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CDSSs are being continuously developed and integrated into routine clinical practice as they assist clinicians and radiologists in dealing with an enormous amount of medical data, reduce clinical errors, and improve diagnostic capabilities. They assist detection, classification, and grading of brain tumours as well as alert physicians of treatment change plans. The aim of this systematic review is to identify various CDSSs that are used in brain tumour diagnosis and prognosis and rely on data captured by any imaging modality. Based on the 2020 preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol, the literature search was conducted in PubMed and Engineering Village Compendex databases. Different types of CDSSs identified through this review include Curiam BT, FASMA, MIROR, HealthAgents, and INTERPRET, among others. This review also examines various CDSS tool types, system features, techniques, accuracy, and outcomes, to provide the latest evidence available in the field of neuro-oncology. An overview of such CDSSs used to support clinical decision-making in the management and treatment of brain tumours, along with their benefits, challenges, and future perspectives has been provided. Although a CDSS improves diagnostic capabilities and healthcare delivery, there is lack of specific evidence to support these claims. The absence of empirical data slows down both user acceptance and evaluation of the actual impact of CDSS on brain tumour management. Instead of emphasizing the advantages of implementing CDSS, it is important to address its potential drawbacks and ethical implications. By doing so, it can promote the responsible use of CDSS and facilitate its faster adoption in clinical settings.

Background Image segmentation is an essential step in the analysis and subsequent characterisation of brain tumours through magnetic resonance imaging. In the literature, segmentation methods are empowered by open-access magnetic resonance imaging datasets, such as the brain tumour segmentation dataset. Moreover, with the increased use of artificial intelligence methods in medical imaging, access to larger data repositories has become vital in method development. Purpose To determine what automated brain tumour segmentation techniques can medical imaging specialists and clinicians use to identify tumour components, compared to manual segmentation. Methods We conducted a systematic review of 572 brain tumour segmentation studies during 2015–2020. We reviewed segmentation techniques using T1-weighted, T2-weighted, gadolinium-enhanced T1-weighted, fluid-attenuated inversion recovery, diffusion-weighted and perfusion-weighted magnetic resonance imaging sequences. Moreover, we assessed physics or mathematics-based methods, deep learning methods, and software-based or semi-automatic methods, as applied to magnetic resonance imaging techniques. Particularly, we synthesised each method as per the utilised magnetic resonance imaging sequences, study population, technical approach (such as deep learning) and performance score measures (such as Dice score). Statistical tests We compared median Dice score in segmenting the whole tumour, tumour core and enhanced tumour. Results We found that T1-weighted, gadolinium-enhanced T1-weighted, T2-weighted and fluid-attenuated inversion recovery magnetic resonance imaging are used the most in various segmentation algorithms. However, there is limited use of perfusion-weighted and diffusion-weighted magnetic resonance imaging. Moreover, we found that the U-Net deep learning technology is cited the most, and has high accuracy (Dice score 0.9) for magnetic resonance imaging-based brain tumour segmentation. Conclusion U-Net is a promising deep learning technology for magnetic resonance imaging-based brain tumour segmentation. The community should be encouraged to contribute open-access datasets so training, testing and validation of deep learning algorithms can be improved, particularly for diffusion- and perfusion-weighted magnetic resonance imaging, where there are limited datasets available.

Abstract Public access defibrillation initiatives make automated external defibrillators available to the public. This facilitates earlier defibrillation of out-of-hospital cardiac arrest victims and could save many lives. It is currently only used for a minority of cases. The aim of this systematic review was to identify barriers and facilitators to public access defibrillation. A comprehensive literature review was undertaken defining formal search terms for a systematic review of the literature in March 2017. Studies were included if they considered reasons affecting the likelihood of public access defibrillation and presented original data. An electronic search strategy was devised searching MEDLINE and EMBASE, supplemented by bibliography and related-article searches. Given the low-quality and observational nature of the majority of articles, a narrative review was performed. Sixty-four articles were identified in the initial literature search. An additional four unique articles were identified from the electronic search strategies. The following themes were identified related to public access defibrillation: knowledge and awareness; willingness to use; acquisition and maintenance; availability and accessibility; training issues; registration and regulation; medicolegal issues; emergency medical services dispatch-assisted use of automated external defibrillators; automated external defibrillator-locator systems; demographic factors; other behavioural factors. In conclusion, several barriers and facilitators to public access defibrillation deployment were identified. However, the evidence is of very low quality and there is not enough information to inform changes in practice. This is an area in urgent need of further high-quality research if public access defibrillation is to be increased and more lives saved. PROSPERO registration number CRD42016035543.

To identify known risk factors for mortality for adult patients, discharged from hospital with diabetes. The systematic review was based on the PRISMA protocol. Studies were identified through EMBASE & MEDLINE databases. The inclusion criteria were papers that were published over the last 6 years, in English language, and focused on risk factors of mortality in adult patients with diabetes, after they were discharged from hospitals. This was followed by data extraction “with quality assessment and semi-quantitative synthesis according to PRISMA guidelines”. There were 35 studies identified, considering risk factors relating to mortality for patients, discharged from hospital with diabetes. These studies are distributed internationally. 48 distinct statistically significant risk factors for mortality can be identified. Risk factors can be grouped into the following categories; demographic, socioeconomic, lifestyle, patient medical, inpatient stay, medication related, laboratory results, and gylcaemic status. These risk factors can be further divided into risk factors identified in generalized populations of patients with diabetes, compared to specific sub-populations of people with diabetes. A relatively small number of studies have considered risk factors relating to mortality for patients, discharged from hospital with a diagnosis of diabetes. Mortality is an important outcome, when considering discharge from hospital with diabetes. However, there has only been limited consideration within the research literature. •Mortality after hospital discharge, is an important outcome for people with diabetes.•This is the 1st systematic review of mortality risk factors post diabetes discharge.•We report 48 distinct statistically significant risk factors.•The literature is at an early stage of maturity.

In April 2020, during the peak of the coronavirus disease 2019 (COVID-19) pandemic in Europe, a cluster of children with hyperinflammatory shock with features similar to Kawasaki disease and toxic shock syndrome was reported in England* (1). The patients' signs and symptoms were temporally associated with COVID-19 but presumed to have developed 2-4 weeks after acute COVID-19; all children had serologic evidence of infection with SARS-CoV-2, the virus that causes COVID-19 (1). The clinical signs and symptoms present in this first cluster included fever, rash, conjunctivitis, peripheral edema, gastrointestinal symptoms, shock, and elevated markers of inflammation and cardiac damage (1). On May 14, 2020, CDC published an online Health Advisory that summarized the manifestations of reported multisystem inflammatory syndrome in children (MIS-C), outlined a case definition, and asked clinicians to report suspected U.S. cases to local and state health departments. As of July 29, a total of 570 U.S. MIS-C patients who met the case definition had been reported to CDC. A total of 203 (35.6%) of the patients had a clinical course consistent with previously published MIS-C reports, characterized predominantly by shock, cardiac dysfunction, abdominal pain, and markedly elevated inflammatory markers, and almost all had positive SARS-CoV-2 test results. The remaining 367 (64.4%) of MIS-C patients had manifestations that appeared to overlap with acute COVID-19 (2-4), had a less severe clinical course, or had features of Kawasaki disease. Median duration of hospitalization was 6 days; 364 patients (63.9%) required care in an intensive care unit (ICU), and 10 patients (1.8%) died. As the COVID-19 pandemic continues to expand in many jurisdictions, clinicians should be aware of the signs and symptoms of MIS-C and report suspected cases to their state or local health departments; analysis of reported cases can enhance understanding of MIS-C and improve characterization of the illness for early detection and treatment.

ObjectivesTo measure pregnancy outcome following attendance at a recurrent miscarriage service and identify factors that influence outcome.DesignProspective, observational electronic cohort study.SettingParticipants attending a specialist recurrent miscarriage clinic, with a history of two or more pregnancy losses. 857 new patients attended over a 30-month period and were invited to participate. Participant data were recorded on a bespoke study database, ‘Tommy’s Net’.Participants777 women consented to participate (90.7% of new patients). 639 (82%) women continued within the cohort, and 138 were lost to follow-up. Mean age of active participants was 34 years for women and 37 years for partners, with a mean of 3.5 (1–19) previous pregnancy losses. Rates of obesity (maternal: 23.8%, paternal: 22.4%), smoking (maternal:7.4%, paternal: 19.4%) and alcohol consumption (maternal: 50%, paternal: 79.2%) were high and 55% of participants were not taking folic acid.Outcome measuresBiannual collection of pregnancy outcomes, either through prompted self-reporting, or existing hospital systems.Results639 (82%) women were followed up. 404 (83.4%) reported conception and 106 (16.6%) reported no pregnancy, at least 6 months following registration. Of those that conceived, 72.8% (294/404) had a viable pregnancy. Maternal smoking and body mass index (BMI) over 30 were significantly higher in those who did not conceive (p=0.001)ConclusionsTommy’s Net provides a secure electronic repository on data for couples with recurrent pregnancy loss and associated outcomes. The study identified that subfertility, as well as repeated miscarriage, maternal BMI and smoking status, contributed to failure to achieve live birth. Study findings may enable comparison of clinic outcomes and inform the development of a personalised holistic care package.

Purpose To investigate the outpatient and inpatient management of odontogenic infections among paediatric patients attending a university hospital. Methods A retrospective study (2013–2015) was carried out which involved retrieving relevant data from past records (manual/electronic) of paediatric patients (under 18-years-old) who presented with odontogenic infections to the Paediatric Dentistry and Oral and Maxillofacial clinic. Data collected was organised using descriptive statistics with SPSS version 12.0.1. Results A total of 153 patients were identified, of which 83.7% were managed as outpatients. Odontogenic infections were more common in females (52.9%) and preschool children (58.2%). The most cases were seen in 2014 and maximum number of cases per month was 12. Common presentations were pain (62.1%), intraoral swelling (37.9%) and spontaneous pus discharge from the tooth and/or surrounding tissues (67.3%) with higher involvement of primary right molars. Dental panoramic tomograph was the most common radiographic investigation done. Outpatients were commonly managed chairside with pulpal opening (46.1%) at the paediatric dental clinic and 7% underwent extraction under general anaesthesia in day-care setting. Inpatients were admitted for 3 days on average and most commonly definitive care was extraction under local/general anaesthesia (68%). There were 22.7% outpatients and 72.0% inpatients who were prescribed antibiotics. Conclusions Overall, treatment and medications prescribed adhered to current guidelines. There was a tendency to solely prescribe antibiotics in 8.6% of outpatients which is contrary to recommendations.

Objective: To review and summarize available evidence to compare the outcomes of home-based rehabilitation to inpatient rehabilitation for older patients with musculoskeletal conditions. Data sources: Relevant articles published prior to August 2011 were identified using MEDLINE, CINAHL and the Cochrane Central Register of Controlled Trials databases. Review methods: English-language articles that compared patient outcomes of home-based and inpatient rehabilitation for older adults were included. Outpatient care was not included as home-based or inpatient rehabilitation. Methodological quality of included studies was evaluated by two reviewers using the PEDro scale. Results: A systematic search yielded eight randomized controlled trials and four cohort studies. Older adults who received rehabilitation in the home had equal or higher gains than the inpatient group in function, cognition, and quality of life; they also reported higher satisfaction. Conclusion: Home-based rehabilitation may be an effective alternative for treating older patients with musculoskeletal conditions.

Penta-source acquisition is the latest addition to modern 3D Marine Seismic Acquisition Methods, a step ahead of the conventional dual and the more recent triple source acquisition methods. In the recent years, it has increasingly become popular due to its ability to deliver higher quality data enabled by finer cross-line sampling. This has been demonstrated through the Baxter Case Study (Hager et. all, 2016) where the 3D survey was successfully acquired and processed though the study area was relatively small. We present a case study from offshore Malaysia where penta-source acquisition method was adopted for the first time for a large 3D survey (~7000 sq.km) to enhance the data quality without compromising the acquisition efficiency. The survey was designed using a robust workflow to optimize acquisition parameters to meet the geophysical objectives, and executed safely and efficiently.

The genus Clavicornaltica Scherer 1974 consists of very small, soil-dwelling flea beetles in South, Southeast and East Asia. Due to their diminutive size and morphological similarities, very little is known about their ecology and taxonomical diversity. It is likely that further studies will reveal this genus to be much more speciose than the 30 species currently recognised. A new species of Clavicornaltica from Brunei Darussalam is described, C. mataikanensis Otani et al., sp. nov. This is the second species of this genus recorded from Ulu Temburong National Park.