Start-Up Strategies for Beginning Farmers

Preliminary information from the U.S. 2002 Agricultural Census has recently been released. The chart groups U.S. census data for Nebraska farmers into three categories: under 34 years of age, 35 to 64 and over 65. The data indicates a 20 year trend of fewer farmers, older farmers and very few beginning farmers. A farmer is defined, for purposes of this census, as anyone producing or selling at least $1,000 of agricultural commodities annually. The average age of Nebraska farmers continues to rise. The average age in 1982 was 48.5 compared to 53.9 in 2002. The increase in average age is due to both an increase in the over 65 age group (8,777 in 1982 to 12,203* in 2002), as well as a decrease in the under 34 age group (13,436 in 1982 to 3,782* in 2002). Even with adjusting for the new calculation method adopted for the year 2002, which if applied to the 1997 census would have resulted in computing an additional 3,085 Nebraska farmers, the total number of farmers in the state also continues to decline. The adjusted number of younger farmers in the age group of 34 and under in the year 2002 is less than one-third the number in that category 20 years ago. There are obvious barriers to beginners such as high capital investment costs, narrowing profit margins and increased cost of family living. But are there strategies that can assist beginners that want to return to agriculture

Impact 2001

Index Competitive Agricultural Systems in a Global Economy ............................................................. 1 Safe and Secure Food and Fiber Systems ............................................................. 20 Healthy, Well-Nourished Population ............................................................. 28 Greater Harmony Between Agriculture and the Environment ............................................................. 38 Economic Development and Quality of Life for People and Communities ............................................................. 46 Society-Ready Graduates ............................................................. 5

Impact 2001

Index Competitive Agricultural Systems in a Global Economy ............................................................. 1 Safe and Secure Food and Fiber Systems ............................................................. 20 Healthy, Well-Nourished Population ............................................................. 28 Greater Harmony Between Agriculture and the Environment ............................................................. 38 Economic Development and Quality of Life for People and Communities ............................................................. 46 Society-Ready Graduates ............................................................. 5

Computed tomography–based pericoronary adipose tissue attenuation in patients undergoing TAVR: a novel method for risk assessment

Objectives This study aims to assess the attenuation of pericoronary adipose tissue (PCAT) surrounding the proximal right coronary artery (RCA) in patients with aortic stenosis (AS) and undergoing transcatheter aortic valve replacement (TAVR). RCA PCAT attenuation is a novel computed tomography (CT)–based marker for evaluating coronary inflammation. Coronary artery disease (CAD) in TAVR patients is common and usually evaluated prior to intervention. The most sensible screening method and consequential treatment approach are unclear and remain a matter of ceaseless discussion. Thus, interest remains for safe and low-demand predictive markers to identify patients at risk for adverse outcomes postaortic valve replacement. Methods This single-center retrospective study included patients receiving a standard planning CT scan prior to TAVR. Conventional CAD diagnostic tools, such as coronary artery calcium score and significant stenosis via invasive coronary angiography and coronary computed tomography angiography, were determined in addition to RCA PCAT attenuation using semiautomated software. These were assessed for their relationship with major adverse cardiovascular events (MACE) during a 24-month follow-up period. Results From a total of 62 patients (mean age: 82 ± 6.7 years), 15 (24.2%) patients experienced an event within the observation period, 10 of which were attributed to cardiovascular death. The mean RCA PCAT attenuation was higher in patients enduring MACE than that in those without an endpoint (−69.8 ± 7.5 vs. −74.6 ± 6.2, P = 0.02). Using a predefined cutoff of >−70.5 HU, 20 patients (32.3%) with high RCA PCAT attenuation were identified, nine (45%) of which met the endpoint within 2 years after TAVR. In a multivariate Cox regression model including conventional CAD diagnostic tools, RCA PCAT attenuation prevailed as the only marker with significant association with MACE (P = 0.02). After dichotomization of patients into high- and low-RCA PCAT attenuation groups, high attenuation was related to greater risk of MACE (hazard ration: 3.82, P = 0.011). Conclusion RCA PCAT attenuation appears to have predictive value also in a setting of concomitant AS in patients receiving TAVR. RCA PCAT attenuation was more reliable than conventional CAD diagnostic tools in identifying patients at risk for MACE

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study

BACKGROUND: Atherosclerotic plaque quantification from coronary CT angiography (CCTA) enables accurate assessment of coronary artery disease burden and prognosis. We sought to develop and validate a deep learning system for CCTA-derived measures of plaque volume and stenosis severity. METHODS: This international, multicentre study included nine cohorts of patients undergoing CCTA at 11 sites, who were assigned into training and test sets. Data were retrospectively collected on patients with a wide range of clinical presentations of coronary artery disease who underwent CCTA between Nov 18, 2010, and Jan 25, 2019. A novel deep learning convolutional neural network was trained to segment coronary plaque in 921 patients (5045 lesions). The deep learning network was then applied to an independent test set, which included an external validation cohort of 175 patients (1081 lesions) and 50 patients (84 lesions) assessed by intravascular ultrasound within 1 month of CCTA. We evaluated the prognostic value of deep learning-based plaque measurements for fatal or non-fatal myocardial infarction (our primary outcome) in 1611 patients from the prospective SCOT-HEART trial, assessed as dichotomous variables using multivariable Cox regression analysis, with adjustment for the ASSIGN clinical risk score. FINDINGS: In the overall test set, there was excellent or good agreement, respectively, between deep learning and expert reader measurements of total plaque volume (intraclass correlation coefficient [ICC] 0·964) and percent diameter stenosis (ICC 0·879; both p<0·0001). When compared with intravascular ultrasound, there was excellent agreement for deep learning total plaque volume (ICC 0·949) and minimal luminal area (ICC 0·904). The mean per-patient deep learning plaque analysis time was 5·65 s (SD 1·87) versus 25·66 min (6·79) taken by experts. Over a median follow-up of 4·7 years (IQR 4·0–5·7), myocardial infarction occurred in 41 (2·5%) of 1611 patients from the SCOT-HEART trial. A deep learning-based total plaque volume of 238·5 mm(3) or higher was associated with an increased risk of myocardial infarction (hazard ratio [HR] 5·36, 95% CI 1·70–16·86; p=0·0042) after adjustment for the presence of deep learning-based obstructive stenosis (HR 2·49, 1·07–5·50; p=0·0089) and the ASSIGN clinical risk score (HR 1·01, 0·99–1·04; p=0·35). INTERPRETATION: Our novel, externally validated deep learning system provides rapid measurements of plaque volume and stenosis severity from CCTA that agree closely with expert readers and intravascular ultrasound, and could have prognostic value for future myocardial infarction

Patient-specific myocardial infarction risk thresholds from AI-enabled coronary plaque analysis

Background: Plaque quantification from coronary computed tomography angiography (CTA) has emerged as a valuable predictor of cardiovascular risk. Deep learning (DL) can provide automated quantification of coronary plaque from CTA. We determined per-patient age and sex-specific distributions of DL-based plaque measurements and further evaluated their risk prediction for myocardial infarction in external samples.Methods: In this international, multicenter study of 2803 patients, a previously validated DL system was used to quantify coronary plaque from CTA. Age and sex-specific distributions of coronary plaque volume were determined from 956 patients undergoing CTA for stable coronary artery disease from 5 cohorts. Multicenter external samples were used to evaluate associations between coronary plaque percentiles and myocardial infarction.Results: Quantitative DL plaque volumes increased with age and were higher in male patients. In the combined external sample (n=1,847), patients in the ≥75th percentile of total plaque volume (unadjusted hazard ratio 2.65, 95% confidence interval 1.47-4.78, p=0.001) were at increased risk of myocardial infarction compared to patients below the 50th percentile. Similar relationships were seen for most plaque volumes and persisted in multivariable analyses adjusting for clinical characteristics, coronary artery calcium, stenosis and plaque volume, with adjusted hazard ratios ranging from 2.38 to 2.50 for patients in the ≥75th percentile of total plaque volume. Conclusions: Per-patient age and sex-specific distributions for deep learning-based coronary plaque volumes are strongly predictive of myocardial infarction, with the highest risk seen in patients with coronary plaque volumes in the ≥75th percentile.Keywords: Deep learning; coronary plaque; risk prediction; coronary CT Angiography; sex-specific analysis; myocardial infarction<br/

Decision Making During Stressful Times

Do you find yourself wondering why you can’t make those snap decisions like you use to? Do you ever wonder why you catch yourself second guessing your decisions more? It may be that stress has gotten to a level in your life that it is having a larger influence on you than you realize. Many factors have caused Nebraska’s farmers and ranchers to experience higher stress levels this year. These factors include the threat of war, the drought, low commodity prices, higher input costs, uncertainty with the federal farm programs, shortage of adequate livestock feed, prospects for a long winter and simply the high cost of living. Many of us are asking questions such as: Will there be enough money to make ends meet? How will I feed my livestock this winter? Will we be able to get operating loans from the bank again? Should I make adjustments in my operation? Should we consider quitting while we still have something left

Farm Business Succession and Estate Planning or “What you need to know before you go to see the attorney”

Nearly everyone agrees that it is important to plan for the future. Why, then, do less than half of all farmers and ranchers have an estate plan? Many will say it is just too complicated so it gets put off until…well, later or maybe never. Farm and ranch estate planning can involve some rather complicated concepts. Attorneys and other estate planning professionals spend a lifetime honing their skills and evaluating various estate planning options. Should a trust or a will be used? What about a corporation or an LLC? Should we have a durable power of attorney and an advanced medical directive? Most farmers and ranchers will never become experts in estate planning, nor do they want to. However, it can be very beneficial for producers to have answers to a few fundamental questions to get the process started

American Taxpayer Relief Act of 2012 Becomes Law

Many farmers and ranchers finally have an increased level of certainty regarding their federal estate and gift tax planning. After several years of worrisome temporary changes and “sun setting” unified credit exclusion amounts, the January 3, 2013 passage of the American Taxpayer Relief Act of 2012 has made permanent the federal estate tax and federal gift tax exclusion at the inflation adjusted amount of $5,000,000 per person or$10,000,000 per married couple. If Congress had failed to act, federal estate tax and federal gift tax exclusion amounts would have reverted back to $1,000,000 per person and federal estate tax rates would have gone up from 35 to 55 percent, which means that individual’s estates over$1,000,000 would have been required to pay a 55 percent tax on asset transfers on amounts over $1,000,000. With the increase in land values this would have created a serious tax consequence for many farmers and ranchers throughout the state