To test the hypothesis that distinct subtypes of Alzheimer disease (AD) exist and underlie the heterogeneity within AD, we conducted a systematic review and meta-analysis on AD subtype studies based on postmortem and neuroimaging data.EMBASE, PubMed, and Web of Science databases were consulted until July 2019.Neuropathology and neuroimaging studies have consistently identified 3 subtypes of AD based on the distribution of tau-related pathology and regional brain atrophy: typical, limbic-predominant, and hippocampal-sparing AD. A fourth subtype, minimal atrophy AD, has been identified in several neuroimaging studies. Typical AD displays tau-related pathology and atrophy both in hippocampus and association cortex and has a pooled frequency of 55%. Limbic-predominant, hippocampal-sparing, and minimal atrophy AD had a pooled frequency of 21%, 17%, and 15%, respectively. Between-subtype differences were found in age at onset, age at assessment, sex distribution, years of education, global cognitive status, disease duration, APOE ε4 genotype, and CSF biomarker levels.We identified 2 core dimensions of heterogeneity: typicality and severity. We propose that these 2 dimensions determine individuals' belonging to one of the AD subtypes based on the combination of protective factors, risk factors, and concomitant non-AD brain pathologies. This model is envisioned to aid with framing hypotheses, study design, interpretation of results, and understanding mechanisms in future subtype studies. Our model can be used along the A/T/N classification scheme for AD biomarkers. Unraveling the heterogeneity within AD is critical for implementing precision medicine approaches and for ultimately developing successful disease-modifying drugs for AD. Variability in age at onset and clinical presentation is known since the very first reports. Extensive research showed marked differences between early-onset and late-onset AD, mostly with early-onset AD showing more pronounced pathologic findings such as more tau-related pathology and brain atrophy.3 it is now timely and unprecedented to review the literature on biologically defined subtypes of AD. We conducted a systematic review on the topic and calculated meta-analytical estimates aiming at characterizing the AD subtypes across key demographic and clinical measures. Our ultimate goal was to advance in our understanding of mechanisms driving heterogeneity in AD, hopefully contributing to guide the search for subtype-specific therapies within the current efforts of precision medicine.Recent progress in biomarker research and wider availability of postmortem data has intensified the study of biologically defined subtypes of AD (based on neuropathologic and neuroimaging data). Several studies have been published including subtypes based on postmortem data, MRI data, and recently, tau-PET data. With the new definition of AD as a biological disease,doi.org.10.5061/dryad.h70rxwdf3): “Alzheimer,” “AD,” “subtype,” “heterogeneity,” “atrophy,” “patterns,” “subtypes,” “MRI,” “Magnetic Resonance,” “PET,” “postmortem,” “neurofibrillary tangle,” and “neuropathological”. Additional relevant publications were identified by scrutinizing references of the included articles.This study followed the PRISMA statement. We conducted a systematic review using EMBASE, PubMed, and Web of Science in July 2019 without any limits in publication dates. The search strategy combined the following medical subject heading and free-text terms  case-control studies reporting summary estimates on subgroups of patients with AD based on grouping strategies applied on MRI, PET, or postmortem data; (2) availability of data on subtypes frequency and key demographic and clinical measures; and (3) studies published in English.doi.org.10.5061/dryad.h70rxwdf3).Study selection was performed by a single researcher (D.F.), involving a second researcher (E.W.) when needed. When the selected studies included data from the same cohort, the studies were included in the meta-analysis if the grouping strategy differed across studies. When the grouping strategy was the same, the study with larger sample or reporting more subtypes was included. When data were missing for a variable, the next larger study was included .Several strategies were followed to reduce risks bias related to publication, data availability, and reviewer selection . Data extraction was performed by a single researcher (D.F.). Studies' methodological quality was assessed with the CASP checklist for case control studies.4 Variables included in the meta-analysis were subtypes frequency (group size), age, sex, years of education, MMSE, CDR sum of boxes (CDR-SOB), age at onset, disease duration, APOE genotype, and CSF levels of amyloid-beta 1–42 (Aβ42), total tau (T-tau), and phosphorylated tau (p-tau). Using random-effects models, weighted pooled means (pM) and proportions (pP) were calculated for each subtype, and post hoc paired comparisons were performed with a p value <0.05 deemed significant. Heterogeneity in these analyses was investigated through visual inspection of forest plots and by computing the I2 parameter. p Values, 95% CI, and other meta-analytical parameters are provided in doi.org.10.5061/dryad.h70rxwdf3. Analyses were conducted in R version 3.2.4 , using the “Meta” package.5Data were collected for the fields listed in data available from Dryad . All the selected studies had an appropriate methodological quality according to the CASP checklist.A total of 11,307 records were identified in the initial search. After removing duplicates and screening by title, abstracts, and full text, 64 records were selected . Of thos6–8 used principal component analysis and other clustering methods on pathologic measures of senile plaques, neurofibrillary tangles (NFTs), and cerebral amyloid angiopathy (CAA). Later studies mainly focused on markers of tau pathology and neurodegeneration. A seminal study investigated 889 brain autopsies and identified 3 AD subtypes based on the distribution of NFT: typical AD, with balanced NFT counts in the hippocampus and association cortex; limbic-predominant AD, with counts predominantly in hippocampus; and hippocampal-sparing AD, with counts predominantly in the association cortex.9 In that study, subtyping was based on a hypothesis-driven strategy in which regions of interest were a priori defined . The subtypes were identified according to patients' distribution on the hippocampus-to-cortex NFT spectrum by separating the groups at 25th and 75th percentiles. The same method was used in later postmortem studies from the same11 and other independent postmortem series.12–14 These subtypes have also been found in neuroimaging studies. Recently, the first study using tau-PET for subtyping was published15 and reported 3 subtypes likely corresponding to the postmortem subtypes. In addition, the postmortem subtypes can be reliably tracked in vivo by investigating patterns of atrophy in structural MRI.12 Hence, neurodegeneration measures are another plausible vein to defining biological subtypes. Several hypothesis-driven MRI studies have reported data on these subtypes by using visual rating scales of brain atrophy16–21 or automated methods for estimating regional brain volume.23 MRI studies have also consistently identified a fourth subtype displaying minimal brain atrophy.16–23–26 In contrast, data-driven methods do not depend on a priori selection of brain regions but investigate interindividual variation in measures of volume or cortical thickness. Several algorithms have been used.25–33 Recently, the first subtyping study using diffusion tensor imaging for white matter integrity was published.34 Our systematic review did not identify any data-driven study on FDG-PET, another imaging modality for measuring neurodegeneration. We identified 3 hypothesis-driven studies comparing patients with AD with different patterns of FDG-PET uptake .Our review shows that both hypothesis-driven and data-driven methods have been used for determining biological subtypes of AD. A number of early studiesWe calculated pooled estimates of the frequency of the subtypes. Typical AD is the most frequent subtype, with a pooled frequency of 55%. In contrast, limbic-predominant, hippocampal-sparing, and minimal atrophy AD had a pooled frequency of 21%, 17%, and 15%, respectively . The fre2 parameter are shown in data available from Dryad, figures e-1–e-28, doi.org.10.5061/dryad.h70rxwdf3. Typical and limbic-predominant were significantly older than hippocampal-sparing and minimal atrophy AD. Limbic-predominant AD included the highest frequency of females. Hippocampal-sparing included highly educated individuals, whereas minimal atrophy AD included less educated individuals. Minimal atrophy AD had better MMSE and CDR scores than the other subtypes. Hippocampal-sparing had earlier disease onset compared with typical and limbic-predominant AD. Minimal atrophy AD had the shortest disease duration. Hippocampal-sparing included a lower frequency of APOE ε4 carriers compared with typical and limbic-predominant AD. Hippocampal-sparing had less amyloid and more tau-related pathology than typical and had more neurodegeneration  than limbic-predominant AD. The I2 parameter indicated high heterogeneity in several models .We also calculated meta-analytical estimates aiming at characterizing the subtypes across key demographic and clinical measures. Results are shown in 35We conducted a systematic review and meta-analyses of studies including biologically defined subtypes of AD. We identified 3 dimensions that are major drivers of the heterogeneity within AD: (1) risk factors, including sex, APOE, and age; (2) protective factors, including aspects such as cognitive reserve, brain resilience, and brain resistance; and (3) concomitant non-AD pathologies that together with amyloid (A) and tau-related pathology (T) may contribute to the neurodegeneration (N) seen in AD, which are formulated under the A/T/N framework for AD.29 whereas limbic-predominant AD has a later onset and slower disease progression. This finding is coherent with the possible contribution of TAR DNA-binding protein 43 (TDP-43) pathology, hippocampal-sclerosis, and the microtubule-associated protein tau (MAPT) H1H1 genotype to limbic-predominant AD, 3 factors that are related to atrophy restricted to the medial temporal lobes, older age, and slower disease progression.The current meta-analysis revealed that hippocampal-sparing AD had the earliest disease onset, and typical and limbic-predominant AD had the latest disease onset. No significant differences were found for minimal atrophy AD, which showed an intermediate age at onset. Because the 4 subtypes do not differ substantially in disease duration, the age at the time of MRI is the lowest in hippocampal-sparing AD and the highest in typical and limbic-predominant AD, with minimal atrophy AD in between. The ADNI cohort mostly included patients with late-onset amnestic AD, and therefore, the hippocampal-sparing subtype found in ADNI studies does not completely correspond to the group of patients with early-onset hippocampal-sparing AD seen in other cohorts. Regarding postmortem studies, our meta-analysis shows that the age results are slightly different because unlike MRI studies usually including younger cohorts with patients at mild to moderate dementia stages, postmortem studies often include older cohorts at advanced stages of the disease. Hence, the age at death in postmortem studies is the oldest for limbic-predominant AD and the youngest for hippocampal-sparing AD, reflecting that hippocampal-sparing is the most aggressive form, with faster progression, and younger age at death,37 This finding was observed also in neonates, whereas APOE ε4 noncarrier neonates had lower volume in parietal, frontal, and occipital cortices.38 This finding in neonates may predispose APOE ε4 carriers and noncarriers to different regional brain vulnerability later in life. A finding supporting this APOE genotype-specific vulnerability is that APOE ε4 carriers have higher tau-PET binding in the entorhinal cortex, whereas APOE ε4 noncarriers have higher tau-PET binding in parietal and occipital cortices.36 Therefore, APOE ε4 negative may increase resistance of the hippocampus to accumulate tau pathology, but would in turn increase vulnerability of posterior brain areas to accumulate tau pathology. This supports the theory that the absence of the APOE ε4 allele may drive pathology toward posterior brain areas36 or, alternatively, expose the effect of pathologies affecting posterior brain areas commonly masked by APOE ε4.2 These masked pathologies may include cerebrovascular disease (CVD) and Lewy body pathology (discussed later in this article).Female patients more frequently had limbic-predominant AD, and male patients more frequently had hippocampal-sparing AD. We also found that APOE ε4 carriers more frequently have limbic-predominant and typical AD, whereas APOE ε4 noncarriers more frequently have hippocampal-sparing AD. APOE ε4 has consistently been associated with lower volume in hippocampus and adjacent regions.37 Below we propose that this triad together with other factors drives the distribution of pathology seen in limbic-predominant and hippocampal-sparing AD, diverging from that seen in typical AD.The strong connection between sex, APOE, and age has been coined as “the triad of risk of AD”.10 However, a study reported that typical AD had the highest frequency of MAPT H1H1 carriers, followed by limbic-predominant and hippocampal-sparing AD.22 These findings suggest that the MAPT H1H1 genotype may play a role in the medial temporal lobe predilection for NFT.Genetic research in AD subtypes has also focused on the MAPT H1H1 genotype. The frequency of the MAPT H1H1 genotype is increased in limbic-predominant AD compared with typical and hippocampal-sparing AD.40 For example, higher cognitive reserve has been associated with lower cortical tau-PET binding,41 which has been interpreted as brain resistance in the sense that higher cognitive reserve may contribute to avoid tau aggregation.40 Another example is that higher cognitive reserve has been associated with lower hippocampal volume in amyloid positive cognitively normal individuals,42 which is commonly interpreted as brain resilience, i.e., higher cognitive reserve contributes to cope with neurodegeneration better.40 However, the presence of 1 APOE ε4 allele can reduce the protective effects of education,43 a proxy of cognitive reserve.Coexisting with risk factors such as female sex, APOE ε4, and older age, there are counteracting protective forces such as cognitive reserve and the related concepts of brain resilience/resistance.22 Why hippocampal sparing has higher levels of education is not known. We suggest that high education could be one of the factors protecting the hippocampus so that pathologies affecting the posterior cortex and thus contributing to hippocampal-sparing AD may be unmasked and have a greater contribution to the clinical expression of the disease.How risk and protective factors balance and cancel each other out is not completely understood. Multiple pathways may exist, which would eventually increase the heterogeneity within AD. Our meta-analysis revealed clear differences in education across subtypes. Hippocampal-sparing AD has the highest level of education, whereas minimal-atrophy AD has the lowest level of education. This finding is observed in the context of similar levels of clinical severity: the 4 subtypes had rather comparable scores on MMSE and CDR-SOB. We acknowledge that statistically significant differences were revealed for both MMSE and CDR-SOB. However, the differences did not exceed more than 1 point in any of these scales, which probably lack clinical relevance. A previous study supports this interpretation showing comparable levels of impairment in activities of daily living across subtypes.39 At similar levels of clinical severity, the cognitive reserve theory would foresee more pathology in individuals with higher reserve and less pathology in individuals with less reserve. The finding of more intense neurodegeneration and more aggressive disease progression in hippocampal-sparing,29 the subtype with the highest level of reserve, supports this hypothesis. The absence of overt brain atrophy in minimal atrophy AD, the subtype with the lowest level of reserve, also supports this hypothesis. The big question is which pathology or pathologies are patients with minimal atrophy AD so vulnerable to? In a previous study, we observed that the frequency of abnormal CSF p-tau and T-tau levels was higher in minimal-atrophy AD than in the other subtypes.17 Based on that observation, we proposed that tau-related pathology and neurodegeneration at the molecular level may be sufficient to give dementia symptoms in patients with minimal atrophy AD in the absence of overt brain atrophy.44 Our meta-analysis provides preliminary support to that explanation by showing higher frequency of abnormal CSF p-tau and T-tau levels in minimal atrophy compared with typical and limbic-predominant AD. However, these comparisons did not yield statistical significance, perhaps due to low statistical power.The concepts of cognitive reserve, brain resilience/resistance connect directly with brain pathology, in this case, amyloid, tau-related pathology, and neurodegeneration. The theory of cognitive reserve postulates that people with higher reserve can cope with brain pathology better.15 limbic-predominant AD had focal tau-PET binding bilaterally in the temporal lobes , extending to the posterior cingulate. Both patients with typical and hippocampal-sparing AD showed tau-PET binding throughout the temporal, parietal, occipital, and frontal lobes, with greater binding in typical AD.In a recent tau-PET study,22 Two other studies showed that hypometabolism matches the patterns of brain atrophy that defines the subtypes.28 Of interest, patients with minimal-atrophy AD also showed reduced metabolism in the parietal cortex despite lacking overt brain atrophy in those regions.24 Below we elaborate on how this finding may be related to network disruption in minimal-atrophy AD.21Apart from CSF T-tau, neurodegeneration has also been investigated through FDG-PET, which at the moment is much more clinically established. Hippocampal-sparing AD displayed greater hypometabolism in prototypic AD regions than typical and limbic-predominant AD.9–45 as well as the tau-PET study15 and 1 MRI study22 exclusively recruited amyloid-positive patients with AD. Our meta-analysis on CSF Aβ42 levels showed that typical AD displayed the highest proportion of amyloid-positive patients (88%), whereas the other 3 subtypes displayed comparable proportions including around 75% of the patients. The proportion of amyloid-positive patients in typical AD differed significantly from hippocampal-sparing and minimal-atrophy AD, whereas it reached a trend for statistical significance when compared with limbic-predominant AD. Primary studies showed no differences in the global amount of senile plaques or global amyloid PET binding across subtypes.22 However, a study reported greater global amyloid PET binding in patients with limbic-predominant AD.15 In contrast, regional analyses have revealed several differences. Typical AD has higher counts of senile plaques in occipital regions compared with limbic-predominant AD.9 Hippocampal-sparing AD showed marked amyloid PET binding in frontal and parietal cortices compared with that in typical and limbic-predominant AD.28 Furthermore, limbic-predominant AD showed greater amyloid PET binding in medial frontal and parietal cortices compared with that in typical AD. Nonetheless, the distribution of amyloid pathology in the brain is rather diffuse, which perhaps explains why we could only find 1 study drawing AD subtypes exclusively from amyloid measures.46All the postmortem studies included in this meta-analysis48 How non-AD brain pathologies contribute to the heterogeneity within AD, perhaps underlying the biological subtypes reviewed here, is a topic of great interest. The scarce amount of data at the time being prevented us to conduct specific meta-analytical calculations.AD pathology rarely occurs in isolation. Patients with AD pathology at autopsy often have concomitant pathologies such as CVD, Lewy body pathology, and/or TDP-43.31 whereas no differences were reported in another study.18 Furthermore, the subtypes seem to be rather comparable in the frequency of other vascular risk factors such as diabetes, dyslipidemia, and cardiovascular disease.31 Regarding CVD, postmortem series from the Mayo Clinic showed increased CVD in typical and limbic-predominant AD.13 However, postmortem series from the Institute of Clinical Neurobiology in Vienna reported increased CVD only in typical AD.14 The burden of white matter hyperintensities (WMHs) in MRI is higher in typical and limbic-predominant AD.25 We recently conducted a comprehensive characterization of the AD subtypes in terms of CVD, including the amount and distribution of deep/lobar microbleeds and WMH, cortical superficial siderosis, perivascular spaces, lacunes, large brain infarction, and intracerebral hemorrhage.17 CAA seemed to make a stronger contribution to hippocampal-sparing and minimal atrophy, whereas hypertensive arteriopathy may make a stronger contribution to typical and limbic-predominant AD.The contribution of vascular factors has been investigated in several studies. Hypertension was reported to be more frequent in typical and limbic-predominant AD,13 hippocampal sclerosis was more frequent in limbic-predominant than in typical and hippocampal-sparing AD, although this observation did not reach statistical significance. Furthermore, hippocampal sclerosis was associated with TDP-43 deposition only in patients with limbic-predominant AD.13 The strong association between hippocampal sclerosis and TDP-43 has been reported several times.11 TDP-43 is increased in typical and limbic-predominant compared with hippocampal-sparing AD.13 This finding converges with previous studies, showing that the amygdala is the first and most commonly affected region by TDP-43 deposition49 and that TDP-43 is strongly associated with smaller hippocampal volume.50 Of interest, clinical presentation in AD seems to be driven by subtype, not by TDP-43.13 Hippocampal sclerosis, TDP-43, and limbic-predominant AD are more common in older women with a slowly progressive amnestic syndrome.10 The clinical entity LATE  has recently emerged.51Other non-AD brain pathologies have received less attention. In the report by Josephs et al.,The MAPT H1H1 genotype may play a role in the medial temporal lobe predilection for NFT. To our knowledge, no previous studies have investigated the association among MAPT H1H1 genotype, hippocampal sclerosis, and TDP-43.48 The postmortem series from the Mayo Clinic in Jacksonville showed increased Lewy body pathology in typical and limbic-predominant AD.10 In contrast, the postmortem series from Vienna and Mayo Clinic in Rochester reported increased Lewy body pathology in hippocampal-sparing AD.12–14 Cholinergic dysfunction is central in DLB and AD. We recently investigated whether the cholinergic basal forebrain is differentially affected and influences different treatment response across AD subtypes.20 We found that the volume of the cholinergic basal forebrain declines more rapidly in typical and limbic-predominant AD, whereas treatment response seemed to be better in hippocampal-sparing AD.20 Dong et al.27 also reported reduced volume of the basal forebrain in 2 AD subtypes likely resembling typical and limbic-predominant AD. Because patients with DLB  and patients with AD with less hippocampal atrophy respond well to cholinesterase inhibitors,53 we suggest that the interplay between pattern of atrophy and the cholinergic system may be an explanation for good response to cholinergic treatment in DLB and hippocampal-sparing AD. Whether a common pattern of brain atrophy or increased Lewy body pathology in hippocampal-sparing AD or both is the reason for this finding needs to be elucidated. The dopaminergic system is heavily involved in DLB, whereas it is spared in AD, which could also explain marginal differences in the response to cholinesterase inhibitors.Despite the clear clinical differentiation between dementia with Lewy bodies (DLBs) and AD, the comorbidity between the 2 is high.21 The finding of reduced metabolism in the parietal cortex in minimal atrophy AD24 supports the explanation regarding network disruption. Increased small vessel disease in posterior white matter in minimal atrophy AD17 could also have an impact on such networks. An almost identical pattern of brain hypometabolism and small vessel disease colocalizes with reduced white matter integrity in diffusion tensor imaging and correlates with cognitive impairment in the absence of overt brain atrophy in DLB.54–57 Of interest, minimal atrophy was the second most common pattern in DLB.19 Therefore, tau and concomitant pathologies may disconnect key brain networks in minimal atrophy AD, giving the symptoms in the absence of overt brain atrophy. We showed that 3 networks involving posterior brain regions  are affected in minimal-atrophy AD.21All these concomitant brain pathologies may be especially harmful to individuals with low cognitive reserve such as patients with minimal-atrophy AD. Tau-related pathology and neurodegeneration at the molecular level may be sufficient to disrupt key brain networks, which could give the symptoms in the absence of overt brain atrophy in minimal-atrophy AD.15 Some cohorts showed virtually no differences in the cognitive profile across subtypes.28 Other cohorts showed greater impairment of nonmemory functions in hippocampal-sparing AD.31 Cognitive trajectories over time more clearly differ across subtypes, highlighting heterogeneity in disease progression as well. Longitudinal decline in MMSE was faster in hippocampal-sparing than in the other subtypes.29 Na et al.29 showed that this finding extends to several memory and nonmemory cognitive domains that also decline faster in hippocampal-sparing AD. However, other studies showed that typical AD has the fastest longitudinal decline in MMSE.18 The results on longitudinal decline in CDR are similar than those for MMSE, that is, faster decline is reported for typical AD in a study,16 whereas faster decline is reported for hippocampal-sparing AD in other studies.29 These contradictory results may depend on differences across cohorts in the frequency of patients with early-onset nonamnestic AD presentations. Regarding psychiatric features, the subtypes have comparable levels of depressive28 and neuropsychiatric symptoms.23Atypical nonamnestic presentations such as PCA, LPPA, and the frontal variant of AD are more common in hippocampal-sparing than in typical and limbic-predominant AD.2 parameter in figures e-1–e-28, doi.org.10.5061/dryad.h70rxwdf3. We conducted random-effect models to partially account for this problem, but the heterogeneity seen in this meta-analysis may have an impact on some of the pooled estimates. Hence, we call for the urgent need to harmonize subtyping methods across studies. Another limitation is that some analyses included few studies due to lack of data at present, and some factors could not be analyzed. Therefore, we encourage that future studies should focus on CSF biomarkers or PET imaging and concomitant pathologies. Finally, most of the MRI studies in this meta-analysis included mixed cohorts of amyloid positive and negative patients. This may include heterogeneity not due to AD. Hence, it is important that future studies focus on amyloid-positive patients with AD and better characterize their participants, for instance, by using the A/T/N framework.This study has some limitations. Different methods have been used in the literature to define the subtypes. This methodological variability together with characteristics of the cohorts may be the explanations for the high heterogeneity in several of our models, as reflected by the I35 The current meta-analysis contributes to better characterize the “N” category, adding a spatial dimension that includes different atrophy patterns connected with different factors that ultimately lead to distinct clinical manifestations of AD. The A and T categories are assumed to be positive in our model, adhering to the current biological definition of AD.3 Cognitive reserve and brain resilience/resistance levels would determine individuals' location along the severity dimension, with lower levels related to minimal atrophy AD. Future studies need to ascertain the distribution of NFT in minimal-atrophy AD. It is even possible that patients with minimal-atrophy AD have not yet reached the Braak stage V.58In this systematic review, we identified 3 factors that may explain a substantial part of the heterogeneity within AD, that is, risk factors, protective factors, and concomitant non-AD brain pathologies. We propose that the balance between risk and protective factors determines brain regional vulnerability along the lifespan, contributing to differential spatial deposition of different pathologies and eventually leading to divergent clinicopathologic presentations of AD. Pursuing our goal of advancing our understanding of mechanisms driving heterogeneity in AD, we propose the model depicted in 59 It is possible that factors such as brain resilience help compensating for these pathologies until a certain level. However, a combination of risk factors might knock these compensatory effects out. This process takes time, which would explain the later-onset and slower progression of limbic-predominant AD, as well as why limbic-predominant AD is more common among females and APOE ε4 carriers. In the absence of these risk factors, brain resistance mechanisms would more efficiently preserve the medial temporal lobes and perhaps drive pathology to the posterior cortex or expose the effect of non-AD pathologies affecting the posterior cortex. This may explain the higher frequency of hippocampal-sparing AD in highly educated, young, APOE ε4 negative males, as well as higher frequency of CAA and Lewy body pathology in hippocampal-sparing AD. The explanation for early onset in hippocampal-sparing AD remains elusive, but the added onslaught of non-AD pathologies and increased vulnerability of key networks such as the default mode network are plausible explanations.Our proposal for explaining what determines individuals' location along the typicality dimension is as follows. The medial temporal lobes are a frequent site for deposition of various pathologies  and are also more vulnerable to cerebrovascular pathology.This meta-analysis and our proposed model highlight the importance of factors such as age, sex, and education as potential drivers of diverging pathophysiologic processes across subtypes. Therefore, these factors should be carefully considered, and whether they should be used as confounding variables is to be decided at the study level depending on the aims and characteristics of the cohorts.35 Here, we identify avenues for future research aiming at moving the field forward. Despite building on previous proposals to explain heterogeneity within AD,60 our current model offers a reformulation based on the findings accumulated during recent years. Our typicality and severity dimensions as well as recognition of key determinants such as compensatory processes are reminiscent of the 3 hypotheses proposed in a previous study,60 that is, the subtype model, phase model, and compensation model, respectively. Likewise, a previous model proposed 3 dimensions delineated by APOE, age at onset, and concomitant brain pathologies,2 which are integrated in our model as well. However, we believe that typicality (subtype model) and severity (phase model) dimensions cannot be teased apart as previously suggested60 and that modulatory factors  are intricate with the other 2 dimensions. All these issues need to be recognized in an updated model; hence, they are integrated in our proposed framework.We envision our proposed model as a framework to aid with framing hypotheses, study design, interpretation of results, and understanding mechanisms in future subtype studies. This framework can be used along the recently proposed A/T/N classification scheme for AD biomarkers.We are still at the beginning of the long journey of completely unraveling the heterogeneity within AD. The extensive research on clinical heterogeneity accumulated during decades, together with the current availability of biological markers that open a window to mechanisms affecting the brain, will illuminate the way toward reaching the goals of precision medicine in the future. This is expected to get us closer to the ultimate goal of developing successful disease-modifying drugs for AD.


N = 635), which included a total of 53 mediation models examining how interventions affect pain-relevant outcomes for youth. Five studies were secondary analyses of randomized controlled trials of psychological interventions for chronic pain; one was a longitudinal observational study of morphine for acute pain. The pain conditions studied were irritable bowel syndrome, functional abdominal pain, juvenile fibromyalgia, mixed chronic pain, and post-operative pain. Fourteen putative mediators were tested, of which three partially mediated treatment effect; seven did not significantly mediate treatment effect and four had mixed results. Methodological and reporting limitations were common. There are substantial gaps in the field with respect to investigating, and therefore understanding, how paediatric interventions work.Clinicians have an increasing number of evidence-based interventions to treat pain in youth. Mediation analysis offers a way of investigating how interventions work, by examining the extent to which an intermediate variable, or mediator, explains the effect of an intervention. This systematic review examined studies that used mediation analysis to investigate mechanisms of interventions on pain-relevant outcomes for youth (3–18 years) with acute or chronic pain, and provides recommendations for future mediation research in this field. We searched five electronic databases for clinical trials or observational longitudinal studies that included a comparison group and conducted mediation analyses of interventions on youth and assessed pain outcomes. We found six studies ( Pain is common in childhood and adolescence ,2, preseMediation analysis is the most frequently used quantitative method for evaluating the mechanisms of interventions . MediatiMediation analyses that examine potential mediators of interventions for paediatric pain exist, but a systematic evaluation of the field is lacking. Systematic reviews of mediation analyses have examined potential mediators of interventions for adults with musculoskeletal pain  and backhttps://osf.io/pw7yb/ (accessed on 10 June 2020)). Deviations from the pre-registered protocol are explained in the following section  and the Open Science Framework (The following electronic databases were searched from their inception up to 4 January 2021: EMBASE (OvidSP), Medline (OvidSP), Emcare (OvidSP), PsycINFO (OvidSP), and Cochrane Central Register of Controlled Trials (CENTRAL). A MEDLINE search strategy was developed in conjunction with a medical librarian and was adapted for other databases  be published, peer-reviewed reports; (2) have enrolled a sample of children and adolescents aged 3 to 18 years (referred to hereafter as ‘youth’), with pain at baseline of any condition and duration; (3) have investigated any therapeutic intervention delivered in-person or via technology; (4) be a clinical trial (including randomized and non-randomized designs) or an observational longitudinal study; (5) have included any comparator/control group(s); (6) have conducted mediation analysis to investigate the role of one or more mediator(s) in explaining the pathway from an intervention for paediatric pain to a pain-related outcome; (7) have assessed an outcome from the PedIMMPACT recommendations for paediatric pain core outcome domains for acute , chronic or recurrent pain  . Wh. Wha), mfounding . We acknfounding  were pubWe considered youth across developmental stages, including children (3–12 years) and adolescents (13–18 years). Where possible, we aimed to interpret the results according to these subgroups, although we acknowledge that a 17-year-old may indeed be more similar to an adult than to a 13-year-old. In this review, we included any intervention but reported results according to intervention type . Heterogeneity in pain condition, intervention, mediators, and outcomes precluded meta-analysis, so data were qualitatively synthesized in accordance with the Synthesis Without Meta-analysis (SWiM) reporting guidelines . Narratia, path b, total effect, direct effect, indirect effect, and proportion mediated. In this review, an indirect effect was reported as significant if the 95% confidence interval did not include 0. To assist with comparison between outcomes, data were transformed to present standardized regression coefficients and 95% CIs where possible. In studies where a 90% confidence interval was reported, this was transformed to a 95% confidence interval using the reported standard error. In studies that reported unstandardized correlation coefficients, these were transformed to standardized coefficients . In stun 2.3 in  but did d path b .The search strategy identified 7334 records for consideration, of which 187 potentially relevant full-text articles were retrieved and screened to determine eligibility. The main reason for exclusion at full-text screening was due to irrelevant study design; full details of reasons for exclusion are provided in n = 3) and Sweden (n = 3) and published between 2011 and 2020. Sample sizes at baseline ranged from 30 to 200 participants. One study included only children ; one study included only adolescents ; four studies included children and adolescents  were undertaken in USA (17 years ). Most  confounders; an adjustment that was not required for the remaining 52 models that analysed randomized data. However, only 21/53 models adjusted for mediator-outcome (path b) confounders. Most models (44/53) included additional analyses to justify the validity of the assumption of temporal ordering. Frequently, models were inconsistent in their engagement with quality domains. Four mediation models reported that they were prospectively planned. Causal diagrams were reported to outline 23/53 mediation models. One model analysed non-randomized data and controlled for intervention-mediator  in analysis, but none evaluated and reported goodness-of-fit indices. Justification for the plausibility of the assumption of no unmeasured confounding was not provided for any models, and no sensitivity analyses were conducted to test this assumption.Across the six included studies, the number of mediation models tested ranged from 1 to 24, amounting to a total of 53 mediation models . The numIn total, 14 putative mediators were assessed in the 53 mediation models. Three mediators were found to significantly mediate treatment effect , seven did not significantly mediate treatment effect  and four had mixed results . A summary of results of mediation analysis are provided in n = 114) indicated that 79% of the intervention effect was mediated by a decrease in post-operative morphine consumption .One study analysed data from a non-randomized observational design, that investigated an intervention for acute pain in children and adolescents (10–18 years) after spinal surgery . One medFive studies analysed 52 mediation models of interventions for youth with chronic pain. All studies performed secondary analyses of data from RCTs and all investigated mechanisms of psychological interventions. A variety of pain conditions were studied, including gastro-intestinal (GI)-related pain  ,29,32, an = 101) at reducing GI symptoms for adolescents (13-17 years) with IBS  [n = 90) at reducing GI symptoms for children (8–12 years) with FAPD  [GI-specific avoidance behaviour mediated 67% of the treatment effect of internet-delivered CBT compared to waitlist control ( −0.62]) . In anot, 3.64]) .n = 90) at reducing GI symptoms for children (8–12 years) with functional abdominal pain disorder  [GI-specific anxiety mediated the treatment effect of internet-delivered CBT compared to treatment as usual  . Perceived pain threat mediated the intervention effect of social-learning CBT on reducing pain intensity at 3-months  and 6-months post-treatment  for children and adolescents (7–17 years) with FAPD . HoweverPain catastrophizing mediated the treatment effect of social-learning CBT at reducing GI symptom severity at 3-months . However, in the same study, pain catastrophising did not mediate the treatment effect on reducing GI-symptom severity at 6- or 12- months; nor did pain catastrophizing mediate the treatment effect on reducing pain intensity at 3-, 6-, or 12 months .n = 101) for adolescents (13–17 years) with IBS  [Perceived stress did not significantly mediate the treatment effect of internet-delivered CBT compared to a waitlist control  .Parent solicitousness did not significantly mediate the treatment effect of social-learning CBT  compared to education on either of two outcomes  for children and adolescents (7–17 years) with FAPD, at any of the three measured time points  . Parent-reported outcomes: Perceived pain threat, pain catastrophizing, parent solicitousness, GI-specific avoidance behaviour and GI-specific anxiety were also evaluated as mediators of treatment effect on outcomes that were parent-reported. Findings were largely similar to those of child-reported outcomes see .n = 30) for children and adolescents (10–18 years) with mixed chronic pain conditions, at reducing pain interference at 3.5-months  and 7-months  and depression at 3.5 months . However, in the same study, pain reactivity did not mediate the treatment effect on reducing depression at 7 months [Pain reactivity mediated the treatment effect of acceptance and commitment therapy (ACT) compared to a multidisciplinary treatment approach with amitriptyline n =  for chiln = 30) for children and adolescents (10–18 years) with mixed chronic pain conditions, at reducing depression at 3.5-months  and 7-months . However, in the same study, pain impairment beliefs did not mediate the treatment effect on reducing pain interference at 3.5- or 7-months [Pain impairment beliefs mediated the treatment effect of ACT compared to a multidisciplinary treatment approach with amitriptyline n =  for chiln = 100) at reducing either of two outcomes  at 6-months post-treatment for children and adolescents (11–18 years) with juvenile fibromyalgia [n = 30) for children and adolescents (10–18 years) with mixed chronic pain conditions, on either of two outcomes  at any measured time-point (3.5- and 7-months post-treatment) [Pain catastrophizing did not mediate the treatment effect of CBT compared to fibromyalgia education  at reducing either of two outcomes  at 6 months post-treatment for children and adolescents (11–18 years) with juvenile fibromyalgia [Pain coping and coping efficacy did not mediate the treatment effect of CBT compared to fibromyalgia education  for children and adolescents (10–18 years) with mixed chronic pain conditions, on either of two outcomes  at any measured time-point (3.5- and 7-months post-treatment) [Self-efficacy, kinesiophobia, and pain intensity did not mediate the treatment effect of ACT compared to a multidisciplinary treatment approach with amitriptyline n =  for chilThere were several important findings from this review. First, the vast majority of analyses reveal variables that did not mediate treatment effect, but there is value in identifying mechanisms that do not explain why interventions work. Second, the mediators that were identified in this review suggest promising targets for interventions. Finally, there are meaningful opportunities to move the field forward by addressing methodological and design considerations.The evidence in this review provides more guidance about mechanisms that do not explain why interventions for youth with pain work, rather than mechanisms that do. That is, 41 of the 53 models did not reveal mediators of treatment effect. While these findings would need to be replicated in a larger number of methodologically-sound studies to increase validity, they provide preliminarily evidence that treatments for youth with pain may not operate via current theoretical explanations. For example, Kashikar-Zuck, et al.  found thThis review revealed mediators that may be promising targets of interventions for youth with pain. Two studies in this review assessed the outcome of GI-symptoms for children  or adoleA key methodological strength of all studies in this review was the establishment of temporality, in that all mediators were measured prior to outcomes. Additionally, three studies conducted sensitivity analyses to test the assumption of temporal precedence. Two studies ,32 incluIn light of the methodological issues raised in this review, and the limited number of included studies, recommendations for future research are provided.b), but the intervention did not affect the mediator , we may modify the intervention to specifically target the mediator. For example, an RCT [All included studies used mediation analysis to investigate mechanisms of effective interventions. However, there is also value in studying failed mechanisms of ineffective interventions. Mediation analysis of unsuccessful interventions can help identify where the hypothesized causal mechanisms break down. The results of such studies can then be used to reproduce or refine interventions. That is, if we identify mediators that have a causal effect on key outcomes , a compThis review also has limitations. Study heterogeneity meant we were unable to compare the magnitude of mediation effects across studies. Publication bias is also a possibility, but the limited number of included studies precluded formal evaluation of it. All but one study  in this This review identified six studies investigating 53 mediation models across a range of interventions for youth with pain. Across two studies, the literature on exposure-based internet CBT for youth with GI-specific chronic pain suggests that GI-avoidance behaviour may be an important mediators of treatment effect. However, comparison of mediating effects across other studies is limited by study heterogeneity. Investigating how treatments for paediatric pain do, and do not work, is an emerging field. Improving the methodological rigour of such investigations is important. Appropriate designs for mediation, emphasising causal assumptions such as confounding and assessing mechanisms of effective and ineffective interventions, should lead to stronger quality evidence for underlying causal mechanisms of interventions for paediatric pain, and ultimately more effective interventions.


The global incidence of tuberculosis (TB) has declined over the last few decades, albeit far slower than envisioned by the World Health Organization (WHO). For 2018–2019, TB incidence only declined by 2.3%, suggesting that WHO objectives for 2030 will not be met2. Ten million persons were infected in 2019, but the burden of TB disease is highest in low- and middle-income countries (LMICs), where 95% of TB deaths occur. The high TB burden countries include India, Indonesia, China, Philippines, and Bangladesh, and these nations also rank among the top ten countries for daily smoking prevalence3. Poverty, poor nutrition, and lack of comprehensive healthcare systems in these nations play into the TB and smoking syndemic.The term ‘syndemic’ describes linked health problems involving two or more conditions that act synergistically, causing an excess burden of disease in the population. These interacting conditions often cluster similarly by person, place, and time. Most importantly, interventions against them must address the underlying conditions that bind the problems together4.Smoking and secondhand smoke exposure are two of several conditions that exacerbate adverse TB outcomes such as recurrent disease, excess mortality, and treatment failure. These conditions include diabetes, poor nutrition, alcohol use, and HIV infection. Because there are over one billion smokers globally, it is not surprising that 17.6% (95% CI: 8.4–21.4) of new cases and 15.2% (95% CI: 1.8–31.9) of TB deaths are attributable to smoking in high burden countries, regardless of other risk factors5, the vast majority of TB patients are neither routinely asked about their smoking status nor advised to quit6.Given the syndemicity of TB and tobacco use, we might ask what would happen if the smoking prevalence among those infected with TB could be effectively reduced through consistent, integrated treatment for tobacco use. Unfortunately, and despite a higher prevalence of smoking in TB patients compared to the general population7 as well as recognition of the need for evidence-based smoking cessation interventions8. The WHO and the Union were first to embrace this challenge in the 2007 Monograph on TB and Tobacco Control, which called for further research and the application of cessation assistance in TB programs9. There are also a few large randomized-controlled trials (RCTs)10 conducted in high-TB burden countries, which highlight that face-to-face behavioral interventions can achieve high quit rates among TB patients8. Those who quit smoking were shown to have better overall clinical outcomes. In these studies, TB staff were able to deliver behavioral interventions for smoking cessation. However, because of several health system barriers11 , no high-TB burden country has so far integrated consistent face-to-face behavioral interventions for smoking cessation within its TB services. Recognizing the challenges of integrating and scaling up face-to-face interventions, WHO has developed a smoking cessation package (mTB-Tobacco) that can be delivered as mobile phone messages to TB patients12.Some progress has been made to meet the syndemic challenge of TB and smoking. There has been increased interest in policies to help TB patients quit smokingThe evidence so far points towards a strong syndemic association between adverse TB outcomes and tobacco use. The evidence is also emerging in support of face-to-face behavioral interventions that can be delivered within health services in high-TB burden countries. On the upcoming World TB Day, we want to emphasize the important contribution of tobacco use in sustaining the TB disease burden and to appeal to policymakers and practitioners in high-TB burden countries that they recognize tobacco cessation as an important part of our efforts to end the global TB epidemic.


Currently, there is minimal data available highlighting the prevalence of venous thromboembolism in patients infected with coronavirus disease 2019 (COVID-19). This case report with a literature review emphasizes a unique presentation of COVID-19 that is highly important for health care providers to consider when treating their patients.A 65-year-old Caucasian male patient presented to the emergency department with a 2-day history of dyspnea on exertion after his wife’s recent diagnosis of COVID-19. He additionally had experienced a couple of episodes of self-resolving diarrhea a few days before presentation. Based on the patient’s clinical presentation and the laboratory workup identifying an elevated D-dimer, a computed tomography angiogram of the chest was obtained, which was significant for moderately large, bilateral pulmonary emboli with a saddle embolus, and an associated small, left lower lobe, pulmonary infarct. Ultrasound of the lower extremity showed non-occlusive deep vein thrombosis at the distal left femoral vein to the left popliteal vein. The patient was additionally diagnosed with COVID-19 when the results of the COVID-19 polymerase chain reaction test returned as positive. The patient was admitted to the COVID unit, and he was started on an intravenously administered, unfractionated heparin drip for management of his bilateral pulmonary emboli and deep vein thrombosis. The patient’s clinical condition improved significantly with anticoagulation, and he was observed in the hospital for 3 days, after which he was discharged home on the enoxaparin bridge with warfarin. Post-discharge telephone calls at day 10 and week 4 revealed that the patient was appropriately responding to anticoagulation treatment and had no recurrence of his symptoms related to venous thromboembolism and COVID-19.As COVID-19 continues to lead to significant mortality, more data is emerging that is exposing its perplexing pathogenicity. Meanwhile, the presentation of venous thromboembolism in patients with COVID-19 remains an unusual finding. It is imperative for health care providers to be mindful of this unique association to make necessary diagnostic evaluations and provide appropriate treatment for the patients. The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), continues to desolate a significant portion of the world’s population, and health care providers continue to see new and frightening displays of its pathogenicity. We report an atypical case involving a 65-year-old male patient with an acute saddle pulmonary embolism and a deep vein thrombosis (DVT) associated with COVID-19.A 65-year-old Caucasian male patient presented to the emergency room with a 2-day history of dyspnea on exertion. He also noted experiencing a couple of episodes of diarrhea a few days before his dyspnea started, which resolved on its own. The patient’s wife had recently been diagnosed with COVID-19. The patient denied any fever, cough, chest pain, or lower-extremity edema. His past medical history included type 2 diabetes, hypertension, and hyperlipidemia. His past surgical history included a remote history of arthroscopic knee surgery. No personal history of malignancy was noted. No family history of hypercoagulable disease or thromboembolism was present. The patient had never smoked, denied drinking alcohol, and had previously been taking metformin, amlodipine, and simvastatin when at home.9/L, hemoglobin of 15.3 g/dL, hematocrit at 44.9%, and platelet count of 158 × 109/L. The basic metabolic panel was within the normal range except for the blood sugar of 235 mg/dL. Troponin was 0.16 ng/mL, with normal total creatinine kinase. D-dimer was elevated at 2241 ng/mL . Pertinent findings on physical examination included clear breath sounds and a regular, rapid heart rhythm on auscultation. There was no lower-extremity edema or calf tenderness. An electrocardiogram (EKG) completed in the emergency room showed sinus tachycardia at a rate of 113 bpm with no acute ST-T segment changes. A chest x-ray showed no acute cardiopulmonary findings. Laboratory data showed a white count of 6.9 × 10The patient was admitted to the COVID unit, and he was started on an intravenously administered, unfractionated heparin drip. Ultrasound of the lower extremity showed a non-occlusive DVT at the distal left femoral vein to the left popliteal vein. Since the patient was hemodynamically stable, tissue plasminogen activator (TPA) administration was not considered. His symptoms significantly improved with anticoagulation. The hypercoagulable panel did not show any other active risk factor for thrombotic conditions.The patient was observed in the hospital for 3 days and then was discharged home on the enoxaparin bridge with warfarin. Since there was a high suspicion of SARS-CoV-2 infection because of exposure through the family member, the patient was instructed to follow strict COVID isolation precautions. Eight days later, his COVID-19 test also came back as positive. Post-discharge telephone calls at day 10 and week 4 revealed that the patient was appropriately responding to anticoagulation treatment and had no recurrence of his symptoms related to VTE/COVID-19.The COVID-19 pandemic started in December 2019 with a collection of patients presenting with pneumonia of unknown origin connected to a seafood wholesale market in Wuhan, China [New evidence, although very limited at this point, showing venous thromboembolism (VTE) as a complication of COVID-19, has started to emerge . The exaViral infections, in general, can lead to an imbalance between pro- and anticoagulant states during the course of the disease and it often involves the disruption of the vascular endothelium . Various. reported objectively confirmed VTE incidence rates of 16%, 33%, and 42% at days 7, 14, and 21, respectively, among hospitalized patients with COVID-19, despite receiving thrombosis prophylaxis. This, however, was a single-center cohort study with a small sample size of 199 patients [. reported a 31% incidence of objectively confirmed VTE and arterial thrombotic complications despite standard thrombotic prophylaxis [In a single-center cohort study, Middeldorp et alDue to the lack of availability of sufficient data, the concept of whether or not to use prophylactic anticoagulation in hospitalized COVID-19 patients to improve their overall clinical outcome continues to remain controversial . Klok etCOVID-19 continues to cause significant mortality as more data is emerging that is aiding in piecing together its perplexing pathogenicity. Scant emerging data is suggesting COVID-19’s role in increased activation of systemic coagulation and further leading to thromboembolic complications such as pulmonary embolism. Here, we presented a case highlighting this very rare presentation. For future direction, we recommend more research focusing on ethical, sound, randomized, controlled clinical trials evaluating the efficacy, safety, dosing, and duration of prophylactic anticoagulation in all hospitalized patients infected with COVID-19 in order to improve survival rates.


Hi-Imagined and Lo-Imagined ePAS significantly increased CME for 30 min post-intervention (p = 0.038 and p = 0.043 respectively). The effects of the two PES intensities were not significantly different. CME was significantly greater after performing imagined movements, compared to voluntary movements, with motor threshold PES (Lo) 15 min post-intervention (p = 0.012). This study supports previous research investigating Lo-Imagined ePAS and extends those findings by illustrating that ePAS interventions that deliver suprathreshold intensities during voluntary or imagined movements (Hi-Voluntary and Hi-Imagined) also increase CME. Importantly, our findings indicate that stimulation intensity and movement type interact in ePAS interventions. Factorial designs are an efficient way to explore the effects of manipulating the parameters of neuromodulatory interventions. Further research is required to ensure that these parameters are appropriately refined to maximise intervention efficacy for people with stroke and to support translation into clinical practice.Advances in our understanding of neural plasticity have prompted the emergence of neuromodulatory interventions, which modulate corticomotor excitability (CME) and hold potential for accelerating stroke recovery. Endogenous paired associative stimulation (ePAS) involves the repeated pairing of a single pulse of peripheral electrical stimulation (PES) with endogenous movement-related cortical potentials (MRCPs), which are derived from electroencephalography. However, little is known about the optimal parameters for its delivery. A factorial design with repeated measures delivered four different versions of ePAS, in which PES intensities and movement type were manipulated. Linear mixed models were employed to assess interaction effects between PES intensity (suprathreshold (Hi) and motor threshold (Lo)) and movement type (Voluntary and Imagined) on CME. ePAS interventions significantly increased CME compared to control interventions, except in the case of Lo-Voluntary ePAS. There was an overall main effect for the Hi-Voluntary ePAS intervention immediately post-intervention ( Advances in our understanding of neural plasticity have prompted the emergence of non-invasive neuromodulatory interventions . These iIn contrast to PAS, endogenous paired associative stimulation (ePAS) is an intervention that substitutes the exogenous TMS stimulation with an endogenous movement-related signal. This endogenous signal is derived from electroencephalography (EEG) and is known as the movement-related cortical potential (MRCP). The MRCP is a slow negative potential observed during the preparation and execution of both imagined and voluntary movements ,16. The Typically, ePAS involves the repeated pairing of a single pulse of electrical stimulation to a peripheral nerve with the MRCP, such that the peripheral afferent stimulus arrives during the peak negativity (PN) of the MRCP ,23. LikePrevious research has shown that ePAS can be delivered with various combinations of afferent stimulation  and endogenous motor activation (imagined or voluntary movement). To date, there has been little systematic exploration of the most effective method of delivering ePAS ,31,32,33Two intervention parameters that may influence the effectiveness of ePAS are (1) the peripheral electrical stimulation (PES) intensity and (2) the movement type: voluntary or imagined. With regards to PES intensity, research to date has delivered ePAS with the electrical stimulation set to motor threshold ,25,28,31When exploring the effect of manipulating both PES intensity and movement type, it is important to consider their interaction. The literature indicates that greater increases in CME are seen when PAS or PES is combined with voluntary movement rather than with no movement ,51,52,53The primary aim of this study was to investigate whether ePAS delivered using single pulses of suprathreshold PES, paired with MRCPs produced during voluntary ankle dorsiflexion movements, would yield a super-additive increase in CME in healthy adults, and whether this effect would be maintained for 45 min post-intervention. The secondary aims of this study were to investigate whether (a) ePAS using suprathreshold PES paired with voluntary dorsiflexion movement would yield the greatest effect on CME compared to all other interventions, (b) ePAS interventions that delivered suprathreshold PES intensities would yield greater effects on CME than those that delivered motor threshold PES or did not deliver PES (control), and (c) ePAS interventions that involved voluntary dorsiflexion movements would yield greater effects on CME than those involving imagined movements.This study employed a factorial design comprising six interventions with repeated measures refer to . FactoriParticipants completed a baseline testing session in which their MRCP was recorded during both voluntary and imagined ankle dorsiflexion movements. This was followed by six intervention sessions, which were completed in a randomised order and separated by at least 48 h. Randomisation was restricted so that no two sequences were identical. Interventions included (1) Hi-Voluntary ePAS: suprathreshold PES and voluntary dorsiflexion; (2) Hi-Imagined e-PAS: suprathreshold PES and imagined dorsiflexion; (3) Lo-Voluntary e-PAS: motor threshold PES and voluntary dorsiflexion; (4) Lo-Imagined e-PAS: motor threshold PES and imagined dorsiflexion; (5) Control-Voluntary: voluntary dorsiflexion alone; and (6) Control-Imagined: imagined dorsiflexion alone. TMS-derived measures of CME were recorded using single-pulse TMS immediately before and at 0, 15, 30, and 45 min following each intervention by a blinded assessor.The study was powered to detect a super-additive effect size of 130 µV, corresponding to a Cohen’s effect size of 0.55 for the primary hypothesis. Simulations were predicated on the most relevant available literature , where THealthy adults aged over 18 years with no known neurological conditions volunteered for the study. Participants were excluded if they were taking medications that may have affected central nervous system excitability. Prior to the study, all participants completed a TMS screening eligibility questionnaire  and provDuring session 1, MRCPs were derived from the EEG recorded during 50 repetitions of visually cued voluntary ankle dorsiflexion movement and 50 repetitions of visually cued imagined ankle dorsiflexion movement. The order of these two recordings was pseudo-randomised and separated by a 10-min rest period. Participants were seated with approximately 100° of hip flexion and the legs supported in 25° knee flexion with the ankles in a relaxed, slightly plantarflexed position. A 40-channel EEG cap  was positioned with the CZ electrode positioned halfway between the nasion and the inion and halfway between each tragus. A sterile blunt needle was used to lightly abrade the scalp and administer conductive gel to the FP1, F3, FZ, F4, C3, CZ, C4, P3, PZ, and P4 electrodes . A reference electrode was positioned over the mastoid process, and a ground electrode was placed on the forehead. Impedance of less than 5 kΩ was maintained.Participants were familiarised with the visual cue displayed on a computer monitor that was customised in MATLAB software 7.13  focus on the screen, (2) prepare for the ankle movement by watching a moving cursor, (3) execute either a ballistic voluntary or imagined dorsiflexion movement with their right ankle at a specified time-point and hold for 1 s, and (4) rest. The length of focus and rest periods varied . Participants completed two sets of 25 repetitions for both voluntary and imagined movement conditions, while continuous EEG was recorded via a 40-channel EEG amplifier  and sampled at 500 Hz with 32-bit accuracy .Continuous EEG signals were imported into MATLAB software 8.5 , where individual EEG channels were band-pass filtered from 0.05 to 5 Hz with a second-order zero-phase Butterworth filter. All channels excluding FP1 were spatially filtered using a large Laplacian filter to acquire a single virtual channel with CZ as the centre electrode . The virEach session was conducted at a similar time of day, and sessions were separated by a minimum of 48 h. Participants adopted the same seated position as described in session 1. The six different interventions were dose-matched (number of repetitions n = 50) and lasted approximately 15 min. Participants followed the same visual cue described in session 1.The primary outcome measure was TMS-induced motor evoked potentials (MEPs) of the tibialis anterior (TA) muscle; this was assessed with single-pulse TMS during a 10% maximal voluntary contraction (MVC) of the dorsiflexor muscles to provide an indication of CME . MEPs weFor recording MEPs, electromyography (EMG) surface electrodes  were placed over the muscle belly of the right TA muscle and a reference electrode was positioned over the right tibia based on SENIAM guidelines . Prior tPrior to CME measurements, each participant’s dorsiflexor MVC was established. Fastening belts were secured around the right foot and ankle and both hips to maintain a stable position. Participants were instructed to dorsiflex their right ankle as hard as possible for 3–5 s and were provided with loud vocal encouragement and continuous visual feedback via an oscilloscope . Participants performed three MVC contractions, each followed by a 2-min rest. Isometric dorsiflexion force data were collected using a single axis load cell , sampled at 100 Hz via a data acquisition board  and processed using Signal software . The MVC was established by measuring the peak amplitude of the largest of the three trials and deducting the mean baseline value recorded at rest . A 10% MFor the application of TMS, participants wore a fitted cap with 1 × 1 cm gridlines relative to the vertex. Single-pulse TMS was administered with a Magstim 200 using a monophasic pulse and posterior-anterior current flow  via a doThe peripheral electrical stimulation  was applied via two additional surface electrodes  that were positioned on the skin over the right deep common peroneal nerve (dCPN), approximately 2–4 cm anteriorly and inferiorly to the head of the fibula, with the cathode placed proximally. The optimal stimulation location was determined by palpating for TA tendon movement without the presence of palpable synergistic and antagonistic activity ,31,32. On = 5, mean intensity 33 mA, mean VAS 4/10). Of the four ePAS interventions, the two interventions Hi-Voluntary and Hi-Imagined delivered a PES intensity at 300% of MTh to elicit a substantial TA muscle contraction. The other two interventions, Lo-Voluntary and Lo-Imagined, delivered a PES intensity at 100% of MTh to elicit a palpable flicker in the TA tendon  of PES were delivered to the dCPN. Each 1 ms PES pulse was delivered 50 ms prior to the PN of the participant’s average MRCP for the corresponding movement condition. The 50 ms represents the average conduction time from the dCPN to the M1 .For the two control interventions (Control-Voluntary and Control-Imagined), participants performed either 50 visually cued voluntary dorsiflexion movements or 50 visually cued imagined dorsiflexion movements of the right ankle. Sham PES was delivered concurrently (set to 0% MTh). An illustration of the laboratory set-up is displayed in TA EMG data were processed using Signal software . A predefined processing criterion was established to address contaminated EMG responses at each of the measurement time-points and is provided in a priori to refrain from applying corrections of adjustment for multiplicity due to the explanatory nature of this study [A detailed account of the pre-specified statistical analysis plan is provided in the is study . Type IIThe mean age of the 25 participants was 28 ± 7 years (range 19–52), and 15 participants were female. Three potential participants were excluded from the study, one due to a recent skull fracture and two due to routinely taking medication that may have altered excitability of the central nervous system.During the processing of the 50 MRCP epochs, on average, 5 ± 2 and 9 ± 6 epochs, for voluntary and imagined movement conditions, respectively, were manually rejected due to eye blinks or artefacts. The timing of the PN of the averaged MRCP occurred at a mean of 13 ± 67 ms after the cue in the voluntary movement condition and 4 ± 155 ms after the cue in the imagined condition. The dCPN PES was delivered at the following intensities during each of the four ePAS interventions: Hi-Voluntary 37 ± 18 mA, Hi-Imagined 33 ± 16 mA, Lo-Voluntary 14 ± 8 mA, and Lo-Imagined 11 ± 4 mA.Baseline raw MEP values for absolute MEP amplitude and MEP area are reported in Due to the explanatory nature of this study, a large number of results were generated from the models. Within this paper, we present the key findings, and all other results are provided in the The primary aim was to investigate whether Hi-Voluntary would yield a super-additive increase in CME, which was maintained for 45 min post-intervention. p = 0.0001) and MEP area (p < 0.00005). The analysis did not reveal a super-additive effect. However, a significant sub-additive effect was observed for absolute MEP area 30 min post-intervention . There was no significant interaction for suprathreshold stimulation versus threshold stimulation and voluntary versus imagined movement for absolute MEP amplitude (p = 0.139) and MEP area (p = 0.108).For the Hi-Voluntary intervention, the analysis revealed an interaction between suprathreshold stimulation intensity versus no stimulation and voluntary versus imagined movement for both absolute MEP amplitude (p = 0.0013) and MEP area (p = 0.0004). A significant sub-additive effect occurred at 15 min post-intervention for the absolute MEP amplitude  and MEP area . This sub-additive effect extended to 30 min post-intervention for absolute MEP area .An unplanned post hoc analysis investigated whether Lo-Voluntary also had a sub-additive effect on CME. This analysis confirmed a significant interaction between threshold stimulation intensity (100% MTh) versus no stimulation (0% MTh) and voluntary versus imagined movement for absolute MEP amplitude (A secondary aim of the study investigated whether ePAS using suprathreshold PES paired with voluntary dorsiflexion movement (Hi-Voluntary) would yield the greatest increase in CME compared to all other interventions. These comparisons are illustrated in p = 0.002) and when compared to Control-Imagined immediately post-intervention . Comparisons for Hi-Voluntary with each of the other ePAS interventions  were non-significant at all time-points .Absolute MEP amplitudes were significantly greater for Hi-Voluntary compared to Control-Voluntary immediately post-intervention .Results for absolute MEP area replicated those of absolute MEP amplitude, except in the case of Hi-Voluntary compared to Lo-Imagined, where a greater significant effect was observed at 15 min post-intervention for the Lo-Imagined intervention  would yield greater increases in CME than those that delivered threshold intensities  and no stimulation . These comparisons are illustrated in p > 0.1 in all comparisons).Comparisons for ePAS interventions delivered with suprathreshold compared to threshold stimulation for either voluntary or imagined movement conditions  were not significant for absolute MEP amplitude or MEP area (p = 0.002). For the imagined movement interventions, absolute MEP amplitudes were significantly greater for Hi-Imagined compared to Control-Imagined immediately , 15 min  and 30 min post-intervention . Results for absolute MEP area replicated those of absolute MEP amplitude, except in the case of the averaged over time comparison that determined a significantly greater increase for Hi-Imagined compared to Control-Imagined .Comparisons determined that absolute MEP amplitudes were significantly greater for Hi-Voluntary compared to Control-Voluntary immediately post-intervention only . However, for Lo-Imagined, there were significant increases in absolute MEP amplitude when compared to Control-Imagined immediately post-intervention , 15 min post-intervention , and averaged over time . The results for absolute MEP area replicated those of absolute MEP amplitude, except in the 30 min post-intervention time-point comparison that revealed a significantly greater increase for Lo-Imagined compared to Control-Imagined .There were no significant differences in absolute MEP amplitude for any of the comparisons made for Lo-Voluntary and Control-Voluntary  would yield greater increases in CME than treatment interventions that involved imagined movements . Comparisons made between voluntary and imagined movement at different intensities of stimulation are illustrated in p > 0.1 in all comparisons).Comparisons for the Hi-Voluntary and Hi-Imagined interventions were non-significant for absolute MEP amplitude and MEP area (p = 0.012). The results for absolute MEP area replicated those of absolute MEP amplitude, except in the case of the averaged over time comparison that determined a significantly greater increase for Lo-Imagined compared to Lo-Voluntary .Comparisons determined that absolute MEP amplitude was significantly greater for Lo-Imagined compared with Lo-Voluntary at 15 min post-intervention only .Comparisons for the Control-Voluntary and Control-Imagined interventions were non-significant for absolute MEP amplitude and MEP area  produced a smaller increase in CME than the sum of these two parameters. Given that CME was significantly greater following Hi-Voluntary than following Control-Voluntary, it can be asserted that while the Hi-Voluntary intervention loses some of the effect of stimulation intensity and voluntary movement when paired, the intervention is more effective at increasing CME than performing voluntary movement alone (Control-Voluntary). A potential explanation for why we did not find a super-additive effect for the Hi-Voluntary intervention could be that the intervention parameters require further refinement and optimisation. Further work is required to fully elucidate the mechanisms of action of this intervention.The primary objective of this study was to investigate whether an ePAS intervention that paired suprathreshold PES with the MRCP during voluntary movement (Hi-Voluntary) would yield a super-additive increase in CME of the TA muscle in healthy adults for up to 45 min post-intervention. Our findings did not confirm this hypothesis. The MEP area analysis did reveal a significant interaction between stimulation intensity and movement type, illustrating a For the secondary analyses of the factor ‘stimulation intensity’, it was hypothesised that interventions that delivered suprathreshold stimulation  would yield greater increases in CME than those that delivered threshold PES  or no stimulation . This hypothesis was not supported, as there was no difference between suprathreshold and threshold stimulation. However, there were differences between stimulation  and no stimulation .sub-additive effect at some time-points post-intervention. It is notable that the magnitude of the sub-additive effect was greater for the Lo-Voluntary intervention than for the Hi-Voluntary intervention. In voluntary movement conditions, the low-intensity afferent volley generated in the Lo-Voluntary intervention may be subsumed by the endogenous motor cortex activation generated during the preparation and execution of voluntary movement. Jochumsen and colleagues [The post hoc analysis investigating the interaction effect of the Lo-Voluntary intervention revealed that, akin to Hi-Voluntary, Lo-Voluntary had a lleagues  showed tlleagues ; muscle lleagues ,75,76,77In contrast to our findings in healthy people, Lo-Voluntary ePAS applied to people with stroke has been shown to be more effective than attempted voluntary movement alone for increasing CME ,29 and mFor the secondary analyses of the factor of ‘movement type’, it was hypothesised that interventions that involved voluntary movement  would yield greater increases in CME than imagined movements . Our findings did not support this hypothesis, demonstrating no difference in CME between voluntary and imagined movement conditions except for the Lo-Imagined intervention. When compared to the Lo-Voluntary intervention, Lo-Imagined yielded larger effects at 15 min post-intervention (MEP amplitude and MEP area) and when all time-points were averaged (MEP area). The effect of the Lo-Imagined intervention has been demonstrated in previous ePAS studies in healthy people ,25,26,27In this study, we used the same ISI across all participants for each of the four ePAS interventions . It is pA final consideration for the delivery of ePAS using either voluntary or imagined movement is its potential application to stroke rehabilitation. Whilst the imagined movement condition was more effective when the PES was delivered at the motor threshold (Lo-Imagined), we have previously acknowledged the potential benefits of giving higher intensity stimulation to people with stroke, and in this study, the combination of higher intensity stimulation with voluntary movement (Hi-Voluntary) produced significant effects. In addition, people with stroke might have difficulty performing motor imagery due to cortical damage , and vola priori statistical analysis plan, including the consideration of baseline covariates that might introduce variability in the data, and an analysis of both MEP amplitude and area and measures of change (absolute and relative). A number of considerations are required when interpreting the results.To our knowledge, this is the first study to begin to unpack the effects of different intervention parameters of a neuromodulatory intervention using a factorial design. The findings of this study are strengthened by the use of a sound First, the study was powered to detect changes in MEP amplitude, not MEP area, yet some findings were only observed in MEP area data. Our choice of MEP amplitude as a primary outcome measure was driven by the availability of data for the sample size calculation . HoweverSecond, whilst the sample size was powered to detect a super-additive effect corresponding to a Cohen’s effect size of 0.55, our data featured a much larger between-participant standard deviation at the pre-intervention time-point than the work used to power this study , resultiThird, whilst we made every effort to ensure high methodological quality during TMS measurement procedures see  the use Fourth, the method used in this study to identify the timing of the peak negativity involved an offline manual method, where the MRCP data were averaged from pre-recorded voluntary and imagined movements. This method has been used extensively in the literature to determine the timing of the temporal pairing in efficacious ePAS interventions ,30,33,92Finally, a factorial design enables the researcher to evaluate multiple intervention parameters and identify potential interactions between these parameters whilst maintaining statistical efficiency . HoweverFactorial designs should be used to explore the interaction effects of different intervention parameters in neuromodulatory interventions; parameters could include stimulation intensity, movement type, ISI, and the number of stimuli.To support translation into clinical practice, this work and similar factorial designs should be undertaken in people with stroke. These studies should not only explore the neurophysiological effects of the intervention but also assess changes in impairment and functional outcomes.Using TMS measurements from both resting and active muscle would allow comparison to previous work and enable the researcher to consider the impact of measurement error on the findings.The baseline covariates AMTh and MVC were considered and suitably adjusted for in the factorial models for the primary analysis of this study. Future research should also consider interactions with baseline covariates as part of a pre-planned blind model selection process. This may shed light on how baseline covariates modulate responses to neuromodulatory interventions.In order to advance our understanding of the optimal delivery of ePAS, we recommend that future research consider the following:Factorial designs are an efficient way to explore the effects of manipulating the parameters of neuromodulatory interventions. The present study systematically unpacked the effect of manipulating PES intensity and movement type in ePAS interventions. Our findings make several contributions to the current evidence. First, the findings are consistent with previous research investigations that support the excitatory effect of Lo-Imagined ePAS interventions on CME in healthy people. Second, this study extends those findings by demonstrating that delivering suprathreshold PES stimulation intensities during both Hi-Imagined and Hi-Voluntary ePAS interventions is also effective. Third, our findings indicate an interaction effect between intervention parameters; this effect was sub-additive for Hi-Voluntary and Hi-Imagined ePAS interventions. From a clinical perspective, we have discussed the potential benefits of delivering Hi-Voluntary ePAS. However, to support translation into clinical practice, further research is necessary to evaluate the efficacy of different configurations of stimulation intensity and movement type in people with stroke. Further factorial study designs should be considered to determine the most effective ePAS intervention parameters for people with stroke.


Foal weight always approximated 10% of mare weight but relative placenta weight was highest in full-size mares. The concentrations of progestins (hormones that maintain pregnancy) and cortisol  was highest in full-size mares. Progestin concentration decreased towards foaling while cortisol concentration increased. Heart rate of mares increased before foaling with the most pronounced increase in small mares. Overall, Shetland mares foaled earlier than larger-size mares. At foaling, atrio-ventricular blocks  regularly occurred in full-size mares but only occasionally in medium-size and small mares, reflecting differences in heart efficiency. In conclusion, some differences exist before and at foaling in horses of different size.Monitoring of the pregnant mare and her fetus is based on hormone analysis and heart rate recordings which may differ among small, medium-size, and full-size horses. Therefore, Shetland (n = 6), Haflinger (n = 8), and Warmblood pregnancies (n = 9) were studied during late gestation and at foaling. Weight of mares, foals and placenta, plasma progestin and cortisol concentration, heart rate and heart rate variability (HRV) were determined. Foal weight always approximated 10% of mare weight but relative placenta weight was highest in full-size mares (p < 0.05). Progestin (p < 0.001) and cortisol (p < 0.05) concentration was highest in full-size mares. Progestin concentration decreased towards parturition (p < 0.001) while cortisol concentration increased (p < 0.01). Maternal heart rate increased before foaling with the most pronounced increase in small mares (p < 0.001). The HRV increased during foaling and decreased when delivery was completed (p < 0.001). Changes were most pronounced in full-size mares (p < 0.001). Atrio-ventricular blocks regularly occurred in parturient full-size mares but only occasionally in medium-size and small mares . This may reflect breed differences in cardiovascular efficiency. Fetal heart rate decreased towards birth (p < 0.001) with the most pronounced decrease in full-size horses (p < 0.01). Fetal HRV showed no consistent changes before birth but increased when the foal was born (p < 0.001), this increase being most pronounced in full-size foals (p < 0.05). In conclusion, this study demonstrates both similarities and differences in peripartum endocrine and cardiac changes in horses of different size.Equine fetomaternal monitoring is based on endocrine and cardiac parameters which may differ among small, medium-size, and full-size horses. Therefore, Shetland ( Despite advances in equine obstetrics and perinatal medicine, late fetal mortality, abortion, and the birth of compromised neonates are still major problems in horses . TherefoA key diagnostic parameter for fetal well-being is heart rate, which can easily be evaluated by fetomaternal electrocardiogram (ECG) recordings. In addition to heart rate, heart rate variability (HRV) reflects the fine-tuning of cardiac regulation by the autonomous nervous system. Changes in the regulatory effects of the autonomous nervous system on the cardiac beat-to-beat interval are interpreted as fetal maturation during gestation. Changes in HRV may also indicate a fetal stress–response to unfavorable conditions ,7,8. FetResearch animals in studies on equine pregnancy and foaling are usually full-size horses or occasionally larger pony breeds. The results, however, are often generalized to horses of all sizes. In cattle, endocrine changes in the peripartum period in part even differ among breeds ,14,15 anThe study was approved by the competent authorities for animal experimentation in Austria  and Germany .n = 6, Shetland pony), medium-size , and full-size . All foals were pure-bred, i.e., all Shetland, Haflinger, and Warmblood mares had been bred to Shetland, Haflinger, and Warmblood stallions, respectively. Age of the mares and sex of their foals are listed in A total of 23 late pregnant mares and their foals were included into the study. All mares were healthy on a thorough physical examination before the start of the study. Depending on their size, the animals were divided into the following groups: small  as described previously and validated for equine plasma in our laboratory [Blood was collected into heparinized tubes  and samples were centrifuged at 1200× boratory . The intr = 0.999) and near-identical [Fetomaternal ECGs were recorded with the Televet 100 device and evaluated with the software version 5.1.1  as described previously . This sodentical .For analysis of heart rate and HRV parameters, the Kubios HRV Software  was used. From the recorded RR intervals, a five-minute sequence was used for determination of heart rate and the HRV variable SDRR  in mares and fetuses.Cardiac arrhythmias in parturient mares were determined as described previously . Maternap-value < 0.05 was considered significant. All values given are means ± standard error of mean (SEM).Statistical comparisons were made with the SPSS statistics software . Data were tested for normal distribution by the Kolmogorov–Smirnov test. Data for gestation length, weight of foal, mare and placenta, time from parturition to expulsion of fetal membranes, time from birth of the foal to first suckling, cortisol and progestin concentrations  were not normally distributed and were compared among groups by the Kruskal–Wallis Test with post-hoc comparisons by the Mann–Whitney Test in the case of an overall significant difference. Data for heart rate, HRV, cortisol, and progestins were not normally distributed and log transformed before analysis. Comparisons were made by ANOVA with a general linear model (GLM) for repeated measures with time as within subject factor and group as between subject factor. In case of an overall significant difference among groups, pair-wise post-hoc comparisons were made by a Tukey test. A p < 0.05) with medium-size (Haflinger) mares not differing from the other two groups. The time from birth of the foal to expulsion of the fetal membranes was shorter in the group of small versus medium and full-size mares (p < 0.05). Time to first suckling of the foal did not differ between groups  than in full-size (Warmblood) mares . Foal body weight in relation to weight of the placenta was highest in full-size breed foals (p < 0.01) but did not differ between small and medium-size foals.The absolute weight of mares and foals on day 1 after parturition as well as placental weight differed significantly among groups , but a group difference was still evident after foaling  mares compared to medium-size (Haflinger) and small (Shetland) mares . Group differences in heart rate were still evident at foaling. In mares from all groups, the heart rate decreased during and shortly after expulsion of the foal and remained largely constant thereafter . The decrease in HRV was more pronounced in small compared to full-size mares . Second degree atrioventricular (AV) blocks were the only cardiac arrhythmias observed and were detected only in parturient mares. The AV blocks were most evident in full-size mares from 30 min before to 120 min after delivery. There were less AV blocks in medium-size and small mares and they were observed only until 45 min after complete delivery of the foal  and differed slightly between full-size and medium-size horses  but increased transiently when the foal was born (time p < 0.001, group p = 0.03, post-hoc comparison Haflinger vs. Shetland p = 0.05; Fetal heart rate was close to identical in all groups on day 20 before birth. Fetal heart rate decreased and increased thereafter in all groups (time This study demonstrates both similarities and clear differences in characteristic endocrine and cardiac changes before, during, and after parturition in horses of different size. With the Shetland as one of the smallest horse breeds, the Haflinger as a medium-size draft-type breed and the Warmblood sport horse as a large full-size breed, the spectrum of weight and size that exists in horses was well represented in the present study. Because of the number of animals included into the study, our results primarily demonstrate the existence of size differences with regard to the parameters determined and indicate the direction of such differences while not yet allowing to define normal ranges for horses of different size or breed .As expected from the experimental design, the weight of mares, their newborn foals, and the placenta clearly differed among small, medium-size, and full-size horses. In agreement with previous studies ,20, in aLate equine gestation is maintained by progestins originating from the fetoplacental unit . In agreSecond degree AV blocks regularly occurred in healthy full-size Warmblood mares during the expulsive phase of labor and the first two hours after delivery but were only occasionally seen in medium-size Haflinger and small Shetland mares. While AV blocks in parturient Warmblood mares of the present study confirm a previous report , their nFetal adrenocortical activation  but alsoFetal heart rate was close to identical in all groups 20 days before foaling. Only during the last 20 days of gestation did the fetal heart rate diverge among groups and remained lower in full-size than in medium-size and small mares until foaling. Towards the end of gestation, the fetal autonomous nervous system undergoes maturational changes and this is reflected by a decrease in fetal heart rate and an increase in HRV in all groups. Heart rate usually increases with decreasing size of the animal and thus is higher in postnatal or adult ponies than in large breed horses ,35. As pHorses in our study were kept at two different localizations but housing at both places was close to identical with regard to stables, paddocks, and space available per horse. All horses were managed and strictly controlled by our research group. Warmblood horses but not Haflinger and Shetland mares were fed oats in addition to hay, but this difference was due to different energy requirements and would have also occurred if all horsed had been kept in the same place. Comparisons between different types, sizes, or breeds in a given species are usually based on different studies often performed at different times and by different authors utilizing different analytical procedures. In contrast, in the present study, all experimental groups were submitted to an identical sampling and observation protocol and all laboratory parameters were determined together at the same place and with the same assays. Results from the three mare groups studied are therefore directly comparable.Although the physiological changes preceding foaling in principal are similar among horses of different size and type, they differ in detail. Foaling occurs under parasympathetic dominance in all horses, but this parasympathetic tone is associated with frequent AV blocks at parturition only in horse breeds selected for athletic performance. Placental progestin synthesis is more efficient in full-size compared to medium size and small mares. These size-related differences have to be taken into account when fetal and maternal well-being needs to be evaluated.