Never Assume Successful Treatment of Septic Arthritis: Bacteria Isolated at Revision ACL Reconstruction 3 Years After Primary ACL Reconstruction "Successfully" Treated for Infection.

Level IV.

Functional connectivity in ADHD children doing Go/No-Go tasks: An fMRI systematic review and meta-analysis.

Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders diagnosed in childhood. Two common features of ADHD are impaired behavioural inhibition and sustained attention. The Go/No-Go experimental paradigm with concurrent functional magnetic resonance imaging (fMRI) scanning has previously revealed important neurobiological correlates of ADHD such as the supplementary motor area and the prefrontal cortex.

Toward a Climate-Ready Health Care System: Institutional Motivators and Workforce Engagement.

Policy Points The US health care system faces mounting pressure to reduce greenhouse gas emissions and adapt to the impacts of climate change; motivated institutions and an engaged health care workforce are essential to the development, implementation, and maintenance of a climate-ready US health care system. Health care workers have numerous profession-specific and role-specific opportunities to address the causes and impacts of climate change. Policies must address institutional barriers to change and create incentives aligned with climate readiness goals.

Health Consequences of Climate Change: Continuing Education Opportunities for Health Professionals in the United States.

Climate change is a looming public health challenge. The health consequences of climate change are increasingly recognized as contributing to negative health outcomes for individuals, families, communities, and populations. The education of health professionals in academic programs and continuing education in clinical practice settings is critical in today's world.

Mental Health Impacts of Climate Change Among Vulnerable Populations Globally: An Integrative Review.

Background: Climate change has been shown to be directly linked to multiple physiological sequelae and to impact health consequences. However, the impact of climate change on mental health globally, particularly among vulnerable populations, is less well understood.

Objective: To explore the mental health impacts of climate change in vulnerable populations globally.

Parcellation-Based Connectivity Model of the Judgement Core.

Judgement is a higher-order brain function utilized in the evaluation process of problem solving. However, heterogeneity in the task methodology based on the many definitions of judgement and its expansive and nuanced applications have prevented the identification of a unified cortical model at a level of granularity necessary for clinical translation. Forty-six task-based fMRI studies were used to generate activation-likelihood estimations (ALE) across moral, social, risky, and interpersonal judgement paradigms.

Leadership in Nursing Education for Advancing a School of Nursing-Led Center for Climate Change, Climate Justice, and Health.

Background: This article examines innovations in the development and advancement of a school of nursing-led climate change center and innovative leadership related to climate change and health in nursing education.

Method: The integration of health consequences of climate change in curricula and continuing education is essential to prepare nursing students and nurses for clinical practice.

Results: Transformational leadership is a key concept for effective leadership in nursing education to address climate change as the looming public health challenge of the 21st century.

A cross-sectional study to assess faculty and student knowledge of climate change and health: Readiness for curricular integration.

Aims: To examine the perceived knowledge, attitudes and beliefs regarding climate change and health of academic faculty and students in programmes for health professionals and to identify barriers/facilitators to and resources required for curriculum integration.

Design: Cross-sectional survey eliciting quantitative and open-ended responses.

Methods: A 22-question survey to assess climate-health knowledge/attitudes/beliefs was distributed to all students and faculty (n = 224) at one academic institution in the United States.

The Future of Nursing 2020-2030: The Critical Role of Nurses and Nurse Leaders in Addressing the Health Impacts of Climate Change.

Climate change represents a looming health challenge and a critical area for nursing leadership at all levels of organizations and settings. With a lens on The Future of Nursing 2020-2030: Charting a Path to Achieve Health Equity, addressing climate change-related health consequences should be a major focus and spotlight for nurses and nurse leaders with a lens on individuals, communities, populations, and from a national and global perspective.

Development of a screening tool for assessment of climate change-related heat illness in the clinical setting.

Extreme heat contributes to heat-related illnesses resulting from heat intolerance, which is the inability to maintain a thermal balance to tolerate heat stress. In the United States, heat-related mortality for older persons has almost doubled in the past 20 years. Other populations at risk for heat-related illness (HRI) include children, pregnant people, those who work outside, young people participating in outdoor sports, and at-risk populations such as Black, indigenous, and populations of color.

Real world demonstration of hand motor mapping using the structural connectivity atlas.

Background: Locating the hand-motor-cortex (HMC) is an essential component within many neurosurgeries. Despite advancements in these localization methods there are still downfalls for each. Additionally, the importance of presurgical planning calls for increasingly accurate and efficient methods of locating specific cortical regions.

An agile, data-driven approach for target selection in rTMS therapy for anxiety symptoms: Proof of concept and preliminary data for two novel targets.

Introduction: Data-driven approaches to transcranial magnetic stimulation (TMS) might yield more consistent and symptom-specific results based on individualized functional connectivity analyses compared to previous traditional approaches due to more precise targeting. We provide a proof of concept for an agile target selection paradigm based on using connectomic methods that can be used to detect patient-specific abnormal functional connectivity, guide treatment aimed at the most abnormal regions, and optimize the rapid development of new hypotheses for future study.

Methods: We used the resting-state functional MRI data of 28 patients with medically refractory generalized anxiety disorder to perform agile target selection based on abnormal functional connectivity patterns between the Default Mode Network (DMN) and Central Executive Network (CEN).

Symptom-circuit mappings of the schizophrenia connectome.

Objective: This paper aims to model the anatomical circuits underlying schizophrenia symptoms, and to explore patterns of abnormal connectivity among brain networks affected by psychopathology.

Methods: T1 magnetic resonance imaging (MRI), diffusion weighted imaging (DWI), and resting-state functional MRI (rsfMRI) were obtained from a total of 126 patients with schizophrenia who were recruited for the study. The images were processed using the Omniscient software (https://www.

Functional connectivity analysis of the depression connectome provides potential markers and targets for transcranial magnetic stimulation.

Background: Despite efforts to improve targeting accuracy of the dorsolateral prefrontal cortex (DLPFC) as a repetitive transcranial magnetic stimulation (rTMS) target for Major Depressive Disorder (MDD), the heterogeneity in clinical response remains unexplained.

Objective: We sought to compare the patterns of functional connectivity from the DLPFC treatment site in patients with MDD who were TMS responders to those who were TMS non-responders.

Methods: Baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI, and diffusion weighted imaging scans were obtained from 37 participants before they underwent a course of rTMS to left Brodmann area 46.

A connectivity model of the anatomic substrates underlying Gerstmann syndrome.

The Gerstmann syndrome is a constellation of neurological deficits that include agraphia, acalculia, left-right discrimination and finger agnosia. Despite a growing interest in this clinical phenomenon, there remains controversy regarding the specific neuroanatomic substrates involved. Advancements in data-driven, computational modelling provides an opportunity to create a unified cortical model with greater anatomic precision based on underlying structural and functional connectivity across complex cognitive domains.

Health Literacy Profiles of Early Intervention Providers: Use of the Health Literacy Questionnaire.

Background: Early intervention (EI) providers work with parents of children with or who have risk factors of developmental delay or disability through Part C of the Individuals with Disabilities Education Act. Many parents in the United States have low health literacy; therefore, EI providers should be aware of and address families' health literacy needs. EI providers need to be health literate themselves to implement evidence-based recommended practices.

Gecko: A time-series model for COVID-19 hospital admission forecasting.

During the COVID-19 pandemic, concerns about hospital capacity in the United States led to a demand for models that forecast COVID-19 hospital admissions. These short-term forecasts were needed to support planning efforts by providing decision-makers with insight about future demands for health care capacity and resources. We present a SARIMA time-series model called Gecko developed for this purpose.

Using a ResNet-18 Network to Detect Features of Alzheimer's Disease on Functional Magnetic Resonance Imaging: A Failed Replication. Comment on Odusami et al. Analysis of Features of Alzheimer's Disease: Detection of Early Stage from Functional Brain Changes in Magnetic Resonance Images Using a Finetuned ResNet18 Network. 2021, , 1071.

There is considerable interest in developing effective tools to detect Alzheimer's Disease (AD) early in its course, prior to clinical progression [...

Machine Learning Decomposition of the Anatomy of Neuropsychological Deficit in Alzheimer's Disease and Mild Cognitive Impairment.

Objective: Alzheimer's Disease (AD) is a progressive condition characterized by cognitive decline. AD is often preceded by mild cognitive impairment (MCI), though the diagnosis of both conditions remains a challenge. Early diagnosis of AD, and prediction of MCI progression require data-driven approaches to improve patient selection for treatment.

Occupational Heat Stress: An Overview for Nurse Practitioners.

The health impacts of climate change are pervasive and complex. The role of nurse practitioners is a key in addressing these emerging health challenges. However, few health care providers are aware of the extensive signs and symptoms that accompany climate-related health sequelae.

Knowledge, attitudes, and practices of primary healthcare providers with assessing and supporting older informal caregivers.

A time burden, financial strain, and prioritizing care recipient needs over their own are key barriers preventing informal caregivers from engaging in health-promoting self-care. Primary healthcare providers are well positioned to assess and support informal caregivers. A cross sectional descriptive, correlational study was used to examine the knowledge, attitudes, and practices of healthcare providers regarding assessment and support of older informal caregivers.

Eigenvector PageRank difference as a measure to reveal topological characteristics of the brain connectome for neurosurgery.

Purpose: Applying graph theory to the human brain has the potential to help prognosticate the impacts of intracerebral surgery. Eigenvector (EC) and PageRank (PR) centrality are two related, but uniquely different measures of nodal centrality which may be utilized together to reveal varying neuroanatomical characteristics of the brain connectome.

Methods: We obtained diffusion neuroimaging data from a healthy cohort (UCLA consortium for neuropsychiatric phenomics) and applied a personalized parcellation scheme to them.

Management of patellar tendinopathy: a systematic review and network meta-analysis of randomised studies.

Objectives: We performed a systematic review and network meta-analysis (NMA) of randomised controlled trials (RCTs) to provide insights into the effectiveness of available treatment modalities in patellar tendinopathy(PT).

Methods: Several databases were searched in May 2021 for RCTs assessing the effectiveness of any intervention compared with any other intervention, placebo or no treatment for pain and/or function in PT. The risk of bias and strength of evidence were assessed with the Cochrane Collaboration and GRADE (Grading of Recommendations, Assessment, Development and Evaluations)/GRADE-NMA tools.