Myocardial Infarction

Gender bias in myocardial infarction

What are Utah farmers' market shoppers willing to do to protect local agriculture?

Title from PDF of title page (University of Missouri--Columbia, viewed on March 30, 2011).The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Thesis advisor: Bill Allen.M.A. University of Missouri--Columbia 2010.The purpose of this study is to determine what actions Utah farmers' market shoppers would be willing to take to protect their supply of local food: agriculture. This qualitative study used in-depth interviews of 32 farmers' market shoppers in Salt Lake City, Utah to determine their perceptions of local agriculture and whether they would consider taking any action to protect local farmland. The study found that they were highly supportive of small-scale farmers who supply fruits and vegetables to farmers markets. The shoppers' most frequently stated actions would be to join an education/outreach program as well as continue to shop at farmers markets. Other actions mentioned were: Work politically to educate other Utahns, help people understand the importance of locally grown food, and lobby state and federal legislators in favor of laws that benefitted small local farming.Includes bibliographical reference

ChatGPT provides inconsistent risk-stratification of patients with atraumatic chest pain

ChatGPT-4 is a large language model with promising healthcare applications. However, its ability to analyze complex clinical data and provide consistent results is poorly known. Compared to validated tools, this study evaluated ChatGPT-4's risk stratification of simulated patients with acute nontraumatic chest pain.Three datasets of simulated case studies were created: one based on the TIMI score variables, another on HEART score variables, and a third comprising 44 randomized variables related to non-traumatic chest pain presentations. ChatGPT-4 independently scored each dataset five times. Its risk scores were compared to calculated TIMI and HEART scores. A model trained on 44 clinical variables was evaluated for consistency.ChatGPT-4 showed a high correlation with TIMI and HEART scores (r = 0.898 and 0.928, respectively), but the distribution of individual risk assessments was broad. ChatGPT-4 gave a different risk 45-48% of the time for a fixed TIMI or HEART score. On the 44-variable model, a majority of the five ChatGPT-4 models agreed on a diagnosis category only 56% of the time, and risk scores were poorly correlated (r = 0.605).While ChatGPT-4 correlates closely with established risk stratification tools regarding mean scores, its inconsistency when presented with identical patient data on separate occasions raises concerns about its reliability. The findings suggest that while large language models like ChatGPT-4 hold promise for healthcare applications, further refinement and customization are necessary, particularly in the clinical risk assessment of atraumatic chest pain patients

Evaluation of the Striped Bass as a Pond-reared Food Fish

Two-day-old larvae of striped bass (Morone saxatilis) were trained to accept artificial feed. When the fish reached 10 g, 1080 were stocked in a 0.4-ha hatchery pond. The fish were stocked on 7 August 1976 and harvested 441 days later on 19 October 1977. They were fed daily through the fall of 1976 and again during the spring, summer, and fall of 1977. The fish stopped feeding in the fall when the water temperature fell to 7°C, and resumed feeding in the spring when the temperature reached 16°C. Once they began to feed, they fed well when the temperature was above 10°C, but poorly when the temperature was 29°C or higher. The fish were fed 291 of the 441 days during which they were held in the pond. The rate of growth was 2.03 g per fish per day; 980 kg/ha of striped bass were produced. Food conversion was 2.8 for the 85% of the population that ate the artificial feed. Survival was 91.8%

Influence of meteorological parameters on the distribution of precipitation across central Colorado mountains, The

May 1970.Includes bibliographical references.Sponsored by the National Science Foundation GA-11574

Efficacy of hemostatic matrix and microporous polysaccharide hemospheres

AbstractBackgroundMicroporous Polysaccharide Hemospheres (MPH) are a new plant-derived polysaccharide powder hemostat. Previous studies investigated MPH as a replacement to nonflowable hemostatic agents of different application techniques (e.g., oxidized cellulose, collagen); therefore, the purpose of this study was to determine if MPH is a surrogate for flowable hemostatic agents of similar handling and application techniques, specifically a flowable thrombin-gelatin hemostatic matrix.MethodsHemostatic efficacy was compared using a heparinized porcine abrasion model mimicking a capsular tear of a parenchymal organ. MPH (ARISTA, 1 g) and hemostatic matrix (Floseal, 1 mL) were applied, according to a randomized scheme, to paired hepatic abrasions (40 lesions per group). Hemostatic success, control of bleeding, and blood loss were assessed 2, 5, and 10 min after treatment. Hemostatic success and control of bleeding were analyzed using odds ratios and blood loss using mean differences.ResultsHemostatic matrix provided superior hemostatic success relative to MPH at 5 (odds ratio: 0.035, 95% confidence interval: 0.004–0.278) and 10 min (0.032, 0.007–0.150), provided superior control of bleeding at 5 (0.006, <0.001–0.037) and 10 min (0.009, 0.001–0.051), and had significantly less blood loss at 5 (mean difference: 0.3118 mL/min, 95% confidence interval: 0.0939–0.5296) and 10 min (0.5025, 0.2489–0.7561).ConclusionsThese findings corroborate other MPH investigations regarding its low-level efficacy and suggest that MPH is not an appropriate surrogate for hemostatic matrix despite similar application techniques. The lack of a procoagulant within MPH may likely be the reason for its lower efficacy and need for multiple applications