Meta‐analysis of variation: ecological and evolutionary applications and beyond

The potential of precision diabetology for type 2 diabetes treatment-evidence from a meta-regression for all-cause mortality from large cardiovascular outcome trials

AIMS

Two prerequisites must be met for the precision treatment approach to be beneficial for treated individuals. First, there must be treatment heterogeneity; second, in case of treatment heterogeneity, clinical predictors to identify people who would benefit from one treatment more than from others must be available. There is an established meta-regression approach to assess these two prerequisites that relies on measuring the variability of a clinical outcome after treatment in placebo-controlled randomised trials. We recently applied this approach to the treatment of type 2 diabetes for the clinical outcomes of glycaemic control and body weight and repeat it for the clinical outcome of all-cause mortality.

METHODS

We performed a meta-regression analysis using digitalized individual participant information on time to death from 10 large cardiovascular outcome trials (7563 deaths from 99,746 participants) on DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT-2 inhibitors with respect to the variability of all-cause mortality and its potential predictors after treatment.

RESULTS

The adjusted difference in log(SD) values of time to death between the verum and placebo arms was -0.036 (95%-CI: -0.059; -0.013), showing larger variability of time to death in the placebo arms. No clinical predictors were found to explain treatment heterogeneity.

CONCLUSIONS

This analysis suggests that the potential of the precision treatment approach in type 2 diabetes is low, at least with regard to improvement of all-cause mortality in population with high cardiovascular risk. This extends our previous findings for the clinical outcomes of glycaemic control and body weight.

Are some people more susceptible to placebos? A systematic review and meta-analysis of inter-individual variability in musculoskeletal pain

Existing data suggest placebo responses to treatments are small, but some people may be more likely to respond. We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) on interindividual variability in response to placebo interventions MEDLINE, EMBASE, CINAHL, Web of Science Core Collection, CENTRAL, and SPORTDiscus were searched from inception to September 2023. Trial registry searches, citation tracking, and searches for prior systematic reviews were completed. The PEDro scale assessed study quality. Random effects robust variance estimation estimated the log variability ratio (VR), identifying subgroups with varying responses. Twenty-six studies were included, comprising various musculoskeletal pain conditions. Analysis of pain intensity (VR: 1.06, 95%-confidence interval (CI):[0.97; 1.16], 95%-prediction interval (PI):[0.75; 1.51], p = 0.17, k = 26 studies, N = 52 outcomes, GRADE: low), physical function (VR: 1.14, 95%-CI:[0.97; 1.34], 95%-PI:[0.62; 2.11], p = 0.11, k = 19, N = 40, GRADE: low), and health-related quality of life (VR: 1.14, 95%-CI:[0.91; 1.41], 95%-PI:[0.72; 1.80], p = 0.19, k = 7, N = 13, GRADE: low) outcomes revealed minimal, non-statistically significant variability in placebo response compared to control. However, wide prediction intervals suggest uncertainty regarding individual response patterns. There are likely no distinct subgroups of people who are more likely to respond to placebo interventions in musculoskeletal pain; although the available data limits the certainty of this assessment. Future work should consider individual participant data meta-analyses to better elucidate potential responder subgroups and optimize treatment strategies for musculoskeletal pain. PERSPECTIVE: This study systematically reviewed and analyzed RCTs to assess interindividual variability in placebo responses for musculoskeletal pain. Findings suggest minimal variability in placebo response, with no distinct subgroups more likely to respond. Wide prediction intervals indicate uncertainty, highlighting the need for future individual participant data meta-analyses to better elucidate potential responder subgroups.

Incorporating stressor interactions into spatially explicit cumulative impact assessments

Human-induced stressors are impacting the oceans and reducing the biodiversity of marine ecosystems. The many stressors affecting marine environments do not act in isolation. However, their cumulative impact is difficult to predict. Most of the available methods for quantifying cumulative impacts on marine ecosystems sum the impact of individual stressors to estimate cumulative impact. We demonstrate how experimental evidence from interacting stressors can be accounted for in cumulative impact assessments. We adapted a widely used additive model to incorporate nonadditive stressor interactions into a marine spatially explicit cumulative impact assessment for seagrasses. We combined experimental data on the impact of multiple stressors with spatial data on stressor intensity to test whether stressor interactions impact seagrasses in a case study region in South Australia. We also assessed how uncertainty about cumulative impacts changes when uncertainty in stressor interactions is included in the impact mapping. The results from an additive spatial cumulative impact assessment model were compared with results from the model incorporating interactions. Cumulative effects from the interaction model were more variable than those produced by the additive model. Five of the 15 stressor interactions that we tested produced impacts that significantly deviated from those predicted by an additive model. Areas of our study region that showed the largest discrepancies between the additive and interactive outputs were also associated with higher uncertainty. Our study demonstrates that the inclusion of stressor interactions changes the pattern and intensity of modeled spatial cumulative impact. Additive models have the potential to misrepresent cumulative impact intensity and do not provide the opportunity for targeted mitigation measures when managing the interactive effects of stressors. Appropriate inclusion of interacting stressor data may have implications for the identification of key stressors and the subsequent spatial planning and management of marine ecosystems and biodiversity.

Sex-Specific Associations between Social Behavior, Its Predictability, and Fitness in a Wild Lizard

AbstractSocial environments impose a number of constraints on individuals' behavior. These constraints have been hypothesized to generate behavioral variation among individuals, social responsiveness, and within-individual behavioral consistency (also termed "predictability"). In particular, the social niche specialization hypothesis posits that higher levels of competition associated with higher population density should increase among-individual behavioral variation and individual predictability as a way to reduce conflicts. Being predictable should hence have fitness benefits in group-living animals. However, to date empirical studies of the fitness consequences of behavioral predictability remain scarce. In this study, we investigated the associations between social behavior, its predictability, and fitness in the eastern water dragon (Intellagama lesueurii), a wild gregarious lizard. Since this species is sexually dimorphic, we examined these patterns both between sexes and among individuals. Although females were more sociable than males, there was no evidence for sex differences in among-individual variation or predictability. However, females exhibited positive associations between social behavior, its predictability, and survival, while males exhibited only a positive association between mean social behavior and fitness. These findings hence partly support predictions from the social niche specialization hypothesis and suggest that the function of social predictability may be sex dependent.

Understanding variability: the role of meta-analysis of variance

Meta-analyses traditionally compare the difference in means between groups for one or more outcomes of interest. However, they do not compare the spread of data (variability), which could mean that important effects and/or subgroups are missed. To address this, methods to compare variability meta-analytically have recently been developed, making it timely to review them and consider their strengths, weaknesses, and implementation. Using published data from trials in major depression, we demonstrate how the spread of data can impact both overall effect size and the frequency of extreme observations within studies, with potentially important implications for conclusions of meta-analyses, such as the clinical significance of findings. We then describe two methods for assessing group differences in variability meta-analytically: the variance ratio (VR) and coefficient of variation ratio (CVR). We consider the reporting and interpretation of these measures and how they differ from the assessment of heterogeneity between studies. We propose general benchmarks as a guideline for interpreting VR and CVR effects as small, medium, or large. Finally, we discuss some important limitations and practical considerations of VR and CVR and consider the value of integrating variability measures into meta-analyses.

Plant Silicon Defences Suppress Herbivore Performance, but Mode of Feeding Is Key

The performance of herbivorous animals depends on the nutritional and defensive traits of the plants they consume. The uptake and deposition of biogenic silicon in plant tissues is arguably the most basic and ubiquitous anti-herbivore defence used by plants, especially grasses. We conducted meta-analyses of 150 studies reporting how vertebrate and invertebrate herbivores performed when feeding on silicon-rich plants relative to those feeding on low-silicon plants. Silicon levels were 52% higher and 32% more variable in silicon-rich plants compared to plants with low silicon, which resulted in an overall 33% decline in herbivore performance. Fluid-feeding herbivore performance was less adversely impacted (-14%) than tissue-chewing herbivores, including mammals (-45%), chewing arthropods (-33%) and plant-boring arthropods (-39%). Fluid-feeding arthropods with a wide diet breadth or those feeding on perennial plant species were mostly unaffected by silicon defences. Unlike many other plant defences, where diet specialisation often helps herbivores overcome their effects, silicon negatively impacts chewing herbivores regardless of diet breadth. We conclude that silicon defences primarily target chewing herbivores and impact vertebrate and invertebrate herbivores to a similar degree.

Treatment effect heterogeneity of cognitive behavioral therapy for insomnia - A meta-analysis

Investigation of the heterogeneity of the treatment effect (HTE) might guide the optimization of cognitive behavioral therapy for insomnia (CBT-I). This study examined HTE in CBT-I thereby analyzing if treatment setting, control group, different CBT-I components, and patient characteristics drive HTE. Randomized controlled trials investigating CBT-I were included. Bayesian random effect meta-regressions were specified to examine variances between the intervention and control groups regarding post-treatment symptom severity. Subgroup analyses analyzing treatment setting and control groups and covariate analysis analyzing treatment components and patient characteristics were specified. No significant HTE in CBT-I was found for the overall data set, settings and control groups. The covariate analyses yielded significant results for baseline severity and the treatment component relaxation therapy. Thus, this study identified potential causes for HTE in CBT-I for the first time, showing that it might be worthwhile to further examine possibilities for precision medicine in CBT-I.

Comparing type 1 and type 2 error rates of different tests for heterogeneous treatment effects

Psychologists are increasingly interested in whether treatment effects vary in randomized controlled trials. A number of tests have been proposed in the causal inference literature to test for such heterogeneity, which differ in the sample statistic they use (either using the variance terms of the experimental and control group, their empirical distribution functions, or specific quantiles), and in whether they make distributional assumptions or are based on a Fisher randomization procedure. In this manuscript, we present the results of a simulation study in which we examine the performance of the different tests while varying the amount of treatment effect heterogeneity, the type of underlying distribution, the sample size, and whether an additional covariate is considered. Altogether, our results suggest that researchers should use a randomization test to optimally control for type 1 errors. Furthermore, all tests studied are associated with low power in case of small and moderate samples even when the heterogeneity of the treatment effect is substantial. This suggests that current tests for treatment effect heterogeneity require much larger samples than those collected in current research.

The role of artificial intelligence in standardizing global longitudinal strain measurements in echocardiography

Aims

To evaluate the accuracy and feasibility of artificial intelligence (AI) in left ventricular global longitudinal strain (GLS) analysis as compared to conventional (Manual) and semi-automated (SemiAuto) method in echocardiography (Echo).

Methods and results

GLS validation was performed on 550 standard Echo exams by expert cardiologists. The performance of a beginner cardiologist without experience of GLS analysis was assessed on a subset of 90 exams. The AI employs fully automated view selection, classification, endocardial border tracing, and calculation of GLS from an entire Echo exam, while SemiAuto requires manual chamber view selection, and Manual involves full user input. Interobserver agreement was assessed using the intraclass correlation coefficient (ICC) for all three methods. Agreement of measures included Pearson's correlation (R) and Bland-Altman analysis [median bias; limits of agreement (LOA)]. With an 89% feasibility the AI showed good agreement with Manual (R = 0.92, bias = 0.7% and LOA: -3.5 to 4.8%) and with SemiAuto (r = 0.90, bias = 0.10% and LOA: -4.5 to 4%). ICCs for GLS were 1.0 for AI, 0.93 for SemiAuto, and 0.80 for Manual. After the 55th analysis, the beginner showed stable time performance with Manual (171 s), contrasting with the consistent performance of SemiAuto (85-69 s) from the beginning. The highest agreement between beginner and expert readers was achieved with AI (R = 1.00), followed by SemiAuto (R = 0.85) and Manual (R = 0.74).

Conclusion

Automated GLS analysis enhances efficiency and accuracy in cardiac diagnostics, particularly for novice users. Integration of automated solutions into routine clinical practice could yield more standardized results.

The Ecology of Hybrid Incompatibilities

Ecologically mediated selection against hybrids, caused by hybrid phenotypes fitting poorly into available niches, is typically viewed as distinct from selection caused by epistatic Dobzhansky-Muller hybrid incompatibilities. Here, we show how selection against transgressive phenotypes in hybrids manifests as incompatibility. After outlining our logic, we summarize current approaches for studying ecology-based selection on hybrids. We then quantitatively review QTL-mapping studies and find traits differing between parent taxa are typically polygenic. Next, we describe how verbal models of selection on hybrids translate to phenotypic and genetic fitness landscapes, highlighting emerging approaches for detecting polygenic incompatibilities. Finally, in a synthesis of published data, we report that trait transgression-and thus possibly extrinsic hybrid incompatibility in hybrids-escalates with the phenotypic divergence between parents. We discuss conceptual implications and conclude that studying the ecological basis of hybrid incompatibility will facilitate new discoveries about mechanisms of speciation.

The Effect of Temperature Variability on Biological Responses of Ectothermic Animals-A Meta-Analysis

Climate change is altering temperature means and variation, and both need to be considered in predictions underpinning conservation. However, there is no consensus in the literature regarding the effects of temperature fluctuations on biological functions. Fluctuations may affect biological responses because of inequalities from non-linear responses, endocrine regulation or exposure to damaging temperatures. Here we establish the current state of knowledge of how temperature fluctuations impact biological responses within individuals and populations compared to constant temperatures with the same mean. We conducted a meta-analysis of 143 studies on ectothermic animals (1492 effect sizes, 118 species). In this study, 89% of effect sizes were derived from diel cycles, but there were no significant differences between diel cycles and shorter (<8 h) or longer (>48 h) cycles in their effect on biological responses. We show that temperature fluctuations have little effect overall on trait mean and variance. Nonetheless, temperature fluctuations can be stressful: fluctuations increased 'gene expression' in aquatic animals, which was driven mainly by increased hsp70. Fluctuating temperatures also decreased longevity, and increased amplitudes had negative effects on population responses in aquatic organisms. We conclude that mean temperatures and extreme events such as heat waves are important to consider, but regular (particularly diel) temperature fluctuations are less so.

Meta-analysis of variance in tDCS effects on response inhibition

Deficiencies in response inhibition are associated with numerous mental health conditions, warranting innovative treatments. Transcranial direct current stimulation (tDCS), a non-invasive brain stimulation technique, modulates cortical excitability and has shown promise in improving response inhibition. However, tDCS effects on response inhibition often yield contradictory findings. Previous research emphasized the importance of inter-individual factors that are mostly ignored in conventional meta-analyses of mean effects. We aimed to fill this gap and promote the complementary use of the coefficient of variation ratio and standardized mean effects. The systematic literature search included single-session and sham-controlled tDCS studies utilizing stop-signal task or Go-NoGo tasks, analyzing 88 effect sizes from 53 studies. Considering the impact of inter-individual factors, we hypothesized that variances increase in the active versus sham tDCS. However, the results showed that variances between both groups did not differ. Additionally, analyzing standardized mean effects supported previous research showing an improvement in the stop-signal task but not in the Go-NoGo task following active tDCS. These findings suggest that inter-individual differences do not increase variances in response inhibition, implying that the heterogeneity cannot be attributed to higher variance in response inhibition during and after active tDCS. Furthermore, methodological considerations are crucial for tDCS efficacy.

Evolutionary drivers of sex-specific parasite prevalence in wild birds

Males and females often differ in ecology, behaviour and lifestyle, and these differences are expected to lead to sex differences in parasite susceptibility. However, neither the sex differences in parasite prevalence, nor their ecological and evolutionary drivers have been investigated across a broad range of taxa using phylogenetically corrected analyses. Using the most extensive dataset yet that includes 755 prevalence estimates from 151 wild bird species in a meta-analytic framework, here we compare sex differences in blood and gastrointestinal parasites. We show that despite sex differences in parasite infection being frequently reported in the literature, only Haemoproteus infections were more prevalent in females than in males. Notably, only seasonality was strongly associated with the sex-specific parasite prevalence of both Leucocytozoon and Haemoproteus, where birds showed greater female bias in prevalence during breeding periods compared to the non-breeding period. No other ecological or sexual selection variables were associated with sex-specific prevalence of parasite prevalence. We suggest that much of the variation in sex-biased prevalence could be idiosyncratic, and driven by local ecology and behavioural differences of the parasite and the host. Therefore, breeding ecology and sexual selection may only have a modest influence on sex-different parasite prevalence across wild birds.

Agreement Between Maximal Lactate Steady State and Critical Power in Different Sports: A Systematic Review and Bayesian's Meta-Regression

ABSTRACT

Borszcz, FK, de Aguiar, RA, Costa, VP, Denadai, BS, and de Lucas, RD. Agreement between maximal lactate steady state and critical power in different sports: A systematic review and Bayesian's meta-regression. J Strength Cond Res 38(6): e320-e339, 2024-This study aimed to systematically review the literature and perform a meta-regression to determine the level of agreement between maximal lactate steady state (MLSS) and critical power (CP). Considered eligible to include were peer-reviewed and "gray literature" studies in English, Spanish, and Portuguese languages in cyclical exercises. The last search was made on March 24, 2022, on PubMed, ScienceDirect, SciELO, and Google Scholar. The study's quality was evaluated using 4 criteria adapted from the COSMIN tool. The level of agreement was examined by 2 separate meta-regressions modeled under Bayesian's methods, the first for the mean differences and the second for the SD of differences. The searches yielded 455 studies, of which 36 studies were included. Quality scale revealed detailed methods and small samples used and that some studies lacked inclusion/exclusion criteria reporting. For MLSS and CP comparison, likely (i.e., coefficients with high probabilities) covariates that change the mean difference were the MLSS time frame and delta criteria of blood lactate concentration, MLSS number and duration of pauses, CP longest predictive trial duration, CP type of predictive trials, CP model fitting parameters, and exercise modality. Covariates for SD of the differences were the subject's maximal oxygen uptake, CP's longest predictive trial duration, and exercise modality. Traditional MLSS protocol and CP from 2- to 15-minute trials do not reflect equivalent exercise intensity levels; the proximity between MLSS and CP measures can differ depending on test design, and both MLSS and CP have inherent limitations. Therefore, comparisons between them should always consider these aspects.

Assessing the potential for precision medicine in body weight reduction with regard to type 2 diabetes mellitus therapies: A meta-regression analysis of 120 randomized controlled trials

AIMS

To assess the potential for precision medicine in type 2 diabetes by quantifying the variability of body weight as response to pharmacological treatment and to identify predictors which could explain this variability.

METHODS

We used randomized clinical trials (RCTs) comparing glucose-lowering drugs (including but not limited to sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists and thiazolidinediones) to placebo from four recent systematic reviews. RCTs reporting on body weight after treatment to allow for calculation of its logarithmic standard deviation (log[SD], i.e., treatment response heterogeneity) in verum (i.e., treatment) and placebo groups were included. Meta-regression analyses were performed with respect to variability of body weight after treatment and potential predictors.

RESULTS

A total of 120 RCTs with a total of 43 663 participants were analysed. A slightly larger treatment response heterogeneity was shown in the verum groups, with a median log(SD) of 2.83 compared to 2.79 from placebo. After full adjustment in the meta-regression model, the difference in body weight log(SD) was -0.026 (95% confidence interval -0.044; 0.008), with greater variability in the placebo groups. Scatterplots did not show any slope divergence (i.e., interaction) between clinical predictors and the respective treatment (verum or placebo).

CONCLUSIONS

We found no major treatment response heterogeneity in RCTs of glucose-lowering drugs for body weight reduction in type 2 diabetes. The precision medicine approach may thus be of limited value in this setting.

A systematic review and meta-analysis of unimodal and multimodal predation risk assessment in birds

Despite a wealth of studies documenting prey responses to perceived predation risk, researchers have only recently begun to consider how prey integrate information from multiple cues in their assessment of risk. We conduct a systematic review and meta-analysis of studies that experimentally manipulated perceived predation risk in birds and evaluate support for three alternative models of cue integration: redundancy/equivalence, enhancement, and antagonism. One key insight from our analysis is that the current theory, generally applied to study cue integration in animals, is incomplete. These theories specify the effects of increasing information level on mean, but not variance, in responses. In contrast, we show that providing multiple complementary cues of predation risk simultaneously does not affect mean response. Instead, as information richness increases, populations appear to assess risk more accurately, resulting in lower among-population variance in response to manipulations of perceived predation risk. We show that this may arise via a statistical process called maximum-likelihood estimation (MLE) integration. Our meta-analysis illustrates how explicit consideration of variance in responses can yield important biological insights.

Comparing long-term patterns of spread of native and invasive plants in a successional forest

A fundamental question in invasive plant ecology is whether invasive and native plants have different ecological roles. Differences in functional traits have been explored, but we lack a comparison of the factors affecting the spread of co-occurring natives and invasives. Some have proposed that to succeed, invasives would colonize a wider variety of sites, would disperse farther, or would be better at colonizing sites with more available light and soil nutrients than natives. We examined patterns of spread over 70 years in a regenerating forest in Connecticut, USA, where both native and invasive species acted as colonizers. We compared seven invasive and 19 native species in the characteristics of colonized plots, variation in these characteristics, and the importance of site variables for colonization. We found little support for the hypotheses that invasive plants succeed by dispersing farther than native plants or by having a broader range of site tolerances. Colonization by invasives was also not more dependent on light than colonization by natives. Like native understory species, invasive plants spread into closed-canopy forest and species-rich communities despite earlier predictions that these communities would resist invasion. The biggest differences were that soil nitrate and the initial land cover being open field increased the odds of colonization for most invasives but only for some natives. In large part, though, the spread of native and invasive plants was affected by similar factors.

New horizons for comparative studies and meta-analyses

Comparative analyses and meta-analyses are key tools to elucidate broad biological principles, yet the two approaches often appear different in purpose. We propose an integrated approach that can generate deeper insights into ecoevolutionary processes. Marrying comparative and meta-analytic approaches will allow for (i) a more accurate investigation of drivers of biological variation, (ii) a greater ability to account for sources of non-independence in experimental data, (iii) more effective control of publication bias, and (iv) improved transparency and reproducibility. Stronger integration of meta-analytic and comparative studies can also broaden the scope from species-centric investigations to community-level responses and function-valued traits (e.g., reaction norms). We illuminate commonalities, differences, and the transformative potential of combining these methodologies for advancing ecology and evolutionary biology.

Estimating heterogeneity of treatment effect in psychiatric clinical trials

Currently, placebo-controlled clinical trials report mean change and effect sizes, which masks information about heterogeneity of treatment effects (HTE). Here, we present a method to estimate HTE and evaluate the null hypothesis (H0) that a drug has equal benefit for all participants (HTE=0). We developed measure termed 'estimated heterogeneity of treatment effect' or eHTE, which estimates variability in drug response by comparing distributions between study arms. This approach was tested across numerous large placebo-controlled clinical trials. In contrast with variance-based methods which have not identified heterogeneity in psychiatric trials, reproducible instances of treatment heterogeneity were found. For example, heterogeneous response was found in a trial of venlafaxine for depression (peHTE=0.034), and two trials of dasotraline for binge eating disorder (Phase 2, peHTE=0.002; Phase 3, 4mg peHTE=0.011; Phase 3, 6mg peHTE=0.003). Significant response heterogeneity was detected in other datasets as well, often despite no difference in variance between placebo and drug arms. The implications of eHTE as a clinical trial outcomes independent from central tendency of the group is considered and the important of the eHTE method and results for drug developers, providers, and patients is discussed.

Meta-analysis of the implied distribution of callous-unemotional traits across sampling methods and informant

Callous-unemotional (CU) traits have been measured in a variety of sample-types (e.g., community or forensic) and from the perspective of different informants (e.g., self-report or parent-report) using the inventory of callous-unemotional traits total score (ICU-T). Although the positive association between CU traits and antisocial behavior is uncontroversial, the degree to which sample-types are different from each other has received little attention despite such knowledge being important for generalization and interpretation of research findings. To address this gap in the literature, we estimated the implied distribution of the ICU-T across sample-types, informants, and their interaction using meta-analytic models of sample means and variances. In unconditional models, we found that sample-type significantly moderated mean ICU-T scores but not variance, while informant significantly moderated the variance of ICU-T scores but not means. There was also a significant interaction between sample-type and informant. Mean parent-reported ICU-T scores were significantly lower than self-reported scores in community samples, but not significantly different in samples with elevated levels of antisocial behavior. Implications of our findings include improved research efficiency, the need for different ICU-T norms across informants, and greater understanding of informant biases.

Meta-analysis shows that wild large herbivores shape ecosystem properties and promote spatial heterogeneity

Megafauna (animals ≥45 kg) have probably shaped the Earth's terrestrial ecosystems for millions of years with pronounced impacts on biogeochemistry, vegetation, ecological communities and evolutionary processes. However, a quantitative global synthesis on the generality of megafauna effects on ecosystems is lacking. Here we conducted a meta-analysis of 297 studies and 5,990 individual observations across six continents to determine how wild herbivorous megafauna influence ecosystem structure, ecological processes and spatial heterogeneity, and whether these impacts depend on body size and environmental factors. Despite large variability in megafauna effects, we show that megafauna significantly alter soil nutrient availability, promote open vegetation structure and reduce the abundance of smaller animals. Other responses (14 out of 26), including, for example, soil carbon, were not significantly affected. Further, megafauna significantly increase ecosystem heterogeneity by affecting spatial heterogeneity in vegetation structure and the abundance and diversity of smaller animals. Given that spatial heterogeneity is considered an important driver of biodiversity across taxonomic groups and scales, these results support the hypothesis that megafauna may promote biodiversity at large scales. Megafauna declined precipitously in diversity and abundance since the late Pleistocene, and our results indicate that their restoration would substantially influence Earth's terrestrial ecosystems.

Association between olanzapine plasma concentrations and treatment response: A systematic review, meta-analysis and individual participant data meta-analysis

AIMS

By meta-analysing pooled studies and available individual participant data, we aim to provide new insight on olanzapine therapeutic drug monitoring in schizophrenia.

METHOD

We conducted a computerized search of bibliographic databases (Pubmed, Cochrane library, Web of Science and PsycINFO) to identify studies that assessed the relationship between olanzapine plasma concentration and the change in patients' clinical scores. We investigated this relationship with olanzapine plasma level 12h00 post-intake using a random-effects model.

RESULTS

7 studies were included in the pooled data analysis (781 patients). We found no difference in oral dose between responders and non-responders but a significantly higher concentration of 4.50 µg/L in responders (p < 0.01). Olanzapine concentration above the thresholds identified in each study was associated with response (odd ratio = 3.50, p = 0.0007). We identified that non-responder patients showed greater inter-individual variability than responders. In the individual data analysis (159 patients), we found no relationship between dose and clinical response but an association between plasma level and response in the shape of a parabolic curve. The Receiver Operating Characteristic curve found a threshold of 22.07 µg/L to identify responders (96% sensitivity, 86% specificity) and a threshold of 56.47 µg/L to identify a decreased probability of response.

CONCLUSION

In contrast to oral dose, our work confirmed that plasma olanzapine levels are associated with clinical response and should therefore be used to optimise treatment. We determined a treatment response threshold of 22.07 µg/L and suggest that a concentration above the therapeutic window may result in a decreased response.

Range expansion is both slower and more variable with rapid evolution across a spatial gradient in temperature

Rapid evolution in colonising populations can alter our ability to predict future range expansions. Recent theory suggests that the dynamics of replicate range expansions are less variable, and hence more predictable, with increased selection at the expanding range front. Here, we test whether selection from environmental gradients across space produces more consistent range expansion speeds, using the experimental evolution of replicate duckweed populations colonising landscapes with and without a temperature gradient. We found that the range expansion across a temperature gradient was slower on average, with range-front populations displaying higher population densities, and genetic signatures and trait changes consistent with directional selection. Despite this, we found that with a spatial gradient range expansion speed became more variable and less consistent among replicates over time. Our results therefore challenge current theory, highlighting that chance can still shape the genetic response to selection to influence our ability to predict range expansion speeds.

Male harm suppresses female fitness, affecting the dynamics of adaptation and evolutionary rescue

One of the most pressing questions we face as biologists is to understand how climate change will affect the evolutionary dynamics of natural populations and how these dynamics will in turn affect population recovery. Increasing evidence shows that sexual selection favors population viability and local adaptation. However, sexual selection can also foster sexual conflict and drive the evolution of male harm to females. Male harm is extraordinarily widespread and has the potential to suppress female fitness and compromise population growth, yet we currently ignore its net effects across taxa or its influence on local adaptation and evolutionary rescue. We conducted a comparative meta-analysis to quantify the impact of male harm on female fitness and found an overall negative effect of male harm on female fitness. Negative effects seem to depend on proxies of sexual selection, increasing inversely to the female relative size and in species with strong sperm competition. We then developed theoretical models to explore how male harm affects adaptation and evolutionary rescue. We show that, when sexual conflict depends on local adaptation, population decline is reduced, but at the cost of slowing down genetic adaptation. This trade-off suggests that eco-evolutionary feedback on sexual conflict can act like a double-edged sword, reducing extinction risk by buffering the demographic costs of climate change, but delaying genetic adaptation. However, variation in the mating system and male harm type can mitigate this trade-off. Our work shows that male harm has widespread negative effects on female fitness and productivity, identifies potential mechanistic factors underlying variability in such costs across taxa, and underscores how acknowledging the condition-dependence of male harm may be important to understand the demographic and evolutionary processes that impact how species adapt to environmental change.

The magnitude and variability of neurocognitive performance in first-episode psychosis: a systematic review and meta-analysis of longitudinal studies

Neurocognitive deficits are a core feature of psychotic disorders, but it is unclear whether they affect all individuals uniformly. The aim of this systematic review and meta-analysis was to synthesize the evidence on the magnitude, progression, and variability of neurocognitive functioning in individuals with first-episode psychosis (FEP). A multistep literature search was conducted in several databases up to November 1, 2022. Original studies reporting on neurocognitive functioning in FEP were included. The researchers extracted the data and clustered the neurocognitive tasks according to the seven Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) domains and six additional domains. Random-effect model meta-analyses, assessment of publication biases and study quality, and meta-regressions were conducted. The primary effect size reported was Hedges g of (1) neurocognitive functioning in individuals at FEP measuring differences with healthy control (HC) individuals or (2) evolution of neurocognitive impairment across study follow-up intervals. Of 30,384 studies screened, 54 were included, comprising 3,925 FEP individuals and 1,285 HC individuals. Variability analyses indicated greater variability in FEP compared to HC at baseline and follow-up. We found better neurocognitive performance in the HC group at baseline and follow-up but no differences in longitudinal neurocognitive changes between groups. Across the 13 domains, individuals with FEP showed improvement from baseline in all studied domains, except for visual memory. Metaregressions showed some differences in several of the studied domains. The findings suggest that individuals with FEP have marked cognitive impairment, but there is greater variability in cognitive functioning in patients than in HC. This suggests that subgroups of individuals suffer severe disease-related cognitive impairments, whereas others may be much less affected. While these impairments seem stable in the medium term, certain indicators may suggest potential further decline in the long term for a specific subgroup of individuals, although more research is needed to clarify this. Overall, this study highlights the need for tailored neurocognitive interventions for individuals with FEP based on their specific deficits and progression.

Atypical hemispheric lateralization of brain function and structure in autism: a comprehensive meta-analysis study

BACKGROUND

Characteristic changes in the asymmetric nature of the human brain are associated with neurodevelopmental differences related to autism. In people with autism, these differences are thought to affect brain structure and function, although the structural and functional bases of these defects are yet to be fully characterized.

METHODS

We applied a comprehensive meta-analysis to resting-state functional and structural magnetic resonance imaging datasets from 370 people with autism and 498 non-autistic controls using seven datasets of the Autism Brain Imaging Data Exchange Project. We studied the meta-effect sizes based on standardized mean differences and standard deviations (s.d.) for lateralization of gray matter volume (GMV), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo). We examined the functional correlates of atypical laterality through an indirect annotation approach followed by a direct correlation analysis with symptom scores.

RESULTS

In people with autism, 85, 51, and 51% of brain regions showed a significant diagnostic effect for lateralization in GMV, fALFF, and ReHo, respectively. Among these regions, 35.7% showed overlapping differences in lateralization in GMV, fALFF, and ReHo, particularly in regions with functional annotations for language, motor, and perceptual functions. These differences were associated with clinical measures of reciprocal social interaction, communication, and repetitive behaviors. A meta-analysis based on s.d. showed that people with autism had lower variability in structural lateralization but higher variability in functional lateralization.

CONCLUSION

These findings highlight that atypical hemispheric lateralization is a consistent feature in autism across different sites and may be used as a neurobiological marker for autism.

Effect of bovine respiratory disease on the respiratory microbiome: a meta-analysis

Background

Bovine respiratory disease (BRD) is the most devastating disease affecting beef and dairy cattle producers in North America. An emerging area of interest is the respiratory microbiome's relationship with BRD. However, results regarding the effect of BRD on respiratory microbiome diversity are conflicting.

Results

To examine the effect of BRD on the alpha diversity of the respiratory microbiome, a meta-analysis analyzing the relationship between the standardized mean difference (SMD) of three alpha diversity metrics (Shannon's Diversity Index (Shannon), Chao1, and Observed features (OTUs, ASVs, species, and reads) and BRD was conducted. Our multi-level model found no difference in Chao1 and Observed features SMDs between calves with BRD and controls. The Shannon SMD was significantly greater in controls compared to that in calves with BRD. Furthermore, we re-analyzed 16S amplicon sequencing data from four previously published datasets to investigate BRD's effect on individual taxa abundances. Additionally, based on Bray Curtis and Jaccard distances, health status, sampling location, and dataset were all significant sources of variation. Using a consensus approach based on RandomForest, DESeq2, and ANCOM-BC2, we identified three differentially abundant amplicon sequence variants (ASVs) within the nasal cavity, ASV5_Mycoplasma, ASV19_Corynebacterium, and ASV37_Ruminococcaceae. However, no ASVs were differentially abundant in the other sampling locations. Moreover, based on SECOM analysis, ASV37_Ruminococcaceae had a negative relationship with ASV1_Mycoplasma_hyorhinis, ASV5_Mycoplasma, and ASV4_Mannheimia. ASV19_Corynebacterium had negative relationships with ASV1_Mycoplasma_hyorhinis, ASV4_Mannheimia, ASV54_Mycoplasma, ASV7_Mycoplasma, and ASV8_Pasteurella.

Conclusions

Our results confirm a relationship between bovine respiratory disease and respiratory microbiome diversity and composition, which provide additional insight into microbial community dynamics during BRD development. Furthermore, as sampling location and sample processing (dataset) can also affect results, consideration should be taken when comparing results across studies.

How amenable is type 2 diabetes treatment for precision diabetology? A meta-regression of glycaemic control data from 174 randomised trials

AIMS/HYPOTHESIS

There are two prerequisites for the precision medicine approach to be beneficial for treated individuals. First, there must be treatment heterogeneity; second, in the case of treatment heterogeneity, we need to detect clinical predictors to identify people who would benefit from one treatment more than from others. There is an established meta-regression approach to assess these two prerequisites that relies on measuring the variability of a clinical outcome after treatment in placebo-controlled randomised trials. Our aim was to apply this approach to the treatment of type 2 diabetes.

METHODS

We performed a meta-regression analysis using information from 174 placebo-controlled randomised trials with 178 placebo and 272 verum (i.e. active treatment) arms including 86,940 participants with respect to the variability of glycaemic control as assessed by HbA1c after treatment and its potential predictors.

RESULTS

The adjusted difference in log(SD) values between the verum and placebo arms was 0.037 (95% CI: 0.004, 0.069). That is, we found a small increase in the variability of HbA1c values after treatment in the verum arms. In addition, one potentially relevant predictor for explaining this increase, drug class, was observed, and GLP-1 receptor agonists yielded the largest differences in log(SD) values.

CONCLUSIONS/INTERPRETATION

The potential of the precision medicine approach in the treatment of type 2 diabetes is modest at best, at least with regard to an improvement in glycaemic control. Our finding of a larger variability after treatment with GLP-1 receptor agonists in individuals with poor glycaemic control should be replicated and/or validated with other clinical outcomes and with different study designs.

FUNDING

The research reported here received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

DATA AVAILABILITY

Two datasets (one for the log[SD] and one for the baseline-corrected log[SD]) to reproduce the analyses from this paper are available on https://zenodo.org/record/7956635 .

Contemporary changes in phenotypic variation, and the potential consequences for eco-evolutionary dynamics

Most studies assessing rates of phenotypic change focus on population mean trait values, whereas a largely overlooked additional component is changes in population trait variation. Theoretically, eco-evolutionary dynamics mediated by such changes in trait variation could be as important as those mediated by changes in trait means. To date, however, no study has comprehensively summarised how phenotypic variation is changing in contemporary populations. Here, we explore four questions using a large database: How do changes in trait variances compare to changes in trait means? Do different human disturbances have different effects on trait variance? Do different trait types have different effects on changes in trait variance? Do studies that established a genetic basis for trait change show different patterns from those that did not? We find that changes in variation are typically small; yet we also see some very large changes associated with particular disturbances or trait types. We close by interpreting and discussing the implications of our findings in the context of eco-evolutionary studies.

Meta-analysis of variation in sport and exercise science: Examples of application within resistance training research

Meta-analysis has become commonplace within sport and exercise science for synthesising and summarising empirical studies. However, most research in the field focuses upon mean effects, particularly the effects of interventions to improve outcomes such as fitness or performance. It is thought that individual responses to interventions vary considerably. Hence, interest has increased in exploring precision or personalised exercise approaches. Not only is the mean often affected by interventions, but variation may also be impacted. Exploration of variation in studies such as randomised controlled trials (RCTs) can yield insight into interindividual heterogeneity in response to interventions and help determine generalisability of effects. Yet, larger samples sizes than those used for typical mean effects are required when probing variation. Thus, in a field with small samples such as sport and exercise science, exploration of variation through a meta-analytic framework is appealing. Despite the value of embracing and exploring variation alongside mean effects in sport and exercise science, it is rarely applied to research synthesis through meta-analysis. We introduce and evaluate different effect size calculations along with models for meta-analysis of variation using relatable examples from resistance training RCTs.

Association Between Clozapine Plasma Concentrations and Treatment Response: A Systematic Review, Meta-analysis and Individual Participant Data Meta-analysis

BACKGROUND AND OBJECTIVES

Although therapeutic drug monitoring of clozapine is recommended, its optimisation is often adjusted only on the basis of dosage. The aim of this study was to assess the link between clozapine plasma concentrations and clinical response by a meta-analysis of published studies and by an individual participant data meta-analysis.

METHODS

We conducted a computerised search of bibliographic databases (EMBASE, PubMed, Clinical Trials, and Web of Science) to identify studies that assessed the relationship between clozapine serum or plasma concentrations and clinical efficacy. Using pooled data, we investigated the association between improvement of clinical outcome and clozapine or norclozapine plasma concentrations, the sum of clozapine and norclozapine plasma concentrations, and the coefficient of variation of clozapine plasma concentrations. Using available individual data, we assessed the relationship between clozapine plasma concentrations and clinical response (changes in the Brief Psychiatric Rating Scale score) and identified a threshold level for a favourable clinical response.

RESULTS

Fifteen studies satisfied inclusion criteria. Our meta-analysis showed that responders had clozapine plasma concentrations that were, on average, 117 ng/mL higher than non-responders. The patients with plasma clozapine concentrations above the thresholds identified in each study had a higher likelihood of responding (odds ratio = 2.94, p < 0.001). Norclozapine plasma concentrations were not associated with a clinical response. The meta-analysis of individual data supported this result and confirmed the link between clozapine concentrations and a change in the Brief Psychiatric Rating Scale score and/or the probability of clinical response. Finally, with the analysis of the coefficient of variation of clozapine plasma concentrations, we found that a greater inter-individual fluctuation in plasma concentrations was associated with a loss of clinical response.

CONCLUSIONS

Our work confirmed that, in contrast to clozapine doses, clozapine plasma concentrations were related to a favourable clinical response, with a mean difference between responders and non-responders of 117 ng/mL. A threshold for a treatment response of 407 ng/mL was determined, with a high discriminatory capacity, and a sensitivity and specificity of 71% and 89.1%, respectively.

The influence of immune challenges on the mean and variance in reproductive investment: a meta-analysis of the terminal investment hypothesis

Finding the optimal balance between survival and reproduction is a central puzzle in life-history theory. The terminal investment hypothesis predicts that when individuals encounter a survival threat that compromises future reproductive potential, they will increase immediate reproductive investment to maximise fitness. Despite decades of research on the terminal investment hypothesis, findings remain mixed. We examined the terminal investment hypothesis with a meta-analysis of studies that measured reproductive investment of multicellular iteroparous animals after a non-lethal immune challenge. We had two main aims. The first was to investigate whether individuals, on average, increase reproductive investment in response to an immune threat, as predicted by the terminal investment hypothesis. We also examined whether such responses vary adaptively on factors associated with the amount of reproductive opportunities left (residual reproductive value) in the individuals, as predicted by the terminal investment hypothesis. The second was to provide a quantitative test of a novel prediction based on the dynamic threshold model: that an immune threat increases between-individual variance in reproductive investment. Our results provided some support for our hypotheses. Older individuals, who are expected to have lower residual reproductive values, showed stronger mean terminal investment response than younger individuals. In terms of variance, individuals showed a divergence in responses, leading to an increase in variance. This increase in variance was especially amplified in longer-living species, which was consistent with our prediction that individuals in longer-living species should respond with greater individual variation due to increased phenotypic plasticity. We find little statistical evidence of publication bias. Together, our results highlight the need for a more nuanced view on the terminal investment hypothesis and a greater focus on the factors that drive individual responses.

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.

Quantitative evidence synthesis: a practical guide on meta-analysis, meta-regression, and publication bias tests for environmental sciences

Meta-analysis is a quantitative way of synthesizing results from multiple studies to obtain reliable evidence of an intervention or phenomenon. Indeed, an increasing number of meta-analyses are conducted in environmental sciences, and resulting meta-analytic evidence is often used in environmental policies and decision-making. We conducted a survey of recent meta-analyses in environmental sciences and found poor standards of current meta-analytic practice and reporting. For example, only ~ 40% of the 73 reviewed meta-analyses reported heterogeneity (variation among effect sizes beyond sampling error), and publication bias was assessed in fewer than half. Furthermore, although almost all the meta-analyses had multiple effect sizes originating from the same studies, non-independence among effect sizes was considered in only half of the meta-analyses. To improve the implementation of meta-analysis in environmental sciences, we here outline practical guidance for conducting a meta-analysis in environmental sciences. We describe the key concepts of effect size and meta-analysis and detail procedures for fitting multilevel meta-analysis and meta-regression models and performing associated publication bias tests. We demonstrate a clear need for environmental scientists to embrace multilevel meta-analytic models, which explicitly model dependence among effect sizes, rather than the commonly used random-effects models. Further, we discuss how reporting and visual presentations of meta-analytic results can be much improved by following reporting guidelines such as PRISMA-EcoEvo (Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Ecology and Evolutionary Biology). This paper, along with the accompanying online tutorial, serves as a practical guide on conducting a complete set of meta-analytic procedures (i.e., meta-analysis, heterogeneity quantification, meta-regression, publication bias tests and sensitivity analysis) and also as a gateway to more advanced, yet appropriate, methods.

Publication bias impacts on effect size, statistical power, and magnitude (Type M) and sign (Type S) errors in ecology and evolutionary biology

Collaborative efforts to directly replicate empirical studies in the medical and social sciences have revealed alarmingly low rates of replicability, a phenomenon dubbed the 'replication crisis'. Poor replicability has spurred cultural changes targeted at improving reliability in these disciplines. Given the absence of equivalent replication projects in ecology and evolutionary biology, two inter-related indicators offer the opportunity to retrospectively assess replicability: publication bias and statistical power. This registered report assesses the prevalence and severity of small-study (i.e., smaller studies reporting larger effect sizes) and decline effects (i.e., effect sizes decreasing over time) across ecology and evolutionary biology using 87 meta-analyses comprising 4,250 primary studies and 17,638 effect sizes. Further, we estimate how publication bias might distort the estimation of effect sizes, statistical power, and errors in magnitude (Type M or exaggeration ratio) and sign (Type S). We show strong evidence for the pervasiveness of both small-study and decline effects in ecology and evolution. There was widespread prevalence of publication bias that resulted in meta-analytic means being over-estimated by (at least) 0.12 standard deviations. The prevalence of publication bias distorted confidence in meta-analytic results, with 66% of initially statistically significant meta-analytic means becoming non-significant after correcting for publication bias. Ecological and evolutionary studies consistently had low statistical power (15%) with a 4-fold exaggeration of effects on average (Type M error rates = 4.4). Notably, publication bias reduced power from 23% to 15% and increased type M error rates from 2.7 to 4.4 because it creates a non-random sample of effect size evidence. The sign errors of effect sizes (Type S error) increased from 5% to 8% because of publication bias. Our research provides clear evidence that many published ecological and evolutionary findings are inflated. Our results highlight the importance of designing high-power empirical studies (e.g., via collaborative team science), promoting and encouraging replication studies, testing and correcting for publication bias in meta-analyses, and adopting open and transparent research practices, such as (pre)registration, data- and code-sharing, and transparent reporting.

The Headphone and Loudspeaker Test - Part I: Suggestions for controlling characteristics of playback devices in internet experiments

In internet experiments on auditory perception, playback devices may be a confounding variable reducing internal validity. A procedure to remotely test multiple characteristics of playback devices does not currently exist. Thus, the main goals of this study were to (i) develop and (ii) evaluate a comprehensive, efficient, and easy-to-handle test procedure for the reliable control and identification of playback device characteristics in online experiments. Based on a counting task paradigm, the first part of the Headphone and Loudspeaker Test (HALT-Part I) was developed with which researchers can standardize sound level adjustments, detect stereo/mono playback, and assess lower frequency limits. In a laboratory study (N = 40), HALT-Part I was evaluated with four playback devices (circumaural and intra-aural headphones; external and laptop loudspeakers). Beforehand, the acoustical properties of all playback devices had been measured (e.g., sound pressure level, frequency response, total harmonic distortion). The analysis suggested that HALT-Part I has high test-retest reliability (rtt = .90 for level adjustment and rtt = .79 for stereo/mono detection) and is an efficient (3.5 minutes for completion) method to remotely test playback devices and listening conditions (sound level, stereo/mono playback). The procedure can help improve data quality in internet experiments.

Submaximal Fitness Test in Team Sports: A Systematic Review and Meta-Analysis of Exercise Heart Rate Measurement Properties

BACKGROUND

Submaximal fitness tests (SMFT) are a pragmatic approach for evaluating athlete's physiological state, due to their time-efficient nature, low physiological burden and relative ease of administration in team sports settings. While a variety of outcome measures can be collected during SMFT, exercise heart rate (HRex) is the most popular. Understanding the measurement properties of HRex can support the interpretation of data and assist in decision making regarding athlete's current physiological state and training effects.

OBJECTIVES

The aims of our systematic review and meta-analysis were to: (1) establish meta-analytic estimates of SMFT HRex reliability and convergent validity and (2) examine the moderating influence of athlete and protocol characteristics on the magnitude of these measurement properties.

METHODS

We conducted a systematic literature search with MEDLINE, Scopus and Web of Science databases for studies published up until January 2022 since records began. Studies were considered for inclusion when they  included team sports athletes and the reliability and/or convergent validity of SMFT HRex was investigated. Reliability statistics included the group mean difference (MD), typical error of measurement (TE) and intraclass correlation coefficient (ICC) derived from test-retest(s) designs. Pearson's correlation coefficient (r) describing the relationship between SMFT HRex and a criterion measure of endurance performance was used as the statistic for convergent validity. Qualitative assessment was conducted using risk of bias assessment tool for non-randomised studies. Mixed-effects, multilevel hierarchical models combined with robust variance estimate tests were performed to obtain pooled measurement property estimates, effect heterogeneity, and meta-regression of modifying effects.

RESULTS

The electronic search yielded 21 reliability (29 samples) and 20 convergent validity (29 samples) studies that met the inclusion criteria. Reliability meta-analysis indicated good absolute (MD = 0.5 [95% CI 0.1 to 0.9] and TE = 1.6 [95% CI 1.4 to 1.9] % points), and high relative (ICC = 0.88 [95% CI 0.84 to 0.91]) reliability. Convergent validity meta-analysis indicated an inverse, large relationship (r = - 0.58 [95% CI - 0.62 to - 0.54]) between SMFT HRex and endurance tests performance. Meta-regression analyses suggested no meaningful influence of SMFT protocol or athlete characteristics on reliability or convergent validity estimates.

CONCLUSIONS

Submaximal fitness test HRex is a reliable and valid proxy indicator of endurance performance in team sport athletes. Athlete and SMFT protocol characteristics do not appear to have a meaningful effect on these measurement properties. Practitioners may implement SMFT HRex for monitoring athlete's physiological state by using our applied implications to guide the interpretation of data in practice. Future research should examine the utility of SMFT HRex to track within-athlete changes in aerobic capacity, as well as any further possible effects of SMFT protocols design elements or HRex analytical methods on measurement properties. Registration Protocol registration can be found in Open Science Framework and available through https://doi.org/10.17605/OSF.IO/9C2JV .

Advanced methods and implementations for the meta-analyses of animal models: Current practices and future recommendations

Meta-analytic techniques have been widely used to synthesize data from animal models of human diseases and conditions, but these analyses often face two statistical challenges due to complex nature of animal data (e.g., multiple effect sizes and multiple species): statistical dependency and confounding heterogeneity. These challenges can lead to unreliable and less informative evidence, which hinders the translation of findings from animal to human studies. We present a literature survey of meta-analysis using animal models (animal meta-analysis), showing that these issues are not adequately addressed in current practice. To address these challenges, we propose a meta-analytic framework based on multilevel (linear mixed-effects) models. Through conceptualization, formulations, and worked examples, we illustrate how this framework can appropriately address these issues while allowing for testing new questions. Additionally, we introduce other advanced techniques such as multivariate models, robust variance estimation, and meta-analysis of emergent effect sizes, which can deliver robust inferences and novel biological insights. We also provide a tutorial with annotated R code to demonstrate the implementation of these techniques.

Extended parental provisioning and variation in vertebrate brain sizes

Large brains provide adaptive cognitive benefits but require unusually high, near-constant energy inputs and become fully functional well after their growth is completed. Consequently, young of most larger-brained endotherms should not be able to independently support the growth and development of their own brains. This paradox is solved if the evolution of extended parental provisioning facilitated brain size evolution. Comparative studies indeed show that extended parental provisioning coevolved with brain size and that it may improve immature survival. The major role of extended parental provisioning supports the idea that the ability to sustain the costs of brains limited brain size evolution.

A robust and readily implementable method for the meta-analysis of response ratios with and without missing standard deviations

The log response ratio, lnRR, is the most frequently used effect size statistic for meta-analysis in ecology. However, often missing standard deviations (SDs) prevent estimation of the sampling variance of lnRR. We propose new methods to deal with missing SDs via a weighted average coefficient of variation (CV) estimated from studies in the dataset that do report SDs. Across a suite of simulated conditions, we find that using the average CV to estimate sampling variances for all observations, regardless of missingness, performs with minimal bias. Surprisingly, even with missing SDs, this simple method outperforms the conventional approach (basing each effect size on its individual study-specific CV) with complete data. This is because the conventional method ultimately yields less precise estimates of the sampling variances than using the pooled CV from multiple studies. Our approach is broadly applicable and can be implemented in all meta-analyses of lnRR, regardless of 'missingness'.

Quantifying Exposure and Intra-Individual Reliability of High-Speed and Sprint Running During Sided-Games Training in Soccer Players: A Systematic Review and Meta-analysis

BACKGROUND

Sided games (i.e., small sided, medium sided, large sided) involve tactical, technical, physical, and psychological elements and are commonly implemented in soccer training. Although soccer sided-games research is plentiful, a meta-analytical synthesis of external load exposure during sided games is lacking.

OBJECTIVE

The objective of this systematic review and meta-analysis was to: (1) synthesize the evidence on high-speed and sprint running exposure induced by sided games in adult soccer players, (2) establish pooled estimates and intra-individual reliability for high-speed and sprint running exposure, and (3) explore the moderating effects of game format and playing constraints.

METHODS

A literature search was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. Four databases (PubMed/MEDLINE, Scopus, SPORTDiscus, Web of Science Core Collection) were systematically searched up to 25 January, 2022. Eligibility criteria were adult soccer players (population); training programs incorporating sided games (intervention); game manipulations including number of players, pitch dimension, and game orientation (comparator); and high-speed, very high-speed, and sprint relative (m[Formula: see text]min^-1) running distances and associated intra-individual reliability (outcome). Eligible study risk of bias was evaluated using RoBANS. Pooled estimates for high-speed and sprint running exposure, and their intra-individual reliability, along with the moderating effect of tracking device running velocity thresholds, pitch dimension (i.e., area per player), and game orientation (i.e. score or possession), were determined via a multi-level mixed-effects meta-analysis. Estimate uncertainty is presented as 95% compatibility intervals (CIs) with the likely range of relative distances in similar future studies determined via 95% prediction intervals.

RESULTS

A total of 104 and 7 studies met our eligibility criteria for the main and reliability analyses, respectively. The range of relative distances covered across small-sided games, medium-sided games, and large-sided games was 14.8 m[Formula: see text]min^-1 (95% CI 12.3-17.4) to 17.2 m[Formula: see text]min^-1 (95% CI 13.5-20.8) for high-speed running, 2.7 m[Formula: see text]min^-1 (95% CI 1.8-3.5) to 3.6 m[Formula: see text]min^-1 (95% CI 2.3-4.8) for very high-speed running, and 0.2 m[Formula: see text]min^-1 (95% CI 0.1-0.4) to 0.7 m[Formula: see text]min^-1 (95% CI 0.5-0.9) for sprinting. Across different game formats, 95% prediction intervals showed future exposure for high-speed, very high-speed running, and sprinting to be 0-46.5 m[Formula: see text]min^-1, 0-14.2 m[Formula: see text]min^-1, and 0-2.6 m[Formula: see text]min^-1, respectively. High-speed, very high-speed running, and sprinting showed poor reliability with a pooled coefficient of variation of 22.8% with distances being moderated by device speed thresholds, pitch dimension, and game orientation.

CONCLUSIONS

This review is the first to provide a detailed synthesis of exposure and intra-individual reliability of high-speed and sprint running during soccer sided games. Our estimates, along with the moderating influence of common programming variables such as velocity thresholds, area per player, and game orientation should be considered for informed planning of small-sided games, medium-sided games, and large-sided games soccer training.

CLINICAL TRIAL REGISTRATION

Open Science Framework available through https://osf.io/a4xr2/ .

Resetting our expectations for parasites and their effects on species interactions: a meta-analysis

Despite the ubiquitous nature of parasitism, how parasitism alters the outcome of host-species interactions such as competition, mutualism and predation remains unknown. Using a phylogenetically informed meta-analysis of 154 studies, we examined how the mean and variance in the outcomes of species interactions differed between parasitized and non-parasitized hosts. Overall, parasitism did not significantly affect the mean or variance of host-species interaction outcomes, nor did the shared evolutionary histories of hosts and parasites have an effect. Instead, there was considerable variation in outcomes, ranging from strongly detrimental to strongly beneficial for infected hosts. Trophically-transmitted parasites increased the negative effects of predation, parasites increased and decreased the negative effects of interspecific competition for parasitized and non-parasitized heterospecifics, respectively, and parasites had particularly strong negative effects on host species interactions in freshwater and marine habitats, yet were beneficial in terrestrial environments. Our results illuminate the diverse ways in which parasites modify critical linkages in ecological networks, implying that whether the cumulative effects of parasitism are considered detrimental depends not only on the interactions between hosts and their parasites but also on the many other interactions that hosts experience.

Sex differences in allometry for phenotypic traits in mice indicate that females are not scaled males

Sex differences in the lifetime risk and expression of disease are well-known. Preclinical research targeted at improving treatment, increasing health span, and reducing the financial burden of health care, has mostly been conducted on male animals and cells. The extent to which sex differences in phenotypic traits are explained by sex differences in body weight remains unclear. We quantify sex differences in the allometric relationship between trait value and body weight for 363 phenotypic traits in male and female mice, recorded in >2 million measurements from the International Mouse Phenotyping Consortium. We find sex differences in allometric parameters (slope, intercept, residual SD) are common (73% traits). Body weight differences do not explain all sex differences in trait values but scaling by weight may be useful for some traits. Our results show sex differences in phenotypic traits are trait-specific, promoting case-specific approaches to drug dosage scaled by body weight in mice.

Basic demographic characteristics and prevalence of comorbidities in acute mesenteric ischemia: a systematic review and proportional meta-analysis

PURPOSE

The aim of this systematic review and meta-analysis was to examine and assess the basic demographic characteristics and prevalence of comorbidities in acute mesenteric ischemia (AMI) and its various subtypes.

PATIENTS AND METHODS

A literature search was conducted by using the databases PubMed, EMBASE, and Google Scholar (to June 1, 2022). Random-effects or fixed-effects models were selected to pool means and proportions and their corresponding 95% confidence intervals (CI), based on heterogeneity between studies. The results of meta-analyses for basic demographic characteristics and prevalence (proportions) of each specific comorbidities of acute mesenteric ischemia (AMI) and its various subtypes were described.

RESULTS

Ninety-nine studies were included in the meta-analysis, including 17,103 patients with AMI. Furthermore, 7941 patients with subclass diagnoses of AMI were identified, including 3,239 patients with arterial occlusive mesenteric ischemia (AOMI), 2,977 patients with nonocclusive mesenteric ischemia (NOMI), and 1,725 patients with mesenteric venous thrombosis (MVT). As a surgical emergency, AMI is associated with older patients and a high likelihood of multisystem comorbidities. Comorbidities of AMI involved multiple systemic diseases, including cardiovascular disease, endocrine and metabolic diseases, kidney diseases, digestive diseases, respiratory diseases, cerebrovascular diseases, vascular diseases, and cancer.

CONCLUSION

The basic demographic characteristics and the prevalence of comorbidities of different subtypes of AMI are different. The management of comorbidities should be an essential part of improving the prognosis of AMI patients and may contribute to precise prevention of AMI.

Predator-induced transgenerational plasticity in animals: a meta-analysis

There is growing evidence that the environment experienced by one generation can influence phenotypes in the next generation via transgenerational plasticity (TGP). One of the best-studied examples of TGP in animals is predator-induced transgenerational plasticity, whereby exposing parents to predation risk triggers changes in offspring phenotypes. Yet, there is a lack of general consensus synthesizing the predator-prey literature with existing theory pertaining to ecology and evolution of TGP. Here, we apply a meta-analysis to the sizable literature on predator-induced TGP (441 effect sizes from 29 species and 49 studies) to explore five hypotheses about the magnitude, form and direction of predator-induced TGP. Hypothesis #1: the strength of predator-induced TGP should vary with the number of predator cues. Hypothesis #2: the strength of predator-induced TGP should vary with reproductive mode. Hypothesis #3: the strength and direction of predator-induced TGP should vary among offspring phenotypic traits because some traits are more plastic than others. Hypothesis #4: the strength of predator-induced TGP should wane over ontogeny. Hypothesis #5: predator-induced TGP should generate adaptive phenotypes that should be more evident when offspring are themselves exposed to risk. We found strong evidence for predator-induced TGP overall, but no evidence that parental predator exposure causes offspring traits to change in a particular direction. Additionally, we found little evidence in support of any of the specific hypotheses. We infer that the failure to find consistent evidence reflects the heterogeneous nature of the phenomena, and the highly diverse experimental designs used to study it. Together, these findings set an agenda for future work in this area.

Variability and efficacy in treatment effects on manic symptoms with lithium, anticonvulsants, and antipsychotics in acute bipolar mania: A systematic review and meta-analysis

BACKGROUND

Acute mania is a psychiatric emergency requiring rapid management. However, randomised controlled trials (RCTs) have shown considerable individual differences in treatment effects on manic symptoms with antimanic drugs.

METHODS

We searched the MEDLINE, CENTRAL, EMBASE, PsycINFO, and ClinicalTrials.gov to identify RCTs without language restrictions from inception to April 19, 2022. We included double-blind RCTs of oral antimanic monotherapy versus placebo in adult patients. The primary outcome was variability in improvement of manic symptoms (assessed using the coefficient of variation ratio [CVR]). The secondary outcomes were overall improvement of manic symptoms and acceptability (i.e., discontinuation for any reason). The pooled effects of outcomes were calculated by random-effects meta-analyses using restricted maximum likelihood methods. The quality of the included studies was assessed using the Cochrane Risk of Bias (ROB) Assessment Tool. This study was registered with OSF (DOI:10.17605/OSF.IO/G4JNY).

FINDINGS

We included 39 RCTs (N=12150; mean age=39·9 years, interquartile range [IQR]=38·7-41·1; mean proportion of female=48·6%, IQR=42·3%-52·3%) and investigated 14 antimanic drugs. We found that eight antimanic drugs compared to placebo were associated with lower CVRs (95% confidence interval [CI]; I²), including risperidone (0·51; 0·37-0·70; 0%), haloperidol (0·54; 0·44-0·67; 4%), olanzapine (0·59; 0·44-0·79; 47%), ziprasidone (0·61; 0·53-0·71; 0%), lithium (0·63; 0·52-0·76; 0%), quetiapine (0·65; 0·48-0·87; 2%), aripiprazole (0·68; 0·56-0·84; 25%), and cariprazine (0·70; 0·49-0·99; 28%). There were nine antimanic drugs associated with greater efficacy than placebo, including risperidone (reported as standardised mean difference; 95% CI; I²: 0·64; 0·31-0·97; 15%), haloperidol (0·57; 0·29-0·85; 64%), cariprazine (0·51; 0·24-0·78; 0%), olanzapine (0·44; 0·30-0·58; 0%), lithium (0·42; 0·29-0·55; 0%), ziprasidone (0·42; 0·26-0·58; 0%), quetiapine (0·40; 0·13-0·67; 0%), asenapine (0·40; 0·13-0·67; 0%), and aripiprazole (0·32; 0·14-0·49; 53%). Ziprasidone (reported as risk ratio; 95% CI; I²: 0·83; 0·79-0·89; 0%) and olanzapine (0·63; 0·49-0·80; 35%) were associated with better acceptability relative to placebo. Among the 39 RCTs, none had a high ROB.

INTERPRETATION

We demonstrated that eight antimanic drugs were associated with lower variability and better efficacy than placebo, suggesting that these antimanic drugs were associated with more homogenous and predictable improvements of manic symptoms in patients with acute mania.

FUNDING

The study was supported by from the Ministry of Science and Technology (MOST-110-2314-B-016-035, MOST-111-2314-B-016-054), Medical Affairs Bureau (MND-MAB-D-111102), and Tri-service General Hospital (TSGH-E-111229).

Greater variability in rhesus macaque (Macaca mulatta) endocranial volume among males than females

The greater male variability (GMV) hypothesis proposes that traits are more variable among males than females, and is supported by numerous empirical studies. Interestingly, GMV is also observed for human brain size and internal brain structure, a pattern which may have implications for sex-biased neurological and psychiatric conditions. A better understanding of neuroanatomical variability in non-human primates may illuminate whether certain species are appropriate models for these conditions. Here, we tested for sex differences in the variability of endocranial volume (ECV, a proxy for brain size) in a sample of 542 rhesus macaques (Macaca mulatta) from a large pedigreed free-ranging population. We also examined the components of phenotypic variance (additive genetic and residual variance) to tease apart the potential drivers of sex differences in variability. Our results suggest that males exhibit more variable ECVs, and that this pattern reflects either balancing/disruptive selection on male behaviour (associated with alternative male mating strategies) or sex chromosome effects (associated with mosaic patterns of X chromosome gene expression in females), rather than extended neurodevelopment among males. This represents evidence of GMV for brain size in a non-human primate species and highlights the potential of rhesus macaques as a model for sex-biased brain-based disorders.

A global meta-analysis reveals higher variation in breeding phenology in urban birds than in their non-urban neighbours

Cities pose a major ecological challenge for wildlife worldwide. Phenotypic variation, which can result from underlying genetic variation or plasticity, is an important metric to understand eco-evolutionary responses to environmental change. Recent work suggests that urban populations might have higher levels of phenotypic variation than non-urban counterparts. This prediction, however, has never been tested across species nor over a broad geographical range. Here, we conducted a meta-analysis of the avian literature to compare urban versus non-urban means and variation in phenology (i.e. lay date) and reproductive effort (i.e. clutch size, number of fledglings). First, we show that urban populations reproduce earlier and have smaller broods than non-urban conspecifics. Second, we show that urban populations have higher phenotypic variation in laying date than non-urban populations. This result arises from differences between populations within breeding seasons, conceivably due to higher landscape heterogeneity in urban habitats. These findings reveal a novel effect of urbanisation on animal life histories with potential implications for species adaptation to urban environments (which will require further investigation). The higher variation in phenology in birds subjected to urban disturbance could result from plastic responses to a heterogeneous environment, or from higher genetic variation in phenology, possibly linked to higher evolutionary potential.

Location-scale models for meta-analysis

Heterogeneity is commonplace in meta-analysis. When heterogeneity is found, researchers often aim to identify predictors that account for at least part of such heterogeneity by using mixed-effects meta-regression models. Another potentially relevant goal is to focus on the amount of heterogeneity as a function of one or more predictors, but this cannot be examined with standard random- and mixed-effects models, which assume a constant (i.e., homoscedastic) value for the heterogeneity variance component across studies. In this paper, we describe a location-scale model for meta-analysis as an extension of the standard random- and mixed-effects models that not only allows an examination of whether predictors are related to the size of the outcomes (i.e., their location), but also the amount of heterogeneity (i.e., their scale). We present estimation methods for such a location-scale model through maximum and restricted maximum likelihood approaches, as well as methods for inference and suggestions for visualization. We also provide an implementation via the metafor package for R that makes this model readily available to researchers. Location-scale models can provide a useful tool to researchers interested in heterogeneity in meta-analysis, with the potential to enhance the scope of research questions in the field of evidence synthesis.