Workplace Health Promotion Programs Available to Emergency Medical Services Clinicians in North Carolina.

BACKGROUND: Emergency medical services (EMS) clinicians demonstrate a high prevalence of chronic medical conditions that place them at risk for early mortality. Workplace health promotion programs improve health outcomes, but the availably of such programs for EMS clinicians has not been described. We investigate the availability, scope, and participation of workplace health promotion programs available to EMS clinicians in North Carolina (NC). METHODS: We administered an electronic survey based on the Centers for Disease Control and Prevention Worksite Health ScoreCard to key representatives of EMS agencies within NC that provide primarily transport-capable 9-1-1 response with ground ambulances. We collected information on agency size, rurality, elements of health promotion programs offered, incentives for participation, and participation rate. We calculated descriptive statistics using frequency and percentage for worksite and health promotion program characteristics. We compared the participation rate for agencies who did and did not incentivize participation using Fisher's exact test. RESULTS: Complete responses were received from 69 of 92 agencies (response = 75%) that collectively employ 6679 EMS clinicians [median employees per agency 71 (IQR 50-131)]. Most agencies (88.4%, 61/69) offered at least one element of a worksite health program, but only 13.0% (9/69) offered all elements of a worksite health program. In descending order, the availability of program elements were employee assistance programs (73.9%, 51/69), supportive physical and social environment (66.7%, 46/69), health education (62.3%, 43/69), health risk assessments (52.2%, 36/69), and organization culture of health promotion (20.3%, 14/69). Of agencies with programs, few (11.5%, 7/61) required participation, but most (59.0%, 36/61) offered incentives to participate. Participation rates were <25% among nearly all of the agencies that did not offer incentives, but >50% among most agencies that did offer incentives (p < 0.001). CONCLUSION: While most agencies offer at least one element of a worksite health promotion program, few agencies offer all elements and participation rates are low.

Use of Routine Emergency Department Care Practices with Deaf American Sign Language Users.

BACKGROUND: Deaf individuals who communicate using American Sign Language (ASL) seem to experience a range of disparities in health care, but there are few empirical data. OBJECTIVE: To examine the provision of common care practices in the emergency department (ED) to this population. METHODS: ED visits in 2018 at a U.S. academic medical center were assessed retrospectively in Deaf adults who primarily use ASL (n = 257) and hearing individuals who primarily use English, selected at random (n = 429). Logistic regression analyses adjusted for confounders compared the groups on the provision or nonprovision of four routine ED care practices (i.e., laboratories ordered, medications ordered, images ordered, placement of peripheral intravenous line [PIV]) and on ED disposition (admitted to hospital or not admitted). RESULTS: The ED encounters with Deaf ASL users were less likely to include laboratory tests being ordered: adjusted odds ratio 0.68 and 95% confidence interval 0.47-0.97. ED encounters with Deaf individuals were also less likely to include PIV placement, less likely to result in images being ordered in the ED care of ASL users of high acuity compared with English users of high acuity (but not low acuity), and less likely to result in hospital admission. CONCLUSION: Results suggest disparate provision of several types of routine ED care for adult Deaf ASL users. Limitations include the observational study design at a single site and reliance on the medical record, underscoring the need for further research and potential reasons for disparate ED care with Deaf individuals.

Dynamic susceptibility-contrast magnetic resonance imaging with contrast agent leakage correction aids in predicting grade in pediatric brain tumours: a multicenter study.

BACKGROUND: Relative cerebral blood volume (rCBV) measured using dynamic susceptibility-contrast MRI can differentiate between low- and high-grade pediatric brain tumors. Multicenter studies are required for translation into clinical practice. OBJECTIVE: We compared leakage-corrected dynamic susceptibility-contrast MRI perfusion parameters acquired at multiple centers in low- and high-grade pediatric brain tumors. MATERIALS AND METHODS: Eighty-five pediatric patients underwent pre-treatment dynamic susceptibility-contrast MRI scans at four centers. MRI protocols were variable. We analyzed data using the Boxerman leakage-correction method producing pixel-by-pixel estimates of leakage-uncorrected (rCBVuncorr) and corrected (rCBVcorr) relative cerebral blood volume, and the leakage parameter, K2. Histological diagnoses were obtained. Tumors were classified by high-grade tumor. We compared whole-tumor median perfusion parameters between low- and high-grade tumors and across tumor types. RESULTS: Forty tumors were classified as low grade, 45 as high grade. Mean whole-tumor median rCBVuncorr was higher in high-grade tumors than low-grade tumors (mean ± standard deviation [SD] = 2.37±2.61 vs. -0.14±5.55; P<0.01). Average median rCBV increased following leakage correction (2.54±1.63 vs. 1.68±1.36; P=0.010), remaining higher in high-grade tumors than low grade-tumors. Low-grade tumors, particularly pilocytic astrocytomas, showed T1-dominant leakage effects; high-grade tumors showed T2*-dominance (mean K2=0.017±0.049 vs. 0.002±0.017). Parameters varied with tumor type but not center. Median rCBVuncorr was higher (mean = 1.49 vs. 0.49; P=0.015) and K2 lower (mean = 0.005 vs. 0.016; P=0.013) in children who received a pre-bolus of contrast agent compared to those who did not. Leakage correction removed the difference. CONCLUSION: Dynamic susceptibility-contrast MRI acquired at multiple centers helped distinguish between children's brain tumors. Relative cerebral blood volume was significantly higher in high-grade compared to low-grade tumors and differed among common tumor types. Vessel leakage correction is required to provide accurate rCBV, particularly in low-grade enhancing tumors.

Emergent SO(5) Symmetry at the Columnar Ordering Transition in the Classical Cubic Dimer Model.

The classical cubic-lattice dimer model undergoes an unconventional transition between a columnar crystal and a dimer liquid, in the same universality class as the deconfined quantum critical point in spin-1/2 antiferromagnets but with very different microscopic physics and microscopic symmetries. Using Monte Carlo simulations, we show that this transition has emergent SO(5) symmetry relating quantities characterizing the two phases. While the low-temperature phase has a conventional order parameter, the defining property of the Coulomb liquid on the high-temperature side is deconfinement of monomers, and so SO(5) relates fundamentally different types of objects. Studying linear system sizes up to L=96, we find that this symmetry applies with an excellent precision, consistently improving with system size over this range. It is remarkable that SO(5) emerges in a system as basic as the cubic dimer model, with only simple discrete degrees of freedom. Our results are important evidence for the generality of the SO(5) symmetry that has been proposed for the noncompact CP^{1} field theory. We describe an interpretation for these results in terms of a consistent hypothesis for the renormalization-group flow structure, allowing for the possibility that SO(5) may ultimately be a near-symmetry rather than exact.

Quantum Slow Relaxation and Metastability due to Dynamical Constraints.

One of the general mechanisms that give rise to the slow cooperative relaxation characteristic of classical glasses is the presence of kinetic constraints in the dynamics. Here we show that dynamical constraints can similarly lead to slow thermalization and metastability in translationally invariant quantum many-body systems. We illustrate this general idea by considering two simple models: (i) a one-dimensional quantum analogue to classical constrained lattice gases where excitation hopping is constrained by the state of neighboring sites, mimicking excluded-volume interactions of dense fluids; and (ii) fully packed quantum dimers on the square lattice. Both models have a Rokhsar-Kivelson (RK) point at which kinetic and potential energy constants are equal. To one side of the RK point, where kinetic energy dominates, thermalization is fast. To the other, where potential energy dominates, thermalization is slow, memory of initial conditions persists for long times, and separation of timescales leads to pronounced metastability before eventual thermalization. Furthermore, in analogy with what occurs in the relaxation of classical glasses, the slow-thermalization regime displays dynamical heterogeneity as manifested by spatially segregated growth of entanglement.

Analysis of laboratory data transmission between two healthcare institutions using a widely used point-to-point health information exchange platform: a case report.

Objective: The objective was to identify information loss that could affect clinical care in laboratory data transmission between 2 health care institutions via a Health Information Exchange platform. Materials and Methods: Data transmission results of 9 laboratory tests, including LOINC codes, were compared in the following: between sending and receiving electronic health record (EHR) systems, the individual Health Level Seven International (HL7) Version 2 messages across the instrument, laboratory information system, and sending EHR. Results: Loss of information for similar tests indicated the following potential patient safety issues: (1) consistently missing specimen source; (2) lack of reporting of analytical technique or instrument platform; (3) inconsistent units and reference ranges; (4) discordant LOINC code use; and (5) increased complexity with multiple HL7 versions. Discussion and Conclusions: Using an HIE with standard messaging, SHIELD (Systemic Harmonization and Interoperability Enhancement for Laboratory Data) recommendations, and enhanced EHR functionality to support necessary data elements would yield consistent test identification and result value transmission.

Derivation of field theory for the classical dimer model using bosonization.

We derive a field theory for the two-dimensional classical dimer model by applying bosonization to Lieb's (fermionic) transfer-matrix solution. Our constructive approach gives results that are consistent with the well-known height theory, previously justified based on symmetry considerations, but also fixes coefficients appearing in the effective theory and the relationship between microscopic observables and operators in the field theory. In addition, we show how interactions can be included in the field theory perturbatively, treating the case of the double dimer model with interactions within and between the two replicas. Using a renormalization-group analysis, we determine the shape of the phase boundary near the noninteracting point, in agreement with results of Monte Carlo simulations.

Applying machine learning classifiers to automate quality assessment of paediatric dynamic susceptibility contrast (DSC-) MRI data.

OBJECTIVE: Investigate the performance of qualitative review (QR) for assessing dynamic susceptibility contrast (DSC-) MRI data quality in paediatric normal brain and develop an automated alternative to QR. METHODS: 1027 signal-time courses were assessed by Reviewer 1 using QR. 243 were additionally assessed by Reviewer 2 and % disagreements and Cohen's κ (κ) were calculated. The signal drop-to-noise ratio (SDNR), root mean square error (RMSE), full width half maximum (FWHM) and percentage signal recovery (PSR) were calculated for the 1027 signal-time courses. Data quality thresholds for each measure were determined using QR results. The measures and QR results trained machine learning classifiers. Sensitivity, specificity, precision, classification error and area under the curve from a receiver operating characteristic curve were calculated for each threshold and classifier. RESULTS: Comparing reviewers gave 7% disagreements and κ = 0.83. Data quality thresholds of: 7.6 for SDNR; 0.019 for RMSE; 3 s and 19 s for FWHM; and 42.9 and 130.4% for PSR were produced. SDNR gave the best sensitivity, specificity, precision, classification error and area under the curve values of 0.86, 0.86, 0.93, 14.2% and 0.83. Random forest was the best machine learning classifier, giving sensitivity, specificity, precision, classification error and area under the curve of 0.94, 0.83, 0.93, 9.3% and 0.89. CONCLUSION: The reviewers showed good agreement. Machine learning classifiers trained on signal-time course measures and QR can assess quality. Combining multiple measures reduces misclassification. ADVANCES IN KNOWLEDGE: A new automated quality control method was developed, which trained machine learning classifiers using QR results.

Universal monopole scaling near transitions from the Coulomb phase.

Certain frustrated systems, including spin ice and dimer models, exhibit a Coulomb phase at low temperatures, with power-law correlations and fractionalized monopole excitations. Transitions out of this phase, at which the effective gauge theory becomes confining, provide examples of unconventional criticality. This Letter studies the behavior at nonzero monopole density near such transitions, using scaling theory to arrive at universal expressions for the crossover phenomena. For a particular transition in spin ice, quantitative predictions are made by mapping to the XY model and confirmed using Monte Carlo simulations.

Establishing Trust in Pharmaceutical Data with an Independent Verification and Validation Methodology.

Our aim is to demonstrate a general-purpose data and knowledge validation approach that enables reproducible metrics for data and knowledge quality and safety. We researched widely accepted statistical process control methods from high-quality, high-safety industries and applied them to pharmacy prescription data being migrated between EHRs. Natural language medication instructions from prescriptions were independently categorized by two terminologists as a first step toward encoding those medication instructions using standardized terminology. Overall, the weighted average of medication instructions that were matched by reviewers was 43%, with strong agreement between reviewers for short instructions (K=0.82) and long instructions (K=0.85), and moderate agreement for medium instructions (K=0.61). Category definitions will be refined in future work to mitigate discrepancies. We recommend incorporating appropriate statistical tests, such as evaluating inter-rater and intra-rater reliability and bivariate comparison of reviewer agreement over an adequate statistical sample, when developing benchmarks for health data and knowledge quality and safety.

Virtual Adaptation of an International Exchange Program in Medical Education.

Medical education has drastically transformed during the COVID-19 pandemic. Measures such as adopting telemedicine visits, minimizing the number of trainees on service, discontinuing external rotations, and converting in-person to online didactics have been broadly and swiftly implemented. While these innovations have promoted greater interconnectivity amongst institutions and made continuing medical education possible, international exchange programs in medical education are still largely disrupted. In response to the changing guidelines and restrictions necessitated by the COVID-19 pandemic, the authors used Kern's six-step approach to design and implement a virtual curriculum to replace the in-person activities of the 2020-2021 Neurology Peru-Rochester exchange program (NeuroPro). Twenty-seven trainees participated in this virtual adaptation. The average daily attendance was ≥85% and the program was rated 9/10 on average in a feedback survey (63% response rate). The median percentage of correct answers during the pre-test was 64% and it increased to 79% during the post-test (P = 0.003). Virtual adaptation of international exchange programs in medical education is feasible to safely continue international collaborative efforts to promote symbiotic building of local expertise and cross-cultural exchange during the ongoing COVID-19 pandemic and beyond.

Topological sectors, dimer correlations, and monomers from the transfer-matrix solution of the dimer model.

We solve the classical square-lattice dimer model with periodic boundaries and in the presence of a field t that couples to the (vector) flux, by diagonalizing a modified version of Lieb's transfer matrix. After deriving the torus partition function in the thermodynamic limit, we show how the configuration space divides into topological sectors corresponding to distinct values of the flux. Additionally, we demonstrate in general that expectation values are t independent at leading order, and obtain explicit expressions for dimer occupation numbers, dimer-dimer correlation functions, and the monomer distribution function. The last of these is expressed as a Toeplitz determinant, whose asymptotic behavior for large monomer separation is tractable using the Fisher-Hartwig conjecture. Our results reproduce those previously obtained using Pfaffian techniques.

Spectroscopic profiling variations in extracellular vesicle biochemistry in a model of myogenesis.

Extracellular vesicles (EVs) hold value as accessible biomarkers for understanding cellular differentiation and related pathologies. Herein, EV biomarkers in models of skeletal muscle dormancy and differentiation have been comparatively profiled using Raman spectroscopy (RS). Significant variations in the biochemical fingerprint of EVs were detected, with an elevation in peaks associated with lipid and protein signatures during early myogenic differentiation (day 2). Principal component analysis revealed a clear separation between the spectra of EVs derived from myogenic and senescent cell types, with non-overlapping interquartile ranges and population median. Observations aligned with nanoparticle tracking data, highlighting a significant early reduction in EV concentration in senescent myoblast cultures as well as notable variations in EV morphology and diameter. As differentiation progressed physical and biochemical differences in the properties of EVs became less pronounced. This study demonstrates the applicability of RS as a high-resolution analytical method for profiling biochemical changes in EVs during early myogenesis.

Combining multi-site magnetic resonance imaging with machine learning predicts survival in pediatric brain tumors.

Brain tumors represent the highest cause of mortality in the pediatric oncological population. Diagnosis is commonly performed with magnetic resonance imaging. Survival biomarkers are challenging to identify due to the relatively low numbers of individual tumor types. 69 children with biopsy-confirmed brain tumors were recruited into this study. All participants had perfusion and diffusion weighted imaging performed at diagnosis. Imaging data were processed using conventional methods, and a Bayesian survival analysis performed. Unsupervised and supervised machine learning were performed with the survival features, to determine novel sub-groups related to survival. Sub-group analysis was undertaken to understand differences in imaging features. Survival analysis showed that a combination of diffusion and perfusion imaging were able to determine two novel sub-groups of brain tumors with different survival characteristics (p < 0.01), which were subsequently classified with high accuracy (98%) by a neural network. Analysis of high-grade tumors showed a marked difference in survival (p = 0.029) between the two clusters with high risk and low risk imaging features. This study has developed a novel model of survival for pediatric brain tumors. Tumor perfusion plays a key role in determining survival and should be considered as a high priority for future imaging protocols.

Interacting Hofstadter spectrum of atoms in an artificial gauge field.

Motivated by experimental advances in the synthesis of gauge potentials for ultracold atoms, we consider the superfluid phase of interacting bosons on a square lattice in the presence of a magnetic field. We show that superfluid order implies spatial symmetry breaking, and predict clear signatures of many-body effects in time-of-flight measurements. By developing a Bogoliubov expansion based on the exact Hofstadter spectrum, we find the dispersion of the quasiparticle modes within the superfluid phase, and describe the consequences for Bragg spectroscopy measurements. The theory also provides an estimate of the critical interaction strength at the transition to the Mott insulator phase.

Distinguishing between paediatric brain tumour types using multi-parametric magnetic resonance imaging and machine learning: A multi-site study.

The imaging and subsequent accurate diagnosis of paediatric brain tumours presents a radiological challenge, with magnetic resonance imaging playing a key role in providing tumour specific imaging information. Diffusion weighted and perfusion imaging are commonly used to aid the non-invasive diagnosis of children's brain tumours, but are usually evaluated by expert qualitative review. Quantitative studies are mainly single centre and single modality. The aim of this work was to combine multi-centre diffusion and perfusion imaging, with machine learning, to develop machine learning based classifiers to discriminate between three common paediatric tumour types. The results show that diffusion and perfusion weighted imaging of both the tumour and whole brain provide significant features which differ between tumour types, and that combining these features gives the optimal machine learning classifier with >80% predictive precision. This work represents a step forward to aid in the non-invasive diagnosis of paediatric brain tumours, using advanced clinical imaging.

Bioreactor-Grown Bacillus of Calmette and Guérin (BCG) Vaccine Protects Badgers against Virulent Mycobacterium bovis When Administered Orally: Identifying Limitations in Baited Vaccine Delivery.

Bovine tuberculosis (TB) in Great Britain adversely affects animal health and welfare and is a cause of considerable economic loss. The situation is exacerbated by European badgers (Meles meles) acting as a wildlife source of recurrent Mycobacterium bovis infection to cattle. Vaccination of badgers against TB is a possible means to reduce and control bovine TB. The delivery of vaccine in oral bait holds the best prospect for vaccinating badgers over a wide geographical area. There are practical limitations over the volume and concentration of Bacillus of Calmette and Guérin (BCG) that can be prepared for inclusion in bait. The production of BCG in a bioreactor may overcome these issues. We evaluated the efficacy of oral, bioreactor-grown BCG against experimental TB in badgers. We demonstrated repeatable protection through the direct administration of at least 2.0 × 108 colony forming units of BCG to the oral cavity, whereas vaccination via voluntary consumption of bait containing the same preparation of BCG did not result in demonstrable protection at the group-level, although a minority of badgers consuming bait showed immunological responses and protection after challenge equivalent to badgers receiving oral vaccine by direct administration. The need to deliver oral BCG in the context of a palatable and environmentally robust bait appears to introduce such variation in BCG delivery to sites of immune induction in the badger as to render experimental studies variable and inconsistent.

Trigeminal Trophic Syndrome Leading to Orbital Cellulitis.

Trigeminal trophic syndrome is a rare condition that develops from trigeminal nerve damage causing dysesthesias that result in self-mutilation. Facial and nasal destruction develops from self-destructive behavior (repetitive picking or scratching) secondary to the altered skin sensation created by the damaged trigeminal nerve. Early recognition of this condition is crucial to the prevention of the detrimental complications of facial ulceration and nasal tissue necrosis that can lead to corneal ulcerations, full-thickness eyelid defect, and canthal lesions. This case demonstrates a previously unreported complication: orbital cellulitis.

Expression profiling using a hexamer-based universal microarray.

We describe a transcriptional analysis platform consisting of a universal micro-array system (UMAS) combined with an enzymatic manipulation step that is capable of generating expression profiles from any organism without requiring a priori species-specific knowledge of transcript sequences. The transcriptome is converted to cDNA and processed with restriction endonucleases to generate low-complexity pools (approximately 80-120) of equal length DNA fragments. The resulting material is amplified and detected with the UMAS system, comprising all possible 4,096 (4(6)) DNA hexamers. Ligation to the arrays yields thousands of 14-mer sequence tags. The compendium of signals from all pools in the array-of-universal arrays comprises a full-transcriptome expression profile. The technology was validated by analysis of the galactose response of Saccharomyces cerevisiae, and the resulting profiles showed excellent agreement with the literature and real-time PCR assays. The technology was also used to demonstrate expression profiling from a hybrid organism in a proof-of-concept experiment where a T-cell receptor gene was expressed in yeast.

My copilot is a nurse--using crew resource management in the OR.

Crew resource management (CRM) has been used for more than 20 years in the aviation industry to teach individual error countermeasures by developing nontechnical (ie, cognitive, social) skills based on the observed traits of successful individuals and crews. The health care industry began to investigate aviation CRM after the Institute of Medicine's report, To Err is Human: Building a Safer Health System, recommended that medicine adopt aviation's approach to safety and error management. Initial results of implementing CRM in health care arenas have demonstrated reduced adverse outcomes, reduced errors, reduced length of stay, improved nurse retention, and changed attitudes and behaviors toward teamwork.