Multidimensional Associations Research Articles

Decoding Metadiscourse Markers in Estonian Academic Texts: A Language-Specific Perspective

This article presents the development of a specialized data set for analyzing Estonian metadiscourse markers in academic usage, extending Hyland's interpersonal metadiscourse model to a non–Indo-European language. Our goal is to show how metadiscourse, as a feature of a writing tradition, can reveal aspects of writing in languages other than English, complementing the traditionally Anglo-centric perspective in metadiscourse research. By analyzing 21 Estonian linguistics research articles, we offer a transparent procedure to address methodological issues in metadiscourse studies and demonstrate the need for language-specific adjustments in the framework. We introduce statistical methods for analyzing multidimensional associations among marker categories, linguistic level, and rhetorical text structure. The findings suggest that Hyland’s metadiscourse model can be adjusted for specific languages, highlighting the influence of language structure on metadiscourse category variation and linguistic expression levels. The study reinforces that the distribution and manifestation of metadiscourse are shaped, among other factors, by unique writing traditions.

Multidimensional associations of physical performance, balance, wellness and daily activities with frailty in older adults with coexisting frailty and diabetes.

The coexistence of frailty and type 2 diabetes mellitus in the older population heightens the risk of adverse events. However, research on functional and wellness factors associated with frailty in this population is limited. To investigate the associations of physical performance, functional dependency, physical activity, nutritional status, sleep, self-perceived health and depression with frailty in community-dwelling older adults with coexisting frailty and type 2 diabetes mellitus. Cross-sectional. The study included 123 community-dwelling older adults (73.7 ± 6.0 years) with pre-frailty/frailty and type 2 diabetes mellitus. Physical performance (Short Physical Performance Battery), functional dependency (Barthel Index and Lawton & Brody), physical activity and inactivity (GeneActiv wrist-worn accelerometer), malnutrition risk (Mini Nutritional Assessment), sleep (Pittsburgh Sleep Quality Index), self-perceived health (EuroQoL 5-Dimension 3-Level) and depression (Yesavage 15-item-Geriatric-Depression-Scale) were evaluated through personal interviews. Principal component analysis (PCA) was performed to categorize the variables into components, and logistic regressions were used to propose the best-fitted model for each component. The PCA identified four components: (i) physical performance, with gait speed and leg mean velocity as the main variables associated with frailty; (ii) balance, showing significant associations with monopodal balance; (iii) daily activities, with moderate to vigorous physical activity and the Lawton and Brody score as the main variables associated with frailty within this component; and (iv) wellness factors, with nutritional status, self-perceived health and depression score as the primary variables associated with frailty. This research underscores the significance of physical function and daily activities as protective factors against frailty in community-dwelling older adults with coexisting frailty and type 2 diabetes mellitus. The health dimension contributes both protective and risk factors, emphasizing the need for comprehensive assessments in managing frailty in this population. The study adhered to the STROBE checklist. No patient or public contribution.

Rationale and design of the CONFIRM2 (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) study

BackgroundIn the last 15 years, large registries and several randomized clinical trials have demonstrated the diagnostic and prognostic value of coronary computed tomography angiography (CCTA). Advances in CT scanner technology and developments of analytic tools now enable accurate quantification of coronary artery disease (CAD), including total coronary plaque volume and low attenuation plaque volume. The primary aim of CONFIRM2, (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) is to perform comprehensive quantification of CCTA findings, including coronary, non-coronary cardiac, non-cardiac vascular, non-cardiac findings, and relate them to clinical variables and cardiovascular clinical outcomes. DesignCONFIRM2 is a multicenter, international observational cohort study designed to evaluate multidimensional associations between quantitative phenotype of cardiovascular disease and future adverse clinical outcomes in subjects undergoing clinically indicated CCTA. The targeted population is heterogenous and includes patients undergoing CCTA for atherosclerotic evaluation, valvular heart disease, congenital heart disease or pre-procedural evaluation. Automated software will be utilized for quantification of coronary plaque, stenosis, vascular morphology and cardiac structures for rapid and reproducible tissue characterization. Up to 30,000 patients will be included from up to 50 international multi-continental clinical CCTA sites and followed for 3–4 years. SummaryCONFIRM2 is one of the largest CCTA studies to establish the clinical value of a multiparametric approach to quantify the phenotype of cardiovascular disease by CCTA using automated imaging solutions.

Kinesiophobia and associated variables in patients with heart failure.

Patients with heart failure (HF) can exhibit kinesiophobia, an excessive, debilitating, and irrational fear of movement. This study aimed to enhance the understanding of kinesiophobia in patients with HF by analysing associations with the following variables: musculoskeletal pain, quality of life, quality of sleep, functional capacity, disability, frailty, sex, and age. In this cross-sectional study, 107 participants were included, with ages ranging from 28 to 97 years (57% men, mean age 73.18 ± 12.68 years). Multiple regression analyses were performed with all variables, including polynomial regressions for variables with a non-linear relationship. Kinesiophobia was significantly correlated (P < 0.01) with musculoskeletal pain, quality of life, quality of sleep, functional capacity, disability, and being at risk of frailty, while age and sex were not statistically significant. Frailty disability and musculoskeletal pain intensity were variables linearly associated with kinesiophobia, while quality of sleep and disability had a non-linear relationship with kinesiophobia. Kinesiophobia needs to be evaluated and better understood in patients with HF to improve physical activity and exercise adherence. This study found that musculoskeletal pain intensity, quality of sleep, disability, and frailty risk have a significant association with kinesiophobia in patients with HF. Our results suggest multi-dimensional associations of kinesiophobia in patients with HF, which require further examination and understanding.

Schizophrenia and the COVID-19 pandemic: A narrative review from the biomedical perspective.

The outbreak of the Coronavirus Disease 2019 (COVID-19) pandemic in 2020 caused a rapid worsening of global mental health. Patients with severe mental disorders, including schizophrenia, are at higher risk of being infected. The neuroinvasive potential of the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) has been confirmed. The aim of this article was to present a narrative and comprehensive review of multidimensional associations between schizophrenia and COVID-19 with special emphasis on common biological pathways. Online searches were performed in the PubMed database and covered the publication period until September 17, 2022. Search terms included "psychosis", "schizophrenia", "inflammation" and "COVID-19". Viewed as a neuroinflammatory state, schizophrenia shares several neurobiological mechanisms with the COVID-19. Environmental stress, common comorbidities of schizophrenia and adverse effects of antipsychotic treatment are associated with the higher severity and mortality of the COVID-19. Additionally, more frequent relapses of psychosis have been observed, and might be related to lower treatment adherence. In the context of clinical manifestation, higher level of negative symptoms has been identified among patients with schizophrenia during the pandemic. Improvements in mental health care policy and treatment adjustment are necessary to protect people with schizophrenia who are the population that is particularly vulnerable to the consequences of the COVID-19 pandemic. Future research will show if prenatal infection with the SARS-CoV-2 increases a risk of psychosis.

Clustered Associations between Musculoskeletal Fitness Tests and Functional Movement Screen in Physically Active Men.

Functional Movement Screen (FMS) is a tool used to assess fundamental movement patterns. There are relationships between musculoskeletal fitness (MSF) and a FMS. However, there is limited data regarding the multidimensional associations between these two constructs. This study is aimed at investigating the associations and detailed structures of FMS components and MSF components and identifying a deeper detailed structure of their relations to physical fitness. The study sample included 114 physically active men with an average body height of 1.81 ± 0.07 (cm), body weight of 80.61 ± 9.49 (kg), and a BMI of 24.65 ± 2.46 (kg/m2). Each participant performed a FMS test, sit-and-reach (S&R) test, sit-ups (ABS) evaluation, balance evaluation on an AMTI platform, handgrip strength (HG) testing, and standing broad jump (SBJ) ability. The Kendall's Tau correlation was performed to identify simple associations between FMS and MSF. Cluster analysis was used to determine the multidimensional nature of the relationships. In the vast majority, a positive correlation was observed suggesting that a high level of MSF improved FMS test results. A cluster analysis revealed 4 separate clusters. Shoulder mobility (SM) was identified as a single cluster. A strong similarity was observed between SBJ and trunk stability push-up (TSPU) forming a second cluster. This cluster joined to another consisting of the S&R test and active straight leg raise (ASLR) test. The last cluster consisted of HG and hurdle step (HS). These results confirmed that FMS and MSF tests measure the same constructs-a foundation for an individual's motor coordination, muscle strength, postural stability, and dynamic balance. This knowledge could be helpful in effectively enhancing physical performance based on combining similar constructs to accelerate the achievement of established goals.

Life Satisfaction and Quality of Life in AML Long-Term Survivors: Primary Results of the AMLCG-Survivorship Study

Introduction An increasing proportion of patients with acute myeloid leukemia (AML) become long-term survivors (AML-LTS). Somatic and psycho-social outcomes are therefore becoming increasingly important, but little is known about the long-term effects of the disease and its treatment. Methods We designed a comprehensive analysis of AML survivorship outcomes including psycho-social well-being and somatic health status, and conducted a questionnaire-based study collecting data from long term survivors and their physicians. This report focuses on general and health-related life satisfaction (gLS/hrLS, measured by the FLZ-M questionnaire). Compared to quality of life (QoL), LS takes into consideration the subjective importance of various areas of life, and the participant's satisfaction with each. Impact of anxiety and depression, incidence of secondary cancer as well as clonal hematopoiesis are reported separately (Görlich et al, Moret et al, Krauss et al). We compared LS of AML-LTS with normative data of German adults not diagnosed with AML. Participants' FLZ-M scores were standardized relative to age- and sex-stratified normal population means and standard deviations. Results 427 former AML patients who had been enrolled in AMLCG clinical trials (AMLCG-1999/-2004/ -2008) or the AMLCG patient registry participated in this study between 5 and 18.6 years [y] after their initial AML diagnosis (median, 11.3y). Median age of AML-LTS was 61y (range 28y-93y), and 56% were female. Thirty-eight percent of participants had been treated with chemotherapy alone, while 62% received at least one allogeneic stem cell transplant (HSCT). A relapse had occurred in 24% of participants. Unexpectedly, the gLS summary score (median, .12) was significantly higher in AML-LTS (p<.001) compared to controls (median, 0), although differences were small (95%CI .03 - .32) and very likely not clinically relevant (difference and CI < 1SD). No significant difference was found for health-related life satisfaction (hrLS). Looking at LS subscales, AML-LTS reported significantly lower satisfaction with hobbies (median, -.24), fitness (median, -.18) and composure (median, -.41), but higher satisfaction with finances (median, .36), living situation (median, .10), family life (median, .37), energy (median, .04), mobility (median, .56) and independence (median, .71; all p<.003). Notably, subgroups of participants reported poor hrLS (>1SD below control mean; 17.5%) or poor gLS (13.5%), while 26% reported poor overall QoL as reported previously. All three outcomes are correlated (r=.63 to .76), with the closest association observed between QoL and hrLS (Figure A). To identify factors associated with poor LS, we fitted logistic regression models including pre-specified cofactors (age, sex, time since initial diagnosis, relapse and alloHSCT) and additional variables that associated with LS in univariate analyses. Risk of poor gLS was increased with younger age, male sex, smaller household size and income, higher depression scores and low social support (Table 1). Factors associated with poor hrLS were previous treatment with chemotherapy alone, female sex, lower number of children, high anxiety and fatigue scores, and high comorbidity burden (Table 1). Participants with higher fatigue and anxiety scores, lower social support and higher comorbidity burden reported significantly lower QoL (Table 1). No influence on QoL was found for other characteristics including treatment (HSCT vs. no HSCT), previous relapse, or AML type (p>.05). Figure A illustrates multi-dimensional associations between risk factors and psycho-social outcomes. Discussion Unlike previous studies of AML survivorship outcomes, our large cohort included a diverse spectrum of patients regarding age, time since diagnosis, and treatment modalities, which allows for new insights into long-term quality of life and life satisfaction. Our study establishes that different factors impact overall QoL and life satisfaction in AML long-term survivors. Importantly, general life satisfaction of AML long-term survivors seems not to be influenced by treatment related factors or somatic comorbidities after AML. Our data suggest AML and its treatment can have long-term psycho-social and somatic health effects, but many former patients nevertheless are satisfied with their overall life situation. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Multidimensional associations between nutrient intake and healthy ageing in humans

BackgroundLittle is known about how normal variation in dietary patterns in humans affects the ageing process. To date, most analyses of the problem have used a unidimensional paradigm, being concerned with the effects of a single nutrient on a single outcome. Perhaps then, our ability to understand the problem has been complicated by the fact that both nutrition and the physiology of ageing are highly complex and multidimensional, involving a high number of functional interactions. Here we apply the multidimensional geometric framework for nutrition to data on biological ageing from 1560 older adults followed over four years to assess on a large-scale how nutrient intake associates with the ageing process.ResultsAgeing and age-related loss of homeostasis (physiological dysregulation) were quantified via the integration of blood biomarkers. The effects of diet were modelled using the geometric framework for nutrition, applied to macronutrients and 19 micronutrients/nutrient subclasses. We observed four broad patterns: (1) The optimal level of nutrient intake was dependent on the ageing metric used. Elevated protein intake improved/depressed some ageing parameters, whereas elevated carbohydrate levels improved/depressed others; (2) There were non-linearities where intermediate levels of nutrients performed well for many outcomes (i.e. arguing against a simple more/less is better perspective); (3) There is broad tolerance for nutrient intake patterns that don’t deviate too much from norms (‘homeostatic plateaus’). (4) Optimal levels of one nutrient often depend on levels of another (e.g. vitamin E and vitamin C). Simpler linear/univariate analytical approaches are insufficient to capture such associations. We present an interactive tool to explore the results in the high-dimensional nutritional space.ConclusionUsing multidimensional modelling techniques to test the effects of nutrient intake on physiological dysregulation in an aged population, we identified key patterns of specific nutrients associated with minimal biological ageing. Our approach presents a roadmap for future studies to explore the full complexity of the nutrition-ageing landscape.

600-P: Examining Beliefs about Type 2 Diabetes Medications: A Multidimensional Approach

Background: Beliefs about type 2 diabetes (T2D) medications predict treatment adherence; yet, factors that influence these beliefs are poorly understood. Further, prior studies reduce the complex interplay between beliefs about treatment necessity and medication-related concerns to a single dimension by using a difference score. This study examined correlates of T2D medication beliefs and modeled the multidimensional associations of beliefs and adherence. Methods: Participants were 812 primarily disadvantaged and ethnic minority adults with T2D (Female = 56.9%; Latino = 86.5%; Mean [SD] Age and A1C = 59.2 [10.8], 9.3 [1.8], respectively) recruited for a self-management trial. Informed by the Common Sense Model and prior research, relations of patient- and illness-related factors with medication beliefs (Horne, Weinman, Hankins, 1999) were examined using linear regression. Confirmatory and exploratory polynomial regression examined associations of medication beliefs and self-reported adherence. Results: Hispanic ethnicity (p &amp;lt; .01) , insulin use (p &amp;lt; .05) , greater number of medications (p &amp;lt; .05) , and lower levels of education (p &amp;lt; .05) were associated with stronger necessity beliefs. Lower income (p &amp;lt; .05) and Hispanic ethnicity (p &amp;lt; .01) were associated with greater concerns. Adherence was lowest among those with strong concerns and weak necessity beliefs. Non-reciprocal effects were also observed, which could not have been assessed using a difference score. Patients with ambivalent beliefs had lower adherence than those with indifferent beliefs. Discussion: Indicators of lower SES were associated with concerns about T2D medications. Increased disease severity and Hispanic ethnicity were associated with stronger necessity beliefs. However, Hispanics also reported more concerns about their medications. Results further support use of polynomial regression to assess medication beliefs and adherence. Addressing concerns, in particular, may enhance T2D medication adherence. Disclosure A.G.Asman: None. L.A.Phillips: None. E.A.Walker: None. L.D.Pappalardo: None. J.S.Gonzalez: Consultant; Virta Health Corp. Funding National Institutes of Health (R18 DK098742) Einstein–Mount Sinai Diabetes Research Center (P30 DK020541) New York Regional Center for Diabetes Translation Research (P30 DK111022) J.S.G. is supported by National Institutes of Health (RDK104845, RDK121298, RDK121896)

Connectomic Profiles and Cognitive Trajectories After Epilepsy Surgery in Children.

Neurocognitive outcomes after surgery for temporal lobe epilepsy in childhood are variable. Postoperative changes are not directly predicted by seizure freedom, and associations between epilepsy, neuropsychological function, and developing neural networks are poorly understood. Here, we leveraged whole-brain connectomic profiling in magnetoencephalography (MEG) to retrospectively study associations between brain connectivity and neuropsychological function in children with temporal lobe epilepsy undergoing resective surgery. Clinical and MEG data were retrospectively analyzed for children who underwent temporal lobe epilepsy surgery at the Hospital for Sick Children from 2000 to 2021. Resting-state connectomes were constructed from neuromagnetic oscillations via the weighted-phase lag index. Using a partial least-squares (PLS) approach, we assessed multidimensional associations between patient connectomes, neuropsychological scores, and clinical covariates. Bootstrap resampling statistics were performed to assess statistical significance. A total of 133 medical records were reviewed, and 5 PLS analyses were performed. Each PLS analysis probed a particular neuropsychological domain and the associations between its baseline and postoperative scores and the connectomic data. In each PLS analysis, a significant latent variable was identified, representing a specific percentage of the variance in the data and relating neural networks to clinical covariates, which included changes in rote verbal memory (n = 41, p = 0.01, σ2 = 0.38), narrative/verbal memory (n = 57, p = 0.00, σ2 = 0.52), visual memory (n = 51, p = 0.00, σ2 = 0.43), working memory (n = 44, p = 0.00, σ2 = 0.52), and overall intellectual function (n = 59, p = 0.00, σ2 = 0.55). Children with more diffuse, bilateral intrinsic connectivity across several frequency bands showed lower scores on all neuropsychological assessments but demonstrated a greater propensity for gains after resective surgery. Here, we report that connectomes characterized by diffuse connectivity, reminiscent of developmentally immature networks, are associated with lower preoperative cognition and postoperative cognitive improvement. These findings provide a potential means to understand neurocognitive function in children with temporal lobe epilepsy and expected changes postoperatively.

The relationship between non-motor features and weight-loss in the premanifest stage of Huntington's disease.

Weight-loss is an integral part of Huntington’s disease (HD) that can start before the onset of motor symptoms. Investigating the underlying pathological processes may help in the understanding of this devastating disease as well as contribute to its management. However, the complex behavior and associations of multiple biological factors is impractical to be interpreted by the conventional statistics or human experts. For the first time, we combine a clinical dataset, expert knowledge and machine intelligence to model the multi-dimensional associations between the potentially relevant factors and weight-loss activity in HD, specifically at the premanifest stage. The HD dataset is standardized and transformed into required knowledge base with the help of clinical HD experts, which is then processed by the class rule mining and self-organising maps to identify the significant associations. Statistical results and experts’ report indicate a strong association between severe weight-loss in HD at the premanifest stage and measures of certain cognitive, psychiatric functional ability factors. These results suggest that the mechanism underlying weight-loss in HD is, at least partly related to dysfunction of certain areas of the brain, a finding that may have not been apparent otherwise. These associations will aid the understanding of the pathophysiology of the disease and its progression and may in turn help in HD treatment trials.

Distributed leadership practices and student science performance through the four-path model: examining failure in underprivileged schools

PurposeAs a failure analysis emphasizing school leadership in underprivileged schools serving socioeconomically disadvantaged and minority students, the study is interested in determining whether and to what extent variations in distributed leadership (DL) practices are related to student performance through the mediating effects of four-path variables.Design/methodology/approachThis research conducted secondary data analysis using the 2015 PISA American data. The study employed factor analysis and structural equation models (SEMs) to investigate multidimensional associations among a set of variables, including school socioeconomic status (SES), student composition, DL practices, school four-path factors and student performance. The research used a design-based resampling approach with balanced repeated replication (BRR) weights to analyze the complex survey data.FindingsThe results indicate that, within a DL framework, teacher leadership in instructional management is positively and directly related to student performance. Governing board leadership in school administration is indirectly related to student performance through four-path variables' mediating effects. Importantly, though the two leadership sources help improve student performance, they are less prevalent in underprivileged schools with disproportional minority and socioeconomically disadvantaged students.Originality/valueThis research is a failure analysis through the lens of DL for underprivileged schools. The study used rigorous quantitative approaches and examined multidimensional associations among school socioeconomic status (SES), DL, school factors that school leaders could maneuver and student performance. The evidence sheds light on remedial actions in failed schools to focus on improving teacher leadership and organizational capacity.

Prevalences of and correlations between childhood trauma and depressive symptoms, anxiety symptoms, and suicidal behavior among institutionalized adolescents in Vietnam

ObjectivesWe investigated the prevalence rates of childhood trauma, depressive symptoms, anxiety symptoms and suicidal behaviors among Vietnamese adolescents and compared the differences between institutionalized adolescents (IAs) and noninstitutionalized adolescents (NIAs). In addition, we examined the multidimensional associations between childhood trauma and psychopathology among IAs. MethodsFive hundred forty-six participants were recruited into two groups (IAs and NIAs) matched by age, sex and grade. They completed a childhood trauma questionnaire, depression scale, anxiety scale, and 3 suicide-related questions. The chi-squared test and logistic regressions were performed. ResultsThe prevalences of anxiety symptoms and suicide attempts among IAs was higher than that among NIAs (25.6 % vs 14.7 %, p = 0.001 and 8.1 vs 3.7, p = 0.03, respectively), while the prevalences of other psychopathologies did not differ significantly. In the IA group, high prevalences of victimization through physical abuse (22.3 %), emotional neglect (57.9 %), and physical neglect (72.9 %) were found, and 58.6 % of the participants had experienced more than one type of trauma. These figures were significantly higher in IAs than in NIAs. Depression and suicidal ideation were more strongly correlated with emotional abuse and neglect than other types of maltreatment, while anxiety, suicide planning and suicide attempts were more strongly correlated with physical abuse. IAs who experienced more than two categories of trauma or greater intensity of trauma were more susceptible to developing depression, anxiety, and suicidal behaviors. ConclusionsChildhood trauma was multidimensionally associated with adverse psychological outcomes. We suggest that various aspects of childhood trauma, as well as psychopathologies, must be routinely assessed.

Analysing the impact of global demographic characteristics over the COVID-19 spread using class rule mining and pattern matching.

Since the coronavirus disease (COVID-19) outbreak in December 2019, studies have been addressing diverse aspects in relation to COVID-19 and Variant of Concern 202012/01 (VOC 202012/01) such as potential symptoms and predictive tools. However, limited work has been performed towards the modelling of complex associations between the combined demographic attributes and varying nature of the COVID-19 infections across the globe. This study presents an intelligent approach to investigate the multi-dimensional associations between demographic attributes and COVID-19 global variations. We gather multiple demographic attributes and COVID-19 infection data (by 8 January 2021) from reliable sources, which are then processed by intelligent algorithms to identify the significant associations and patterns within the data. Statistical results and experts' reports indicate strong associations between COVID-19 severity levels across the globe and certain demographic attributes, e.g. female smokers, when combined together with other attributes. The outcomes will aid the understanding of the dynamics of disease spread and its progression, which in turn may support policy makers, medical specialists and society, in better understanding and effective management of the disease.

Whose leadership role is more substantial for teacher professional collaboration, job satisfaction and organizational commitment: a lens of distributed leadership

ABSTRACT Research evidence has suggested distributed leadership might help improve school outcomes, but the conceptualization and operationalization of distributed leadership itself remain inconsistent, and the evidence of distributed leadership on many school outcomes is far from complete. This research used the multi-country 2013 Teaching and Learning International Study data to reveal how variations in principal, management team, and teachers’ leadership in three primary school leadership functions are associated with teacher professional collaboration, teacher job satisfaction, and teacher organizational commitment. The study investigated multi-dimensional associations using a three-level Structural Equation Model, and found teacher reported shared decision-making was significantly and positively related to all interested outcomes. While using the distributed leadership operational variables, which emphasized the variations in each leader unit’s leadership and managerial roles, this study found practically, management team leadership in instructional management and teacher development, and teacher leadership in teacher development were associated with desired teacher collaboration and teacher attitudes.

Machine Learning and Clinical Prediction Rules: A Perfect Match?

* Abbreviations: EHR — : electronic health record PCA — : principal component analysis The field of machine learning involves the study of algorithms that can be used to discover mathematical functions for classification and prediction. Increasing computational power and larger data sets have allowed for the detection of complex, multidimensional associations not discoverable with traditional statistical modeling techniques, such as logistic regression. In this issue of Pediatrics , Ramgopal et al1 apply a mix of traditional statistical techniques and machine learning to the vexing problem of the young infant (≤60 days) with fever. Several clinical decision rules have been developed to help the clinician decide which patients are at low risk of bacterial infection and can forego lumbar puncture and/or hospital admission. The authors used a public use data set from the Pediatric Emergency Care Applied Research Network (PECARN) study of young infants with fever and tested several different models to attempt to improve on PECARN’s own decision rule.2 The authors were indeed able to improve on the PECARN decision rule, achieving an improvement in specificity from 60% to 75% without a loss of almost perfect sensitivity. They were able to accomplish this despite a small data set by machine learning standards, with only 138 patients with bacterial infection. The most successful model was a random forest … Address correspondence to James M. Chamberlain, MD, Division of Emergency Medicine, Children’s National Hospital, 111 Michigan Ave NW, Washington, DC 20010. E-mail: jchamber{at}childrensnational.org

Temporal-plus epilepsy in children: A connectomic analysis in magnetoencephalography.

Seizure recurrence following surgery for temporal lobe (TL) epilepsy may be related to extratemporal epileptogenic foci, so-called temporal-plus (TL+) epilepsy. Here, we sought to leverage whole brain connectomic profiling in magnetoencephalography (MEG) to identify neural networks indicative of TL+ epilepsy in children. Clinical and MEG data were analyzed for 121 children with TL and TL+ epilepsy spanning 20years at the Hospital for Sick Children. Resting-state connectomes were derived using the weighted phase lag index from neuromagnetic oscillations. Multidimensional associations between patient connectomes, TL versus TL+ epilepsy, seizure freedom, and clinical covariates were performed using a partial least squares (PLS) analysis. Bootstrap resampling statistics were performed to assess statistical significance. A single significant latent variable representing 66% of the variance in the data was identified with significant contributions from extent of epilepsy (TL vs TL+), duration of illness, and underlying etiology. This component was associated with significant bitemporal and frontotemporal connectivity in the theta, alpha, and beta bands. By extracting a brain score, representative of the observed connectivity profile, patients with TL epilepsy were dissociated from those with TL+, independent of their postoperative seizure outcome. By analyzing 121 connectomes derived from MEG data using a PLS approach, we find that connectomic profiling could dissociate TL from TL+ epilepsy. These findings may inform patient selection for resective procedures and guide decisions surrounding invasive monitoring.

Clustering-Based Hybrid Approach for Identifying Quantitative Multidimensional Associations Between Patient Attributes, Drugs and Adverse Drug Reactions.

The activity of post-marketing surveillance results in a collection of large amount of data. The analysis of data is very useful for raising early warnings on possible adverse reactions of drugs. Association rule mining techniques have been heavily explored by the research community for identifying binary association between drugs and their adverse effects. But these techniques perform poorly and miss out several interesting associations when it comes to analysis of multidimensional data which may include multiple patient attributes, drugs and adverse drug reactions. In the present work, a clustering-based hybrid approach has been presented for finding quantitative multidimensional association from the large amount of data. Firstly, it employs clustering technique for segmentation of data into semantically coherent clusters. Furthermore, disproportionality method called proportional reporting ratio is applied on clustered data for generating statistically strong associations. The performance of the proposed methodology has been examined on the data taken from the U.S. Food and Drug Administration Adverse Event Reporting System database corresponding to Aspirin and nine other drugs which are prescribed along with Aspirin. The experimental results show that the proposed approach discovered a number of association rules which are very comprehensive and informative regarding relationship of patient traits and drugs with adverse drug reactions. On comparing experimental results with LPMiner, it is observed that the quantitative association rules discovered by LPMiner are just 8.3% of what have been discovered by the proposed methodology.

Non-responsive feeding practices mediate the relationship between maternal and child obesogenic eating behaviours

Both genetic and environmental influences underpin complex multidimensional associations between maternal and child eating behaviours, maternal feeding practices and child obesity risk. The aim of the present study was to explore cross-sectional relationships between maternal and child eating behaviours, and to examine whether maternal feeding practices mediate these relationships. Data were available from 478 Australian mothers (M = 38.8 years, SD = 5.6) of a 5–10 year old child (M = 7.0 years, SD = 1.1; 48.2% male). Mothers completed an online survey that included validated measures of maternal eating behaviours, maternal feeding practices and child eating behaviours. Maternal emotional overeating and food responsiveness, were each positively associated with the parallel child eating behaviour (r = 0.29 and r = 0.21, ps < .001, respectively). Mediation analyses showed that both the relationship between maternal and child emotional overeating and between maternal and child food responsiveness, were partially mediated by use of food as a reward and overt restriction (total indirect effect: .04, 95% CI 0.02, 0.07 and 0.82, 95% CI 0.04, 0.13, respectively). Findings suggest a role for feeding practices in explaining the concordance between maternal and child eating behaviours. Moreover, the results highlight the need for interventions that support parents to recognise these eating behaviours in themselves and their children and understand how these may potentially influence the feeding practices they use. Future longitudinal research that confirms the cross-sectional relationships between maternal and child eating behaviours and feeding practices reported here will strengthen the evidence to support the importance of feeding practices in the development of dietary intake patterns and obesity risk.

Multidimensional associations between cognition and connectome organization in temporal lobe epilepsy

ObjectiveTemporal lobe epilepsy (TLE) is known to affect large-scale structural networks and cognitive function in multiple domains. The study of complex relations between structural network organization and cognition requires comprehensive analytical methods and a shift towards multivariate techniques. Here, we sought to identify multidimensional associations between cognitive performance and structural network topology in TLE. MethodsWe studied 34 drug-resistant adult TLE patients and 24 age- and sex-matched healthy controls. Participants underwent a comprehensive neurocognitive battery and multimodal MRI, allowing for large-scale connectomics, and morphological evaluation of subcortical and neocortical regions. Using canonical correlation analysis, we identified a multivariate mode that links cognitive performance to a brain structural network. Our approach was complemented by bootstrap-based hierarchical clustering to derive cognitive subtypes and associated patterns of macroscale connectome anomalies. ResultsBoth methodologies provided converging evidence for a close coupling between cognitive impairments across multiple domains and large-scale structural network compromise. Cognitive classes presented with an increasing gradient of abnormalities (increasing cortical and subcortical atrophy and less efficient white matter connectome organization in patients with increasing degrees of cognitive impairments). Notably, network topology characterized cognitive performance better than morphometric measures did. ConclusionsOur multivariate approach emphasized a close coupling of cognitive dysfunction and large-scale network anomalies in TLE. Our findings contribute to understand the complexity of structural connectivity regulating the heterogeneous cognitive deficits found in epilepsy.