High-precision stereotactic irradiation for focal drug-resistant epilepsy versus standard treatment: a randomized waitlist-controlled trial (the PRECISION trial).

INTRODUCTION: The standard treatment for patients with focal drug-resistant epilepsy (DRE) who are not eligible for open brain surgery is the continuation of anti-seizure medication (ASM) and neuromodulation. This treatment does not cure epilepsy but only decreases severity. The PRECISION trial offers a non-invasive, possibly curative intervention for these patients, which consist of a single stereotactic radiotherapy (SRT) treatment. Previous studies have shown promising results of SRT in this patient population. Nevertheless, this intervention is not yet available and reimbursed in the Netherlands. We hypothesize that: SRT is a superior treatment option compared to palliative standard of care, for patients with focal DRE, not eligible for open surgery, resulting in a higher reduction of seizure frequency (with 50% of the patients reaching a 75% seizure frequency reduction at 2 years follow-up). METHODS: In this waitlist-controlled phase 3 clinical trial, participants are randomly assigned in a 1:1 ratio to either receive SRT as the intervention, while the standard treatments consist of ASM continuation and neuromodulation. After 2-year follow-up, patients randomized for the standard treatment (waitlist-control group) are offered SRT. Patients aged ≥ 18 years with focal DRE and a pretreatment defined epileptogenic zone (EZ) not eligible for open surgery will be included. The intervention is a LINAC-based single fraction (24 Gy) SRT treatment. The target volume is defined as the epileptogenic zone (EZ) on all (non) invasive examinations. The seizure frequency will be monitored on a daily basis using an electronic diary and an automatic seizure detection system during the night. Potential side effects are evaluated using advanced MRI, cognitive evaluation, Common Toxicity Criteria, and patient-reported outcome questionnaires. In addition, the cost-effectiveness of the SRT treatment will be evaluated. DISCUSSION: This is the first randomized trial comparing SRT with standard of care in patients with DRE, non-eligible for open surgery. The primary objective is to determine whether SRT significantly reduces the seizure frequency 2 years after treatment. The results of this trial can influence the current clinical practice and medical cost reimbursement in the Netherlands for patients with focal DRE who are not eligible for open surgery, providing a non-invasive curative treatment option. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT05182437. Registered on September 27, 2021.

Clinical implementation of standardized neurocognitive assessment before and after radiation to the brain.

Background: Radiotherapy induced impairment of cognitive function can lead to a reduced quality of life. The aim of this study was to describe the implementation and compliance of standardized neurocognitive assessment. In addition, the first results of cognitive changes for patients receiving a radiation dose to the brain are described. Materials and methods: Patients that received radiation dose to the brain (neuro, head and neck and prophylactic cranial irradiation between April-2019 and Dec-2021 were included. Three neuro cognitive tests were performed a verbal learning and memory test, the Hopkins Verbal Learning Test; a verbal fluency test, the Controlled Oral Word Association Test and a speed and cognitive flexibility test, the Trail Making Test A&B. Tests were performed before the start of radiation, 6 months (6 m) and 1 year (1y) after irradiation. The Reliable Change Index (RCI) between baseline and follow-up was calculated using reference data from literature. Results: 644 patients performed the neurocognitive tests at baseline, 346 at 6 months and 205 at 1y after RT, with compliance rates of 90.4%, 85.6%, and 75.3%, respectively. Reasons for non-compliance were: 1. Patient did not attend appointment (49%), 2. Patient was unable to perform the test due to illness (12%), 3. Patient refused the test (8 %), 4. Various causes, (31%). A semi-automated analysis was developed to evaluate the test results. In total, 26% of patients showed a significant decline in at least one of variables at 1y and 11% on at least 2 variables at 1y. However, an increase in cognitive performance was observed in 49% (≥1 variable) and 22% (≥2 variables). Conclusion: Standardized neurocognitive testing within the radiotherapy clinic was successfully implemented, with a high patient compliance. A semi-automatic method to evaluate cognitive changes after treatment was defined. Data collection is ongoing, long term follow-up (up to 5 years after treatment) and dose-effect analysis will be performed.

Estimating the energetic cost of feeding excess dietary nitrogen to dairy cows.

Feeding N in excess of requirement could require the use of additional energy to metabolize excess protein, and to synthesize and excrete urea; however, the amount and fate of this energy is unknown. Little progress has been made on this topic in recent decades, so an extension of work published in 1970 was conducted to quantify the effect of excess N on ruminant energetics. In part 1 of this study, the results of previous work were replicated using a simple linear regression to estimate the effect of excess N on energy balance. In part 2, mixed model methodology and a larger data set were used to improve upon the previously reported linear regression methods. In part 3, heat production, retained energy, and milk energy replaced the composite energy balance variable previously proposed as the dependent variable to narrow the effect of excess N. In addition, rumen degradable and undegradable protein intakes were estimated using table values and included as covariates in part 3. Excess N had opposite and approximately equal effects on heat production (+4.1 to +7.6 kcal/g of excess N) and retained energy (-4.2 to -6.6 kcal/g of excess N) but had a larger negative effect on milk gross energy (-52 to -68 kcal/g of excess N). The results suggest that feeding excess N increases heat production, but more investigation is required to determine why excess N has such a large effect on milk gross energy production.

A practical approach to programmatic assessment design.

Assessment of complex tasks integrating several competencies calls for a programmatic design approach. As single instruments do not provide the information required to reach a robust judgment of integral performance, 73 guidelines for programmatic assessment design were developed. When simultaneously applying these interrelated guidelines, it is challenging to keep a clear overview of all assessment activities. The goal of this study was to provide practical support for applying a programmatic approach to assessment design, not bound to any specific educational paradigm. The guidelines were first applied in a postgraduate medical training setting, and a process analysis was conducted. This resulted in the identification of four steps for programmatic assessment design: evaluation, contextualisation, prioritisation and justification. Firstly, the (re)design process starts with sufficiently detailing the assessment environment and formulating the principal purpose. Key stakeholders with sufficient (assessment) expertise need to be involved in the analysis of strengths and weaknesses and identification of developmental needs. Central governance is essential to balance efforts and stakes with the principal purpose and decide on prioritisation of design decisions and selection of relevant guidelines. Finally, justification of assessment design decisions, quality assurance and external accountability close the loop, to ensure sound underpinning and continuous improvement of the assessment programme.

Cost-effectiveness of feeding strategies to reduce greenhouse gas emissions from dairy farming.

The objective of this paper was to evaluate the cost-effectiveness of 3 feeding strategies to reduce enteric CH4 production in dairy cows by calculating the effect on labor income at the farm level and on greenhouse gas (GHG) emissions at the chain level (i.e., from production of farm inputs to the farm gate). Strategies included were (1) dietary supplementation of an extruded linseed product (56% linseed; 1kg/cow per day in summer and 2kg/cow per day in winter), (2) dietary supplementation of a nitrate source (75% nitrate; 1% of dry matter intake), and (3) reducing the maturity stage of grass and grass silage (grazing at 1,400 instead of 1,700kg of dry matter/ha and harvesting at 3,000 instead of 3,500kg of dry matter/ha). A dairy farm linear programing model was used to define an average Dutch dairy farm on sandy soil without a predefined feeding strategy (reference situation). Subsequently, 1 of the 3 feeding strategies was implemented and the model was optimized again to determine the new economically optimal farm situation. Enteric CH4 production in the reference situation and after implementing the strategies was calculated based on a mechanistic model for enteric CH4 and empirical formulas explaining the effect of fat and nitrate supplementation on enteric CH4 production. Other GHG emissions along the chain were calculated using life cycle assessment. Total GHG emissions in the reference situation added up to 840kg of CO2 equivalents (CO2e) per t of fat- and protein-corrected milk (FPCM) and yearly labor income of €42,605. Supplementation of the extruded linseed product reduced emissions by 9kg of CO2e/t of FPCM and labor income by €16,041; supplementation of the dietary nitrate source reduced emissions by 32kg of CO2e/t of FPCM and labor income by €5,463; reducing the maturity stage of grass and grass silage reduced emissions by 11kg of CO2e/t of FPCM and labor income by €463. Of the 3 strategies, reducing grass maturity was the most cost-effective (€57/t of CO2e compared with €241/t of CO2e for nitrate supplementation and €2,594/t of CO2e for linseed supplementation) and had the greatest potential to be used in practice because the additional costs were low.

A model for programmatic assessment fit for purpose.

We propose a model for programmatic assessment in action, which simultaneously optimises assessment for learning and assessment for decision making about learner progress. This model is based on a set of assessment principles that are interpreted from empirical research. It specifies cycles of training, assessment and learner support activities that are complemented by intermediate and final moments of evaluation on aggregated assessment data points. A key principle is that individual data points are maximised for learning and feedback value, whereas high-stake decisions are based on the aggregation of many data points. Expert judgement plays an important role in the programme. Fundamental is the notion of sampling and bias reduction to deal with the inevitable subjectivity of this type of judgement. Bias reduction is further sought in procedural assessment strategies derived from criteria for qualitative research. We discuss a number of challenges and opportunities around the proposed model. One of its prime virtues is that it enables assessment to move, beyond the dominant psychometric discourse with its focus on individual instruments, towards a systems approach to assessment design underpinned by empirically grounded theory.

A multi-level hierarchic Markov process with Bayesian updating for herd optimization and simulation in dairy cattle.

Herd optimization models that determine economically optimal insemination and replacement decisions are valuable research tools to study various aspects of farming systems. The aim of this study was to develop a herd optimization and simulation model for dairy cattle. The model determines economically optimal insemination and replacement decisions for individual cows and simulates whole-herd results that follow from optimal decisions. The optimization problem was formulated as a multi-level hierarchic Markov process, and a state space model with Bayesian updating was applied to model variation in milk yield. Methodological developments were incorporated in 2 main aspects. First, we introduced an additional level to the model hierarchy to obtain a more tractable and efficient structure. Second, we included a recently developed cattle feed intake model. In addition to methodological developments, new parameters were used in the state space model and other biological functions. Results were generated for Dutch farming conditions, and outcomes were in line with actual herd performance in the Netherlands. Optimal culling decisions were sensitive to variation in milk yield but insensitive to energy requirements for maintenance and feed intake capacity. We anticipate that the model will be applied in research and extension.

A new framework for designing programmes of assessment.

Research on assessment in medical education has strongly focused on individual measurement instruments and their psychometric quality. Without detracting from the value of this research, such an approach is not sufficient to high quality assessment of competence as a whole. A programmatic approach is advocated which presupposes criteria for designing comprehensive assessment programmes and for assuring their quality. The paucity of research with relevance to programmatic assessment, and especially its development, prompted us to embark on a research project to develop design principles for programmes of assessment. We conducted focus group interviews to explore the experiences and views of nine assessment experts concerning good practices and new ideas about theoretical and practical issues in programmes of assessment. The discussion was analysed, mapping all aspects relevant for design onto a framework, which was iteratively adjusted to fit the data until saturation was reached. The overarching framework for designing programmes of assessment consists of six assessment programme dimensions: Goals, Programme in Action, Support, Documenting, Improving and Accounting. The model described in this paper can help to frame programmes of assessment; it not only provides a common language, but also a comprehensive picture of the dimensions to be covered when formulating design principles. It helps identifying areas concerning assessment in which ample research and development has been done. But, more importantly, it also helps to detect underserved areas. A guiding principle in design of assessment programmes is fitness for purpose. High quality assessment can only be defined in terms of its goals.

Study of the lactation curve in dairy cattle on farms in central Mexico.

Accurate knowledge of lactation curves has an important relevance to management and research of dairy production systems. A number of equations have been proposed to describe the lactation curve, the most widely applied being the gamma equation. The objective of this work was to compare and evaluate candidate functions for their predictive ability in describing lactation curves from central Mexican dairy cows reared under 2 contrasting management systems. Five equations were considered: Gaines (exponential decay), Wood (gamma equation), Rook (Michaelis-Menten xexponential), and 2 more mechanistic ones (Dijkstra and Pollott). A database consisting of 701 and 1283 records of cows in small-scale and intensive systems, respectively, was used in the analysis. Before analysis, the database was divided into 6 groups representing first, second, and third and higher parity cows in both systems. In all cases except second and above parity cows in small-scale systems, all models improved on the Gaines equation. The Wood equation explained much of the variation, but its parameters do not have direct biological interpretation. Although the Rook equation fitted the data well, some of the parameter estimates were not significant. The Dijkstra equation consistently gave better predictions, and its parameters were usually statistically significant and lend themselves to physiological interpretation. As such, the differences between systems and parity could be explained due to variations in theoretical initial milk production at parturition, specific rates of secretory cell proliferation and death, and rate of decay, all of which are parameters in the model. The Pollott equation, although containing the most biology, was found to be over-parameterized and resulted in nonsignificant parameter estimates. For central Mexican dairy cows, the Dijkstra equation was the best option to use in describing the lactation curve.

SIMPLE: assessment of non-point phosphorus pollution from agricultural land to surface waters by means of a new methodology.

In the past, environmental Phosphorus (P) parameters like soil P indices have been used to catogorize the potential risk of P losses from agricultural land. In order to assess the actual risk of P pollution of groundwater and surface waters, dynamic process oriented soil and water quality models have been frequently used. Recently, an approximating model for phosphorus, called SIMPLE, has been developed. This model approximates the output from a complex dynamic water quality model. The approximating model is called a metamodel. This simple P-model proves to be a powerful tool for quick assessment of the risk of P pollution from agricultural land to surface waters.

A dynamic model of N metabolism in the lactating dairy cow and an assessment of impact of N excretion on the environment.

Improving N utilization in dairy cows and especially reducing N output in excreta is desirable due to global concerns of agricultural contribution of N to environmental pollution, particularly as ammonia. Data from five N balance experiments were used to develop a dynamic model that was evaluated with independent data. Model predictions of feces, urine, and milk outputs were close to observed values. Statistical analysis showed that 96% of mean square prediction error for feces and urine N output predictions was due to random variation. However, the model tends to overpredict milk N output, especially at higher N intake levels. Evaluation of model predictions for independent experimental observations from Agricultural Development Advisory Service at Bridgets (U.K.) showed good agreement between predicted and observed urine N output (95% due to random variation). However, there was a slight underprediction for fecal N output (14% mean square prediction error due to bias) and overprediction of milk N output (22% of mean square prediction error due to bias). The model predictions of N outputs in excreta were sensitive to changes in energy concentration of the diet. Dietary protein degradability had only a small influence on predicted fecal N output. However, the model was sensitive in its predictions of urine N when protein degradability was varied. Application of the model to assess reduction in ammonia emissions from dairy cows showed that increasing the energy concentration could potentially reduce ammonia emissions by up to 25% per cow. Similarly, reducing CP concentration in the diet to about 16% could reduce ammonia production by 20% and lower degradability of CP to match microbial requirement by 19% per cow. The model is a first step toward a mechanistic approach of nutrient modeling, and it is a valuable method for predicting N excretions and estimating N emissions from dairy systems.

Functional assessment of sciatic nerve reconstruction: biodegradable poly (DLLA-epsilon-CL) nerve guides versus autologous nerve grafts.

The aim of this study was to compare functional nerve recovery after reconstruction with a biodegradable p(DLLA-epsilon-CL) nerve guide filled with modified denatured muscle tissue (MDMT), or an autologous nerve graft. We evaluated nerve recovery using walking track analysis (measurement of the sciatic function index [SFI]) and electrostimulation tests. Functional nerve recovery after reconstruction with a biodegradable p(DLLA-epsilon-CL) nerve guide filled with MDMT was faster when compared with nerve reconstruction using an autologous nerve graft. We conclude that in case of a short nerve gap in the rat, reconstruction can best be carried out using a p(DLLA-epsilon-CL) biodegradable nerve guide filled with MDMT.

Transesophageal color flow Doppler mapping in the assessment of native mitral valvular regurgitation: comparison with left ventricular angiography.

Transesophageal echocardiography (TEE) was performed within 24 hours after cardiac catheterization in 45 patients for assessment of native mitral valvular regurgitation. Color flow mapping was used in evaluating systolic regurgitant jet sizes. A jet demonstrated by TEE was 96% sensitive and 44% specific for angiographic mitral regurgitation. The presence of angiographic mitral regurgitation was best predicted by (single measurement) (1) a holosystolic jet, (2) a jet length greater than 2.5 cm, and (3) a jet area greater than 2 cm2. Severe angiographic mitral regurgitation (grades 3 and 4) was best predicted by (single measurement) (1) a jet area greater than 5 cm2, and (2) a jet length greater than 4 cm. It is concluded that the assessment of angiographic mitral regurgitation by TEE is improved by the measurement of these jet parameters, which have a high sensitivity and higher specificity than the presence of a jet alone. Furthermore, with TEE one is able to differentiate severe (grades 3 and 4) from absent or mild mitral regurgitation (grades 0, 1, and 2).