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Obsessive-compulsive disorder (OCD) is a neurobehavioral condition that can lead to functional impairment and decreased quality of life. In this chapter, clinical presentation, diagnostic considerations, and pathophysiology of OCD are reviewed. An overview of the theoretical models of OCD are provided, and evidence-based treatments for OCD, specifically cognitive behavioral therapy (CBT) with exposure and response prevention (ERP), pharmacotherapy, and neurosurgery, are discussed. The chapter concludes with suggestions for future research directions.
To compare the incidence of surgical site infection (SSI) between cefazolin 3 g and 2 g surgical prophylaxis in patients weighing ≥120 kg that undergo elective colorectal surgery.
Methods:
A multicenter, retrospective cohort study was performed utilizing a validated database of elective colorectal surgeries in Michigan acute care hospitals. Adults weighing ≥120 kg who received cefazolin and metronidazole for surgical prophylaxis between 7/2012 and 6/2021 were included. The primary outcome was SSI, which was defined as an infection diagnosed within 30 days following the principal operative procedure. Multivariable logistic regression was used to identify variables associated with SSI; the exposure of interest was cefazolin 3 g surgical prophylaxis.
Results:
A total of 581 patients were included; of these, 367 (63.1%) received cefazolin 3 g, while 214 (36.8%) received 2 g. Patients who received cefazolin 3 g had less optimal antibiotic timing (324 [88.3%] vs 200 [93.5%]; P = .043) and a higher receipt of at least 1 of the prophylaxis antibiotics after incision (22 [6%] vs 5 [2.3%]; P = .043). There was no SSI difference between cefazolin 3 g and 2 g cohorts (23 [6.3%] vs 16 [7.5%], P = .574). When accounting for age, smoking status, and surgical duration, cefazolin 3 g was not associated with a reduction in SSI (adjOR, .64; 95%CI, .32–1.29).
Conclusions:
Surgical prophylaxis with cefazolin 3 g, in combination with metronidazole, was not associated with decreased SSI compared to 2 g dosing in obese patients undergoing elective colorectal surgery.
This work studies upper-limb impairment resulting from stroke or traumatic brain injury and presents a simple technological solution for a subset of patients: a soft, active stretching aid for at-home use. To better understand the issues associated with existing associated rehabilitation devices, customer discovery conversations were conducted with 153 people in the healthcare ecosystem (60 patients, 30 caregivers, and 63 medical providers). These patients fell into two populations: spastic (stiff, clenched hands) and flaccid (limp hands). Focusing on the first category, a set of design constraints was developed based on the information collected from the customer discovery. With these constraints in mind, a powered wrist-hand stretching orthosis (exoskeleton) was designed and prototyped as a preclinical study (T0 basic science research) to aid in recovery. The orthosis was tested on two patients for proof-of-concept, one survivor of stroke and one of traumatic brain injury. The prototype was able to consistently open both patients’ hands. A mathematical model was developed to characterize joint stiffness based on experimental testing. Donning and doffing times for the prototype averaged 76 and 12.5 s, respectively, for each subject unassisted. This compared favorably to times shown in the literature. This device benefits from simple construction and low-cost materials and is envisioned to become a therapy device accessible to patients in the home. This work lays the foundation for phase 1 clinical trials and further device development.
Severe fatigue and cognitive complaints are frequently reported after SARS-CoV-2 infection and may be accompanied by depressive symptoms and/or limitations in physical functioning. The long-term sequelae of COVID-19 may be influenced by biomedical, psychological, and social factors, the interplay of which is largely understudied over time. We aimed to investigate how the interplay of these factors contribute to the persistence of symptoms after COVID-19.
Methods
RECoVERED, a prospective cohort study in Amsterdam, the Netherlands, enrolled participants aged⩾16 years after SARS-CoV-2 diagnosis. We used a structural network analysis to assess relationships between biomedical (initial COVID-19 severity, inflammation markers), psychological (illness perceptions, coping, resilience), and social factors (loneliness, negative life events) and persistent symptoms 24 months after initial disease (severe fatigue, difficulty concentrating, depressive symptoms and limitations in physical functioning). Causal discovery, an explorative data-driven approach testing all possible associations and retaining the most likely model, was performed.
Results
Data from 235/303 participants (77.6%) who completed the month 24 study visit were analysed. The structural model revealed associations between the putative factors and outcomes. The outcomes clustered together with severe fatigue as its central point. Loneliness, fear avoidance in response to symptoms, and illness perceptions were directly linked to the outcomes. Biological (inflammatory markers) and clinical (severity of initial illness) variables were connected to the outcomes only via psychological or social variables.
Conclusions
Our findings support a model where biomedical, psychological, and social factors contribute to the development of long-term sequelae of SARS-CoV-2 infection.
This study analyzes disparities in initial health care responses in Turkey and Syria following the 2023 earthquakes.
Methods
Using Humanitarian Data Exchange, Crude Mortality Rates (CMR) and injury rates in both countries were calculated, and temporal trends of death tolls and injuries in the first month post- catastrophe were compared. World Health Organization (WHO) Flash Appeal estimated funding requirements, and ratios of humanitarian aid personnel in Urban Search and Rescue (USAR) teams per population from ReliefWeb and MAPACTION data were used to gauge disparities.
Results
56 051 096 individuals were exposed, with Turkey having 44 million vs 12 million in Syria. Turkey had higher CMR in affected areas (10.5 vs. 5.0 per 10,000), while Syria had higher CMR in intensely seismic regions (9.3 vs. 7.7 per 1,000). Turkey had higher injury rates (24.6 vs. 9.9 per 10 000). Death and injury rates plateaued in Syria after 3 days, but steadily rose in Turkey. Syria allocated more funding for all priorities per population except health care facilities’ rehabilitation. Turkey had 219 USAR teams compared to Syria’s 6, with significantly more humanitarian aid personnel (23 vs. 2/100,000).
Conclusions
Significant disparities in the initial health care response were observed between Turkey and Syria, highlighting the need for policymakers to enhance response capabilities in conflict-affected events to reduce the impact on affected populations.
Narrative Abstract
The 2023 Turkish-Syrian earthquakes, the most devastating in the region since 1939, heightened challenges in Syria’s health care system amid ongoing conflict, disrupting Gaziantep’s humanitarian aid supply route. The initial health care responses post-earthquakes in Turkey and Syria were analyzed through a descriptive study, where Crude Mortality Rates (CMR) and injury rates during the first week were calculated. The World Health Organization’s funding priorities and the ratio of humanitarian aid personnel in Urban Search and Rescue teams per population were assessed. Turkey had 4-fold higher earthquake exposure and experienced higher CMR and injuries per population, while Syria had higher CMR in intensely seismic regions. Temporal trends showed plateaued death and injury rates in Syria within 3 days, while Turkey’s continued to increase. Syria required more funding across nearly all priorities while Turkey had more humanitarian aid personnel per population. Significant health care response disparities were observed, emphasizing the imperative for policymakers to enhance initial responses in conflict-affected events.
Stroke causes neurological and physical impairment in millions of people around the world every year. To better comprehend the upper-limb needs and challenges stroke survivors face and the issues associated with existing technology and formulate ideas for a technological solution, the authors conversed with 153 members of the ecosystem (60 neuro patients, 30 caregivers, and 63 medical providers). Patients fell into two populations depending on their upper-limb impairment: spastic (stiff, clenched hands) and flaccid (limp hands). For this work, the authors chose to focus on the second category and developed a set of design constraints based on the information collected through customer discovery. With these in mind, they designed and prototyped a 3D-printed powered wrist–hand grasping orthosis (exoskeleton) to aid in recovery. The orthosis is easily custom-sized based on two parameters and derived anatomical relationships. The researchers tested the prototype on a survivor of stroke and modeled the kinematic behavior of the orthosis with and without load. The prototype neared or exceeded the target design constraints and was able to grasp objects consistently and stably, as well as exercise the patients’ hands. In particular, donning time was only 42 s, as compared to the next fastest time of 3 min reported in literature. This device has the potential for effective neurorehabilitation in a home setting, and it lays the foundation for clinical trials and further device development.
Disease-modifying therapies (DMTs) for Alzheimer’s disease (AD) are emerging following successful clinical trials of therapies targeting amyloid beta (Aβ) protofibrils or plaques. Determining patient eligibility and monitoring treatment efficacy and adverse events, such as Aβ-related imaging abnormalities, necessitates imaging with MRI and PET. The Canadian Consortium on Neurodegeneration in Aging (CCNA) Imaging Workgroup aimed to synthesize evidence and provide recommendations on implementing imaging protocols for AD DMTs in Canada.
Methods:
The workgroup employed a Delphi process to develop these recommendations. Experts from radiology, neurology, biomedical engineering, nuclear medicine, MRI and medical physics were recruited. Surveys and meetings were conducted to achieve consensus on key issues, including protocol standardization, scanner strength, monitoring protocols based on risk profiles and optimal protocol lengths. Draft recommendations were refined through multiple iterations and expert discussions.
Results:
The recommendations emphasize standardized acquisition imaging protocols across manufacturers and scanner strengths to ensure consistency and reliability of clinical treatment decisions, tailored monitoring protocols based on DMTs’ safety and efficacy profiles, consistent monitoring regardless of perceived treatment efficacy and MRI screening on 1.5T or 3T scanners with adapted protocols. An optimal protocol length of 20–30 minutes was deemed feasible; specific sequences are suggested.
Conclusion:
The guidelines aim to enhance imaging data quality and consistency, facilitating better clinical decision-making and improving patient outcomes. Further research is needed to refine these protocols and address evolving challenges with new DMTs. It is recognized that administrative, financial and logistical capacity to deliver additional MRI and positron emission tomography scans require careful planning.
Accounting for 53% of United States peanuts (Arachis hypogaea L.), Georgia is the top peanut-producing state with approximately 1.42 billion kg produced in 2023. Peanut producers often use the ALS imidazolinone herbicide imazapic but reduced yellow nutsedge (Cyperus esculentus L.) control was reported in Georgia peanuts after four-years of continuous imazapic use. This study aimed to determine the level of resistance (LD50, I50, and GR50), potential cross-resistance for the suspected resistant population, and identify the associated genetic mutations conferring resistance. A susceptible biotype was treated with 0, 0.0088, 0.0175, 0.035, 0.07, 0.14, 0.28, and 0.56 kg ai ha-1, and a resistant biotype was sprayed with 0, 0.07, 0.14, 0.28, 0.56, 1.13, 2.26, and 4.5 kg ai ha-1 of imazapic. To determine if the suspected resistant biotype was cross-resistant to halosulfuron-methyl, an ALS herbicide used to control nutsedge spp., both biotypes were treated with 0, 0.0117, 0.0233, 0.0466, 0.0933, 0.187, 0.373, and 0.746 g ai ha-1 of halosulfuron-methyl. Plants were rated for injury 7, 14, and 28 days after treatment (DAT), and above-ground biomass harvested at 28 DAT. For imazapic, LD50 was 0.041 and 1.503 kg ai ha-1 and the GR50 was estimated to be 0.0128 and 1.853 kg ai ha-1 for Sus and Res biotypes, respectively, indicating 36 and 145-fold increase in resistance of the Res biotype for I50 and GR50, respectively. Both biotypes responded similarly to applications of halosulfuron-methyl, with biomass reductionat rates greater than 0.023 kg ai ha-1. Transcriptome profiles revealed a mutation in the target-site gene of the resistant biotype, causing an amino acid substitution from Alanine to Valine at position 205 (Ala205Val). Growers should continue to rotate chemistries and implement integrated weed management approaches for control of C. esculentus as the use of imazapic over consecutive years has led to resistance in C. esculentus.
Accelerating COVID-19 Treatment Interventions and Vaccines (ACTIV) was initiated by the US government to rapidly develop and test vaccines and therapeutics against COVID-19 in 2020. The ACTIV Therapeutics-Clinical Working Group selected ACTIV trial teams and clinical networks to expeditiously develop and launch master protocols based on therapeutic targets and patient populations. The suite of clinical trials was designed to collectively inform therapeutic care for COVID-19 outpatient, inpatient, and intensive care populations globally. In this report, we highlight challenges, strategies, and solutions around clinical protocol development and regulatory approval to document our experience and propose plans for future similar healthcare emergencies.
The Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Cross-Trial Statistics Group gathered lessons learned from statisticians responsible for the design and analysis of the 11 ACTIV therapeutic master protocols to inform contemporary trial design as well as preparation for a future pandemic. The ACTIV master protocols were designed to rapidly assess what treatments might save lives, keep people out of the hospital, and help them feel better faster. Study teams initially worked without knowledge of the natural history of disease and thus without key information for design decisions. Moreover, the science of platform trial design was in its infancy. Here, we discuss the statistical design choices made and the adaptations forced by the changing pandemic context. Lessons around critical aspects of trial design are summarized, and recommendations are made for the organization of master protocols in the future.
The malicious use of artificial intelligence is growing rapidly, creating major security threats for individuals and the healthcare sector. Individuals with mental illness may be especially vulnerable. Healthcare provider data are a prime target for cybercriminals. There is a need to improve cybersecurity to detect and prevent cyberattacks against individuals and the healthcare sector, including the use of artificial intelligence predictive tools.
White extremism has been a rising trend in North American and European countries over the past two decades. Despite the systemically engrained privileged status of people who identify as white in US society, one of the causes of white extremism is a perceived threat of being sidelined/disadvantaged by individuals with non-white identities. For example, the mainstreaming of the great replacement theory among right-wing media outlets and politicians demonstrates this perception. We examine this perception, and white extremism rhetoric and radicalization broadly, within the context of social exclusion at both the individual and systemic levels. We further embed this analysis within theories and research focused on concepts of “the self,” social identity, and related psychological needs usually impacted by social exclusion. We recommend researchers and practitioners interested in extremism and radicalization to intentionally consider self-related theories and constructs going forward.
Leveraging the National COVID-19 Cohort Collaborative (N3C), a nationally sampled electronic health records repository, we explored associations between individual-level social determinants of health (SDoH) and COVID-19-related hospitalizations among racialized minority people with human immunodeficiency virus (HIV) (PWH), who have been historically adversely affected by SDoH.
Methods:
We retrospectively studied PWH and people without HIV (PWoH) using N3C data from January 2020 to November 2023. We evaluated SDoH variables across three domains in the Healthy People 2030 framework: (1) healthcare access, (2) economic stability, and (3) social cohesion with our primary outcome, COVID-19-related hospitalization. We conducted hierarchically nested additive and adjusted mixed-effects logistic regression models, stratifying by HIV status and race/ethnicity groups, accounting for age, sex, comorbidities, and data partners.
Results:
Our analytic sample included 280,441 individuals from 24 data partner sites, where 3,291 (1.17%) were PWH, with racialized minority PWH having higher proportions of adverse SDoH exposures than racialized minority PWoH. COVID-19-related hospitalizations occurred in 11.23% of all individuals (9.17% among PWH, 11.26% among PWoH). In our initial additive modeling, we observed that all three SDoH domains were significantly associated with hospitalizations, even with progressive adjustments (adjusted odds ratios [aOR] range 1.36–1.97). Subsequently, our HIV-stratified analyses indicated economic instability was associated with hospitalization in both PWH and PWoH (aOR range 1.35–1.48). Lastly, our fully adjusted, race/ethnicity-stratified analysis, indicated access to healthcare issues was associated with hospitalization across various racialized groups (aOR range 1.36–2.00).
Conclusion:
Our study underscores the importance of assessing individual-level SDoH variables to unravel the complex interplay of these factors for racialized minority groups.
Understanding characteristics of healthcare personnel (HCP) with SARS-CoV-2 infection supports the development and prioritization of interventions to protect this important workforce. We report detailed characteristics of HCP who tested positive for SARS-CoV-2 from April 20, 2020 through December 31, 2021.
Methods:
CDC collaborated with Emerging Infections Program sites in 10 states to interview HCP with SARS-CoV-2 infection (case-HCP) about their demographics, underlying medical conditions, healthcare roles, exposures, personal protective equipment (PPE) use, and COVID-19 vaccination status. We grouped case-HCP by healthcare role. To describe residential social vulnerability, we merged geocoded HCP residential addresses with CDC/ATSDR Social Vulnerability Index (SVI) values at the census tract level. We defined highest and lowest SVI quartiles as high and low social vulnerability, respectively.
Results:
Our analysis included 7,531 case-HCP. Most case-HCP with roles as certified nursing assistant (CNA) (444, 61.3%), medical assistant (252, 65.3%), or home healthcare worker (HHW) (225, 59.5%) reported their race and ethnicity as either non-Hispanic Black or Hispanic. More than one third of HHWs (166, 45.2%), CNAs (283, 41.7%), and medical assistants (138, 37.9%) reported a residential address in the high social vulnerability category. The proportion of case-HCP who reported using recommended PPE at all times when caring for patients with COVID-19 was lowest among HHWs compared with other roles.
Conclusions:
To mitigate SARS-CoV-2 infection risk in healthcare settings, infection prevention, and control interventions should be specific to HCP roles and educational backgrounds. Additional interventions are needed to address high social vulnerability among HHWs, CNAs, and medical assistants.
This paper introduces DivFolio, a multiperiod portfolio selection and analytic software application that incorporates automated and user-determined divestment practices accommodating Environmental Social Governance (ESG) and portfolio carbon footprint considerations. This freely available portfolio analytics software tool is written in R with a GUI interface developed as an R Shiny application for ease of user experience. Users can utilize this software to dynamically assess the performance of asset selections from global equity, exchange-traded funds, exchange-traded notes, and depositary receipts markets over multiple time periods. This assessment is based on the impact of ESG investment and fossil-fuel divestment practices on portfolio behavior in terms of risk, return, stability, diversification, and climate mitigation credentials of associated investment decisions. We highlight two applications of DivFolio. The first revolves around using sector scanning to divest from a specialized portfolio featuring constituents of the FTSE 100. The second, rooted in actuarial considerations, focuses on divestment strategies informed by environmental risk assessments for mixed pension portfolios in the US and UK.
Chemical data from three different series of diagenetic illite/smectites (I/S), analyzed statistically by two regresion techniques, indicate that the content of fixed-K per illite layer is not constant, but ranges from ~0.55 per O10(OH)2 for illite layers in randomly interstratified I/S (R=0; >50% smectite layers) to ~ 1.0 per O10(OH)2 for illite layers formed in ordered I/S (R>0; <50% smectite layers). By extrapolation of the experimental data, the following chemical characteristics were obtained for end-member illite derived from the alteration of smectite in bentonite: average fixed-K per illite layer = 0.75 per O10(OH)2; total charge = about -0.8; cation-exchange capacity = 15 meq/100 g; surface area (EGME) = 150 m2/g.