Abandon Statistical Significance

Bayesian estimation in veterinary pharmacology: A conceptual and practical introduction

Sophisticated mathematical and computational tools have become widespread and important in veterinary pharmacology. Although the theoretical basis and practical applications of these have been widely explored in the literature, statistical inference in the context of these models has received less attention. Optimization methods, often with frequentist statistical inference, have been predominant. In contrast, Bayesian statistics have not been widely applied, but offer both practical utility and arguably greater interpretability. Veterinary pharmacology applications are generally well supported by relevant prior information, from either existing substantive knowledge, or an understanding of study and model design. This facilitates practical implementation of Bayesian analyses that can take advantage of this knowledge. This essay will explore the specification of Bayesian models relevant to veterinary pharmacology, including demonstration of prior selection, and illustrate the capability of these models to generate practically useful statistics, including uncertainty statements, that are difficult or impossible to obtain otherwise. Case studies using simulated data will describe applications in clinical trials, pharmacodynamics, and pharmacokinetics, all including multilevel modeling. This content may serve as a suitable starting point for researchers in veterinary pharmacology and related disciplines considering Bayesian estimation for their applied work.

Exploring the variation in associations between socioeconomic indicators and non-communicable diseases in the Tromsø Study: an algorithmic approach

AIMS

We contribute to the methodological literature on the assessment of health inequalities by applying an algorithmic approach to evaluate the capabilities of socioeconomic variables in predicting the prevalence of non-communicable diseases in a Norwegian health survey.

METHODS

We use data from the seventh survey of the population based Tromsø Study (2015-2016), including 11,074 women and 10,009 men aged 40 years and above. We apply the random forest algorithm to predict four non-communicable disease outcomes (heart attack, cancer, diabetes and stroke) based on information on a number of social root causes and health behaviours. We evaluate our results using the classification error, the mean decrease in accuracy, partial dependence statistics.

RESULTS

Results suggest that education, household income and occupation to a variable extent contribute to predicting non-communicable disease outcomes. Prediction misclassification ranges between 25.1% and 35.4% depending on the non-communicable diseases under study. Partial dependences reveal mostly expected health gradients, with some examples of complex functional relationships. Out-of-sample model validation shows that predictions translate to new data input.

CONCLUSIONS

Algorithmic modelling can provide additional empirical detail and metrics for evaluating heterogeneous inequalities in morbidity. The extent to which education, income and occupation contribute to predicting binary non-communicable disease outcomes depends on both non-communicable diseases and socioeconomic indicator. Partial dependences reveal that social gradients in non-communicable disease outcomes vary in shape between combinations of non-communicable disease outcome and socioeconomic status indicator. Misclassification rates highlight the extent of variation within socioeconomic groups, suggesting that future studies may improve predictive accuracy by exploring further subpopulation heterogeneity.

Effects of aerobic exercise training on cerebral pulsatile hemodynamics in middle-aged adults with elevated blood pressure/stage 1 hypertension

Mechanisms behind the protective effects of aerobic exercise on brain health remain elusive but may be vascular in origin and relate to cerebral pulsatility. This pilot study investigated the effects of 12-wk aerobic exercise training on cerebral pulsatility and its vascular contributors (large artery stiffness, characteristic impedance) in at-risk middle-aged adults. Twenty-eight inactive middle-aged adults with elevated blood pressure or stage 1 hypertension were assigned to either moderate/vigorous aerobic exercise training (AET) for 3 days/wk or no-exercise control (CON) group. Middle cerebral artery (MCA) pulsatility index (PI), large artery (i.e., aorta, carotid) stiffness, and characteristic impedance were assessed via Doppler and tonometry at baseline, 6, and 12 wk, whereas cardiorespiratory fitness (V̇o2peak) was assessed via incremental exercise test and cognitive function via computerized battery at baseline and 12 wk. V̇o2peak increased 6% in AET and decreased 4% in CON (P < 0.05). Proximal aortic compliance increased (P = 0.04, partial η2 = 0.14) and aortic characteristic impedance decreased (P = 0.02, partial η2 = 0.17) with AET but not CON. Cerebral pulsatility showed a medium-to-large effect size increase with AET, although not statistically significant (P = 0.07, partial η2 = 0.11) compared with CON. Working memory reaction time improved with AET but not CON (P = 0.02, partial η2 = 0.20). Our data suggest 12-wk AET elicited improvements in central vascular hemodynamics (e.g., proximal aortic compliance and characteristic impedance) along with apparent, paradoxical increases in cerebral pulsatile hemodynamics.NEW & NOTEWORTHY We identify differential central versus cerebrovascular responses to 12 wk of aerobic exercise training in middle-aged adults. Although proximal aortic compliance and characteristic impedance improved after 12 wk of exercise, cerebral pulsatility tended to unexpectedly increase. These data suggest short-term aerobic exercise training may lead to more immediate benefits in the central vasculature, whereas longer duration exercise training may be required for beneficial changes in pulsatility within the cerebrovasculature.

Screen time and sleep duration in pediatric critical care: Secondary analysis of a pilot observational study

PURPOSE

Quantify and describe screen time (screen type, child engagement, adult co-viewing) in eight critically ill children and determine its association with sleep duration before (parent report) and during (actigraphy) a 24-h period in the PICU.

DESIGN AND METHODS

Exploratory secondary analysis of 24-h video and actigraphy recordings in eight children 1-4 years old in the PICU. Videos were coded for screen time using Noldus Observer XT® software. Screen time was compared to American Academy of Pediatrics recommendations (0 h/day <2 years, ≤1 h/day 2-5 years). Parents completed the Brief Infant Sleep Questionnaire-Revised-Short Form (BISQ-R-SF) to understand children's pre-hospital sleep. Actigraphy was used to measure PICU sleep duration. Associations between screen time and sleep were determined with bivariate analyses.

RESULTS

Average age was 23.1 months (SD = 9.7). Daily screen time was 10.7 h (SD = 7), ranging from 2.4 to 21.4 h. Children (15.1% of sampling intervals) and adults (16.3%) spent little time actively engaged with screen media. BISQ-R-SF scores ranged from 48.9 to 97.7. Children had an average of 7.9 (SD = 1.2) night shift (19:00-6:59) sleep hours. Screen time was associated with worse pre-hospital sleep quality and duration with large effect sizes (rs= -0.7 to -1) and fewer nighttime sleep hours with a medium effect size (rs= -0.5).

CONCLUSIONS

All children exceeded screen time recommendations. Screen time was associated with worse pre-hospital sleep quality and duration, and decreased PICU sleep duration. Large-scale studies are needed to explore PICU screen time and sleep disruption.

PRACTICE IMPLICATIONS

Clinicians should model developmentally appropriate screen media use in PICU.

Prime-induced illusion of control: The influence of unconscious priming on self-initiated actions and the role of regression to the mean

To what degree human cognition is influenced by subliminal stimuli is a controversial empirical question. One striking example was reported by Linser and Goschke (2007): participants overestimated how much control they had over objectively uncontrollable stimuli when masked congruent primes were presented immediately before the action. Critically, however, unawareness of the masked primes was established by post hoc data selection. In our preregistered study we sought to explore these findings while adjusting prime visibility based on individual thresholds, so that each participant underwent both visible and non-visible conditions. In experiment 1, N = 39 participants engaged in a control judgement task: following the presentation of a semantic prime, they freely selected between two keys, which triggered the appearance of a colored circle. The color of the circles, however, was independent of the key-press. Subsequently, participants assessed their perceived control over the circle's color, based on their key-presses, via a rating scale that ranged from 0 % (no control) to 100 % (complete control). Contrary to Linser and Goschke (2007)'s findings, this experiment demonstrated that predictive information influenced the experience of agency only when primes were consciously processed. In experiment 2, utilizing symbolic (arrow) primes, N = 35 participants had to rate their feeling of control over the effect-stimulus' identity during a two-choice identification paradigm (i.e., they were instructed to press a key corresponding to a target stimulus; with a contingency between target and effect stimulus of 75 %/25 %). The results revealed no significant influence of subliminal priming on agency perceptions. In summary, this study implies that unconscious stimuli may not exert a substantial influence on the conscious experience of agency, underscoring the need for careful consideration of methodological aspects and experimental design's impact on observed phenomena.

Exploring an objective measure of overactivity in children with rare genetic syndromes

BACKGROUND

Overactivity is prevalent in several rare genetic neurodevelopmental syndromes, including Smith-Magenis syndrome, Angelman syndrome, and tuberous sclerosis complex, although has been predominantly assessed using questionnaire techniques. Threats to the precision and validity of questionnaire data may undermine existing insights into this behaviour. Previous research indicates objective measures, namely actigraphy, can effectively differentiate non-overactive children from those with attention-deficit hyperactivity disorder. This study is the first to examine the sensitivity of actigraphy to overactivity across rare genetic syndromes associated with intellectual disability, through comparisons with typically-developing peers and questionnaire overactivity estimates.

METHODS

A secondary analysis of actigraphy data and overactivity estimates from The Activity Questionnaire (TAQ) was conducted for children aged 4-15 years with Smith-Magenis syndrome (N=20), Angelman syndrome (N=26), tuberous sclerosis complex (N=16), and typically-developing children (N=61). Actigraphy data were summarized using the M10 non-parametric circadian rhythm variable, and 24-hour activity profiles were modelled via functional linear modelling. Associations between actigraphy data and TAQ overactivity estimates were explored. Differences in actigraphy-defined activity were also examined between syndrome and typically-developing groups, and between children with high and low TAQ overactivity scores within syndromes.

RESULTS

M10 and TAQ overactivity scores were strongly positively correlated for children with Angelman syndrome and Smith-Magenis syndrome. M10 did not substantially differ between the syndrome and typically-developing groups. Higher early morning activity and lower evening activity was observed across all syndrome groups relative to typically-developing peers. High and low TAQ group comparisons revealed syndrome-specific profiles of overactivity, persisting throughout the day in Angelman syndrome, occurring during the early morning and early afternoon in Smith-Magenis syndrome, and manifesting briefly in the evening in tuberous sclerosis complex.

DISCUSSION

These findings provide some support for the sensitivity of actigraphy to overactivity in children with rare genetic syndromes, and offer syndrome-specific temporal descriptions of overactivity. The findings advance existing descriptions of overactivity, provided by questionnaire techniques, in children with rare genetic syndromes and have implications for the measurement of overactivity. Future studies should examine the impact of syndrome-related characteristics on actigraphy-defined activity and overactivity estimates from actigraphy and questionnaire techniques.

Learning epistatic polygenic phenotypes with Boolean interactions

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1, a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. We identify individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlate across body sites, suggesting systemic dynamics influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals show altered microbial stability and associations among microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Development and Initial Validation of a Frailty Score for Pediatric Patients with Congenital and Acquired Heart Disease

Frailty is a multi-dimensional clinical syndrome that is associated with increased morbidity and mortality and decreased quality of life. Children/adolescents with heart disease (HD) perform significantly worse for each frailty domain compared to non-HD peers. Our study aimed to create a composite frailty score (CFS) that can be applied to children/adolescents with HD and evaluate associations between the CFS and outcomes. Children and adolescents (n = 30) with HD (73% single ventricle, 20% heart failure, 7% pulmonary hypertension) were recruited from 2016 to 2017 (baseline). Five frailty domains were assessed at baseline using measures validated for pediatrics: (1) Slowness: 6-min walk test; (2) Weakness: handgrip strength; (3) Fatigue: PedsQL Multi-dimensional Fatigue Scale; (4) Body composition: triceps skinfold thickness; and (5) Physical activity questionnaire. Frailty points per domain (range = 0-5) were assigned based on z-scores or raw questionnaire scores and summed to produce a CFS (0 = least frail; 25 = most frail). Nonparametric bootstrapping was used to identify correlations between CFS and cross-sectional change in outcomes over 2.2 ± 0.2 years. The mean CFS was 12.5 ± 3.5. In cross-sectional analyses of baseline data, correlations (|r|≥ 0.30) were observed between CFS and NYHA class, the number of ancillary specialists, total prescribed medications, heart failure medications/day, exercise test derived chronotropic index and percent predicted VO2peak, and between child and parent proxy PEDsQL. At follow-up, CFS was correlated with an increase in the number of heart failure medications (r = 0.31). CFS was associated with cross-sectional outcomes in youth with heart disease. Longitudinal analyses were limited by small sample sizes due to loss to follow-up.

A Confidence Interval for the Difference Between Standardized Regression Coefficients

Researchers are often interested in comparing predictors, a practice commonly done via informal comparisons of standardized regression slopes. However, formal interval-based approaches offer advantages over informal comparison. Specifically, this article examines a delta-method-based confidence interval for the difference between two standardized regression coefficients, building upon previous work on confidence intervals for single coefficients. Using Monte Carlo simulation studies, the proposed approach is evaluated at finite sample sizes with respect to coverage rate, interval width, Type I error rate, and statistical power under a variety of conditions, and is shown to outperform an alternative approach that uses the standard covariance matrix found in regression textbooks. Additional simulations evaluate current software implementations, small sample performance, and multiple comparison procedures for simultaneously testing multiple differences of interest. Guidance on sample size planning for narrow confidence intervals, an R function to conduct the proposed method, and two empirical demonstrations are provided. The goal is to offer researchers a different tool in their toolbox for when comparisons among standardized coefficients are desired, as a supplement to, rather than a replacement for, other potentially useful analyses.

Accuracy of Intraset Repetitions-in-Reserve Predictions During the Bench Press Exercise in Resistance-Trained Male and Female Subjects

ABSTRACT

Refalo, MC, Remmert, JF, Pelland, JC, Robinson, ZP, Zourdos, MC, Hamilton, DL, Fyfe, JJ, and Helms, ER. Accuracy of intraset repetitions-in-reserve predictions during the bench press exercise in resistance-trained male and female subjects. J Strength Cond Res 38(3): e78-e85, 2024-This study assessed the accuracy of intraset repetitions-in-reserve (RIR) predictions to provide evidence for the efficacy of RIR prescription as a set termination method to inform proximity to failure during resistance training (RT). Twenty-four resistance trained male ( n = 12) and female ( n = 12) subjects completed 2 experimental sessions involving 2 sets performed to momentary muscular failure (barbell bench press exercise) with 75% of 1 repetition maximum (1RM), whereby subjects verbally indicated when they perceived to had reached either 1 RIR or 3 RIR. The difference between the predicted RIR and the actual RIR was defined as the "RIR accuracy" and was quantified as both raw (i.e., direction of error) and absolute (i.e., magnitude of error) values. High raw and absolute mean RIR accuracy (-0.17 ± 1.00 and 0.65 ± 0.78 repetitions, respectively) for 1-RIR and 3-RIR predictions were observed (including all sets and sessions completed). We identified statistical equivalence (equivalence range of ±1 repetition, thus no level of statistical significance was set) in raw and absolute RIR accuracy between (a) 1-RIR and 3-RIR predictions, (b) set 1 and set 2, and (c) session 1 and session 2. No evidence of a relationship was found between RIR accuracy and biological sex, years of RT experience, or relative bench press strength. Overall, resistance-trained individuals are capable of high absolute RIR accuracy when predicting 1 and 3 RIR on the barbell bench press exercise, with a minor tendency for underprediction. Thus, RIR prescriptions may be used in research and practice to inform the proximity to failure achieved upon set termination.

Why are there differences across German states in student achievement and cognitive ability?

Background

For more than twenty years, large and generally stable differences in academic achievement and cognitive ability have been reported within Germany. In such studies, the southern regions lead in the west and east, while city-states lag behind. Expressed in school learning time, the students in Bavaria are 14 months ahead of the students in Bremen. It is striking that there are no or only marginally received studies on causes and consequences.

Purpose

This study attempts to explore the causes and consequences of the differences within Germany and what can be learned in general about their development.

Materials and methods

We use data from student assessment and other studies (e.g., PISA, IQB) and apply correlational and path analyses, controlled for various background factors.

Results

There are no stable correlations with evolution (genes), educational level of society (adult school years) and wealth (GDP per capita). However, there are high correlations, robust across indicators, with "burgher-conservative" education policies, e.g., central exit examinations, early tracking, grades at a young age (around r ≈ .65); with measures of students' quantity of education (hours of instruction, no teacher shortage; r ≈ .40); with measures of tertiary educational quality and appreciation of education (university quality, short duration of studies, professors' salaries; r ≈ .50); with student native/immigrant ratio (r ≈ .50); with middle-class burgher lifestyle (less private debt, less welfare dependency and less crime; r ≈ .60); and with burgher-conservative-right politics (share of votes for CDU/CSU and non-left parties, non-left state governments; r ≈ .80). Longitudinal analyses over four decades reveal interaction effects, i.e., more burgher policies statistically lead to more cognitively competent students (β ≈ .45) and more cognitively competent populations vote for burgher parties (β ≈ .30).

Conclusions

The results, which support the efficacy a bourgeois-conservative education policy and of lower immigration rates, are delicate for the practice of student achievement research and for the political milieu that dominates the social sciences.

Uncontrolled pain: a call for better study design

Studies assessing animal pain in veterinary research are often performed primarily for the benefit of animals. Frequently, the goal of these studies is to determine whether the analgesic effect of a novel treatment is clinically meaningful, and therefore has the capacity to improve the welfare of treated animals. To determine the treatment effect of a potential analgesic, control groups are necessary to allow comparison. There are negative control groups (where pain is unattenuated) and positive control groups (where pain is attenuated). Arising out of animal welfare concerns, there is growing reluctance to use negative control groups in pain studies. But for studies where pain is experimentally induced, the absence of a negative control group removes the opportunity to demonstrate that the study methods could differentiate a positive control intervention from doing nothing at all. For studies that are controlled by a single comparison group, the capacity to distinguish treatment effects from experimental noise is more difficult; especially considering that pain studies often involve small sample sizes, small and variable treatment effects, systematic error and use pain assessment measures that are unreliable. Due to these limitations, and with a focus on farm animals, we argue that many pain studies would be enhanced by the simultaneous inclusion of positive and negative control groups. This would help provide study-specific definitions of pain and pain attenuation, thereby permitting more reliable estimates of treatment effects. Adoption of our suggested refinements could improve animal welfare outcomes for millions of animals globally.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Study Highlights

The stability of the human microbiome varies among individuals and body sites.Highly individualized microbial genera are more stable over time.At each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected.Individuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions.

Maximal Number of Repetitions at Percentages of the One Repetition Maximum: A Meta-Regression and Moderator Analysis of Sex, Age, Training Status, and Exercise

The maximal number of repetitions that can be completed at various percentages of the one repetition maximum (1RM) [REPS ~ %1RM relationship] is foundational knowledge in resistance exercise programming. The current REPS ~ %1RM relationship is based on few studies and has not incorporated uncertainty into estimations or accounted for between-individuals variation. Therefore, we conducted a meta-regression to estimate the mean and between-individuals standard deviation of the number of repetitions that can be completed at various percentages of 1RM. We also explored if the REPS ~ %1RM relationship is moderated by sex, age, training status, and/or exercise. A total of 952 repetitions-to-failure tests, completed by 7289 individuals in 452 groups from 269 studies, were identified. Study groups were predominantly male (66%), healthy (97%), < 59 years of age (92%), and resistance trained (60%). The bench press (42%) and leg press (14%) were the most commonly studied exercises. The REPS ~ %1RM relationship for mean repetitions and standard deviation of repetitions were best described using natural cubic splines and a linear model, respectively, with mean and standard deviation for repetitions decreasing with increasing %1RM. More repetitions were evident in the leg press than bench press across the loading spectrum, thus separate REPS ~ %1RM tables were developed for these two exercises. Analysis of moderators suggested little influences of sex, age, or training status on the REPS ~ %1RM relationship, thus the general main model REPS ~ %1RM table can be applied to all individuals and to all exercises other than the bench press and leg press. More data are needed to develop REPS ~ %1RM tables for other exercises.

Why Stating Hypotheses in Grant Applications Is Unnecessary

This Viewpoint argues that a hypothesis-centric approach to writing grant applications is problematic and instead suggests that funding applications should be evaluated by their relevance and methodological quality rather than by qualitative assertions before the study is conducted.

The Continuous Fragility Index of Statistically Significant Findings in Randomized Controlled Trials That Compare Interventions for Anterior Shoulder Instability

BACKGROUND

Evidence-based care relies on robust research. The fragility index (FI) is used to assess the robustness of statistically significant findings in randomized controlled trials (RCTs). While the traditional FI is limited to dichotomous outcomes, a novel tool, the continuous fragility index (CFI), allows for the assessment of the robustness of continuous outcomes.

PURPOSE

To calculate the CFI of statistically significant continuous outcomes in RCTs evaluating interventions for managing anterior shoulder instability (ASI).

STUDY DESIGN

Meta-analysis; Level of evidence, 2.

METHODS

A search was conducted across the MEDLINE, Embase, and CENTRAL databases for RCTs assessing management strategies for ASI from inception to October 6, 2022. Studies that reported a statistically significant difference between study groups in ≥1 continuous outcome were included. The CFI was calculated and applied to all available RCTs reporting interventions for ASI. Multivariable linear regression was performed between the CFI and various study characteristics as predictors.

RESULTS

There were 27 RCTs, with a total of 1846 shoulders, included. The median sample size was 61 shoulders (IQR, 43). The median CFI across 27 RCTs was 8.2 (IQR, 17.2; 95% CI, 3.6-15.4). The median CFI was 7.9 (IQR, 21; 95% CI, 1-22) for 11 studies comparing surgical methods, 22.6 (IQR, 16; 95% CI, 8.2-30.4) for 6 studies comparing nonsurgical reduction interventions, 2.8 for 3 studies comparing immobilization methods, and 2.4 for 3 studies comparing surgical versus nonsurgical interventions. Significantly, 22 of 57 included outcomes (38.6%) from studies with completed follow-up data had a loss to follow-up exceeding their CFI. Multivariable regression demonstrated that there was a statistically significant positive correlation between a trial's sample size and the CFI of its outcomes (r = 0.23 [95% CI, 0.13-0.33]; P < .001).

CONCLUSION

More than a third of continuous outcomes in ASI trials had a CFI less than the reported loss to follow-up. This carries the significant risk of reversing trial findings and should be considered when evaluating available RCT data. We recommend including the FI, CFI, and loss to follow-up in the abstracts of future RCTs.

Cortical surface analysis for focal cortical dysplasia diagnosis by using PET images

Focal cortical dysplasia (FCD) is a neurological disorder distinguished by faulty brain cell structure and development. Repetitive and uncontrollable seizures may be linked to FCD's aberrant cortical thickness, gyrification, and sulcal depth. Quantitative cortical surface analysis is a crucial alternative to ineffective visual inspection. This study recruited 42 subjects including 22 FCD patients who underwent surgery and 20 healthy controls (HC). For the FCD patients, T1-weighted and PET images were obtained by a PET-MRI scanner, and the confirmed epileptogenic zone (EZ) was collected from postsurgical follow-up. For the HCs, CT and PET images were obtained by a PET-CT scanner. Cortical thickness, gyrification index, and sulcal depth were calculated using a computational anatomical toolbox (CAT12). A cluster-based analysis is carried out to determine each FCD patient's aberrant cortical surface. After parcellating the cerebral cortex into 68 regions by the Desikan-Killiany atlas, a region of interest (ROI) analysis was conducted to know whether the feature in the FCD group is significantly different from that in the HC group. Finally, the features of all ROIs were utilised to train a support vector machine classifier (SVM). The classification performance is evaluated by the leave-one-out cross-validation. The cluster-based analysis can localize the EZ cluster with the highest accuracy of 54.5 % (12/22) for cortical thickness, 40.9 % (9/22) and 13.6 % (3/22) for sulcal depth and gyrification, respectively. Moderate concordance (Kappa, 0.6) is observed between the confirmed EZs and identified clusters by using the cortical thickness. Fair concordance (Kappa, 0.3) and no concordance (Kappa, 0.1) is found by using sulcal depth and gyrification. Significant differences are found in 46 of 68 regions (67.7 %) for the three measures. The trained SVM classifier achieved a prediction accuracy of 95.5 % for the cortical thickness, while the sulcal depth and the gyrification obtained 86.0 % and 81.5 %. Cortical thickness, as determined by quantitative cortical surface analysis of PET data, has a greater ability than sulcal depth and gyrification to locate aberrant EZ clusters in FCD. Surface measures might be different in many regions for FCD and HC. By integrating machine learning and cortical morphologies features, individual prediction of FCD seems to be feasible.

On the use of receiver operating characteristic curve analysis to determine the most appropriate p value significance threshold

BACKGROUND

p value is the most common statistic reported in scientific research articles. Choosing the conventional threshold of 0.05 commonly used for the p value in research articles, is unfounded. Many researchers have tried to provide a reasonable threshold for the p value; some proposed a lower threshold, eg, 0.005. However, none of the proposals has gained universal acceptance. Using the analogy between the diagnostic tests with continuous results and statistical inference tests of hypothesis, I wish to present a method to calculate the most appropriate p value significance threshold using the receiver operating characteristic curve (ROC) analysis.

RESULTS

As with diagnostic tests where the most appropriate cut-off values are different depending on the situation, there is no unique cut-off for the p significance threshold. Unlike the previous proposals, which mostly suggest lowering the threshold to a fixed value (eg, from 0.05 to 0.005), the most appropriate p significance threshold proposed here, in most instances, is much less than the conventional cut-off of 0.05 and varies from study to study and from statistical test to test, even within a single study. The proposed method provides the minimum weighted sum of type I and type II errors.

CONCLUSIONS

Given the perplexity involved in using the frequentist statistics in a correct way (dealing with different p significance thresholds, even in a single study), it seems that the p value is no longer a proper statistic to be used in our research; it should be replaced by alternative methods, eg, Bayesian methods.

Primate social organization evolved from a flexible pair-living ancestor

Explaining the evolution of primate social organization has been fundamental to understand human sociality and social evolution more broadly. It has often been suggested that the ancestor of all primates was solitary and that other forms of social organization evolved later, with transitions being driven by various life history traits and ecological factors. However, recent research showed that many understudied primate species previously assumed to be solitary actually live in pairs, and intraspecific variation in social organization is common. We built a detailed database from primary field studies quantifying the number of social units expressing different social organizations in each population. We used Bayesian phylogenetic models to infer the probability of each social organization, conditional on several socioecological and life history predictors. Here, we show that when intraspecific variation is accounted for, the ancestral social organization of primates was inferred to be variable, with the most common social organization being pair-living but with approximately 10 to 20% of social units of the ancestral population deviating from this pattern by being solitary living. Body size and activity patterns had large effects on transitions between types of social organizations. As in other mammalian clades, pair-living is closely linked to small body size and likely more common in ancestral species. Our results challenge the assumption that ancestral primates were solitary and that pair-living evolved afterward emphasizing the importance of focusing on field data and accounting for intraspecific variation, providing a flexible statistical framework for doing so.

Furosemide versus placebo for fluid overload in intensive care patients-The randomised GODIF trial second version: Statistical analysis plan

BACKGROUND

Fluid overload is associated with increased mortality in intensive care unit (ICU) patients. The GODIF trial aims to assess the benefits and harms of fluid removal with furosemide versus placebo in stable adult patients with moderate to severe fluid overload in the ICU. This article describes the detailed statistical analysis plan for the primary results of the second version of the GODIF trial.

METHODS

The GODIF trial is an international, multi-centre, randomised, stratified, blinded, parallel-group, pragmatic clinical trial, allocating 1000 adult ICU patients with moderate to severe fluid overload 1:1 to furosemide versus placebo. The primary outcome is days alive and out of hospital within 90 days post-randomisation. With a power of 90% and an alpha level of 5%, we may reject or detect an improvement of 8%. The primary analyses of all outcomes will be performed in the intention-to-treat population. For the primary outcome, the Kryger Jensen and Lange method will be used to compare the two treatment groups adjusted for stratification variables supplemented with sensitivity analyses in the per-protocol population and with further adjustments for prognostic variables. Secondary outcomes will be analysed with multiple linear regressions, logistic regressions or the Kryger Jensen and Lange method as suitable with adjustment for stratification variables.

CONCLUSION

The GODIF trial data will increase the certainty about the effects of fluid removal using furosemide in adult ICU patients with fluid overload.

TRIAL REGISTRATIONS

EudraCT identifier: 2019-004292-40 and ClinicalTrials.org: NCT04180397.

A Utilitarian Perspective on Risk Quantification for Clinical Significance in Binary Outcomes

Null hypothesis significance testing (NHST) in medical research is increasingly being supplemented by estimation statistics, focusing on effect sizes (ESs) and confidence intervals (CIs). This study evaluates the expression of ESs and CIs for binary outcomes. A utilitarian framework is proposed, emphasizing the number of beneficiaries and the impact level. To evaluate clinical significance, minimal clinically important risk difference (MCIRD) is proposed based on event magnitude (EM). Within this framework, risk difference (RD) is introduced as the primary measure. To assess the performance of RD, we compared its statistical power against other measures (risk ratio, RR; odds ratio, OR; Cohen's h) in individual study scenarios, and visual information conveyance in meta-analysis scenarios. RDs maintain statistical power in comparison to other measures in individual studies. They provide clarity on the true impact of clinical interventions without compromising statistical integrity. Meta-analytic results indicate that using RDs directly enhances transparency, uncovers heterogeneity, and addresses misaligned assumptions. This approach, by quantifying clinical effectiveness under a utilitarian perspective, facilitates the applicability of research to patient care and encourages shared decision-making. The study advocates for reporting baseline risks (BRs) with RDs and recommends a standardized presentation of these statistics. In a utilitarian perspective, adopting RD as the preferred ES can foster a transparent, patient-focused research ethos. This aids in accurately presenting the magnitude and variability of treatment effects, offering a new direction in methodology.

A New Look at P Values for Randomized Clinical Trials

BACKGROUND: We have examined the primary efficacy results of 23,551 randomized clinical trials from the Cochrane Database of Systematic Reviews. METHODS: We estimate that the great majority of trials have much lower statistical power for actual effects than the 80 or 90% for the stated effect sizes. Consequently, “statistically significant” estimates tend to seriously overestimate actual treatment effects, “nonsignificant” results often correspond to important effects, and efforts to replicate often fail to achieve “significance” and may even appear to contradict initial results. To address these issues, we reinterpret the P value in terms of a reference population of studies that are, or could have been, in the Cochrane Database. RESULTS: This leads to an empirical guide for the interpretation of an observed P value from a “typical” clinical trial in terms of the degree of overestimation of the reported effect, the probability of the effect’s sign being wrong, and the predictive power of the trial. CONCLUSIONS: Such an interpretation provides additional insight about the effect under study and can guard medical researchers against naive interpretations of the P value and overoptimistic effect sizes. Because many research fields suffer from low power, our results are also relevant outside the medical domain. (Funded by the U.S. Office of Naval Research.)

Using Powerlifting Athletes to Determine Strength Adaptations Across Ages in Males and Females: A Longitudinal Growth Modelling Approach

INTRODUCTION

Several retrospective studies of strength sport athletes have reported strength adaptations over months to years; however, such adaptations are not linear.

METHODS

We explored changes in strength over time in a large, retrospective sample of powerlifting (PL) athletes. Specifically, we examined the rate and magnitude of strength adaptation based on age category and weight class for PL competition total, and the squat, bench press, and deadlift, respectively. Mixed effects growth modelling was performed for each operationalised performance outcome (squat, bench press, deadlift, and total) as the dependent variables, with outcomes presented on both the raw, untransformed time scale and on the common logarithmic scale. Additionally, the fitted values were rescaled as a percentage.

RESULTS

Collectively, the greatest strength gains were in the earliest phase of PL participation (~ 7.5-12.5% increase in the first year, and up to an ~ 20% increase after 10 years). Females tended to display faster progression, possibly because of lower baseline strength. Additionally, female Masters 3 and 4 athletes (> 59 years) still displayed ~ 2.5-5.0% strength improvement, but a slight strength loss was observed in Masters 4 (> 69 years) males (~ 0.35%/year).

CONCLUSION

Although directly applicable to PL, these findings provide population-level support for the role of consistent and continued strength training to improve strength across the age span and, importantly, to mitigate, or at least largely attenuate age-related declines in strength compared to established general population norms. This information should be used to encourage participation in strength sports, resistance training more generally, and to support future public health messaging.

Surface inoculation method impacts microbial reduction and transfer of Salmonella Enteritidis PT 30 and potential surrogates during dry sanitation

Dry sanitation methods are often limited to physical removal strategies such as brushing or wiping with sanitary cleaning tools. However, the relative efficacy of these approaches to remove microbiota on surfaces, and the risk of transferring cells to other surfaces via the cleaning tool, is unclear. The effect of dry wiping with a single-use towel on the removal of four different bacteria (Salmonella Enteritidis, Enterococcus faecium, Listeria innocua, Escherichia coli) was investigated. We also quantified the number of cells transferred to the towel itself during dry cleaning. Three different surface inoculation methods (spot, glass bead, contaminated milk powder) were assessed and significantly impacted initial surface microbial load. Higher initial counts corresponded to lower transfer coefficients (e.g., proportion of transferred cells). The effect of bacterial identity was significant on reduction after dry wiping for all three inoculation methods. Moreover, both bacterial identity and inoculation method had significant effects on the number of cells transferred to the towel. In most scenarios, dry wiping resulted in a reduction <1.0 log CFU/coupon. Although, on surfaces inoculated via contaminated milk powder, reductions of up to 1.6 ± 0.3 log CFU/coupon were obtained. Overall, E. faecium transferred more readily to the towel. These results may help guide experimental design for future research on dry sanitation.

Power analysis for idiographic (within-subject) clinical trials: Implications for treatments of rare conditions and precision medicine

Power analysis informs a priori planning of behavioral and medical research, including for randomized clinical trials that are nomothetic (i.e., studies designed to infer results to the general population based on interindividual variabilities). Far fewer investigations and resources are available for power analysis of clinical trials that follow an idiographic approach, which emphasizes intraindividual variabilities between baseline (control) phase versus one or more treatment phases. We tested the impact on statistical power to detect treatment outcomes of four idiographic trial design factors that are under researchers' control, assuming a multiple baseline design: sample size, number of observations per participant, proportion of observations in the baseline phase, and competing statistical models (i.e., hierarchical modeling versus piecewise regression). We also tested the impact of four factors that are largely outside of researchers' control: population size, proportion of intraindividual variability due to residual error, treatment effect size, and form of outcomes during the treatment phase (phase jump versus gradual change). Monte Carlo simulations using all combinations of the factors were sampled with replacement from finite populations of 200, 1750, and 3500 participants. Analyses characterized the unique relative impact of each factor individually and all two-factor combinations, holding all others constant. Each factor impacted power, with the greatest impact being from larger treatment effect sizes, followed respectively by more observations per participant, larger samples, less residual variance, and the unexpected improvement in power associated with assigning closer to 50% of observations to the baseline phase. This study's techniques and R package better enable a priori rigorous design of idiographic clinical trials for rare diseases, precision medicine, and other small-sample studies.

A re-analysis of 150 women's health trials to investigate how the Bayesian approach may offer a solution to the misinterpretation of statistical findings

OBJECTIVE

To investigate whether a Bayesian interpretation might help prevent misinterpretation of statistical findings and support authors to differentiate evidence of no effect from statistical uncertainty.

DESIGN

A Bayesian re-analysis to determine posterior probabilities of clinically important effects (e.g., a large effect is set at a 4 percentage point difference and a trivial effect to be within a 0.5 percentage point difference). Posterior probabilities greater than 95% are considered as strong statistical evidence, and less than 95% as inconclusive.

SAMPLE

150 major women's health trials with binary outcomes.

MAIN OUTCOME MEASURES

Posterior probabilities of large, moderate, small and trivial effects.

RESULTS

Under frequentist methods, 48 (32%) were statistically significant (p-value ≤ 0.05) and 102 (68%) statistically non-significant. The frequentist and Bayesian point estimates and confidence intervals showed strong concordance. Of the statistically non-significant trials (n = 102), the Bayesian approach classified the majority (94, 92%) as inconclusive, neither able to confirm or refute effectiveness. A small number of statistically non-significant findings (8, 8%) were classified as having strong statistical evidence of an effect.

CONCLUSIONS

Whilst almost all trials report confidence intervals, in practice most statistical findings are interpreted on the basis of statistical significance, mostly concluding evidence of no effect. Findings here suggest the majority are likely uncertain. A Bayesian approach could help differentiate evidence of no effect from statistical uncertainty.

When do the effects of single-session interventions persist? Testing the mindset + supportive context hypothesis in a longitudinal randomized trial

Background

Single-session interventions have the potential to address young people's mental health needs at scale, but their effects are heterogeneous. We tested whether the mindset + supportive context hypothesis could help explain when intervention effects persist or fade over time. The hypothesis posits that interventions are more effective in environments that support the intervention message. We tested this hypothesis using the synergistic mindsets intervention, a preventative treatment for stress-related mental health symptoms that helps students appraise stress as a potential asset in the classroom (e.g., increasing oxygenated blood flow) rather than debilitating. In an introductory college course, we examined whether intervention-consistent messages from instructors sustained changes in appraisals over time, as well as impacts on students' predisposition to try demanding academic tasks that could enhance learning.

Methods

We randomly assigned 1675 students in the course to receive the synergistic mindsets intervention (or a control activity) at the beginning of the semester, and subsequently, to receive intervention-supportive messages from their instructor (or neutral messages) four times throughout the term. We collected weekly measures of students' appraisals of stress in the course and their predisposition to take on academic challenges. Trial-registration: OSF.io; DOI: 10.17605/osf.io/fchyn.

Results

A conservative Bayesian analysis indicated that receiving both the intervention and supportive messages led to the greatest increases in positive stress appraisals (0.35 SD; 1.00 posterior probability) and challenge-seeking predisposition (2.33 percentage points; 0.94 posterior probability), averaged over the course of the semester. In addition, intervention effects grew larger throughout the semester when complemented by supportive instructor messages, whereas without these messages, intervention effects shrank somewhat over time.

Conclusions

This study shows, for the first time, that supportive cues in local contexts can be the difference in whether a single-session intervention's effects fade over time or persist and even amplify.

Long-Term Time-Course of Strength Adaptation to Minimal Dose Resistance Training Through Retrospective Longitudinal Growth Modeling

Public health guidelines for resistance training emphasize a minimal effective dose intending for individuals to engage in these behaviors long term. However, few studies have adequately examined the longitudinal time-course of strength adaptations to resistance training. Purpose: The aim of this study was to examine the time-course of strength development from minimal-dose resistance training in a large sample through retrospective training records from a private international exercise company. Methods: Data were available for analysis from 14,690 participants (60% female; aged 48 ± 11 years) having undergone minimal-dose resistance training (1x/week, single sets to momentary failure of six exercises) up to 352 weeks (~6.8 years) in length. Linear-log growth models examined strength development over time allowing random intercepts and slopes by participant. Results: All models demonstrated a robust linear-log relationship with the first derivatives (i.e., changes in strength with time) trending asymptotically such that by ~1-2 years strength had practically reached a "plateau." Sex, bodyweight, and age had minimal interaction effects. However, substantial strength gains were apparent; approximately ~30-50% gains over the first year reaching ~50-60% of baseline 6 years later. Conclusion: It is unclear if the "plateau" can be overcome through alternative approaches, or whether over the long-term strength gains differ. Considering this, our results support public health recommendations for minimal-dose resistance training for strength adaptations in adults.

Support for resource management: The role of information sources and affinitive trust

Public trust in natural resources agencies is critical for successful resource management and can facilitate an environment of management innovation and experimentation. However, building public trust in natural resources management is often challenging, particularly in resource management systems where people may receive information from a variety of different sources. We used a mail survey to analyze the relationship between affinitive trust (a measure of perceived shared values), information source use, and overall support for management in marine fisheries in the United States. The results of our mixed linear model showed that higher levels of affinitive trust and more use of official sources were most strongly associated with higher levels of support for management. The use of website sources (e.g., fishing websites and blogs), third-party sources (e.g., fishing organizations, advocacy groups, tv, and bait or tackle shops), older age, and higher levels of income were most associated with lower levels of support. The results imply that engendering higher levels of affinitive trust by promoting institutional values may lead to higher support for management.

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.

Associations Between Physiological Correlates of Cochlear Synaptopathy and Tinnitus in a Veteran Population

PURPOSE

Animal models and human temporal bones indicate that noise exposure is a risk factor for cochlear synaptopathy, a possible etiology of tinnitus. Veterans are exposed to high levels of noise during military service. Therefore, synaptopathy may explain the high rates of noise-induced tinnitus among Veterans. Although synaptopathy cannot be directly evaluated in living humans, animal models indicate that several physiological measures are sensitive to synapse loss, including the auditory brainstem response (ABR), the middle ear muscle reflex (MEMR), and the envelope following response (EFR). The purpose of this study was to determine whether tinnitus is associated with reductions in physiological correlates of synaptopathy that parallel animal studies.

METHOD

Participants with normal audiograms were grouped according to Veteran status and tinnitus report (Veterans with tinnitus, Veterans without tinnitus, and non-Veteran controls). The effects of being a Veteran with tinnitus on ABR, MEMR, and EFR measurements were independently modeled using Bayesian regression analysis.

RESULTS

Modeled point estimates of MEMR and EFR magnitude showed reductions for Veterans with tinnitus compared with non-Veterans, with the most evident reduction observed for the EFR. Two different approaches were used to provide context for the Veteran tinnitus effect on the EFR by comparing to age-related reductions in EFR magnitude and synapse numbers observed in previous studies. These analyses suggested that EFR magnitude/synapse counts were reduced in Veterans with tinnitus by roughly the same amount as over 20 years of aging.

CONCLUSION

These findings suggest that cochlear synaptopathy may contribute to tinnitus perception in noise-exposed Veterans.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.24347761.

Safety and upscaling of remote consulting for long-term conditions in primary health care in Nigeria and Tanzania (REaCH trials): stepped-wedge trials of training, mobile data allowance, and implementation

BACKGROUND

In-person health care poses risks to health workers and patients during pandemics. Remote consultations can mitigate these risks. The REaCH intervention comprised training and mobile data allowance provision for mobile phones to support remotely delivered primary care in Africa compared with no training and mobile data allowance. The aim of this study was to estimate the effects of REaCH among adults with non-communicable diseases on remote and face-to-face consultation rates, patient safety, and trustworthiness of consultations.

METHODS

In these two independent stepped-wedge cluster randomised controlled trials, we enrolled 20 primary care clusters in each of two settings (Oyo State, Nigeria, and Morogoro Region, Tanzania). Eligible clusters had 100 or more patients with diabetes, hypertension, and cardiovascular or pulmonary disease employing five health workers. Clusters were computer-randomised to one of ten (Nigeria) or one of seven (Tanzania) sequences to receive the REaCH intervention. Only outcome assessors were masked. Primary outcomes were consultation, prescription, and investigation rates, and trustworthiness collected monthly for 12 months (Nigeria) and 9 months (Tanzania) from open cohorts. Ten randomly sampled consulting patients per cluster-month completed patient reported outcome measures. This trial was registered with ISRCTN, ISRCTN17941313.

FINDINGS

Overall, 40 clusters comprising 8776 (Nigeria) and 3246 (Tanzania) patients' open cohort data were analysed (6377 [72·7%] of 8776 females in Nigeria, and 2235 [68·9%] of 3246 females in Tanzania). The mean age of the participants was 55·3 years (SD 13·9) in Nigeria and 59·2 years (14·2) in Tanzania. In Nigeria, no evidence of change in face-to-face consulting rate was observed (rate ratio [RR] 1·06, 95% CI 0·98 to 1·09; p=0·16); however, remote consultations increased four-fold (4·44, 1·34 to >10; p=0·01). In Tanzania, face-to-face (0·94, 0·61 to 1·67; p=0·99) and remote consulting rates (1·17, 0·56 to 5·57; p=0·39) were unchanged. There was no evidence of difference in prescribing rates (Nigeria: 1·05, 0·60 to 1·14; p=0·23; Tanzania: 0·92, 0·60 to 1·67; p=0·97), investigation rates (Nigeria: 1·06, 0·23 to 2·12; p=0·49; Tanzania: 1·15, 0·35 to 1·64; 0·58) or trustworthiness scores (Nigeria: mean difference 0·05, 95% CI -0·45 to 0·42; p=0·89; Tanzania: 0·07, -0·15 to 0·76; p=0·70).

INTERPRETATION

REaCH can be implemented and could improve intervention versus control health-care access. Remote consultations appear safe and trustworthy, supporting universal health coverage.

FUNDING

The UK Research and Innovation Collective Fund.

TRANSLATIONS

For the Swahili and Yoruba translations of the abstract see Supplementary Materials section.

Cardiovascular Outcomes of α-Blockers vs 5-α Reductase Inhibitors for Benign Prostatic Hyperplasia

Importance

The most prescribed class of medications for benign prostatic hyperplasia (BPH) is α-blockers (ABs). However, the cardiovascular safety profile of these medications among patients with BPH is not well understood.

Objective

To compare the safety of ABs vs 5-α reductase inhibitors (5-ARIs) for risk of adverse cardiovascular outcomes.

Design, Setting, and Participants

This active comparator, new-user cohort study was conducted using insurance claims data from a 20% random sample of Medicare beneficiaries from 2007 to 2019 to evaluate the 1-year risk of adverse cardiovascular outcomes. Males aged 66 to 90 years were indexed into the cohort at new use of an AB or 5-ARI. Twelve months of continuous enrollment and at least 1 diagnosis code for BPH within 12 months prior to initiation were required. Data were analyzed from January 2007 through December 2019.

Exposures

Exposure was defined by a qualifying prescription fill for an AB or 5-ARI after at least 12 months without a prescription for these drug classes.

Main Outcomes and Measures

Follow-up began at a qualified refill for the study drug. Primary study outcomes were hospitalization for heart failure (HF), composite major adverse cardiovascular events (MACE; hospitalization for stroke, myocardial infarction, or death), composite MACE or hospitalization for HF, and death. Inverse probability of treatment and censoring-weighted 1-year risks, risk ratios (RRs), and risk differences (RDs) were estimated for each outcome.

Results

Among 189 868 older adult males, there were 163 829 patients initiating ABs (mean [SD] age, 74.6 [6.2] years; 579 American Indian or Alaska Native [0.4%], 5890 Asian or Pacific Islander [3.6%], 9179 Black [5.6%], 10 610 Hispanic [6.5%], and 133 510 non-Hispanic White [81.5%]) and 26 039 patients initiating 5-ARIs (mean [SD] age, 75.3 [6.4] years; 76 American Indian or Alaska Native [0.3%], 827 Asian or Pacific Islander [3.2%], 1339 Black [5.1%], 1656 Hispanic [6.4%], and 21 605 non-Hispanic White [83.0%]). ABs compared with 5-ARIs were associated with an increased 1-year risk of MACE (8.95% [95% CI, 8.81%-9.09%] vs 8.32% [95% CI, 7.92%-8.72%]; RR = 1.08 [95% CI, 1.02-1.13]; RD per 1000 individuals = 6.26 [95% CI, 2.15-10.37]), composite MACE and HF (RR = 1.07; [95% CI, 1.03-1.12]; RD per 1000 individuals = 7.40 [95% CI, 2.88-11.93 ]), and death (RR = 1.07; [95% CI, 1.01-1.14]; RD per 1000 individuals = 3.85 [95% CI, 0.40-7.29]). There was no difference in risk for HF hospitalization alone.

Conclusions and Relevance

These results suggest that ABs may be associated with an increased risk of adverse cardiovascular outcomes compared with 5-ARIs. If replicated with more detailed confounder data, these results may have important public health implications given these medications' widespread use.

Evaluating a scalable ARCHES (Addressing Reproductive Coercion in Health Settings) model in government health facilities in Uasin Gishu county, Kenya: study protocol for a cluster-randomized controlled trial

BACKGROUND

Since 2013, the World Health Organization has recommended that reproductive coercion (RC) and intimate partner violence (IPV) be addressed within reproductive health services and, in 2018, the Lancet Commission on Sexual and Reproductive Health and Rights found that RC and IPV were significant contributors to unmet need for family planning (FP) and unintended pregnancy. In Kenya, the Ministry of Health (MOH) has made reduction of unintended pregnancy and gender-based violence a primary objective. Despite this need and guidance, no clinic-based intervention models outside of the U.S. (apart from the one described here) have demonstrated efficacy to improve FP use and reduce IPV or RC thereby reducing unintended pregnancy. ARCHES (Addressing Reproductive Coercion in Health Settings) is a brief, clinic-based intervention delivered by existing FP providers aiming to: (1) Increase women's ability to use FP without interference, (2) Provide a safe and supportive environment for IPV disclosure and referral to support services, and (3) Improve quality of FP counseling, including addressing RC and IPV. The objective of this study is to generate evidence on scaling integrated FP services (including FP, RC, and IPV) in public sector health facilities in Uasin Gishu county, Kenya via adaptation and implementation of ARCHES in partnership with the Kenya MOH.

METHODS

A cluster-randomized controlled trial paired with concurrent implementation science assessments will test effectiveness of the ARCHES model, adapted for scale by the Kenya MOH, in reducing unintended pregnancy. Female FP clients aged 15-49 years at selected sites will complete baseline surveys (immediately prior to receiving care), immediately post-visit exit surveys, and 6-month follow-up surveys. Provider surveys will assess changes in gender-equitable attitudes and self-efficacy to address violence reported by their clients. Costs associated with scaling ARCHES will be tracked and utilized in combination with results of the effectiveness trial to assess costs and cost-effectiveness relative to the standard of care.

DISCUSSION

This study will provide evidence of the effectiveness of a facility-based intervention to address RC and IPV within public sector FP services at scale, as adapted and implemented in Uasin Gishu county, Kenya. Trial registration Trial registered on 28 September 2023 with clinicaltrials.gov NCT06059196.

Surface electromyographic frequency characteristics of the quadriceps differ between continuous high- and low-torque isometric knee extension to momentary failure

Surface EMG (sEMG) has been used to compare loading conditions during exercise. Studies often explore mean/median frequencies. This potentially misses more nuanced electrophysiological differences between exercise tasks. Therefore, wavelet-based analysis was used to evaluate electrophysiological characteristics in the sEMG signal of the quadriceps under both higher- and lower-torque (70 % and 30 % of MVC, respectively) isometric knee extension performed to momentary failure. Ten recreationally active adult males with previous resistance training experience were recruited. Using a within-session, repeated-measures, randomised crossover design, participants performed isometric knee extension whilst sEMG was collected from the vastus medialis (VM), rectus femoris (RF) and vastus lateralis (VL). Mean signal frequency showed similar characteristics in each condition at momentary failure. However, individual wavelets revealed different frequency component changes between the conditions. All frequency components increased during the low-torque condition. But low-frequency components increased, and high-frequency components decreased, in intensity throughout the high-torque condition. This resulted in convergence of the low-torque and high-torque trial wavelet characteristics towards the end of the low-torque trial. Our results demonstrate a convergence of myoelectric signal properties between low- and high-torque efforts with fatigue via divergent signal adaptations. Further work should disentangle factors influencing frequency characteristics during exercise tasks.

Reducing the false discovery rate of preclinical animal research with Bayesian statistical decision criteria

The success of preclinical research hinges on exploratory and confirmatory animal studies. Traditional null hypothesis significance testing is a common approach to eliminate the chaff from a collection of drugs, so that only the most promising treatments are funneled through to clinical research phases. Balancing the number of false discoveries and false omissions is an important aspect to consider during this process. In this paper, we compare several preclinical research pipelines, either based on null hypothesis significance testing or based on Bayesian statistical decision criteria. We build on a recently published large-scale meta-analysis of reported effect sizes in preclinical animal research and elicit a non-informative prior distribution under which both approaches are compared. After correcting for publication bias and shrinkage of effect sizes in replication studies, simulations show that (i) a shift towards statistical approaches which explicitly incorporate the minimum clinically important difference reduces the false discovery rate of frequentist approaches and (ii) a shift towards Bayesian statistical decision criteria can improve the reliability of preclinical animal research by reducing the number of false-positive findings. It is shown that these benefits hold while keeping the number of experimental units low which are required for a confirmatory follow-up study. Results show that Bayesian statistical decision criteria can help in improving the reliability of preclinical animal research and should be considered more frequently in practice.

Liquid-assisted mechanochemical synthesis, crystallographic, theoretical and molecular docking study on HIV instasome of novel copper complexes: (µ-acetato)-bis(2,2'-bipyridine)-copper and bromidotetrakis(2-methyl-1H-imidazole)-copper bromide

In the present work the two new Cu(II) complexes, (µ-acetato)-bis(2,2'-bipyridine)-copper [Cu(bpy)2(CH3CO2)] and bromidotetrakis(2-methyl-1H-imidazole)-copper bromide [Cu(2-methylimid)4Br]Br have been synthesized by liquid assisted mechanochemical method. The [Cu(bpy)2(CH3CO2)] complex (1) and [Cu(2-methylimid)4Br]Br complex (2) characterised by IR and UV-visible spectroscopy and the structure are confirmed by XRD diffraction studies. Complex (1) crystallized in the Monoclinic with the space group of C2/c where a = 24.312(5) Å, b = 8.5892(18) Å, c = 14.559(3) Å, α = 90°, β = 106.177(7)° and γ = 90° and Complex (2) crystallized in the Tetragonal with the space group of P4nc, a = 9.9259(2) Å, b = 9.9259(2) Å, c = 10.9357(2) Å, α = 90°, β = 90° and γ = 90°. The complex (1) has distorted octahedral geometry where the acetate ligand showed bidentate bridging with the central metal ion and complex (2) has slightly deformed square pyramidal geometry. The HOMO-LUMO energy gap value and the low chemical potential showed that the complex (2) is stable and difficult to polarize compare to complex (1). The molecular docking study of complexes with the HIV instasome nucleoprotein showed the binding energy values - 7.1 and - 5.3 kcal/mol for complex (1) and complex (2) respectively. The negative binding energy values showed the complexes have affinity to bind with HIV instasome nucleoproteins. The in-silico pharmacokinetic study of the complex (1) and complex (2) showed non AMES toxicity, non-carcinogens and low honey Bee toxicity but weakly inhibit Human Ether-a-go-go-related gene.

veRification: an R Shiny application for laboratory method verification and validation

OBJECTIVES

According to international standards, clinical laboratories are required to verify the performance of assays prior to their implementation in routine practice. This typically involves the assessment of the assay's imprecision and trueness vs. appropriate targets. The analysis of these data is typically performed using frequentist statistical methods and often requires the use of closed source, proprietary software. The motivation for this paper was therefore to develop an open-source, freely available software capable of performing Bayesian analysis of verification data.

METHODS

The veRification application presented here was developed with the freely available R statistical computing environment, using the Shiny application framework. The codebase is fully open-source and is available as an R package on GitHub.

RESULTS

The developed application allows the user to analyze imprecision, trueness against external quality assurance, trueness against reference material, method comparison, and diagnostic performance data within a fully Bayesian framework (with frequentist methods also being available for some analyses).

CONCLUSIONS

Bayesian methods can have a steep learning curve and thus the work presented here aims to make Bayesian analyses of clinical laboratory data more accessible. Moreover, the development of the application and seeks to encourage the dissemination of open-source software within the community and provides a framework through which Shiny applications can be developed, shared, and iterated upon.

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.

Balanced resuscitation and earlier mortality end points: bayesian post hoc analysis of the PROPPR trial

Introduction

The Pragmatic Randomized Optimal Platelet and Plasma Ratios (PROPPR) trial failed to demonstrate a mortality difference for hemorrhaging patients receiving a balanced (1:1:1) vs a 1:1:2 resuscitation at 24 hours and 30 days. Recent guidelines recommend earlier mortality end points for hemorrhage-control trials, and the use of contemporary statistical methods. The aim of this post hoc analysis of the PROPPR trial was to evaluate the impact of a balanced resuscitation strategy at early resuscitation time points using a Bayesian analytical framework.

Methods

Bayesian hierarchical models were created to assess mortality differences at the 1, 3, 6, 12, 18, and 24 hours time points between study cohorts. Posterior probabilities and Bayes factors were calculated for each time point.

Results

A 1:1:1 resuscitation displayed a 96%, 99%, 94%, 92%, 96%, and 94% probability for mortality benefit at 1, 3, 6, 12, 18, and 24 hours, respectively, when compared with a 1:1:2 approach. Associated Bayes factors for each respective time period were 21.2, 142, 14.9, 11.4, 26.4, and 15.5, indicating 'strong' to 'decisive' supporting evidence in favor of balanced transfusions.

Conclusion

This analysis provides evidence in support that a 1:1:1 resuscitation has a high probability of mortality benefit when compared with a 1:1:2 strategy, especially at the newly defined more proximate time points during the resuscitative period. Researchers should consider using Bayesian approaches, along with more proximate end points when assessing hemorrhage-related mortality, for the analysis of future clinical trials.

Level of evidence

Level III/Therapeutic.

Association between the timing of childhood adversity and epigenetic patterns across childhood and adolescence: findings from the Avon Longitudinal Study of Parents and Children (ALSPAC) prospective cohort

BACKGROUND

Childhood adversity is a potent determinant of health across development and is associated with altered DNA methylation signatures, which might be more common in children exposed during sensitive periods in development. However, it remains unclear whether adversity has persistent epigenetic associations across childhood and adolescence. We aimed to examine the relationship between time-varying adversity (defined through sensitive period, accumulation of risk, and recency life course hypotheses) and genome-wide DNA methylation, measured three times from birth to adolescence, using data from a prospective, longitudinal cohort study.

METHODS

We first investigated the relationship between the timing of exposure to childhood adversity between birth and 11 years and blood DNA methylation at age 15 years in the Avon Longitudinal Study of Parents and Children (ALSPAC) prospective cohort study. Our analytic sample included ALSPAC participants with DNA methylation data and complete childhood adversity data between birth and 11 years. We analysed seven types of adversity (caregiver physical or emotional abuse, sexual or physical abuse [by anyone], maternal psychopathology, one-adult households, family instability, financial hardship, and neighbourhood disadvantage) reported by mothers five to eight times between birth and 11 years. We used the structured life course modelling approach (SLCMA) to identify time-varying associations between childhood adversity and adolescent DNA methylation. Top loci were identified using an R2 threshold of 0·035 (ie, ≥3·5% of DNA methylation variance explained by adversity). We attempted to replicate these associations using data from the Raine Study and Future of Families and Child Wellbeing Study (FFCWS). We also assessed the persistence of adversity-DNA methylation associations we previously identified from age 7 blood DNA methylation into adolescence and the influence of adversity on DNA methylation trajectories from ages 0-15 years.

FINDINGS

Of 13 988 children in the ALSPAC cohort, 609-665 children (311-337 [50-51%] boys and 298-332 [49-50%] girls) had complete data available for at least one of the seven childhood adversities and DNA methylation at 15 years. Exposure to adversity was associated with differences in DNA methylation at 15 years for 41 loci (R2 ≥0·035). Sensitive periods were the most often selected life course hypothesis by the SLCMA. 20 (49%) of 41 loci were associated with adversities occurring between age 3 and 5 years. Exposure to one-adult households was associated with differences in DNA methylation at 20 [49%] of 41 loci, exposure to financial hardship was associated with changes at nine (22%) loci, and physical or sexual abuse was associated with changes at four (10%) loci. We replicated the direction of associations for 18 (90%) of 20 loci associated with exposure to one-adult household using adolescent blood DNA methylation from the Raine Study and 18 (64%) of 28 loci using saliva DNA methylation from the FFCWS. The directions of effects for 11 one-adult household loci were replicated in both cohorts. Differences in DNA methylation at 15 years were not present at 7 years and differences identified at 7 years were no longer apparent by 15 years. We also identified six distinct DNA methylation trajectories from these patterns of stability and persistence.

INTERPRETATION

These findings highlight the time-varying effect of childhood adversity on DNA methylation profiles across development, which might link exposure to adversity to potential adverse health outcomes in children and adolescents. If replicated, these epigenetic signatures could ultimately serve as biological indicators or early warning signs of initiated disease processes, helping identify people at greater risk for the adverse health consequences of childhood adversity.

FUNDING

Canadian Institutes of Health Research, Cohort and Longitudinal Studies Enhancement Resources, EU's Horizon 2020, US National Institute of Mental Health.

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.

Repetition Performance, Rating of Perceived Discomfort, and Blood Lactate Responses to Different Rest Interval Lengths in Single-Joint and Multijoint Lower-Body Exercise

ABSTRACT

Rosa, A, Coleman, M, Haun, C, Grgic, J, and Schoenfeld, BJ. Repetition performance, rating of perceived discomfort, and blood lactate responses to different rest interval lengths in single-joint and multijoint lower-body exercise. J Strength Cond Res 37(7): 1350-1357, 2023-The purpose of this study was to examine the effects of different rest interval lengths (RILs) on repetition performance, rating of discomfort, and blood lactate responses during lower-body single-joint and multijoint exercises. This study used a counterbalanced design where each subject performed the Smith machine back squat (BS) and leg extension (LE) using 3 different RIL configurations (1, 2, and 3 minutes) in a randomized fashion. Data collection occurred over the span of 3 separate days. Volunteers were randomly allocated to perform the independent variables (RILs and exercises) in 1 of 12 potential configurations. The initial session was allotted for familiarization with the rating of discomfort scale and 10 repetition maximum testing. The other 2 sessions involved training with the different configurations of RIL length using both the BS and LE. Randomization ensured that the BS was performed first in one of the training sessions and the LE was performed first in the other session. Results indicated that longer RILs had a small positive effect on repetition performance, with longer rest durations allowing for more repetitions compared with shorter durations. The largest difference in repetition performance between RILs was observed between 1 minute and 2-3 minutes rest; there were trivial differences in repetition performance between 2 and 3 minutes rest for both the BS and LE. Blood lactate levels were slightly higher with longer RILs. Overall, BS showed greater increases in blood lactate compared with LE, and these differences were magnified over time. Exercise selection and RIL both influenced rating of discomfort, with LE producing less discomfort than BS and longer RILs reducing perceived discomfort. Our findings suggest that RIL influences the repetition performance, blood lactate, and rating of discomfort responses between single-joint and multijoint exercises.

Highlight results, don't hide them: Enhance interpretation, reduce biases and improve reproducibility

Most neuroimaging studies display results that represent only a tiny fraction of the collected data. While it is conventional to present "only the significant results" to the reader, here we suggest that this practice has several negative consequences for both reproducibility and understanding. This practice hides away most of the results of the dataset and leads to problems of selection bias and irreproducibility, both of which have been recognized as major issues in neuroimaging studies recently. Opaque, all-or-nothing thresholding, even if well-intentioned, places undue influence on arbitrary filter values, hinders clear communication of scientific results, wastes data, is antithetical to good scientific practice, and leads to conceptual inconsistencies. It is also inconsistent with the properties of the acquired data and the underlying biology being studied. Instead of presenting only a few statistically significant locations and hiding away the remaining results, studies should "highlight" the former while also showing as much as possible of the rest. This is distinct from but complementary to utilizing data sharing repositories: the initial presentation of results has an enormous impact on the interpretation of a study. We present practical examples and extensions of this approach for voxelwise, regionwise and cross-study analyses using publicly available data that was analyzed previously by 70 teams (NARPS; Botvinik-Nezer, et al., 2020), showing that it is possible to balance the goals of displaying a full set of results with providing the reader reasonably concise and "digestible" findings. In particular, the highlighting approach sheds useful light on the kind of variability present among the NARPS teams' results, which is primarily a varied strength of agreement rather than disagreement. Using a meta-analysis built on the informative "highlighting" approach shows this relative agreement, while one using the standard "hiding" approach does not. We describe how this simple but powerful change in practice-focusing on highlighting results, rather than hiding all but the strongest ones-can help address many large concerns within the field, or at least to provide more complete information about them. We include a list of practical suggestions for results reporting to improve reproducibility, cross-study comparisons and meta-analyses.

Trials and tribulations of statistical significance in biochemistry and omics

Over recent years many statisticians and researchers have highlighted that statistical inference would benefit from a better use and understanding of hypothesis testing, p-values, and statistical significance. We highlight three recommendations in the context of biochemical sciences. First recommendation: to improve the biological interpretation of biochemical data, do not use p-values (or similar test statistics) as thresholded values to select biomolecules. Second recommendation: to improve comparison among studies and to achieve robust knowledge, perform complete reporting of data. Third recommendation: statistical analyses should be reported completely with exact numbers (not as asterisks or inequalities). Owing to the high number of variables, a better use of statistics is of special importance in omic studies.

The Eccentric:Concentric Strength Ratio of Human Skeletal Muscle In Vivo: Meta-analysis of the Influences of Sex, Age, Joint Action, and Velocity

For decades, researchers have observed that eccentric (ECC) muscle strength is greater than concentric (CON) muscle strength. However, knowledge of the ECC:CON strength ratio is incomplete and might inform resistance exercise prescriptions. Our purposes were to determine the magnitude of the ECC:CON ratio of human skeletal muscle in vivo and explore if sex, age, joint actions/exercises, and movement velocity impact it. A total of 340 studies were identified through searches. It was possible to analyse 1516 ECC:CON ratios, aggregated from 12,546 individuals who made up 564 groups in 335 of the identified studies. Approximately 98% of measurements occurred on isokinetic machines. Bayesian meta-analyses were performed using log-ratios as response variables then exponentiated back to raw ratios. The overall main model estimate for the ECC:CON ratio was 1.41 (95% credible interval [CI] 1.38-1.44). The ECC:CON ratio was slightly less in men (1.38 [CI 1.34-1.41]) than women (1.47 [CI 1.43-1.51]), and greater in older adults (1.62 [CI 1.57-1.68]) than younger adults (1.39 [CI 1.36-1.42]). The ratio was similar between grouped upper-body (1.42 [CI 1.38-1.46]) and lower-body joint actions/exercises (1.40 [CI 1.37-1.44]). However, heterogeneity in the ratio existed across joint actions/exercises, with point estimates ranging from 1.32 to 2.61. The ECC:CON ratio was most greatly impacted by movement velocity, with a 0.20% increase in the ratio for every 1°/s increase in velocity. The results show that ECC muscle strength is ~ 40% greater than CON muscle strength. However, the ECC:CON ratio is greatly affected by movement velocity and to lesser extents age and sex. Differences between joint actions/exercises likely exist, but more data are needed to provide more precise estimates.