Survey among FELASA members about rehoming of animals used for scientific and educational purposes

Rehoming is an important fate, which should be considered for animals used for scientific and educational purposes, and which is highlighted in the European Directive 2010/63 EU. In 2018, the Federation of European Laboratory Animal Science Associations (FELASA) convened a working group to review current literature and identify existing practices with the aim of issuing general recommendations on the rehoming of research animals. In order to understand the number and species of animals being rehomed and which species and information to include in the recommendations, the working group launched a survey that was distributed among FELASA members, yielding 97 valid records for analysis. Most respondents of the survey considered the rehoming of cats, dogs, mice, rats, rabbits, pigs and minipigs. The most important issues reported by the respondents were related to availability/suitability of animals, availability of adopters and legal issues. Based on the data and information collected in this survey, the working group decided on the format and content of the future recommendations: a first section containing a general protocol for rehoming, addressing the issues raised by the respondents, and a second section containing species-specific information and advice about cats, dogs, small prey mammals, equines, primates, camelids and minipigs

FELASA recommendations for the rehoming of animals used for scientific and educational purposes

Directive 2010/63/EU of the European Parliament and the Council of 22 September 2010 states that at the end of a procedure, the most appropriate decision on the future of an animal previously used or intended for use in scientific procedures should be taken on the basis of animal welfare and potential risks to the environment. Member States may allow animals to be rehomed provided the health of the animal allows it, there is no danger to public health, animal health or the environment and if appropriate measures have been taken to safeguard the wellbeing of the animal. In countries where rehoming is permitted, it is the responsibility of the Animal Welfare Body to advise on a rehoming scheme which must include appropriate socialization in order to help facilitate successful rehoming, avoid unnecessary distress to the animals and guarantee public safety. This paper reviews the EU legislation, existing guidance, current literature and best practice to define rehoming, sets out general considerations for rehoming laboratory animals including socialization and provides practical advice on the steps required in a rehoming scheme. For those species most frequently rehomed, more detailed species-specific sections are included

Predictie van functionele achteruitgang bij ambulante geriatrische patiënten op de spoedgevallendienst

Doel Het doel van deze studie is de predictieve validiteit te onderzoeken van vijf screeningsinstrumenten in het voorspellen van functionele achteruitgang bij ouderen die ambulant verzorgd werden op een spoedgevallendienst. Methode Bij 83 ouderen die ambulant op de spoedgevallendienst van UZ Leuven werden verzorgd, werden de Identification of Seniors at Risk (ISAR), Triage Risk Screening Tool (TRST), de vragenlijst van Runciman, de vragenlijst van Rowland en de Voorlopige Indicator voor Plaatsing (VIP) afgenomen. De functionele status 14 dagen voor opname, bij opname, en 14, 30 en 90 dagen na ontslag werd in kaart gebracht met behulp van de Katz schaal. Resultaten De screeningsinstrumenten met de beste verhouding tussen de sensitiviteit en negatief predictieve waarde 14 dagen na ontslag zijn de vragenlijst van Rowland en de ISAR. Dertig en negentig dagen na ontslag is dit de ISAR. Conclusie Uit dit onderzoek blijkt dat, in aanmerking genomen dat voor een screeningsinstrument de sensitiviteit en negatief predictieve waarde de belangrijkste parameters zijn, de ISAR het meest geschikte instrument is om functionele achteruitgang bij ouderen na een ambulante verzorging op de spoedgevallendienst te voorspellen. De ISAR is eenvoudig in het verpleegdossier te integreren en kan standaard bij elke patiënt op de spoedgevallendienst afgenomen worden

Course and prognosis of recovery for chronic non-specific low back pain: design, therapy program and baseline data of a prospective cohort study

Background: There has been increasing focus on factors predicting the development of chronic musculoskeletal disorders. For patients already experiencing chronic non-specific low back pain it is also relevant to investigate which prognostic factors predict recovery. We present the design of a cohort study that aims to determine the course and prognostic factors for recovery in patients with chronic non-specific low back pain. Methods/Design. All participating patients were recruited (Jan 2003-Dec 2008) from the same rehabilitation centre and were evaluated by means of (postal) questionnaires and physical examinations at baseline, during the 2-month therapy program, and at 5 and 12 months after start of therapy. The therapy protocol at the rehabilitation centre used a bio-psychosocial approach to stimulate patients to adopt adequate (movement) behaviour aimed at physical and functional recovery. The program is part of regular care and consists of 16 sessions of 3 hours each, over an 8-week period (in total 48 hours), followed by a 3-month self-management program. The primary outcomes are low back pain intensity, disability, quality of life, patient's global perceived effect of recovery, and participation in work. Baseline characteristics include information on socio-demographics, low back pain, employment status, and additional clinical items status such as fatigue, duration of activities, and fear of kinesiophobia. Prognostic variables are determined for recovery at short-term (5 months) and long-term (12 months) follow-up after start of therapy. Discussion. In a routine clinical setting it is important to provide patients suffering from chronic non-specific low back pain with adequate information about the prognosis of their complaint

Individualised variable-interval risk-based screening for sight-threatening diabetic retinopathy: the Liverpool Risk Calculation Engine

Aims/hypothesis Individualised variable-interval risk-based screening offers better targeting and improved cost-effectiveness in screening for diabetic retinopathy. We developed a generalisable risk calculation engine (RCE) to assign personalised intervals linked to local population characteristics, and explored differences in assignment compared with current practice. Methods Data from 5 years of photographic screening and primary care for people with diabetes, screen negative at the first of > 1 episode, were combined in a purpose-built near-real-time warehouse. Covariates were selected from a dataset created using mixed qualitative/quantitative methods. Markov modelling predicted progression to screen-positive (referable diabetic retinopathy) against the local cohort history. Retinopathy grade informed baseline risk and multiple imputation dealt with missing data. Acceptable intervals (6, 12, 24 months) and risk threshold (2.5%) were established with patients and professional end users. Results Data were from 11,806 people with diabetes (46,525 episodes, 388 screen-positive). Covariates with sufficient predictive value were: duration of known disease, HbA1c, age, systolic BP and total cholesterol. Corrected AUC (95% CIs) were: 6 months 0.88 (0.83, 0.93), 12 months 0.90 (0.87, 0.93) and 24 months 0.91 (0.87, 0.94). Sensitivities/specificities for a 2.5% risk were: 6 months 0.61, 0.93, 12 months 0.67, 0.90 and 24 months 0.82, 0.81. Implementing individualised RCE-based intervals would reduce the proportion of people becoming screen-positive before the allocated screening date by > 50% and the number of episodes by 30%. Conclusions/interpretation The Liverpool RCE shows sufficient performance for a local introduction into practice before wider implementation, subject to external validation. This approach offers potential enhancements of screening in improved local applicability, targeting and cost-effectiveness

A prediction rule to stratify mortality risk of patients with pulmonary tuberculosis

Tuberculosis imposes high human and economic tolls, including in Europe. This study was conducted to develop a severity assessment tool for stratifying mortality risk in pulmonary tuberculosis (PTB) patients. A derivation cohort of 681 PTB cases was retrospectively reviewed to generate a model based on multiple logistic regression analysis of prognostic variables with 6-month mortality as the outcome measure. A clinical scoring system was developed and tested against a validation cohort of 103 patients. Five risk features were selected for the prediction model: hypoxemic respiratory failure (OR 4.7, 95% CI 2.8-7.9), age >= 50 years (OR 2.9, 95% CI 1.7-4.8), bilateral lung involvement (OR 2.5, 95% CI 1.44.4), >= 1 significant comorbidity-HIV infection, diabetes mellitus, liver failure or cirrhosis, congestive heart failure and chronic respiratory disease-(OR 2.3, 95% CI 1.3-3.8), and hemoglobin = 6) mortality risk. The mortality associated with each group was 2.9%, 22.9% and 53.9%, respectively. The model performed equally well in the validation cohort. We provide a new, easy-to-use clinical scoring system to identify PTB patients with high-mortality risk in settings with good healthcare access, helping clinicians to decide which patients are in need of closer medical care during treatment.This work was supported by Fundacao Amelia de Mello/Jose de Mello Saude and Sociedade Portuguesa de Pneumologia (SPP). This work was developed under the scope of the project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). NSO is a FCT (Fundacao para a Ciencia e Tecnologia) investigator. MS is an Associate FCT Investigator. The fundershad no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Research methods for subgrouping low back pain

<p>Abstract</p> <p>Background</p> <p>There is considerable clinician and researcher interest in whether the outcomes for patients with low back pain, and the efficiency of the health systems that treat them, can be improved by 'subgrouping research'. Subgrouping research seeks to identify subgroups of people who have clinically important distinctions in their treatment needs or prognoses. Due to a proliferation of research methods and variability in how subgrouping results are interpreted, it is timely to open discussion regarding a conceptual framework for the research designs and statistical methods available for subgrouping studies (a method framework). The aims of this debate article are: (1) to present a method framework to inform the design and evaluation of subgrouping research in low back pain, (2) to describe method options when investigating prognostic effects or subgroup treatment effects, and (3) to discuss the strengths and limitations of research methods suitable for the hypothesis-setting phase of subgroup studies.</p> <p>Discussion</p> <p>The proposed method framework proposes six phases for studies of subgroups: studies of assessment methods, hypothesis-setting studies, hypothesis-testing studies, narrow validation studies, broad validation studies, and impact analysis studies. This framework extends and relabels a classification system previously proposed by McGinn et al (2000) as suitable for studies of clinical prediction rules. This extended classification, and its descriptive terms, explicitly anchor research findings to the type of evidence each provides. The inclusive nature of the framework invites appropriate consideration of the results of diverse research designs. Method pathways are described for studies designed to test and quantify prognostic effects or subgroup treatment effects, and examples are discussed. The proposed method framework is presented as a roadmap for conversation amongst researchers and clinicians who plan, stage and perform subgrouping research.</p> <p>Summary</p> <p>This article proposes a research method framework for studies of subgroups in low back pain. Research designs and statistical methods appropriate for sequential phases in this research are discussed, with an emphasis on those suitable for hypothesis-setting studies of subgroups of people seeking care.</p

Automatic Monitoring of Pig Locomotion Using Image Analysis

The purpose of this study is to investigate the feasibility and validity of an automated image processing method to detect the locomotion of pigs housed under experimental conditions. Top-view video images were captured for forty piglets, housed ten per pen. On average, piglets had a weight of 27 kg (SD = 4.4 kg) at the start of experiments and 40kg (SD=6.5) at the end. Each pen was monitored by a top-view CCD camera. The image analysis protocol to automatically quantify locomotion consisted localising pigs through background subtraction and tracking them over time. To validate the accuracy of detecting pigs “In Locomotion” or “Not In Locomotion”, they were compared to offline manually labelled behavioural data ('In Locomotion' versus 'Not In Locomotion'). This is the first study to show that locomotion of “pigs in a group” can be determined using image analysis with an accuracy of 89.8 %. Since locomotion is known to be associated with issues such as lameness, careful monitoring can give an accurate indication of the health and welfare of pigs.publisher: Elsevier articletitle: Automatic monitoring of pig locomotion using image analysis journaltitle: Livestock Science articlelink: http://dx.doi.org/10.1016/j.livsci.2013.11.007 content_type: article copyright: Copyright © 2013 Elsevier B.V. All rights reserved.status: publishe

Automatic Monitoring of Pig Activity Using Image Analysis

The purpose of this study is to investigate the feasibility and validity of an automated image processing method to detect the active pigs housed under experimental conditions. Top-view video images were captured for forty piglets, housed ten per pen. On average, piglets had a weight of 27 kg (SD = 4.4 kg) kilograms at the start of experiments and 40kg (SD=6.5) at the end. Each pen was monitored by a top-view CCD camera. The image analysis protocol to automatically quantify activity consisted of several steps. First, in order to localise the pigs, ellipse fitting algorithms were employed. Subsequently, activity was calculated by subtracting image background and comparing binarised images. To validate the results, they were compared to manually labelled behavioural data ('active' versus 'inactive'). This is the first study to show that active pigs in a group can be detected using image analysis with an accuracy of 89.8 %. Since being active is known to be associated with the behavioural status, careful monitoring can give an indication of the health and welfare of pigs.status: publishe