136 research outputs found

    Water governance in the Kyrgyz agricultural sector: on its way to integrated water resource management?

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    "As a reaction to growing water scarcity worldwide, sustainable water allocation and use, and in particular the role of agriculture as a major water user, have become important topics in the development discourse. In recent years Integrated Water Resources Management (IWRM) emerged as an answer to many water management problems. IWRM approaches water management from a holistic perspective and encompasses, among others, the integration of economic, ecological and social aspects. Is implementation of such a holistic approach feasible in developing countries and countries in transition or does it rather overburden them? First experiences have been made with the implementation of IWRM in several developing and transition countries. The aim of this study is to provide some answers to the question of what has been achieved so far. Based on an analysis of Kyrgyz water governance, the study assesses the status quo as well as the potentials for and obstacles to the realization of the normative framework of IWRM in a transition country. Comparing today's institutional framework of water management with this normative concept, it reveals the most significant gaps between norm and reality, but also identifies progress towards IWRM. Recommendations on how to further develop Kyrgyz water governance towards IWRM are provided." (author's abstract

    Do Semantics Matter in Empathetic Person Perception of Children or Adults with Mental Illness?

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    Experiences of stigma, discrimination, or aggression negatively affect the well-being of people experiencing symptoms of psychopathology. However, empathy is thought to undermine prejudice and discrimination and is linked with positive outcomes (e.g., greater well-being, more social support, etc.) among those with stigmatized mental illnesses. The current work investigates the influence of target age (adult or child) and language type (person-first or identity-first) on how much empathic concern perceivers report toward individuals with a hypothetical mental health condition. This research contributes to an ongoing debate about whether person-first or identity-first language carries stigmatizing or protective effects, while also considering a novel potential moderator: target age (i.e., does person-first and identity-first language similarly affect perceptions of adults and children?). To this end, we employed an experimental vignette design examining empathy expressed toward individuals with a mental health condition, where age was manipulated within subjects and language was manipulated between subjects. The results determine that perceivers report greater empathy towards children than adults. However, the use of person-first and identity-first language did not result in significant findings. Thus, whether language type influences empathic concern remains uncertain. These findings suggest a need for increased empirical examination of interventions to inspire empathy towards people, perhaps especially adults, experiencing symptoms of psychopathology

    Frequency and Predictive Factors of Hypoglycemia in Patients Treated With rhIGF-1: Data From the Eu-IGFD Registry

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    The European Increlex® Growth Forum Database (Eu-IGFD) is an ongoing surveillance registry (NCT00903110) established to collect long-term safety and effectiveness data on the use of recombinant human insulin-like growth factor-1 (rhIGF-1, mecasermin, Increlex) for the treatment of children/adolescents with severe primary insulin-like growth factor-1 deficiency (SPIGFD). Objective: This analysis of Eu-IGFD data aimed to identify the frequency and predictive factors for hypoglycemia adverse events (AEs) in children treated with rhIGF-1. Methods: Data were collected from December 2008 to May 2021. Logistic regression was performed to identify predictive risk factors for treatment-induced hypoglycemia AEs. Odds ratios (ORs) are presented with 95% CIs for each factor. Results: In total, 306 patients were enrolled in the registry; 84.6% were diagnosed with SPIGFD. Patients who experienced ≥ 1 hypoglycemia AE (n = 80) compared with those with no hypoglycemia AEs (n = 224) had a lower mean age at treatment start (8.7 years vs 9.8 years), a more frequent diagnosis of Laron syndrome (27.5% vs 10.3%), and a history of hypoglycemia (18.8% vs 4.5%). Prior history of hypoglycemia (OR 0.25; 95% CI: [0.11; 0.61]; P = .002) and Laron syndrome diagnosis (OR 0.36; 95% CI: [0.18; 0.72]; P = .004) predicted future hypoglycemia AEs. Total hypoglycemia AEs per patient per treatment year was 0.11 and total serious hypoglycemia AEs per patient per treatment year was 0.01. Conclusion: Hypoglycemia occurs more frequently in patients with prior history of hypoglycemia and/or Laron syndrome compared with patients without these risk factors, and these patients should be carefully monitored for this AE throughout treatment

    The GnRH system : importance for precocious puberty in children

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    We discuss here the secular early onset of puberty in children, the central mechanisms of puberty as well as the clinical aspects of central precocious puberty in children. How to suspect it, how to explore it and how to treat it are the main topics of this articleAprès avoir rappelé les mécanismes centraux de la puberté, nous nous focalisons sur les aspects cliniques de la puberté précoce centrale chez l’enfant. Comment la suspecter, comment l’explorer, comment la traiter : voilà les points qui sont développés dans cet articl

    The Role of PIVKA-II as a Predictor of Early Hepatocellular Carcinoma Recurrence-Free Survival after Liver Transplantation in a Low Alpha-Fetoprotein Population

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    Introduction: AFP and the RETREAT score are currently used to predict HCC recurrence after LT. However, superior discriminating models are needed for low AFP populations. The aim of this study is to investigate the predictive value of PIVKA-II on recurrence-free survival after LT in a low AFP population and microvascular invasion on explant. Methods: A retrospective cohort study including all consecutive patients transplanted for HCC between 1989 and 2019 in the Erasmus MC University Medical Center in Rotterdam, the Netherlands, was used. AFP and PIVKA-II levels were determined in serum samples collected at the time of transplantation. Data on tumor load and microvascular invasion were retrieved from patients’ records. Results: The study cohort consisted of 121 patients, with HCC recurrence in 15 patients (12.4%). The median AFP was 7.7 ng/mL (4.4–20.2), and the median PIVKA-II was 72.0 mAU/mL (41.0–213.5). Patients with low AFP (≤8 ng/mL) and PIVKA-II (≤90 mAU/mL) had a 5-year recurrence-free survival of 100% compared to 85.7% in patients with low AFP and high PIVKA-II (p = 0.026). Regardless of the AFP level, patients within the Milan criteria (based on explant pathology) with a low PIVKA-II level had a 5-year recurrence-free survival of 100% compared to patients with a high PIVKA-II level of 81.1% (p = 0.002). In patients with microvascular invasion, the AUC for PIVKA-II was slightly better than the AUC for AFP (0.775 vs. 0.687). Conclusions: The dual model of PIVKA-II ≤ 90 mAU/mL with either AFP ≤ 8 ng/mL or with patients within the Milan criteria identifies patient groups which can be exempted from HCC surveillance after LT in a low AFP population. PIVKA-II may be a better predictor for explant microvascular invasion than AFP and could play a role in future models identifying LT candidates with the highest risk for HCC recurrence.</p

    The Role of PIVKA-II as a Predictor of Early Hepatocellular Carcinoma Recurrence-Free Survival after Liver Transplantation in a Low Alpha-Fetoprotein Population

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    Introduction: AFP and the RETREAT score are currently used to predict HCC recurrence after LT. However, superior discriminating models are needed for low AFP populations. The aim of this study is to investigate the predictive value of PIVKA-II on recurrence-free survival after LT in a low AFP population and microvascular invasion on explant. Methods: A retrospective cohort study including all consecutive patients transplanted for HCC between 1989 and 2019 in the Erasmus MC University Medical Center in Rotterdam, the Netherlands, was used. AFP and PIVKA-II levels were determined in serum samples collected at the time of transplantation. Data on tumor load and microvascular invasion were retrieved from patients’ records. Results: The study cohort consisted of 121 patients, with HCC recurrence in 15 patients (12.4%). The median AFP was 7.7 ng/mL (4.4–20.2), and the median PIVKA-II was 72.0 mAU/mL (41.0–213.5). Patients with low AFP (≤8 ng/mL) and PIVKA-II (≤90 mAU/mL) had a 5-year recurrence-free survival of 100% compared to 85.7% in patients with low AFP and high PIVKA-II (p = 0.026). Regardless of the AFP level, patients within the Milan criteria (based on explant pathology) with a low PIVKA-II level had a 5-year recurrence-free survival of 100% compared to patients with a high PIVKA-II level of 81.1% (p = 0.002). In patients with microvascular invasion, the AUC for PIVKA-II was slightly better than the AUC for AFP (0.775 vs. 0.687). Conclusions: The dual model of PIVKA-II ≤ 90 mAU/mL with either AFP ≤ 8 ng/mL or with patients within the Milan criteria identifies patient groups which can be exempted from HCC surveillance after LT in a low AFP population. PIVKA-II may be a better predictor for explant microvascular invasion than AFP and could play a role in future models identifying LT candidates with the highest risk for HCC recurrence.</p

    The Yield of Routine Post-Operative Doppler Ultrasound to Detect Early Post-Liver Transplantation Vascular Complications

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    Early detection of liver transplantation (LT) vascular complications enables timely management. Our aim was to assess if routine Doppler ultrasound (rDUS) improves the detection of hepatic artery thrombosis (HAT), portal vein thrombosis (PVT) and hepatic venous outflow obstruction (HVOO). We retrospectively analysed timing and outcomes, number needed to diagnose one complication (NND) and positive predictive value (PPV) of rDUS on post-operative day (POD) 0,1 and 7 in 708 adult patients who underwent primary LT between 2010–2022. We showed that HAT developed in 7.1%, PVT in 8.2% and HVOO in 3.1% of patients. Most early complications were diagnosed on POD 0 (26.9%), 1 (17.3%) and 5 (17.3%). rDUS correctly detected 21 out of 26 vascular events during the protocol days. PPV of rDUS was 53.8%, detection rate 1.1% and NND was 90.5. Median time to diagnosis was 4 days for HAT and 47 days for PVT and 21 days for HVOO. After intervention, liver grafts were preserved in 57.1%. In conclusion, rDUS protocol helps to detect first week’s vascular events, but with low PPV and a high number of ultrasounds needed.</p

    The Yield of Routine Post-Operative Doppler Ultrasound to Detect Early Post-Liver Transplantation Vascular Complications

    Get PDF
    Early detection of liver transplantation (LT) vascular complications enables timely management. Our aim was to assess if routine Doppler ultrasound (rDUS) improves the detection of hepatic artery thrombosis (HAT), portal vein thrombosis (PVT) and hepatic venous outflow obstruction (HVOO). We retrospectively analysed timing and outcomes, number needed to diagnose one complication (NND) and positive predictive value (PPV) of rDUS on post-operative day (POD) 0,1 and 7 in 708 adult patients who underwent primary LT between 2010–2022. We showed that HAT developed in 7.1%, PVT in 8.2% and HVOO in 3.1% of patients. Most early complications were diagnosed on POD 0 (26.9%), 1 (17.3%) and 5 (17.3%). rDUS correctly detected 21 out of 26 vascular events during the protocol days. PPV of rDUS was 53.8%, detection rate 1.1% and NND was 90.5. Median time to diagnosis was 4 days for HAT and 47 days for PVT and 21 days for HVOO. After intervention, liver grafts were preserved in 57.1%. In conclusion, rDUS protocol helps to detect first week’s vascular events, but with low PPV and a high number of ultrasounds needed.</p

    Data abstractions for decision tree induction

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    AbstractWhen descriptions of data values in a database are too concrete or too detailed, the computational complexity needed to discover useful knowledge from the database will be generally increased. Furthermore, discovered knowledge tends to become complicated. A notion of data abstraction seems useful to resolve this kind of problems, as we obtain a smaller and more general database after the abstraction, from which we can quickly extract more abstract knowledge that is expected to be easier to understand. In general, however, since there exist several possible abstractions, we have to carefully select one according to which the original database is generalized. An inadequate selection would make the accuracy of extracted knowledge worse.From this point of view, we propose in this paper a method of selecting an appropriate abstraction from possible ones, assuming that our task is to construct a decision tree from a relational database. Suppose that, for each attribute in a relational database, we have a class of possible abstractions for the attribute values. As an appropriate abstraction for each attribute, we prefer an abstraction such that, even after the abstraction, the distribution of target classes necessary to perform our classification task can be preserved within an acceptable error range given by user.By the selected abstractions, the original database can be transformed into a small generalized database written in abstract values. Therefore, it would be expected that, from the generalized database, we can construct a decision tree whose size is much smaller than one constructed from the original database. Furthermore, such a size reduction can be justified under some theoretical assumptions. The appropriateness of abstraction is precisely defined in terms of the standard information theory. Therefore, we call our abstraction framework Information Theoretical Abstraction.We show some experimental results obtained by a system ITA that is an implementation of our abstraction method. From those results, it is verified that our method is very effective in reducing the size of detected decision tree without making classification errors so worse
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