The Use of Near Infrared Reflectance Spectroscopy (NIRS) to Follow the Leaf/Stem Ratio of Legumes During Drying

Legume-rich mixed swards allow the production of a high quantity protein-rich forage with low nitrogen input. Nevertheless, during hay or silage making, dry matter losses as high as, 40 and 25 % have been recorded (Ciotti & Cavallero, 1979; Stilmant et al., 2004). These losses have mainly been linked to the high sensitivity to physical loss of legume leaves during drying. The development of a tool to characterise leaf losses or leaf/stem ratio during drying will help us to define the technical approach to reach the best compromise between quality loss reduction and good pre-wilting of legum-rich mixed swards. The aim of the present work was to test the potentialities of near infrared reflectance spectroscopy (NIRS) to quantify legume leaf/stem ratio in mixed grass-legume swards. The mixtures tested were perennial ryegrass-white clover (PR-WC), perennial ryegrass-red clover (PR-RC), timothy-red clover (T-RC) and cocksfoot-lucerne (C-L) swards. This technique has been successfully used to quantify leaf/stem ratio in pure perennial ryegrass swards (Leconte et al. 1999)

Management of Gastro-Intestinal Parasite Pressure, Under Grazing in Organic Farms: Development of a Decision Support System Through the Mobilisation of a Participative Research Process

Under grazing, gastro-intestinal parasite management remains a major problem in ruminant production systems, more especially in systems respecting organic farming rules following their obligations (1) to perform grazing as soon as pedo-climatic conditions are adapted and (2) to use anti-parasitic products only in a curative way. Surprisingly, this problem has not been highlighted by the different stakeholders in the food chain from cattle meat production to consumption. This could arise from the lack of a clear and pertinent norm or infestation threshold that would allow differentiation between preventive and curative treatments. Such a norm would indicate to the breeder whether he was permitted to treat his herd or not. The question is how to involve the stakeholders in a participative research process in order to develop a decision support system (DSS) adapted to their needs, when there is, initially, no clear demand for such a system. We present the steps followed to develop such a DSS: (1) stakeholder sensitisation to the question, (2) data recording with farmers and developing the DSS principle, (3) data processing and DSS calibration and validation

Determinants and impact of multidrug antibiotic resistance in pathogens causing ventilator-associated-pneumonia

Introduction The idea that multidrug resistance (MDR) to antibiotics in pathogens causing ventilator-associated pneumonia (VAP) is an independent risk factor for adverse outcome is still debated. We aimed to identify the determinants of MDR versus non-MDR microbial aetiology in VAP and assessed whether MDR versus non-MDR VAP was independently associated with increased 30-day mortality. Methods We performed a retrospective analysis of a prospectively registered cohort of adult patients with microbiologically confirmed VAP, diagnosed at a university hospital intensive care unit during a three-year period. Determinants of MDR as compared with non-MDR microbial aetiology and impact of MDR versus non-MDR aetiology on mortality were investigated using multivariate logistic and competing risk regression analysis. Results MDR pathogens were involved in 52 of 192 episodes of VAP (27%): methicillin-resistant Staphylococcus aureus in 12 (6%), extended-spectrum beta-lactamase producing Enterobacteriaceae in 28 (15%), MDR Pseudomonas aeruginosa and other non-fermenting pathogens in 12 (6%). Multivariable logistic regression identified the Charlson index of comorbidity (odds ratio (OR) = 1.38, 95% confidence interval (CI) = 1.08 to 1.75, p = 0.01) and previous exposure to more than two different antibiotic classes (OR = 5.11, 95% CI = 1.38 to 18.89, p = 0.01) as predictors of MDR aetiology. Thirty-day mortality after VAP diagnosis caused by MDR versus non-MDR was 37% and 20% (p = 0.02), respectively. A multivariate competing risk regression analysis showed that renal replacement therapy before VAP (standardised hazard ratio (SHR) = 2.69, 95% CI = 1.47 to 4.94, p = 0.01), the Charlson index of comorbidity (SHR = 1.21, 95% CI = 1.03 to 1.41, p = 0.03) and septic shock on admission to the intensive care unit (SHR = 1.86, 95% CI = 1.03 to 3.35, p = 0.03), but not MDR aetiology of VAP, were independent predictors of mortality. Conclusions The risk of MDR pathogens causing VAP was mainly determined by comorbidity and prior exposure to more than two antibiotics. The increased mortality of VAP caused by MDR as compared with non-MDR pathogens was explained by more severe comorbidity and organ failure before VAP

Explainability in medicine in an era of AI-based clinical decision support systems

This is the final version. Available on open access from Frontiers Media via the DOI in this recordData availability statement: The original contributions presented in the study are included in the article/supplementary material; further inquiries can be directed to the corresponding author.The combination of "Big Data" and Artificial Intelligence (AI) is frequently promoted as having the potential to deliver valuable health benefits when applied to medical decision-making. However, the responsible adoption of AI-based clinical decision support systems faces several challenges at both the individual and societal level. One of the features that has given rise to particular concern is the issue of explainability, since, if the way an algorithm arrived at a particular output is not known (or knowable) to a physician, this may lead to multiple challenges, including an inability to evaluate the merits of the output. This "opacity" problem has led to questions about whether physicians are justified in relying on the algorithmic output, with some scholars insisting on the centrality of explainability, while others see no reason to require of AI that which is not required of physicians. We consider that there is merit in both views but find that greater nuance is necessary in order to elucidate the underlying function of explainability in clinical practice and, therefore, its relevance in the context of AI for clinical use. In this paper, we explore explainability by examining what it requires in clinical medicine and draw a distinction between the function of explainability for the current patient versus the future patient. This distinction has implications for what explainability requires in the short and long term. We highlight the role of transparency in explainability, and identify semantic transparency as fundamental to the issue of explainability itself. We argue that, in day-to-day clinical practice, accuracy is sufficient as an "epistemic warrant" for clinical decision-making, and that the most compelling reason for requiring explainability in the sense of scientific or causal explanation is the potential for improving future care by building a more robust model of the world. We identify the goal of clinical decision-making as being to deliver the best possible outcome as often as possible, and find-that accuracy is sufficient justification for intervention for today's patient, as long as efforts to uncover scientific explanations continue to improve healthcare for future patients.Research Foundation Flanders (FWO

Attributable Mortality of Ventilator-associated Pneumonia. Replicating Findings, Revisiting Methods.

Rationale: Estimating the impact of ventilator-associated pneumonia (VAP) from routinely collected intensive care unit (ICU) data is methodologically challenging.Objectives: We aim to replicate earlier findings of limited VAP-attributable ICU mortality in an independent cohort. By refining statistical analyses, we gradually tackle different sources of bias.Methods: Records of 2,720 adult patients admitted to Ghent University Hospital ICUs (2013-2017) and receiving mechanical ventilation within 48 hours after admission were extracted from linked Intensive Care Information System and Computer-based Surveillance and Alerting of Nosocomial Infections, Antimicrobial Resistance, and Antibiotic Consumption in the ICU databases. The VAP-attributable fraction of ICU mortality was estimated using a competing risk analysis that is restricted to VAP-free patients (approach 1), accounts for VAP onset by treating it as either a competing (approach 2) or censoring event (approach 3), or additionally adjusts for time-dependent confounding via inverse probability weighting (approach 4).Results: A total of 210 patients (7.7%) acquired VAP. Based on benchmark approach 4, we estimated that (compared with current preventive measures) hypothetical eradication of VAP would lead to a relative ICU mortality reduction of 1.7% (95% confidence interval, -1.3 to 4.6) by Day 10 and of 3.6% (95% confidence interval, 0.7 to 6.5) by Day 60. Approaches 1-3 produced estimates ranging from -0.7% to 2.5% by Day 10 and from 5.2% to 5.5% by Day 60.Conclusions: In line with previous studies using appropriate methodology, we found limited VAP-attributable ICU mortality given current state-of-the-art VAP prevention measures. Our study illustrates that inappropriate accounting of the time dependency of exposure and confounding of its effects may misleadingly suggest protective effects of early-onset VAP and systematically overestimate attributable mortality

Outcome in patients perceived as receiving excessive care across different ethical climates : a prospective study in 68 intensive care units in Europe and the USA

Whether the quality of the ethical climate in the intensive care unit (ICU) improves the identification of patients receiving excessive care and affects patient outcomes is unknown. In this prospective observational study, perceptions of excessive care (PECs) by clinicians working in 68 ICUs in Europe and the USA were collected daily during a 28-day period. The quality of the ethical climate in the ICUs was assessed via a validated questionnaire. We compared the combined endpoint (death, not at home or poor quality of life at 1 year) of patients with PECs and the time from PECs until written treatment-limitation decisions (TLDs) and death across the four climates defined via cluster analysis. Of the 4747 eligible clinicians, 2992 (63%) evaluated the ethical climate in their ICU. Of the 321 and 623 patients not admitted for monitoring only in ICUs with a good (n = 12, 18%) and poor (n = 24, 35%) climate, 36 (11%) and 74 (12%), respectively were identified with PECs by at least two clinicians. Of the 35 and 71 identified patients with an available combined endpoint, 100% (95% CI 90.0-1.00) and 85.9% (75.4-92.0) (P = 0.02) attained that endpoint. The risk of death (HR 1.88, 95% CI 1.20-2.92) or receiving a written TLD (HR 2.32, CI 1.11-4.85) in patients with PECs by at least two clinicians was higher in ICUs with a good climate than in those with a poor one. The differences between ICUs with an average climate, with (n = 12, 18%) or without (n = 20, 29%) nursing involvement at the end of life, and ICUs with a poor climate were less obvious but still in favour of the former. Enhancing the quality of the ethical climate in the ICU may improve both the identification of patients receiving excessive care and the decision-making process at the end of life

Support vector machine versus logistic regression modeling for prediction of hospital mortality in critically ill patients with haematological malignancies

Background: Several models for mortality prediction have been constructed for critically ill patients with haematological malignancies in recent years. These models have proven to be equally or more accurate in predicting hospital mortality in patients with haematological malignancies than ICU severity of illness scores such as the APACHE II or SAPS II [1]. The objective of this study is to compare the accuracy of predicting hospital mortality in patients with haematological malignancies admitted to the ICU between models based on multiple logistic regression (MLR) and support vector machine (SVM) based models. Methods: 352 patients with haematological malignancies admitted to the ICU between 1997 and 2006 for a life-threatening complication were included. 252 patient records were used for training of the models and 100 were used for validation. In a first model 12 input variables were included for comparison between MLR and SVM. In a second more complex model 17 input variables were used. MLR and SVM analysis were performed independently from each other. Discrimination was evaluated using the area under the receiver operating characteristic (ROC) curves (+/- SE). Results: The area under ROC curve for the MLR and SVM in the validation data set were 0.768 (+/- 0.04) vs. 0.802 (+/- 0.04) in the first model (p = 0.19) and 0.781 (+/- 0.05) vs. 0.808 (+/- 0.04) in the second more complex model (p = 0.44). SVM needed only 4 variables to make its prediction in both models, whereas MLR needed 7 and 8 variables in the first and second model respectively. Conclusion: The discriminative power of both the MLR and SVM models was good. No statistically significant differences were found in discriminative power between MLR and SVM for prediction of hospital mortality in critically ill patients with haematological malignancies

Outcome in patients perceived as receiving excessive care across different ethical climates: a prospective study in 68 intensive care units in Europe and the USA.

PURPOSE: Whether the quality of the ethical climate in the intensive care unit (ICU) improves the identification of patients receiving excessive care and affects patient outcomes is unknown. METHODS: In this prospective observational study, perceptions of excessive care (PECs) by clinicians working in 68 ICUs in Europe and the USA were collected daily during a 28-day period. The quality of the ethical climate in the ICUs was assessed via a validated questionnaire. We compared the combined endpoint (death, not at home or poor quality of life at 1 year) of patients with PECs and the time from PECs until written treatment-limitation decisions (TLDs) and death across the four climates defined via cluster analysis. RESULTS: Of the 4747 eligible clinicians, 2992 (63%) evaluated the ethical climate in their ICU. Of the 321 and 623 patients not admitted for monitoring only in ICUs with a good (n = 12, 18%) and poor (n = 24, 35%) climate, 36 (11%) and 74 (12%), respectively were identified with PECs by at least two clinicians. Of the 35 and 71 identified patients with an available combined endpoint, 100% (95% CI 90.0-1.00) and 85.9% (75.4-92.0) (P = 0.02) attained that endpoint. The risk of death (HR 1.88, 95% CI 1.20-2.92) or receiving a written TLD (HR 2.32, CI 1.11-4.85) in patients with PECs by at least two clinicians was higher in ICUs with a good climate than in those with a poor one. The differences between ICUs with an average climate, with (n = 12, 18%) or without (n = 20, 29%) nursing involvement at the end of life, and ICUs with a poor climate were less obvious but still in favour of the former. CONCLUSION: Enhancing the quality of the ethical climate in the ICU may improve both the identification of patients receiving excessive care and the decision-making process at the end of life

Attitude towards pre-implantation genetic diagnosis for hereditary cancer

The use of pre-implantation genetic diagnosis (PGD) for hereditary cancer is subject to on-going debate, particularly among professionals. This study evaluates the attitude towards PGD and attitude-associated characteristics of those concerned: family members with a hereditary cancer predisposition. Forty-eight Von Hippel-Lindau and 18 Li–Fraumeni Syndrome families were identified via the 9 family cancer clinics in the Netherlands. In total, 216 high risk family members and partners were approached, of whom 179 (83%) completed a self-report questionnaire. Of the high risk family members, 35% expressed a positive attitude towards PGD. Those with a current desire to have children were significantly more likely to have a positive attitude: 48% would consider the use of PGD. No other sociodemographic, medical or psychosocial variables were associated significantly with a positive attitude. The most frequently reported advantage of PGD is the avoidance of a possible pregnancy termination. Uncertainty about late effects was the most frequently reported disadvantage. These results indicate that approximately half of those contemplating a future pregnancy would consider the use of PGD. The actual uptake, however, is expected to be lower. There is no indication that psychosocial factors affect interest in PGD

A Decade of Genetic Counseling in Frontotemporal Dementia Affected Families: Few Counseling Requests and much Familial Opposition to Testing

A decade of genetic counseling of frontotemporal dementia (FTD) affected families has generated two important observations. First, the uptake rate for presymptomatic testing for FTD is low in our department of Clinical Genetics at the Erasmus Medical Center in the Netherlands. Second, FTD at-risk counselees reported substantial familial opposition to genetic testing, which is distinct from the attitude in Huntington Disease affected families. We hypothesize that the low acceptance for FTD genetic counseling is consequential to the familial opposition and explain this within the theoretical framework of separation-individuation. Furthermore, we hypothesize that separation-individuation problems do not similarly influence the acceptance of HD genetic counseling, due to the educative role of the well-organised patient organization for HD in the Netherlands. We offer counseling recommendations that serve to facilitate the individuation of the counselee with respect to the FTD genetic test