Mapping Individual Differences in Intermodal Coupling in Neurodevelopment.

Within-individual coupling between measures of brain structure and function evolves in development and may underlie differential risk for neuropsychiatric disorders. Despite increasing interest in the development of structure-function relationships, rigorous methods to quantify and test individual differences in coupling remain nascent. In this article, we explore and address gaps in approaches for testing and spatially localizing individual differences in intermodal coupling.

Network enrichment significance testing in brain-phenotype association studies.

Functional networks often guide our interpretation of spatial maps of brain-phenotype associations. However, methods for assessing enrichment of associations within networks of interest have varied in terms of both scientific rigor and underlying assumptions. While some approaches have relied on subjective interpretations, others have made unrealistic assumptions about spatial properties of imaging data, leading to inflated false positive rates.

Diagnosis concealment behaviors and disclosure beliefs are associated with health and quality of life in people with multiple sclerosis.

Background: People with multiple sclerosis (pwMS) struggle with whether, how, and how much to disclose their diagnosis. They often expend resources to conceal their diagnosis, and hold beliefs that it may negatively affect their personal relationships and/or professional opportunities. To better understand these effects, we developed a measure to quantify concealment behaviors and disclosure beliefs.

Similarity-based multimodal regression.

To better understand complex human phenotypes, large-scale studies have increasingly collected multiple data modalities across domains such as imaging, mobile health, and physical activity. The properties of each data type often differ substantially and require either separate analyses or extensive processing to obtain comparable features for a combined analysis. Multimodal data fusion enables certain analyses on matrix-valued and vector-valued data, but it generally cannot integrate modalities of different dimensions and data structures.

Network Enrichment Significance Testing in Brain-Phenotype Association Studies.

Functional networks often guide our interpretation of spatial maps of brain-phenotype associations. However, methods for assessing enrichment of associations within networks of interest have varied in terms of both scientific rigor and underlying assumptions. While some approaches have relied on subjective interpretations, others have made unrealistic assumptions about the spatial structure of imaging data, leading to inflated false positive rates.

Development of top-down cortical propagations in youth.

Hierarchical processing requires activity propagating between higher- and lower-order cortical areas. However, functional neuroimaging studies have chiefly quantified fluctuations within regions over time rather than propagations occurring over space. Here, we leverage advances in neuroimaging and computer vision to track cortical activity propagations in a large sample of youth (n = 388).

Impact of a Virtual Wellness Program on Quality of Life Measures for Patients Living With Multiple Sclerosis During the COVID-19 Pandemic.

Background: Patients with multiple sclerosis (MS) were vulnerable to the effects of physical inactivity during the COVID-19 pandemic. As patients returned to in-person visits, providers reported seeing increased weakness, balance issues, falls, worsening pain, and spasticity. Social isolation also contributed to increased stress, depression, and anxiety.

Spatially-enhanced clusterwise inference for testing and localizing intermodal correspondence.

With the increasing availability of neuroimaging data from multiple modalities-each providing a different lens through which to study brain structure or function-new techniques for comparing, integrating, and interpreting information within and across modalities have emerged. Recent developments include hypothesis tests of associations between neuroimaging modalities, which can be used to determine the statistical significance of intermodal associations either throughout the entire brain or within anatomical subregions or functional networks. While these methods provide a crucial foundation for inference on intermodal relationships, they cannot be used to answer questions about where in the brain these associations are most pronounced.

Penalized decomposition using residuals (PeDecURe) for feature extraction in the presence of nuisance variables.

Neuroimaging data are an increasingly important part of etiological studies of neurological and psychiatric disorders. However, mitigating the influence of nuisance variables, including confounders, remains a challenge in image analysis. In studies of Alzheimer's disease, for example, an imbalance in disease rates by age and sex may make it difficult to distinguish between structural patterns in the brain (as measured by neuroimaging scans) attributable to disease progression and those characteristic of typical human aging or sex differences.

Voxel-wise intermodal coupling analysis of two or more modalities using local covariance decomposition.

When individual subjects are imaged with multiple modalities, biological information is present not only within each modality, but also between modalities - that is, in how modalities covary at the voxel level. Previous studies have shown that local covariance structures between modalities, or intermodal coupling (IMCo), can be summarized for two modalities, and that two-modality IMCo reveals otherwise undiscovered patterns in neurodevelopment and certain diseases. However, previous IMCo methods are based on the slopes of local weighted linear regression lines, which are inherently asymmetric and limited to the two-modality setting.

Dissociable multi-scale patterns of development in personalized brain networks.

The brain is organized into networks at multiple resolutions, or scales, yet studies of functional network development typically focus on a single scale. Here, we derive personalized functional networks across 29 scales in a large sample of youths (n = 693, ages 8-23 years) to identify multi-scale patterns of network re-organization related to neurocognitive development. We found that developmental shifts in inter-network coupling reflect and strengthen a functional hierarchy of cortical organization.

Multiple sclerosis diagnosis: Knowledge gaps and opportunities for educational intervention in neurologists in the United States.

Background: Few studies have addressed the results of educational efforts concerning proper use of McDonald criteria (MC) revisions outside multiple sclerosis (MS) subspecialty centers. Neurology residents and MS subspecialist neurologists demonstrated knowledge gaps for core elements of the MC in a recent prior study.

Objective: To assess comprehension and application of MC core elements by non-MS specialist neurologists in the United States who routinely diagnose MS.

A simple permutation-based test of intermodal correspondence.

Many key findings in neuroimaging studies involve similarities between brain maps, but statistical methods used to measure these findings have varied. Current state-of-the-art methods involve comparing observed group-level brain maps (after averaging intensities at each image location across multiple subjects) against spatial null models of these group-level maps. However, these methods typically make strong and potentially unrealistic statistical assumptions, such as covariance stationarity.

Simulation-based design of pragmatic trials in psoriatic arthritis using propensity scores.

Background/aims: Design of clinical trials requires careful decision-making across several dimensions, including endpoints, eligibility criteria, and subgroup enrichment. Clinical trial simulation can be an informative tool in trial design, providing empirical evidence by which to evaluate and compare the results of hypothetical trials with varying designs. We introduce a novel simulation-based approach using observational data to inform the design of a future pragmatic trial.

Modifiable factors associated with postoperative delirium after hip fracture repair: An age-stratified retrospective cohort study.

Background: Postoperative delirium in hip fracture patients is common and is associated with substantial morbidity and consumption of resources.

Objective: Using data from the USA, we aimed to examine the relationship between postoperative delirium and (modifiable) peri-operative factors mentioned in the American Geriatrics Society Best Practice Statement on Postoperative Delirium in Older Adults, stratified by 'young old' (<80 years) and 'old-old' (≥80 years) categories.

Design: Retrospective cohort study from 2006 to 2016.

Risk factors for postoperative delirium in patients undergoing lower extremity joint arthroplasty: a retrospective population-based cohort study.

Background: With an ageing population, the demand for joint arthroplasties and the burden of postoperative delirium is likely to increase. Given the lack of large-scale data, we investigated associations between perioperative risk factors and postoperative delirium in arthroplasty surgery.

Methods: This retrospective population-based cohort study, utilized national claims data from the all-payer Premier Healthcare database containing detailed billing information from >25% nationwide hospitalizations.

Perioperative impact of sleep apnea in a high-volume specialty practice with a strong focus on regional anesthesia: a database analysis.

Background And Objectives: Obstructive sleep apnea (OSA) is a risk factor for adverse postoperative outcome and perioperative professional societies recommend the use of regional anesthesia to minimize perioperative detriment. We studied the impact of OSA on postoperative complications in a high-volume orthopedic surgery practice, with a strong focus on regional anesthesia.

Methods: After Institutional Review Board approval, 41 766 cases of primary total hip and knee arthroplasties (THAs/TKAs) from 2005 to 2014 were extracted from institutional data of the Hospital for Special Surgery (approximately 5000 THAs and 5000 TKAs annually, of which around 90% under neuraxial anesthesia).

Lack of Association Between Levels and Length of Intraoperative Controlled Hypotension and Acute Kidney Injury in Total Hip Arthroplasty Patients Receiving Neuraxial Anesthesia.

Background And Objectives: Previous research suggests that increased duration and lower levels of intraoperative hypotension (IOH) are associated with postoperative acute kidney injury (AKI). However, this association has not been evaluated in the context of intraoperative controlled hypotension (IOCH), a practice that has been linked in the past to improved outcomes with respect to blood loss and transfusion needs. This study aimed to investigate whether IOCH is associated with postoperative AKI among total hip arthroplasty patients at an institution where this technique is commonly practiced.