Comparative surgical outcomes of navigated vs non-navigated posterior spinal fusions in ankylosing spondylitis patients.

INTRODUCTION: Ankylosing Spondylitis (AS) patients with acute spinal fractures represent a challenge for practicing spine surgeons due to difficult operative anatomy and susceptibility to complications. RESEARCH QUESTION: Does intraoperative CT-navigation improve outcomes in patients with ankylosing spondylitis undergoing surgery? METHODS: A retrospective review was carried out at our centre from 05/2016-06/2021 to identify AS patients presenting with a traumatic spinal fracture, managed surgically with posterior spinal fusion (PSF). Cohorts were categorised and compared for outcomes based on those who underwent PSF with intraoperative CT-navigation versus those surgically managed with traditional intraoperative fluoroscopy. RESULTS: 37 AS patients were identified. 29/37 (78.4%) underwent PSF. Intraoperative navigation was used in 14 (48.3%) cases. Mean age of the entire cohort was 67.6 years. No difference existed between the navigated and non-navigated groups for mean levels fused (5.35 vs 5.07; p â€‹= â€‹0.31), length of operation (217.9mins vs 175.3mins; p â€‹= â€‹0.07), overall length-of-stay (12 days vs 21.9 days; p â€‹= â€‹0.16), patients requiring HDU (3/14 vs 5/15; p â€‹= â€‹0.09) or ICU (5/14 vs 9/15; p â€‹= â€‹0.10), postoperative neurological improvement (1/14 vs 1/15; p â€‹= â€‹0.48) or deterioration (1/14 vs 0/15; p â€‹= â€‹0.15), intraoperative complications (2/14 vs 3/15; p â€‹= â€‹0.34), postoperative complications 4/14 vs 4/15; p â€‹= â€‹0.46), revision surgeries (3/14 vs 1/15; p â€‹= â€‹0.16) and 30-day mortality (0/14 vs 0/15). CONCLUSION: This is the first study that compares surgical outcomes of navigated vs non-navigated PSFs for AS patients with an acute spinal fracture. Although limited by its retrospective design and sample size, this study highlights the non-inferiority of intraoperative navigation as a surgical aid in a challenging cohort.

You Cannot Function in "Overwhelm": Helping Primary Care Navigate the Slow End of the Pandemic.

GOAL: This study was developed to explicate underlying organizational factors contributing to the deterioration of primary care clinicians' mental health during the COVID-19 pandemic. METHODS: Using data from the Larry A. Green Center for the Advancement of Primary Health Care for the Public Good's national survey of primary care clinicians from March 2020 to March 2022, a multidisciplinary team analyzed more than 11,150 open-ended comments. Phase 1 of the analysis happened in real-time as surveys were returned, using deductive and inductive coding. Phase 2 used grounded theory to identify emergent themes. Qualitative findings were triangulated with the survey's quantitative data. PRINCIPAL FINDINGS: The clinicians shifted from feelings of anxiety and uncertainty at the start of the pandemic to isolation, lack of fulfillment, moral injury, and plans to leave the profession. The frequency with which they spoke of depression, burnout, and moral injury was striking. The contributors to this distress included crushing workloads, worsening staff shortages, and insufficient reimbursement. Consequences, both felt and anticipated, included fatigue and demoralization from the inability to manage escalating workloads. Survey findings identified responses that could alleviate the mental health crisis, namely: (1) measuring and customizing workloads based on work capacity; (2) quantifying resources needed to return to sufficient staffing levels; (3) promoting state and federal support for sustainable practice infrastructures with less administrative burden; and (4) creating patient visits of different lengths to rebuild relationships and trust and facilitate more accurate diagnoses. PRACTICAL APPLICATIONS: Attention to clinicians' mental health should be rapidly directed to on-demand, confidential mental health support so they can receive the care they need and not worry about any stigma or loss of license for accepting that help. Interventions that address work-life balance, workload, and resources can improve care, support retention of the critically important primary care workforce, and attract more trainees to primary care careers.

Epidemiological data analysis of viral quasispecies in the next-generation sequencing era.

The unprecedented coverage offered by next-generation sequencing (NGS) technology has facilitated the assessment of the population complexity of intra-host RNA viral populations at an unprecedented level of detail. Consequently, analysis of NGS datasets could be used to extract and infer crucial epidemiological and biomedical information on the levels of both infected individuals and susceptible populations, thus enabling the development of more effective prevention strategies and antiviral therapeutics. Such information includes drug resistance, infection stage, transmission clusters and structures of transmission networks. However, NGS data require sophisticated analysis dealing with millions of error-prone short reads per patient. Prior to the NGS era, epidemiological and phylogenetic analyses were geared toward Sanger sequencing technology; now, they must be redesigned to handle the large-scale NGS datasets and properly model the evolution of heterogeneous rapidly mutating viral populations. Additionally, dedicated epidemiological surveillance systems require big data analytics to handle millions of reads obtained from thousands of patients for rapid outbreak investigation and management. We survey bioinformatics tools analyzing NGS data for (i) characterization of intra-host viral population complexity including single nucleotide variant and haplotype calling; (ii) downstream epidemiological analysis and inference of drug-resistant mutations, age of infection and linkage between patients; and (iii) data collection and analytics in surveillance systems for fast response and control of outbreaks.

Correlative image learning of chemo-mechanics in phase-transforming solids.

Constitutive laws underlie most physical processes in nature. However, learning such equations in heterogeneous solids (for example, due to phase separation) is challenging. One such relationship is between composition and eigenstrain, which governs the chemo-mechanical expansion in solids. Here we developed a generalizable, physically constrained image-learning framework to algorithmically learn the chemo-mechanical constitutive law at the nanoscale from correlative four-dimensional scanning transmission electron microscopy and X-ray spectro-ptychography images. We demonstrated this approach on LiXFePO4, a technologically relevant battery positive electrode material. We uncovered the functional form of the composition-eigenstrain relation in this two-phase binary solid across the entire composition range (0 ≤ X ≤ 1), including inside the thermodynamically unstable miscibility gap. The learned relation directly validates Vegard's law of linear response at the nanoscale. Our physics-constrained data-driven approach directly visualizes the residual strain field (by removing the compositional and coherency strain), which is otherwise impossible to quantify. Heterogeneities in the residual strain arise from misfit dislocations and were independently verified by X-ray diffraction line profile analysis. Our work provides the means to simultaneously quantify chemical expansion, coherency strain and dislocations in battery electrodes, which has implications on rate capabilities and lifetime. Broadly, this work also highlights the potential of integrating correlative microscopy and image learning for extracting material properties and physics.

Lowering Re-excision Rates After Breast-Conserving Surgery: Unraveling the Intersection Between Surgeon Case Volumes and Techniques.

BACKGROUND: The re-excision rates after breast-conserving surgery (BCS) are significantly varied, with surgeon case volume as one influential factor. Surgeons with higher case volumes have been shown to have lower reoperation rates. This study attempted to determine whether this may be attributable to excessive breast tissue removal during initial BCS. METHODS: A retrospective study analyzed referrals to the authors' cancer center during 3 years. Patients undergoing initial BCS for ductal carcinoma in situ or T1-T3 breast cancers were included. Patient age, tumor factors, surgeon case volume, and the calculated resection ratio (CRR) were analyzed. The total resection volume was divided by the optimal resection volume to produce the CRR, which reflected the magnitude of excess tissue resected during initial BCS. Comparison of the mean CRR between surgeon case-volume categories was performed with a repeated measures analysis of variance. A multivariate regression model assessed the effects of the CRR and surgeon case volume on re-excision rates. RESULTS: Larger tumor size, lobular histology, and lower CRR were associated with increased re-excision rates. The CRR was similar for each surgeon case-volume group. Surgeon case volume was not independently associated with re-excision rates, but surgeons with very high case volumes had lower odds of re-excision than surgeons with intermediate case volumes (odds ratio 0.44; 95% confidence interval 0.21-0.91). CONCLUSIONS: When control was used for the CRR, apparent differences in re-excision rates between surgeon case-volume groups were observed, suggesting that surgeons with higher case volumes may be more accurate when performing BCS.

py4DSTEM: A Software Package for Four-Dimensional Scanning Transmission Electron Microscopy Data Analysis.

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

Neonatal Sepsis: A Review of Pathophysiology and Current Management Strategies.

BACKGROUND: Early-onset sepsis, occurring within 72 hours of birth, and late-onset sepsis, occurring after this time period, present serious risks for neonates. While culture-based screening and intrapartum antibiotics have decreased the number of early-onset cases, sepsis remains a top cause of neonatal morbidity and mortality in the United States. PURPOSE: To provide a review of neonatal sepsis by identifying its associated risk factors and most common causative pathogens, reviewing features of the term and preterm neonatal immune systems that increase vulnerability to infection, describing previous and the most current management recommendations, and discussing relevant implications for the neonatal nurse and novice neonatal nurse practitioner. METHODS/SEARCH STRATEGY: An integrative review of literature was conducted using key words in CINAHL, Google Scholar, and PubMed. FINDINGS/RESULTS: Group B streptococcus and Escherichia coli are the most common pathogens in early-onset sepsis, while Coagulase-negative staphylococci comprise the majority of cases in late-onset. The neonatal immune system is vulnerable due to characteristics including decreased cellular activity, underdeveloped complement systems, preferential anti-inflammatory responses, and insufficient pathogenic memory. Blood cultures remain the criterion standard of diagnosis, with several other adjunct tests under investigation for clinical use. The recent development of the sepsis calculator has been a useful tool in the management of early-onset cases. IMPLICATIONS FOR PRACTICE: It is vital to understand the mechanisms behind the neonate's elevated risk for infection and to implement evidence-based management. IMPLICATIONS FOR RESEARCH: Research needs exist for diagnostic methods that deliver timely and sensitive results. A tool similar to the sepsis calculator does not exist for preterm infants or late-onset sepsis, groups for which antibiotic stewardship is not as well practiced.Video Abstract available athttps://journals.lww.com/advancesinneonatalcare/Pages/videogallery.aspx?autoPlay=false&videoId=40.

Engaging With Communities - Lessons (Re)Learned From COVID-19.

Coronavirus disease 2019 (COVID-19) has underscored longstanding societal differences in the drivers of health and demonstrated the value of applying a health equity lens to engage at-risk communities, communicate with them effectively, share data, and partner with them for program implementation, dissemination, and evaluation. Examples of engagement - across diverse communities and with community organizations; tribes; state and local health departments; hospitals; and universities - highlight the opportunity to apply lessons from COVID-19 for sustained changes in how public health and its partners work collectively to prevent disease and promote health, especially with our most vulnerable communities.

A Model for Risk-Based Screening and Prioritization of Human Exposure to Chemicals from Near-Field Sources.

Exposure- and risk-based assessments for chemicals used indoors or applied to humans (i.e., in near-field environments) necessitate an aggregate exposure pathway framework that aligns chemical exposure information from use sources to internal dose and eventually to their potential for health effects. Such a source-to-effect continuum is advocated to balance the complexity of human exposure and the insufficiency of relevant data for thousands of existing and emerging chemicals. Here, we introduce the Risk Assessment, IDentification And Ranking-Indoor and Consumer Exposure (RAIDAR-ICE) model, which establishes an integrated framework to evaluate human exposure due to indoor use and direct application of chemicals to humans. As a model evaluation, RAIDAR-ICE faithfully reproduces exposure estimates inferred from biomonitoring data for 37 chemicals with direct and indirect near-field sources. RAIDAR-ICE generates different rankings for 131 chemicals based on different exposure- and risk-based assessment metrics, demonstrating its versatility for diverse chemical screening goals. When coupled with a far-field RAIDAR model, the near-field RAIDAR-ICE model enables assessment of aggregate human exposure. Overall, RAIDAR-ICE is a powerful tool for high-throughput screening and prioritization of human exposure to neutral organic chemicals used indoors.

Perinatal Bacterial Exposure Contributes to IL-13 Aeroallergen Response.

There is a high prevalence of aeroallergen sensitivity in asthmatic populations, and seroreactivity to aeroallergens early in infancy is associated with increased risk of developing asthma later in life. In addition to allergen sensitivity, asthma development has been associated with differential microbial exposure and infection in early life. We have previously shown that cord blood mononuclear cells respond to common aeroallergens (i.e., house dust mite [Der f1] and cockroach [Bla g2]) as assayed by lymphoproliferation and cytokine (IL-13 and IFN-γ) production. We hypothesized that there is a relationship between perinatal microbial exposure and response to specific aeroallergens. To test this hypothesis, we isolated DNA from cord blood serum samples with known lymphoproliferative and cytokine responses to Bla g2 and Der f1. Bacterial 16S ribosomal DNA amplicon libraries were generated and analyzed using high throughput sequencing of cord blood serum samples. In our analysis, we identified major compositional differences, including diversity and abundance of specific taxa, between groups whose IL-13 response to Der f1 and Bla g2 differed. We demonstrate a strong association between the ratio of Acinetobacter to Proteobacteria and IL-13 production and the probability of IL-13 production after allergen exposure. IL-13 concentrations in serum were also significantly correlated with the diversity of bacterial DNA. Together, these results underscore the relationship between immune responses to allergens and bacterial exposure during perinatal development.

Simultaneous Scanning Electron Microscope Imaging of Topographical and Chemical Contrast Using In-Lens, In-Column, and Everhart-Thornley Detector Systems.

The scanning electron microscope provides a platform for subnanometer resolution characterization of material morphology with excellent topographic and chemical contrast dependent on the used detectors. For imaging applications, the predominantly utilized signals are secondary electrons (SEs) and backscattered electrons (BSEs) that are emitted from the sample surface. Recent advances in detector technology beyond the traditional Everhart-Thornley geometry have enabled the simultaneous acquisition and discrimination of SE and BSE signals. This study demonstrates the imaging capabilities of a recently introduced new detector system that consists of the combination of two in-lens (I-L) detectors and one in-column (I-C) detector. Coupled with biasing the sample stage to reduce electron-specimen interaction volumes, this trinity of detector geometry allows simultaneous acquisition of signals to distinguish chemical contrast from topographical changes of the sample, including the identification of surface contamination. The I-C detector provides 4× improved topography, whereas the I-L detector closest to the sample offers excellent simultaneous chemical contrast imaging while not limiting the minimization of working distance to obtain optimal lateral resolution. Imaging capabilities and contrast mechanisms for all three detectors are discussed quantitatively in direct comparison to each other and the conventional Everhart-Thornley detector.

You can't hide the bridges.

After witnessing a man commit suicide during residency, I struggled to reconcile the trauma itself, my own competence, and multiple boundary issues I was exploring as a newly minted doctor. My powerlessness in the face of inevitability challenged my sense of capability to fulfill the very calling that brought me into medicine in the beginning-to help fix important problems in the lives of my patients. In the aftermath, I chose to remain connected to the experience in the way I honor him still today.

Health is primary: Family medicine for America's health.

PURPOSE: More than a decade ago the American Academy of Family Physicians, American Academy of Family Physicians Foundation, American Board of Family Medicine, Association of Departments of Family Medicine, Association of Family Practice Residency Directors, North American Primary Care Research Group, and Society of Teachers of Family Medicine came together in the Future of Family Medicine (FFM) to launch a series of strategic efforts to "renew the specialty to meet the needs of people and society," some of which bore important fruit. Family Medicine for America's Health was launched in 2013 to revisit the role of family medicine in view of these changes and to position family medicine with new strategic and communication plans to create better health, better health care, and lower cost for patients and communities (the Triple Aim). METHODS: Family Medicine for America's Health was preceded and guided by the development of a family physician role definition. A consulting group facilitated systematic strategic plan development over 9 months that included key informant interviews, formal stakeholder surveys, future scenario testing, a retreat for family medicine organizations and stakeholder representatives to review strategy options, further strategy refinement, and finally a formal strategic plan with draft tactics and design for an implementation plan. A second communications consulting group surveyed diverse stakeholders in coordination with strategic planning to develop a communication plan. The American College of Osteopathic Family Physicians joined the effort, and students, residents, and young physicians were included. RESULTS: The core strategies identified include working to ensure broad access to sustained, primary care relationships; accountability for increasing primary care value in terms of cost and quality; a commitment to helping reduce health care disparities; moving to comprehensive payment and away from fee-for-service; transformation of training; technology to support effective care; improving research underpinning primary care; and actively engaging patients, policy makers, and payers to develop an understanding of the value of primary care. The communications plan, called Health is Primary, will complement these strategies. Eight family medicine organizations have pledged nearly $20 million and committed representatives to a multiyear implementation team that will coordinate these plans in a much more systematic way than occurred with FFM. CONCLUSIONS: Family Medicine for America's Health is a new commitment by 8 family medicine organizations to strategically align work to improve practice models, payment, technology, workforce and education, and research to support the Triple Aim. It is also a humble invitation to patients and to clinical and policy partners to collaborate in making family medicine even more effective.

The residential segregation of detailed Hispanic and Asian groups in the United States: 1980-2010.

BACKGROUND: Racial and ethnic diversity continues to grow in communities across the United States, raising questions about the extent to which different ethnic groups will become residentially integrated. OBJECTIVE: While a number of studies have examined the residential patterns of pan-ethnic groups, our goal is to examine the segregation of several Asian and Hispanic ethnic groups - Cubans, Dominicans, Mexicans, Puerto Ricans, Salvadorans, Asian Indians, Chinese, Filipinos, Japanese, Koreans, and Vietnamese. We gauge the segregation of each group from several alternative reference groups using two measures over the 1980 to 2010 period. RESULTS: We find that the dissimilarity of Hispanics and Asians from other groups generally held steady or declined, though, because most Hispanic and Asian groups are growing, interaction with Whites also often declined. Our analyses also indicate that pan-ethnic segregation indexes do not always capture the experience of specific groups. Among Hispanics, Mexicans are typically less residentially segregated (as measured using the dissimilarity index) from Whites, Blacks, Asians, and other Hispanics than are other Hispanic-origin groups. Among Asian ethnic groups, Japanese and Filipinos tend to have lower levels of dissimilarity from Whites, Blacks, and Hispanics than other Asian groups. Examining different dimensions of segregation also indicates that dissimilarity scores alone often do not capture to what extent various ethnic groups are actually sharing neighborhoods with each other. Finally, color lines vary across groups in some important ways, even as the dominant trend has been toward reduced racial and ethnic residential segregation over time. CONCLUSIONS: The overarching trend is that ethnic groups are becoming more residentially integrated, suggestive of assimilation, though there is significant variation across ethnic groups.