignificant results were rare in Cochrane reviews - a metaepidemiological study

OBJECTIVES

To assess the language used by systematic review authors to emphasize that statistically nonsignificant results show meaningful differences. To determine whether the magnitude of these treatment effects was distinct from nonsignificant results that authors interpreted as not different.

STUDY DESIGN AND SETTING

We screened Cochrane reviews published between 2017 and 2022 for statistically nonsignificant effect estimates that authors presented as meaningful differences. We classified interpretations qualitatively and assessed them quantitatively by calculating the areas under the curve of the portions of confidence intervals exceeding the null or a minimal important difference, indicating one intervention's greater effect.

RESULTS

In 2,337 reviews, we detected 139 cases where authors emphasized meaningful differences in nonsignificant results. Authors commonly used qualifying words to express uncertainty (66.9%). Sometimes (26.6%), they made absolute claims about one intervention's greater benefit or harm without acknowledging statistical uncertainty. The areas under the curve analyses indicated that some authors may overstate the importance of nonsignificant differences, whereas others may overlook meaningful differences in nonsignificant effect estimates.

CONCLUSION

Nuanced interpretations of statistically nonsignificant results were rare in Cochrane reviews. Our study highlights the need for a more nuanced approach by systematic review authors when interpreting statistically nonsignificant effect estimates.

Postoperative analgesia for upper gastrointestinal surgery: a retrospective cohort analysis

BACKGROUND

Thoracic epidural analgesia is commonly used for upper gastrointestinal surgery. Intrathecal morphine is an appealing opioid-sparing non-epidural analgesic option, especially for laparoscopic gastrointestinal surgery.

METHODS

Following ethics committee approval, we extracted data from the electronic medical records of patients at Royal North Shore Hospital (Sydney, Australia) that had upper gastrointestinal surgery between November 2015 and October 2020. Postoperative morphine consumption and pain scores were modelled with a Bayesian mixed effect model.

RESULTS

A total of 427 patients were identified who underwent open (n = 300), laparoscopic (n = 120) or laparoscopic converted to open (n = 7) upper gastrointestinal surgery. The majority of patients undergoing open surgery received a neuraxial technique (thoracic epidural [58%, n = 174]; intrathecal morphine [21%, n = 63]) compared to a minority in laparoscopic approaches (thoracic epidural [3%, n = 4]; intrathecal morphine [12%, n = 14]). Intrathecal morphine was superior over non-neuraxial analgesia in terms of lower median oral morphine equivalent consumption and higher probability of adequate pain control; however, this effect was not sustained beyond postoperative day 2. Thoracic epidural analgesia was superior to both intrathecal and non-neuraxial analgesia options for both primary outcomes, but at the expense of higher rates of postoperative hypotension (60%, n = 113) and substantial technique failure rates (32%).

CONCLUSIONS

We found that thoracic epidural analgesia was superior to intrathecal morphine, and intrathecal morphine was superior to non-neuraxial analgesia, in terms of reduced postoperative morphine requirements and the probability of adequate pain control in patients who underwent upper gastrointestinal surgery. However, the benefits of thoracic epidural analgesia and intrathecal morphine were not sustained across all time periods regarding control of pain. The study is limited by its retrospective design, heterogenous group of upper gastrointestinal surgeries and confounding by indication.

The reporting quality and transparency of orthopaedic studies using Bayesian analysis requires improvement: A systematic review

Background

Bayesian methods are being used more frequently in orthopaedics. To advance the use and transparent reporting of Bayesian studies, reporting guidelines have been recommended. There is currently little known about the use or applications of Bayesian analysis in orthopedics including adherence to recommended reporting guidelines. The objective is to investigate the reporting of Bayesian analysis in orthopedic surgery studies; specifically, to evaluate if these papers adhere to reporting guidelines.

Methods

We searched PUBMED to December 2nd, 2020. Two reviewers independently identified studies and full-text screening. We included studies that focused on one or more orthopaedic surgical interventions and used Bayesian methods.

Results

After full-text review, 100 articles were included. The most frequent study designs were meta-analysis or network meta-analysis (56%, 95% CI 46-65) and cohort studies (25%, 95% CI 18-34). Joint replacement was the most common subspecialty (33%, 95% CI 25-43). We found that studies infrequently reported key concepts in Bayesian analysis including, specifying the prior distribution (37-39%), justifying the prior distribution (18%), the sensitivity to different priors (7-8%), and the statistical model used (22%). In contrast, general methodological items on the checklists were largely well reported.

Conclusions

There is an opportunity to improve reporting quality and transparency of orthopaedic studies using Bayesian analysis by encouraging adherence to reporting guidelines such as ROBUST, JASP, and BayesWatch. There is an opportunity to better report prior distributions, sensitivity analyses, and the statistical models used.

Collective endpoint of visual acuity and contrast sensitivity function from hierarchical Bayesian joint modeling

Clinical trials typically analyze multiple endpoints for signals of efficacy. To improve signal detection for treatment effects using the high-dimensional data collected in trials, we developed a hierarchical Bayesian joint model (HBJM) to compute a five-dimensional collective endpoint (CE5D) of contrast sensitivity function (CSF) and visual acuity (VA). The HBJM analyzes row-by-row CSF and VA data across multiple conditions, and describes visual functions across a hierarchy of population, individuals, and tests. It generates joint posterior distributions of CE5D that combines CSF (peak gain, peak frequency, and bandwidth) and VA (threshold and range) parameters. The HBJM was applied to an existing dataset of 14 eyes, each tested with the quantitative VA and quantitative CSF procedures in four Bangerter foil conditions. The HBJM recovered strong correlations among CE5D components at all levels. With 15 qVA and 25 qCSF rows, it reduced the variance of the estimated components by 72% on average. Combining signals from VA and CSF and reducing noises, CE5D exhibited significantly higher sensitivity and accuracy in discriminating performance differences between foil conditions at both the group and test levels than the original tests. The HBJM extracts valuable information about covariance of CSF and VA parameters, improves precision of the estimated parameters, and increases the statistical power in detecting vision changes. By combining signals and reducing noise from multiple tests for detecting vision changes, the HBJM framework exhibits potential to increase statistical power for combining multi-modality data in ophthalmic trials.

Objective and subjective sleep health in adolescence: Associations with puberty and affect

Sleep health tends to worsen during adolescence, partially due to pubertal-related changes that, in combination with social and psychological factors, can lead to long-lasting impairments in sleep health and affective functioning. Discrepant findings between subjective and objective measures of sleep in relation to affect have been reported in studies of adults; however, few investigations have assessed both subjective and objective sleep quality in a single sample, and fewer have examined this in the context of pubertal development. We aimed to (1) characterise pubertal associations with subjective sleep satisfaction, objective sleep efficiency, and objective and subjective sleep duration in adolescents; (2) examine the longitudinal association between daily affect and sleep metrics; and (3) test whether pubertal stage moderated this association. Eighty-nine participants (64% female, ages 13-20) completed an ecological momentary assessment (EMA) and actigraphy protocol. Independent of age, advanced pubertal stage was associated with lower subjective sleep satisfaction but not with objective sleep indices. Subjective sleep satisfaction was associated with within-person trajectories of negative affect, but not with positive affect. Pubertal stage and sleep satisfaction did not interact to predict within-day negative or positive affect. These findings are consistent with previous reports showing that objective and subjective sleep health are associated differently with puberty, and that subjective sleep health is associated with daily affect. Pubertal stage may be a more important indicator of subjective sleep quality in adolescence than is chronological age, most likely due to hormonal changes and psychological adjustment to the physical changes associated with the pubertal transition.

Foliar Application of Selenium Associated with a Multi-Nutrient Fertilizer in Soybean: Yield, Grain Quality, and Critical Se Threshold

Selenium uptake and its content in soybean grains are affected by Se application methods. This study evaluated the impact of Se foliar application combined with a multi-nutrient fertilizer (MNF) on soybean, establishing a Se threshold to better understand the relationship between Se content in grains and yield of two genotypes (58I60 Lança and M5917). Two trials were conducted in a 4 × 2 factorial design: four Se rates (0, 10, 40, 80 g Se ha-1) and two methods of foliar Se application (Se combined or not with MNF). Foliar fertilizers were applied twice, at phenological stages of beginning of pod development and grain filling. Grain yield increased with the application of MNF, yet Se rates increased Se contents linearly up to 80 g Se ha-1, regardless of the use of MNF. Lança and M5917 genotypes had grain Se critical thresholds of 1.0 and 3.0 mg kg-1, respectively. The application of Se favored higher contents of K, P, and S in grains of genotype Lança and higher contents of Mn and Fe in grains of genotype M5917. Our findings highlight the importance of addressing different Se fertilization strategies as well as genotypic variations when assessing the effects of Se on soybean yield and grain quality.

Symbolic and non-symbolic predictors of number line task in Italian kindergarteners

The number line estimation task (NLE) is often used as a predictor for broader measures of mathematical achievement. In spite of its popularity, it is still not clear whether the task is based on symbolic or non-symbolic numerical competence. In particular, there is only a very limited amount of studies investigating the relationship between NLE performance and symbolic vs. non-symbolic math skills in children who have not yet begun formal schooling. This study investigates the strength of the association between NLE performance and symbolic and non-symbolic tasks in young kindergarteners. Ninety two 5-year-old children completed the NLE task (range 0-100) and a battery of early numerical competence tests including symbolic-lexical tasks, symbolic semantic tasks, and non-symbolic semantic tasks. The relationship between symbolic and non-symbolic early numerical competence and NLE performance was analyzed using a regression model based on the Bayesian Information Criterion (BIC). Results show that only symbolic semantic tasks are significant predictors of NLE performance. These results suggest that symbolic numerical knowledge is involved in number line processing among young children, whilst non-symbolic knowledge is not. This finding brings new data to the debate on the relationship between non-symbolic numeral knowledge and symbolic number processing and supports the evidence of a primary role of symbolic number processing already in young kindergarteners.

Bayesian stroke modeling details sex biases in the white matter substrates of aphasia

Ischemic cerebrovascular events often lead to aphasia. Previous work provided hints that such strokes may affect women and men in distinct ways. Women tend to suffer strokes with more disabling language impairment, even if the lesion size is comparable to men. In 1401 patients, we isolate data-led representations of anatomical lesion patterns and hand-tailor a Bayesian analytical solution to carefully model the degree of sex divergence in predicting language outcomes ~3 months after stroke. We locate lesion-outcome effects in the left-dominant language network that highlight the ventral pathway as a core lesion focus across different tests of language performance. We provide detailed evidence for sex-specific brain-behavior associations in the domain-general networks associated with cortico-subcortical pathways, with unique contributions of the fornix in women and cingular fiber bundles in men. Our collective findings suggest diverging white matter substrates in how stroke causes language deficits in women and men. Clinically acknowledging such sex disparities has the potential to improve personalized treatment for stroke patients worldwide.

Amygdala and anterior insula control the passage from nociception to pain

Activation of the spinothalamic system does not always result in a subjective pain perception. While the cerebral network processing nociception is relatively well known, the one underlying its transition to conscious pain remains poorly described. We used intracranial electroencephalography in epileptic patients to investigate whether the amplitudes and functional connectivity of posterior and anterior insulae (PI and AI) and amygdala differ according to the subjective reports to laser stimuli delivered at a constant intensity set at nociceptive threshold. Despite the constant intensity of stimuli, all patients reported variable subjective perceptions from one stimulus to the other. Responses in the sensory PI remained stable throughout the experiment, hence reflecting accurately the stability of the stimulus. In contrast, both AI and amygdala responses showed significant enhancements associated with painful relative to nonpainful reports, in a time window corresponding to the conscious integration of the stimulus. Functional connectivity in the gamma band between these two regions increased significantly, both before and after stimuli perceived as painful. While the PI appears to transmit faithfully the actual stimulus intensity received via the spinothalamic tract, the AI and the amygdala appear to play a major role in the transformation of nociceptive signals into a painful perception.