Bridging the Gap between Field Experiments and Machine Learning: The EC H2020 B-GOOD Project as a Case Study towards Automated Predictive Health Monitoring of Honey Bee Colonies.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping.

Exposure and risk assessment of acetamiprid in honey bee colonies under a real exposure scenario in Eucalyptus sp. landscapes.

Honey bee colonies have shown abnormal mortality rates over the last decades. Colonies are exposed to biotic and abiotic stressors including landscape changes caused by human pressure. Modern agriculture and even forestry, rely on pesticide inputs and these chemicals have been indicated as one of the major causes for colony losses. Neonicotinoids are a common class of pesticides used worldwide that are specific to kill insect pests, with acetamiprid being the only neonicotinoid allowed to be applied outdoors in the EU. To evaluate honeybees' exposure to acetamiprid under field conditions as well as to test the use of in-situ tools to monitor pesticide residues, two honeybee colonies were installed in five Eucalyptus sp. plantations having different area where Epik® (active substance: acetamiprid) was applied as in a common spraying event to control the eucalyptus weevil pest. Flowers, fresh nectar, honey bees and colony products samples were collected and analyzed for the presence of acetamiprid residues. Our main findings were that (1) acetamiprid residues were found in samples collected outside the spraying area, (2) the amount of residues transported into the colonies increased with the size of the sprayed area, (3) according to the calculated Exposure to Toxicity Ratio (ETR) values, spraying up to 22 % of honeybees foraging area does not harm the colonies, (4) colony products can be used as a valid tool to monitor colony accumulation of acetamiprid and (5) the use of Lateral Flow Devices (LFDs) can be a cheap, fast and easy tool to apply in the field, to evaluate the presence of acetamiprid residues in the landscape and colony products.

Nurse practitioners leading the way: An exploratory study on the added value of nurse practitioners in outpatient care in the Netherlands.

BACKGROUND: Many Dutch nurse practitioners (NPs) work together with physicians and specialized nurses (SNs) in outpatient clinics, although the latter have questioned the added value of NPs in the outpatient clinic. Clarification of the distinction between and the added value of both nursing professions in relation to each other could lead to optimal use of the unique competencies of each type of nurse. PURPOSE: To explore NPs' perspectives on their added value in relation to SNs in the outpatient clinic. METHODOLOGICAL ORIENTATION: Data were analyzed by Braun and Clarke's thematic analysis. The CanMEDS competences were used to identify the NPs' comments about their practice. SAMPLE: Twelve semi-structured interviews were conducted with NPs from two hospital settings. CONCLUSIONS: The added value of NPs was most evident in: nursing leadership, integrating care and cure and performing an expert level of nursing expertise, and competencies in science. To optimize their roles, NPs and SNs need to make all team members aware of their unique competences and promote role clarification. IMPLICATIONS FOR PRACTICE: This study provides barriers in barriers that influence optimal positioning of NPs within the interdisciplinary team, stresses the importance of discussion on the optimal skill mix within the interdisciplinary team, and describes the NPs' leadership role because this is the encompassing link between the main competencies of their practice. Addressing and overcoming these findings could improve the NPs' positioning and effective collaboration within (the outpatient clinic's) interprofessional teams.

CINGLE-trial: cochlear implantation for siNGLE-sided deafness, a randomised controlled trial and economic evaluation.

BACKGROUND: Individuals with single-sided deafness (SSD) have problems with speech perception in noise, localisation of sounds and with communication and social interaction in their daily life. Current treatment modalities (Contralateral Routing of Sound systems [CROS] and Bone Conduction Devices [BCD]) do not restore binaural hearing. Based on low level of evidence studies, CROS and BCD do not improve speech perception in noise or sound localisation. In contrast, cochlear implantation (CI) may overcome the limitations of CROS and BCD, as binaural input can be restored. Promising results have previously been achieved on speech perception in noise, sound localisation, tinnitus and quality of life. METHODS AND DESIGN: A single-center Randomised Controlled Trial (RCT) was designed to compare all treatment strategies for SSD. One hundred and twenty adult single-sided deaf patients (duration of deafness >3 months and maximum 10 years; pure tone average at 0.5, 1, 2, 4 kHz, deaf ear: threshold equal to or more than 70 dB, better ear: threshold of maximum 30 dB) will be included in this trial and randomised to CI, 'first BCD, then CROS' or 'first CROS, then BCD'-groups. After the trial period, patients in the two latter groups may choose with which treatment option they continue. Outcomes of interest are speech perception in noise, sound localization, tinnitus and quality of life. These outcomes will be measured during a baseline visit and at follow up visits, which will take place at 6, 12, 18, 24, 36, 48 and 60 months after onset of treatment. Furthermore, an economic evaluation will be performed and adverse events will be monitored. DISCUSSION: This RCT allows for a comparison between the two current treatment modalities for single-sided deafness and a new promising treatment strategy, CI, on a range of health outcomes: speech perception in noise, sound localization, tinnitus and quality of life. Additionally, we will be able to answer the question if the additional costs of CI are justified by increased benefits, when compared to current treatment strategies. This study will inform health policy makers with regard to reimbursement of CI. TRIAL REGISTRATION: Netherlands Trial Register (www.trialregister.nl): NTR4580.

Assessment of the quality of reporting of randomised controlled trials in otorhinolaryngologic literature - adherence to the CONSORT statement.

BACKGROUND: Randomised Controlled Trials (RCTs) are the preferred study design when comparing therapeutical interventions in medicine. To improve clarity, consistency and transparency of reporting RCTs, the Consolidated Standards of Reporting Trials (CONSORT) statement was developed. OBJECTIVES: (1) To assess the quality of reports and abstracts of RCTs in otorhinolaryngologic literature by using CONSORT checklists, (2) to compare the quality of reports and abstracts of otorhinolaryngologic RCTs between the top 5 general medical journals and top 5 otorhinolaryngologic journals, and (3) to formulate recommendations for authors and editors of otorhinolaryngologic ('ENT') journals. METHODS: Based on 2012 ISI Web of Knowledge impact factors, the top 5 general medical and ENT journals were selected. On 25 June 2014, using a highly sensitive Cochrane RCT filter and ENT filter, possibly relevant articles since January 1st, 2010 were retrieved and relevant RCTs were selected. We assessed how many CONSORT items were reported adequately in reports and abstracts and compared the two journal types. RESULTS: Otorhinolaryngologic RCTs (n = 15) published in general medical journals reported a mean of 92.1% (95% confidence interval: 89.5%-94.7%) of CONSORT items adequately, whereas RCTs (n = 18) published in ENT journals reported a mean of 71.8% (66.7%-76.8%) adequately (p < 0.001). For abstracts, means of 70.0% (63.7%-76.3%) and 32.3% (26.6-38.0%) were found respectively (p < 0.001). Large differences for specific items exist between the two journal types. CONCLUSION: The quality of reporting of RCTs in otorhinolaryngologic journals is suboptimal. RCTs published in general medical journals have a higher quality of reporting than RCTs published in ENT journals. We recommend authors to report their trial according to the CONSORT Statement and advise editors to endorse the CONSORT Statement and implement the CONSORT Statement in the editorial process to ensure more adequate reporting of RCTs and their abstracts.