BACKGROUND:Optimal management of anaemia following surgery for colorectal cancer remains unclear. Peri-operative anaemia is common in patients undergoing resectional surgery for colorectal cancer. A significant amount of research has been conducted into the management of pre-operative anaemia; however, little work has investigated post-operative anaemia. We intended to investigate the facilitators of and barriers against the standardised correction of post-operative anaemia. These can aid in identifying optimum treatment for patients following surgery for colorectal cancer. METHODS:Four focus groups were held with 29 participants from a multidisciplinary panel of healthcare professionals from two different NHS hospital sites in the UK. The discussions were audio recorded and underwent professional transcription. Transcripts were checked against recordings before undergoing thematic analysis using a realist approach. RESULTS:Four themes were identified. The key barriers to standardised post-operative anaemia correction were a lack of protocoled guidelines or a defined pathway, insufficient education and training, and systemic barriers, such as financial drivers and drug availability. The key facilitator identified was collaboration and communication. DISCUSSION:This study has identified several key barriers and thresholds which can be used in future studies to improve the standardised management of post-operative anaemia.

Among the dairy sector's current concerns, the assessment of global animal health status is a complex challenge. Its multidimensionality means that global monitoring tools are rarely considered. Instead, specific disease detection is often studied separately and, due to financial and ethical issues, uses small-scale data sets focusing on few biomarkers. Several studies have already been conducted using milk Fourier transform mid-infrared (FT-MIR) spectroscopy to detect mastitis and lameness or to quantify health-related biomarkers in milk or blood. Those studies are relevant but they focus mainly on one biomarker or disease. To solve this issue and the small-scale data set, in this study, we proposed a holistic approach using big data obtained from milk recording, including milk yield, somatic cell count, and 27 FT-MIR-based predictors related to milk composition and animal health status. Using 740,454 records collected from 114,536 first-parity Holstein cows in southern Belgium, we performed repeated unsupervised learning algorithms based on Ward's agglomerative hierarchical clustering method to find potential interesting patterns. A divide-and-conquer approach was used to overcome the limitation of computational resources in clustering a relatively large data set. Five groups of records were identified. Differences observed in the fourth group suggested a relationship to metabolic disorders. The fifth group seemed to be related to mastitis. In a second step, we performed a partial least squares discriminant analysis (PLS-DA) to predict the probability of belonging to those specific groups for the entire data set. The obtained global accuracy was 0.77 and the balanced accuracy (i.e., the mean between sensitivity and specificity) of discriminating the fourth and fifth groups was 0.88 and 0.96, respectively. Then, a validation of the interpretation of those groups was performed using 204 milk and blood reference records. The predicted probability associated with the metabolic disorders issue had significant correlations of 0.54 with blood β-hydroxybutyrate, 0.44 with blood nonesterified fatty acids, -0.32 with blood glucose, -0.23 with milk glucose-6-phosphate, and 0.38 with milk isocitrate. In contrast, the predicted probability of belonging to the mastitis group had correlations of 0.69 with milk lactate dehydrogenase, 0.46 with milk N-acetyl-β-d-glucosaminidase, -0.18 with milk free glucose, and 0.16 with milk glucose-6-phosphate. Consequently, these results suggest that the obtained quantitative traits indirectly reflect some of the main health disorders in dairy farming and could be used to monitor dairy cows on a large scale. By using unsupervised learning on large-scale milk recording data and then validating the pattern using reference laboratory measures, we propose a new approach to quickly assess dairy cow health status.

BACKGROUND:Group education is increasing in popularity as a means of preparing patients for surgery. In recent years, these 'surgery schools' have evolved from primarily informing patients of what to expect before and after surgery, to providing support and encouragement for patients to 'prehabilitate' prior to surgery, through improving physical fitness, nutrition and emotional wellbeing.METHOD:A survey aimed at clinicians delivering surgery schools was employed to capture a national overview of activity to establish research and practice priorities in this area. The survey was circulated online via the Enhanced Recovery after Surgery UK Society and the Centre for Perioperative Care mailing lists as well as social media.RESULTS:There were 80 responses describing 28 active and 4 planned surgery schools across the UK and Ireland. Schools were designed and delivered by multidisciplinary teams, contained broadly similar content and were well attended. Most were funded by the National Health Service. The majority included aspects of prehabilitation most commonly the importance of physical fitness. Seventy five percent of teams collected patient outcome data, but less than half collected data to establish the clinical effectiveness of the school. Few describe explicit inclusion of evidence-based behavior change techniques, but collaboration and partnerships with community teams, gyms and local charities were considered important in supporting patients to make changes in health behaviors prior to surgery.CONCLUSION:It is recommended that teams work with patients when designing surgery schools and use evidence-based behavior change frameworks and techniques to inform their content. There is a need for high-quality research studies to determine the clinical effectiveness of this type of education intervention.

Background: As international concern grows regarding the reported early oncological outcomes and technical challenges of transanal total mesorectal excision (TaTME), there is a need for a structured and robust quality assurance process to ensure safe introduction and monitoring of a novel surgical technique. The IDEAL framework has been advocated to guide such a process. The aim of this study was the report the application of IDEAL framework in the development and implementation of TaTME training in the UK. Methods: A five-stage outline (idea, development, exploration, assessment, and long-term study) was applied to describe the development, delivery and assessment of the TaTME training initiative in the UK. Surveys that incorporated the experience of both learners and more experienced surgeons of TaTME, together with experts in education, initiated the process with concepts and development of the training initiative explored at a centrally co-ordinated pilot training programme. Key components included a cadaver training workshop and a formal proctorship process. Data were recorded on demographics, tumour location, intraoperative, post-operative and histological outcomes. Educational assessment of technical progress was performed using custom-made Global Assessment Scoring (GAS) forms which were completed by both learners and proctors. Long-term outcomes were captured at 24 months. Results: Five selected pilot sites were used by 10 colorectal surgeons during the training initiative and 24 cases were proctored in this period in the exploration phase. Median operative time reduced from initial 331 +/- 90 [195-610] to 283 +/- 62 [195-340] minutes in the final case. No visceral injuries were reported however there was one conversion to open (4.2%). Histological assessment reported as intact mesorectal TME specimens with clear distal margin and no bowel or tumour perforation in all cases. One case had positive circumferential margin (4%). Assessment of educational outcomes showed GAS score 5 (independent performance) was achieved by case 5 in most operative steps. Long-term follow up showed no evidence of local or regional recurrence but three liver and one lung metastasis at 24 months. Conclusions: Dissemination of a new surgical technique within the confines of IDEAL framework demonstrates the feasibility and safety of surgical training programme for TaTME at a national level.

The main objective of this study was to test the efficiency of a management system combining metabolic clustering of cows based on Fourier-transform mid-infrared (FT-MIR) spectra of milk and targeted treatment of metabolically imbalanced cows with propylene glycol drench. We hypothesized that cows identified in a metabolically imbalanced status during early lactation were associated with subsequent impaired health, reproduction, and production, and that treatment with propylene glycol treatment would improve health, reproduction, and production relatively more in these cows than in control cows. We completed a prospective, randomized controlled trial with 356 early-lactation cows in 2 private dairy herds in Denmark from December 2017 to April 2018. Milk samples of cows were collected before treatment, from 4 to 9 d in milk, and after treatment, from 22 to 27 d in milk. Milk samples were analyzed using FT-MIR spectroscopy. We also measured 4 milk metabolites (β-hydroxybutyrate, isocitrate, malate, and glutamate) and fat and protein contents. Based on FT-MIR spectra and cluster analyses, cows were clustered into groups of metabolically imbalanced and healthy cows. Within each group, cows were allocated randomly to treatment with propylene glycol (500 mL for 5 d) or no treatment. We analyzed the effect of the treatment on cow-level variables: metabolic cluster, milk metabolites, fat and protein contents, and fat-to-protein ratio at a milk sampling after the treatment. Furthermore, we analyzed daily milk yield, calving to first service interval, and disease occurrence. Results showed only a few effects of propylene glycol treatment and few interactions between treatment and metabolic clusters. We found no significant main effects of propylene glycol treatment in any of these analyses. A negative effect of the imbalanced metabolic cluster was found for the outcome of calving to first service interval for multiparous cows. In conclusion, we found a longer calving to first service interval in metabolically imbalanced cows, but we were not able to demonstrate overall benefits from the applied detection of cows in imbalanced metabolic status in early lactation and follow-up by treatment with propylene glycol.

Blood biomarkers may be used to detect physiological imbalance and potential disease. However, blood sampling is difficult and expensive, and not applicable in commercial settings. Instead, individual milk samples are readily available at low cost, can be sampled easily and analysed instantly. The present observational study sampled blood and milk from 234 Holstein dairy cows from experimental herds in six European countries. The objective was to compare the use of three different sets of milk biomarkers for identification of cows in physiological imbalance and thus at risk of developing metabolic or infectious diseases. Random forests was used to predict body energy balance (EBAL), index for physiological imbalance (PI-index) and three clusters differentiating the metabolic status of cows created on basis of concentrations of plasma glucose, β-hydroxybutyrate (BHB), non-esterified fatty acids (NEFA) and serum IGF-1. These three metabolic clusters were interpreted as cows in balance, physiological imbalance and "intermediate cows" with physiological status in between. The three sets of milk biomarkers used for prediction were: milk Fourier transform mid-IR (FT-MIR) spectra, 19 immunoglobulin G (IgG) N-glycans and 8 milk metabolites and enzymes (MME). Blood biomarkers were sampled twice; around 14 days after calving (days in milk (DIM)) and around 35 DIM. MME and FT-MIR were sampled twice weekly 1-50 DIM whereas IgG N-glycan were measured only four times. Performances of EBAL and PI-index predictions were measured by coefficient of determination (R2cv) and root mean squared error (RMSEcv) from leave-one-cow-out cross-validation (cv). For metabolic clusters, performance was measured by sensitivity, specificity and global accuracy from this cross-validation. Best prediction of PI-index was obtained by MME (R2cv = 0.40 (95 % CI: 0.29-0.50) at 14 DIM and 0.35 (0.23-0.44) at 35 DIM) while FT-MIR showed a better performance than MME for prediction of EBAL (R2cv = 0.28 (0.24-0.33) vs 0.21 (0.18-0.25)). Global accuracies of predicting metabolic clusters from MME and FT-MIR were at the same level ranging from 0.54 (95 % CI: 0.39-0.68) to 0.65 (0.55-0.75) for MME and 0.51 (0.37-0.65) to 0.68 (0.53-0.81) for FT-MIR. R2cv and accuracies were lower for IgG N-glycans. In conclusion, neither EBAL nor PI-index were sufficiently well predicted to be used as a management tool for identification of risk cows. MME and FT-MIR may be used to predict the physiological status of the cows, while the use of IgG N-glycans for prediction still needs development. Nevertheless, accuracies need to be improved and a larger training data set is warranted.

Aim Transanal total mesorectal excision (TaTME) has attracted substantial interest amongst colorectal surgeons but its technical challenges may underlie the early reports of visceral injuries and oncological concerns. The aim of this study was to report on the feasibility, development and the outcome of the national pilot training initiative for TaTME-UK. Methods TaTME-UK was successfully launched in September 2017 in partnership with the healthcare industry and endorsed by the Association of Coloproctology of Great Britain and Ireland. This multi-modal training curriculum consisted of three phases: (i) set-up; (ii) selection of pilot sites; and (iii) formal proctorship programme. Bespoke Global Assessment Scoring (GAS) forms were designed and completed by both trainees and mentors. Data were collected on patient demographics, tumour characteristics and perioperative clinical and histological outcomes. Results Twenty-four proctored cases were performed by 10 colorectal surgeons from five selected pilot sites. Median operative time was 331 +/- 90 (195-610) min which was reduced to 283 +/- 62 (195-340) min in the final case. Independent performance (GAS score of 5) was achieved for most operative steps by case 5. There was one conversion (4.2%), but no visceral injuries. Pathological data confirmed no bowel perforation and intact quality of the mesorectal TME specimens with clear distal margin in all cases and circumferential margins in 23/24 cases (96%). Conclusion This exploratory study demonstrates acceptable early outcomes in a small cohort suggesting that a competency-based multi-modal training programme for TaTME can be feasible and safe to implement at a national level.

Modern perioperative medicine has dramatically altered the care for patients undergoing major surgery. Anaesthetic and surgical practice has been directed at mitigating the surgical stress response and reducing physiological insult. The development of standardised enhanced recovery programmes combined with minimally invasive surgical techniques has lead to reduction in length of stay, morbidity, costs, and improved outcomes. The enhanced recovery after surgery (ERAS) society and its national chapters provide a means for sharing best practice in this field and developing evidence based guidelines. Research has highlighted persisting challenges with compliance as well as ensuring the effectiveness and sustainability of ERAS. There is also a growing need for increasingly personalised care programmes as well as complex geriatric assessment of frailer patients. Continuous collection of outcome and process data combined with machine learning, offers a potentially powerful solution to delivering bespoke care pathways and optimising individual management. Long-term data from ERAS programmes remain scarce and further evaluation of functional recovery and quality of life is required.

The objective of this study was to develop a generic risk management system based on the Hazard Analysis and Critical Control Point (HACCP) principles for the prevention of critical negative energy balance (NEB) in dairy herds using an expert panel approach. In addition, we discuss the advantages and limitations of the system in terms of implementation in the individual dairy herd. For the expert panel, we invited 30 researchers and advisors with expertise in the field of dairy cow feeding and/or health management from eight European regions. They were invited to a Delphi-based set-up that included three inter-correlated questionnaires in which they were asked to suggest risk factors for critical NEB and to score these based on 'effect' and 'probability'. Finally, the experts were asked to suggest critical control points (CCPs) specified by alarm values, monitoring frequency and corrective actions related to the most relevant risk factors in an operational farm setting. A total of 12 experts (40 %) completed all three questionnaires. Of these 12 experts, seven were researchers and five were advisors and in total they represented seven out of the eight European regions addressed in the questionnaire study. When asking for suggestions on risk factors and CCPs, these were formulated as 'open questions', and the experts' suggestions were numerous and overlapping. The suggestions were merged via a process of linguistic editing in order to eliminate doublets. The editing process revealed that the experts provided a total of 34 CCPs for the 11 risk factors they scored as most important. The consensus among experts was relatively high when scoring the most important risk factors, while there were more diverse suggestions of CCPs with specification of alarm values and corrective actions. We therefore concluded that the expert panel approach only partly succeeded in developing a generic HACCP for critical NEB in dairy cows. We recommend that the output of this paper is used to inform key areas for implementation on the individual dairy farm by local farm teams including farmers and their advisors, who together can conduct herd-specific risk factor profiling, organise the ongoing monitoring of herd-specific CCPs, as well as implement corrective actions when CCP alarm values are exceeded.

Objectives: Prehabilitation is a collection of measures that aim to optimise a patient's physical and psychological wellbeing before treatment. This survey, run on behalf of the Enhanced Recovery after Surgery Society (UK), aimed to map the current status of prehabilitation.

Enhanced Recovery After Surgery (ERAS) programmes are an innovative approach to optimising patient outcomes in the perioperative period and have been implemented in various surgical departments across a range of specialties, with varying degrees of success. ERAS is an evidence-based, multimodal programme that has repeatedly demonstrated a reduction in post-operative complications and reduced the length of hospital stays following elective surgery. However, despite extensive evidence to support these benefits, several barriers to ERAS implementation have been identified. This article outlines the components of ERAS, focusing on the barriers to its implementation and how these could be overcome. It also discusses the implications of ERAS for patients, nurses and healthcare organisations.

Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (β-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-β-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites' levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring.

Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to (1) evaluate the potential of milk mid-IR spectra to predict these blood components individually and (2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on six experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status was defined by k-means clustering (k=3) based on the four blood components. Milk mid-IR analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using four subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R 2 of calibration of 0.55, 0.69, 0.49 and 0.77, and R 2 of cross-validation of 0.44, 0.61, 0.39 and 0.70. Although these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the data set into three groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the three groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-IR analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows.

Background Enhanced Recovery After Surgery (ERAS) is widely accepted in current surgical practice due to its positive impact on patient outcomes. The successful implementation of ERAS is challenging and compliance with protocols varies widely. Continual staff education is essential for successful ERAS programmes. Teaching modalities exist, but there remains no agreement regarding the optimal training curriculum or how its effectiveness is assessed. We aimed to draw consensus from an expert panel regarding the successful training and implementation of ERAS. Methods A modified Delphi technique was used; three rounds of questionnaires were sent to 58 selected international experts from 11 countries across multiple ERAS specialities and multidisciplinary teams (MDT) between January 2016 and February 2017. We interrogated opinion regarding four topics: (1) the components of a training curriculum and the structure of training courses; (2) the optimal framework for successful implementation and audit of ERAS including a guide for data collection; (3) a framework to assess the effectiveness of training; (4) criteria to define ERAS training centres of excellence. Results An ERAS training course must cover the evidence-based principles of ERAS with team-oriented training. Successful implementation requires strong leadership, an ERAS facilitator and an effective MDT. Effectiveness of training can be measured by improved compliance. A training centre of excellence should show a willingness to teach and demonstrable team working. Conclusions We propose an international expert consensus providing an ERAS training curriculum, a framework for successful implementation, methods for assessing effectiveness of training and a definition of ERAS training centres of excellence.

INTRODUCTION:There has been a wide uptake in the use of Minimal Invasive Surgery (MIS) globally across different surgical specialties. Whilst evidence exists for a structured training curriculum for basic laparoscopic surgery, there is little agreement on a complete framework for an advanced MIS training curriculum, defining the essential elements of the curriculum including the optimal assessment methods. The aim of this study is to obtain a consensus on the essential elements of a training curriculum for advanced MIS.MATERIALS AND METHODS:A Delphi study was carried out involving 57 international experts in advanced MIS across different surgical specialties. A three round survey was conducted to reach consensus on the essential domains of a curriculum. This included defining the learners, trainers and training centres; curriculum content and competency based assessment.RESULTS:Unanimous agreement was reached for the completion of basic laparoscopic training before entry into advanced training. A trainer should have reached competency in advanced MIS and attended a 'Train the trainer' course. The curriculum should be delivered as modular training, including a multi-modal approach with a structured clinical proctorship programme. Formative assessment was considered as an integral part of learning and should be performed using objective work based assessment tools such as global assessment scale (GAS) forms. Accreditation in advanced MIS can be achieved by objective assessment of technical performance of unedited videos in addition to key clinical performance outcomes.CONCLUSION:A consensus on the framework of an advanced MIS training curriculum has been achieved defining the essential elements of entry criteria, selection of trainers and training units and curriculum content. Multimodal learning, clinical proctorship programme and competency based assessment are integral parts of the curriculum.

Objectives: Digital learning platforms are becoming more commonplace as an adjunct for the education of healthcare professionals and patients. The current uptake of digital learning platforms within perioperative care and Enhanced Recovery After Surgery (ERAS) programmes is not known. Therefore, we aimed to report the availability, uptake and efficacy of digital learning platforms in perioperative care and ERAS care. Methods: A systematic search of the Pubmed, Embase and Cochrane databases was conducted in keeping with the PRISMA principles. Inclusion criteria were articles published between 2000 and 2017 reporting on the nature and use of digital ERAS educational platforms. The search strategy captured terms for perioperative care, ERAS, computer assisted instruction and e-learning. Articles were independently screened by two authors using a dedicated data extraction form. Results: Twenty six studies were included from 10 surgical specialities. The majority were not used within dedicated ERAS programmes. Digital platforms included e-learning (31%), website based learning (27%), online clinical pathways (with an educational theme) (12%), online virtual patients (12%), mobile/tablet learning programs (15%) and interactive DVDs (4%). Targeted learners include patients (65%), surgical multidisciplinary teams (8%), surgical residents (8%), perioperative staff (8%) and medical and nursing students (8%).Three reported digital learning interventions incorporated entire perioperative clinical pathways with one study investigated the effect within an established ERAS programme. Few studies investigated the impact of their tool. Outcomes measures included knowledge recall (23%), post-operative pain (12%), anxiety (12%), length of stay (8%) and usability (8%). Where reported ERAS protocol deviation, length of stay and patient satisfaction were improved with digital learning interventions. Conclusion: A number of digital learning platforms are currently used within perioperative care with very few dedicated digital ERAS tools. There is an opportunity to design bespoke ERAS learning interventions addressing multi-disciplinary needs and encompassing the whole ERAS pathway. Disclosure of Interest: None declared.

Objectives: The successful implementation of ERAS is challenging and patchy with wide variations in compliance to ERAS elements across disciplines. Several ERAS teaching programs and courses exist but there is no consensus regarding the optimal training curriculum or course structure. We aim to draw consensus from a selected expert panel regarding the ideal curriculum for ERAS training.

Body condition score (BCS) change is an indirect measure of energy balance. Energy balance before calving may affect production and health in the following lactation. It is likely that cows may experience BCS loss before calving due to negative energy balance. The objective of this study was to determine if loss of BCS 15d before calving affected milk production, BCS profile, and metabolic status during the transition period and early lactation. On d -15 to d 0 relative to calving, BCS was assessed (1=emaciated, 5=obese) for 98 Holstein-Friesian cows. The cows were divided into 2groups: those that did not lose BCS between d -15 and d 0 (maintained, BCS-M, n=55) and those that lost BCS from d -15 to d 0 (lost, BCS-L, n=43, average loss of 0.29±0.11 BCS). The fixed effects of BCS group, parity, week (day when analyzing milk production records), their interactions, and a random effect of cow were analyzed using PROC MIXED of SAS (SAS Institute Inc., Cary, NC). Before calving, BCS-L cows tended to have higher concentrations of nonesterified fatty acids than BCS-M cows (0.88 vs. 0.78mmol/L). After calving, BCS-L cows had higher nonesterified fatty acid concentrations in wk 1 (0.93 vs. 0.71mmol/L), wk 2 (0.84 vs. 0.69mmol/L), and wk 4 (0.81 vs. 0.63mmol/L) than BCS-M cows. The BCS-L cows had higher concentrations of β-hydroxybutyrate (BHB) in wk 1 (0.72 vs. 0.57mmol/L), wk 2 (0.97 vs. 0.70mmol/L), and wk 4 (0.94 vs. 0.67mmol/L) compared with BCS-M cows. We detected significant reductions in insulin concentrations in BCS-L cows from wk -1 (2.23 vs. 1.37 µIU/mL) to wk 2 (1.68 vs. 0.89 µIU/mL) and wk 4 (2.21 vs 1.59 µIU/mL) compared with BCS-M cows. Prevalence of subclinical ketosis increased in BCS-L cows in wk 3 and 4 when BHB was ≥1.4mmol/L and in wk 1, 3, and 4 when BHB was ≥1.2mmol/L. In wk 1, BCS-L cows tended to have lower levels of calcium than BCS-M cows (2.33 vs. 2.27mmol/L). We found no differences between the groups of cows for milk yield and energy-corrected milk. The BCS-L cows had lower BCS up to 75d in lactation. Overall, BCS-L cows had higher somatic cell scores with an elevated somatic cell score on d 45, d 60, and d 75. There was an overall tendency for BCS-L cows to have higher fat yield and an overall significant increase in fat percentage. Overall, BCS-L cows had lower lactose percentage, with a reduction on d 60. This work shows that BCS loss before calving may have significant consequences for metabolic status, milk composition, somatic cell score, and BCS profile in dairy cows.

Background The interest and adoption of transanal total mesorectal excision (TaTME) is growing amongst the colorectal surgical community, but there is no clear guidance on the optimal training framework to ensure safe practice for this novel operation. The aim of this study was to establish a consensus on a detailed structured training curriculum for TaTME.Methods A consensus process to agree on the framework of the TaTME training curriculum was conducted, seeking views of 207 surgeons across 18 different countries, including 52 international experts in the field of TaTME. The process consisted of surveying potential learners of this technique, an international experts workshop and a final expert's consensus to draw an agreement on essential elements of the curriculum.Results Appropriate case selection was strongly recommended, and TaTME should be offered to patients with mid and low rectal cancers, but not proximal rectal cancers. Pre-requisites to learn TaTME should include completion of training and accreditation in laparoscopic colorectal surgery, with prior experience in transanal surgery. Ideally, two surgeons should undergo training together in centres with high volume for rectal cancer surgery. Mentorship and multidisciplinary training were the two most important aspects of the curriculum, which should also include online modules and simulated training for purse-string suturing. Mentors should have performed at least 20 TaTME cases and be experienced in laparoscopic training. Reviewing the specimens' quality, clinical outcome data and entering data into a registry were recommended. Assessment should be an integral part of the curriculum using Global Assessment Scales, as formative assessment to promote learning and competency assessment tool as summative assessment.Conclusions A detailed framework for a structured TaTME training curriculum has been proposed. It encompasses various training modalities and assessment, as well as having the potential to provide quality control and future research initiatives for this novel technique.