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The creation of undesirable (soggy) sauerkraut resulted in the loss of $1,000,000 worth of organic sauerkraut in 2022, which prompted a multistep investigation of the cause and potential solution. The cause of this condition has been previously reported as unique fermentation conditions and the lack of key trace nutrients essential for cabbage (Brassica oleracea var. capitata) cell wall integrity. Because the condition was limited to organic sauerkraut in 2022, this investigation initially focused on differences in fermentation conditions between organic and conventional sauerkraut. No differences in fermentation conditions accounted for the condition; therefore, attention was focused on analyzing the mineral content of cabbage grown for sauerkraut production that pinpointed a deficiency in critical micronutrients such as iron, copper, manganese, boron, and zinc. This deficiency was traced to the use of poultry manure that was contaminated with glyphosate residue from conventionally fed turkeys and chickens that consumed genetically engineered (GE) feed and used as the fertilizer for organic cabbage production. The presence of glyphosate, a potent mineral chelator and antibiotic, was identified as a significant factor that impairs the absorption and physiological function of essential minerals in the shikimate metabolic pathway whereby cell walls and lignin are produced, thus compromising the structural quality of the sauerkraut. After this discovery, the study progressed to evaluate various remediation strategies aimed at eliminating glyphosate from the soil and restoring nutrient uptake. Corn grain and silage were selected as the test crops for this phase. Among the tested remediation solutions were raw sauerkraut juice containing Lactobacillus plantarum, which is reported to degrade glyphosate in the rumen of dairy cows and two patented proprietary microbial mixtures, PB027 and PB027SK, that degrade glyphosate by all three of the known metabolic pathways. These treatments were specifically formulated to degrade residual glyphosate in the soil. The results showed that these interventions could reduce soil glyphosate levels by 80% to 90% within 6 to 7 months to significantly enhance both the yield and quality of corn grain and silage. The increase in corn grain yield from glyphosate degradation on the Shiocton silt loam soil was 907.89 kg·ha-1 (13.5 bushels/acre). The increase in yield on the irrigated Kidder sandy loam soil was quantified at 726.31 kg·ha-1 (10.8 bushels/acre) for corn grain and 6.62 t·ha-1 (2.68 t/acre) for silage, with an additional improvement in silage feed quality beneficial for milk production. The findings underscore the importance of addressing both micronutrient sufficiency and glyphosate residue in soil to ensure the optimal growth of cabbage and the quality of sauerkraut produced. By successfully identifying manure as a subtle source of nutrient immobilization and implementing effective soil remediation techniques, this research highlights a clear path forward for improving crop yield and quality to ultimately enhance the structural integrity and consumer acceptance of sauerkraut. This study has broader applications for the nutritional content and crop yields of many organic crops that use conventional poultry and animal manures that may contain glyphosate in desiccated plant tissues or GE feeding operations. [ABSTRACT FROM AUTHOR]

Objective: Shared decision making is important when decisions are preference sensitive, as in incurable cancer. A prerequisite for shared decision making is health literacy, which is essential to facilitate good understanding of an individual's current situation, the decision to be made, and the options available to them. This study sought to learn about the challenges for shared decision making faced by patients with incurable cancer and health literacy difficulties. Methods: Semi-structured telephone and video interviews were used to collect data on participants' experiences, decision making, and challenges faced. Study procedures followed health literacy principles, with information offered in various formats to suit individuals' preferences, the use of a verbal consent process, and flexibility in whether interviews were conducted over telephone or video call. Data were analysed using Framework Analysis (Ritchie et al. 2003), with initial verbatim transcription of interviews, iterative development of the analysis framework, indexing using Nvivo 12 software and summarising of the data before systematic categorisation and development of final themes. Results: Twenty participants (aged 31–80, of whom 13 male) with a variety of cancers (including breast, central nervous system, gastrointestinal, gynaecological, lung, head and neck, and urological) and experience of a range of treatments were interviewed. Seven themes were identified, including: supportive staff in an imperfect system, additional pressure from COVID-19, in the expert's hands, treatment not so bad, emotional hurdles, accessing information to further understanding and wanting to be a good patient. Conclusion: In order to support patients with incurable cancer and health literacy difficulties to become involved in decisions about their care, we must address the emotional, social and informational challenges they face. Recommendations for achieving this include addressing peoples' emotional needs, facilitating control over information, developing a partnership, involving others, and organisational changes. [ABSTRACT FROM AUTHOR]

Objective To measure univariate and covariate‐adjusted trends in children's mental health‐related emergency department (MH‐ED) use across geographically diverse areas of the U.S. during the first wave of the Coronavirus‐2019 (COVID‐19) pandemic. Method This is a retrospective, cross‐sectional cohort study using electronic health records from four academic health systems, comparing percent volume change and adjusted risk of child MH‐ED visits among children aged 3–17 years, matched on 36‐week (3/18/19–11/25/19 vs. 3/16/20–11/22/20) and 12‐week seasonal time intervals. Adjusted incidence rate ratios (IRR) were calculated using multivariate Poisson regression. Results Visits declined during spring‐fall 2020 (n = 3892 vs. n = 5228, −25.5%) and during spring (n = 1051 vs. n = 1839, −42.8%), summer (n = 1430 vs. n = 1469, −2.6%), and fall (n = 1411 vs. n = 1920, −26.5%), compared with 2019. There were greater declines among males (28.2% vs. females −22.9%), children 6–12‐year (−28.6% vs. −25.9% for 3–5 years and −22.9% for 13–17 years), and Black children (−34.8% vs. −17.7% to −24.9%). Visits also declined for developmental disorders (−17.0%) and childhood‐onset disorders (e.g., attention deficit and hyperactivity disorders; −18.0%). During summer‐fall 2020, suicide‐related visits rose (summer +29.8%, fall +20.4%), but were not significantly elevated from 2019 when controlling for demographic shifts. In contrast, MH‐ED use during spring‐fall 2020 was significantly reduced for intellectual disabilities (IRR 0.62 [95% CI 0.47–0.86]), developmental disorders (IRR 0.71 [0.54–0.92]), and childhood‐onset disorders (IRR 0.74 [0.56–0.97]). Conclusions The early pandemic brought overall declines in child MH‐ED use alongside co‐occurring demographic and diagnostic shifts. Children vulnerable to missed detection during instructional disruptions experienced disproportionate declines, suggesting need for future longitudinal research in this population.

Abstract Background Open online forums like Reddit provide an opportunity to quantitatively examine COVID-19 vaccine perceptions early in the vaccine timeline. We examine COVID-19 misinformation on Reddit following vaccine scientific announcements, in the initial phases of the vaccine timeline. Methods We collected all posts on Reddit (reddit.com) from January 1 2020 - December 14 2020 (n=266,840) that contained both COVID-19 and vaccine-related keywords. We used topic modeling to understand changes in word prevalence within topics after the release of vaccine trial data. Social network analysis was also conducted to determine the relationship between Reddit communities (subreddits) that shared COVID-19 vaccine posts, and the movement of posts between subreddits. Results There was an association between a Pfizer press release reporting 90% efficacy and increased discussion on vaccine misinformation. We observed an association between Johnson and Johnson temporarily halting its vaccine trials and reduced misinformation. We found that information skeptical of vaccination was first posted in a subreddit (r/Coronavirus) which favored accurate information and then reposted in subreddits associated with antivaccine beliefs and conspiracy theories (e.g. conspiracy, NoNewNormal). Conclusions Our findings can inform the development of interventions where individuals determine the accuracy of vaccine information, and communications campaigns to improve COVID-19 vaccine perceptions, early in the vaccine timeline. Such efforts can increase individual- and population-level awareness of accurate and scientifically sound information regarding vaccines and thereby improve attitudes about vaccines, especially in the early phases of vaccine roll-out. Further research is needed to understand how social media can contribute to COVID-19 vaccination services.

ObjectiveThis study aimed to develop and validate predictive models using electronic health records (EHR) data to determine whether hospitalized COVID-19-positive patients would be admitted to alternative medical care or discharged home.MethodsWe conducted a retrospective cohort study using deidentified data from the University of Florida Health Integrated Data Repository. The study included 1,578 adult patients (≥18 years) who tested positive for COVID-19 while hospitalized, comprising 960 (60.8%) female patients with a mean (SD) age of 51.86 (18.49) years and 618 (39.2%) male patients with a mean (SD) age of 54.35 (18.48) years. Machine learning (ML) model training involved cross-validation to assess their performance in predicting patient disposition.ResultsWe developed and validated six supervised ML-based prediction models (logistic regression, Gaussian Naïve Bayes, k-nearest neighbors, decision trees, random forest, and support vector machine classifier) to predict patient discharge status. The models were evaluated based on the area under the receiver operating characteristic curve (ROC-AUC), precision, accuracy, F1 score, and Brier score. The random forest classifier exhibited the highest performance, achieving an accuracy of 0.84 and an AUC of 0.72. Logistic regression (accuracy: 0.85, AUC: 0.71), k-nearest neighbor (accuracy: 0.84, AUC: 0.63), decision tree (accuracy: 0.84, AUC: 0.61), Gaussian Naïve Bayes (accuracy: 0.84, AUC: 0.66), and support vector machine classifier (accuracy: 0.84, AUC: 0.67) also demonstrated valuable predictive capabilities.SignificanceThis study's findings are crucial for efficiently allocating healthcare resources during pandemics like COVID-19. By harnessing ML techniques and EHR data, we can create predictive tools to identify patients at greater risk of severe symptoms based on their medical histories. The models developed here serve as a foundation for expanding the toolkit available to healthcare professionals and organizations. Additionally, explainable ML methods, such as Shapley Additive Explanations, aid in uncovering underlying data features that inform healthcare decision-making processes.

Abstract Objective: This study aims to develop a generalizable architecture for enhancing an enterprise data warehouse for research (EDW4R) with results from a natural language processing (NLP) model, which allows discrete data derived from clinical notes to be made broadly available for research use without need for NLP expertise. The study also quantifies the additional value that information extracted from clinical narratives brings to EDW4R. Materials and methods: Clinical notes written during one month at an academic health center were used to evaluate the performance of an existing NLP model and to quantify its value added to the structured data. Manual review was utilized for performance analysis. The architecture for enhancing the EDW4R is described in detail to enable reproducibility. Results: Two weeks were needed to enhance EDW4R with data from 250 million clinical notes. NLP generated 16 and 39% increase in data availability for two variables. Discussion: Our architecture is highly generalizable to a new NLP model. The positive predictive value obtained by an independent team showed only slightly lower NLP performance than the values reported by the NLP developers. The NLP showed significant value added to data already available in structured format. Conclusion: Given the value added by data extracted using NLP, it is important to enhance EDW4R with these data to enable research teams without NLP expertise to benefit from value added by NLP models.

Objective: Quality of physician consultations are best assessed via direct observation, but require intensive in-clinic research staffing. To evaluate physician consultation quality remotely, we pilot tested the feasibility of parents using their personal mobile phones to facilitate audio recordings of pediatric visits. Methods: Across four academic pediatric primary care clinics, we invited all physicians with a patient panel (n = 20). For participating physicians, we identified scheduled patients from medical records. We invited parents to participate via text message and phone calls. During their adolescent's appointment, parents used their mobile phone to connect to Zoom for remote research staff to audio record. Results: In Spring 2021, five of 20 (25%) physicians participated. During a nine-week period, we invited parents of all 54 patients seen by participating physicians of which 15 (28%) completed adult consent and adolescent assent and 10 (19%) participated. For 9 recordings, at least 45% of the conversation was audible. Conclusions: It was feasible and acceptable to directly observe physician consultations virtually with Zoom, although participation rates and potentially audio quality were lower. Innovation: Patients used their cellular phone calling features to connect to Zoom where research staff audio-recorded their physician consultation to evaluate communication quality.

Objective: At a large public university, we aimed to evaluate an intervention designed to increase serogroup B meningococcal (MenB) vaccine uptake and awareness. Methods: Using a pretest-posttest design with a double posttest, we evaluated an intervention conducted by a local foundation and the Florida Department of Health that distributed MenB vaccine on campus and conducted an educational campaign. Prior to intervention activities, we recruited students to complete a survey about their MenB knowledge and attitudes. For survey participants who provided contact information, we sent two follow-up surveys and assessed MenB vaccine records. We used chi-square tests, adjusted for nonindependence, to compare preintervention to postintervention (three-month and one-year) vaccination and attitudes. Results: Among the 686 students with accessible vaccine records, MenB vaccine initiation increased 9% (from 24% to 33%) and completion increased 8% (from 13% to 21%) from before the intervention to one year after the intervention. When restricting to students who completed the relevant follow-up surveys, the percentage of students who heard of the MenB vaccine increased by 15% (p > .001) from before the intervention to three months after (n = 188 students) and maintained a 10% increase (p > .001) one year after the intervention (n = 261 students). Among students that heard of the MenB vaccine, the percentage of students who thought they needed the MenB vaccine even though they received the MenACWY increased 14% (p = .03) by the three-month postintervention survey and up to 18% by the one-year follow-up (p = .002). Conclusions: A university-wide, on-campus vaccination and educational campaign increased college students’ MenB vaccine initiation, completion, and knowledge. Clinicaltrials.gov ID: NCT02975596.

To be effective, palliative care education interventions need to be informed, among others, by evidence and best practices related to curriculum development and design. Designing palliative care continuing professional development (CPD) courses for large-scale, national deployment requires decisions about various design elements, including competencies and learning objectives to be addressed, overall learning approaches, content, and courseware material. Designing for interprofessional education (IPE) adds additional design complexity. Several design elements present themselves in the form of polarities, resulting in educators having to make choices or compromises between the various options. This article describes the learning design decisions that underpin Pallium Canada's interprofessional Learning Essential Approaches to Palliative Care (LEAP) courses. Social constructivism provides a foundational starting point for LEAP course design, as it lends itself well to both CPD and IPE. We then explore design polarities that apply to the LEAP courseware development. These include, among others, which professions to target and how to best support interprofessional learning, class sizes, course length and content volume, courseware flexibility, regional adaptations, facilitator criteria, and learning methods. In some cases, compromises have had to be made between optimal perfect design and pragmatism.