Abstract Background. Fever in children is common and mostly caused by self-limiting infections. However, parents of febrile children often consult in general practice, in particular during out-of-hours care. To improve management, it is important to understand experiences of GPs managing these consultations. Objective. To describe GPs’ experiences regarding management of childhood fever during out-ofhours care. Methods. A descriptive qualitative study using purposeful sampling, five focus group discussions were held among 37 GPs. Analysis was based on constant comparative technique using open and axial coding. Results. Main categories were: (i) Workload and general experience; (ii) GPs’ perceptions of determinants of consulting behaviour; (iii) Parents’ expectations from the GP’s point of view; (iv) Antibiotic prescribing decisions; (v) Uncertainty of GPs versus uncertainty of parents and (vi) Information exchange during the consultation. GPs felt management of childhood fever imposes a considerable workload. They perceived a mismatch between parental concerns and their own impression of illness severity, which combined with time–pressure can lead to frustration. Diagnostic uncertainty is driven by low incidences of serious infections and dealing with parental demand for antibiotics is still challenging. Conclusion. Children with a fever account for a high workload during out-of-hours GP care which provides a diagnostic challenge due to the low incidence of serious illnesses and lacking longterm relationship. This can lead to frustration and drives antibiotics prescription rates. Improving information exchange during consultations and in the general public to young parents, could help provide a safety net thereby enhancing self-management, reducing consultations and workload, and subsequent antibiotic prescriptions.
Objectives : To systematically review the literature regarding the reliability and validity of assessment methods available in primary care for bladder outlet obstruction or benign prostatic obstruction in men with lower urinary tract symptoms (LUTS). Design : Systematic review with best evidence synthesis. Setting : Primary care. Participants : Men with LUTS due to bladder outlet obstruction or benign prostatic obstruction. Review methods: PubMed, Ebsco/CINAHL and Embase databases were searched for studies on the validity and reliability of assessment methods for bladder outlet obstruction and benign prostatic obstruction in primary care. Methodological quality was assessed with the COSMIN checklist. Studies with poor methodology were excluded from the best evidence synthesis. Results : Of the 5644 studies identified, 61 were scored with the COSMIN checklist, 37 studies were included in the best evidence synthesis, 18 evaluated bladder outlet obstruction and 17 benign prostatic obstruction, 2 evaluated both. Overall, reliability was poorly evaluated. Transrectal and transabdominal ultrasound showed moderate to good validity to evaluate bladder outlet obstruction. Measured prostate volume with these ultrasound methods, to identify benign prostatic obstruction, showed moderate to good accuracy, supported by a moderate to high level of evidence. Uroflowmetry for bladder outlet obstruction showed poor to moderate diagnostic accuracy, depending on used cut-off values. Questionnaires were supported by high-quality evidence, although correlations and diagnostic accuracy were poor to moderate compared with criterion tests. Other methods were supported by low level evidence. Conclusion :Clinicians in primary care can incorporate transabdominal and transrectal ultrasound or uroflowmetry in the evaluation of men with LUTS but should not solely rely on these methods as the diagnostic accuracy is insufficient and reliability remains insufficiently researched. Low-to-moderate levels of evidence for most assessment methods were due to methodological shortcomings and inconsistency in the studies. This highlights the need for better study designs in this domain.
MULTIFILE
Current methods for energy diagnosis in heating, ventilation and air conditioning (HVAC) systems are not consistent with process and instrumentation diagrams (P&IDs) as used by engineers to design and operate these systems, leading to very limited application of energy performance diagnosis in practice. In a previous paper, a generic reference architecture – hereafter referred to as the 4S3F (four symptoms and three faults) framework – was developed. Because it is closely related to the way HVAC experts diagnose problems in HVAC installations, 4S3F largely overcomes the problem of limited application. The present article addresses the fault diagnosis process using automated fault identification (AFI) based on symptoms detected with a diagnostic Bayesian network (DBN). It demonstrates that possible faults can be extracted from P&IDs at different levels and that P&IDs form the basis for setting up effective DBNs. The process was applied to real sensor data for a whole year. In a case study for a thermal energy plant, control faults were successfully isolated using balance, energy performance and operational state symptoms. Correction of the isolated faults led to annual primary energy savings of 25%. An analysis showed that the values of set probabilities in the DBN model are not outcome-sensitive. Link to the formal publication via its DOI https://doi.org/10.1016/j.enbuild.2020.110289
Production processes can be made ‘smarter’ by exploiting the data streams that are generated by the machines that are used in production. In particular these data streams can be mined to build a model of the production process as it was really executed – as opposed to how it was envisioned. This model can subsequently be analyzed and stress-tested to explore possible causes of production prob-lems and to analyze what-if scenarios, without disrupting the production process itself. It has been shown that such models can successfully be used to diagnose possible causes of production problems, including scrap products and machine defects. Ideally, they can even be used to model and analyze production processes that have not been implemented yet, based on data from existing production pro-cesses and techniques from artificial intelligence that can predict how the new process is likely to be-have in practice in terms of data that its machines generate. This is especially important in mass cus-tomization processes, where the process to create each product may be unique, and can only feasibly be tested using model- and data-driven techniques like the one proposed in this project. Against this background, the goal of this project is to develop a method and toolkit for mining, mod-elling and analyzing production processes, using the time series data that is generated by machines, to: (i) analyze the performance of an existing production process; (ii) diagnose causes of production prob-lems; and (iii) certify that a new – not yet implemented – production process leads to high-quality products. The method is developed by researching and combining techniques from the area of Artificial Intelli-gence with techniques from Operations Research. In particular, it uses: process mining to relate time series data to production processes; queueing networks to determine likely paths through the produc-tion processes and detect anomalies that may be the cause of production problems; and generative adversarial networks to generate likely future production scenarios and sample scenarios of production problems for diagnostic purposes. The techniques will be evaluated and adapted in implementations at the partners from industry, using a design science approach. In particular, implementations of the method are made for: explaining production problems; explaining machine defects; and certifying the correct operation of new production processes.
Routine neuropathology diagnostic methods are limited to histological staining techniques or directed PCR for pathogen detection and microbial cultures of brain abscesses are negative in one-third of the cases. Fortunately, due to improvements in technology, metagenomic sequencing of a conserved bacterial gene could provide an alternative diagnostic method. For histopathological work up, formalin-fixed paraffin-embedded (FFPE) tissue with highly degraded nucleic acids is the only material being available. Innovative amplicon-specific next-generation sequencing (NGS) technology has the capability to identify pathogens based on the degraded DNA within a few hours. This approach significantly accelerates diagnostics and is particularly valuable to identify challenging pathogens. This ensures optimal treatment for the patient, minimizing unnecessary health damage. Within this project, highly conserved primers in a universal PCR will be used, followed by determining the nucleotide sequence. Based on the obtained data, it is then precisely determined which microorganism(s) is/are responsible for the infection, even in cases of co-infection with multiple pathogens. This project will focus to answer the following research question; how can a new form of rapid molecular diagnostics contribute to the identification of microbial pathogens in CNS infections? The SME partner Molecular Biology Systems B.V. (MBS) develops and sells equipment for extremely rapid execution of the commonly used PCR. In this project, the lectorate Analysis Techniques in the Life Sciences (Avans) will, in collaboration with MBS, Westerdijk Institute (WI-KNAW) and the Institute of Neuropathology (Münster, DE) establish a new molecular approach for fast diagnosis within CNS infections using this MBS technology. This enables the monitoring of infectious diseases in a fast and user-friendly manner, resulting in an improved treatment plan.
New innovative methods to determine the DNA sequences of different bacterial species are rising. In the field of microbiology, these methods are very important since it is now possible to determine all the genetic characteristics of the bacterium in one step! This enables to define e.g. the species family, drug resistance or relatedness to other bacteria in outbreak evaluations which is necessary to efficiently treat the bacteria or target potential outbreaks. For many years, PCR-based methods have been the technique of choice to determine DNA sequences (including next-generation sequencing techniques). Recently, a new technique has been introduced to the market that is based on single molecule real-time sequencing (SMRT) with the possibility to determine the DNA sequence of a bacterium. This SMRT MinION sequencing technique is housed on an USB stick and is known for its user-friendliness and huge data output. However, before such a new technique can be implemented and presented in laboratories and used for educational purposes, methods should be harmonized and evaluated to proof its applicability. Harmonisation of the methodology regarding new laboratory techniques is very important to be able to compare results generated by different laboratories. A single consistent protocol, applied in each lab, is essential to obtain the best results in interlaboratory comparisons. During this KIEM-hbo project, we – i.e. Avans UAS, Maastricht University Medical Center and the company IS-diagnostics – will determine the DNA sequence of bacterial species and mixes thereof with a harmonized protocol for an interlaboratory comparison. We will compare this technique to the IS-PRO, an existing technology. Finally a workshop will be organized for medical technicians and other SMRT sequencing users to evaluate the protocols. This will, generate an up-to-date and harmonized sequencing protocol which can be expanded to future research and diagnostics in the different areas.
