Mobile applications (apps) can be very useful software on smartphones for all aspects of people's lives. Chronic diseases, such as diabetes, can be made manageable with the support of mobile apps. Applications on smartphones can also help people with diabetes to control their fitness and health. A systematic review of free apps in the English language for smartphones in three of the most popular mobile app stores: Google Play (Android), App Store (iOS) and Windows Phone Store, was performed from November to December 2015. The review of freely available mobile apps for self-management of diabetes was conducted based on the criteria for promoting diabetes self-management as defined by Goyal and Cafazzo (monitoring blood glucose level and medication, nutrition, physical exercise and body weight). The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) was followed. Three independent experts in the field of healthcare-related mobile apps were included in the assessment for eligibility and testing phase. We tested and evaluated 65 apps (21 from Google Play Store, 31 from App Store and 13 from Windows Phone Store). Fifty-six of these apps did not meet even minimal requirements or did not work properly. While a wide selection of mobile applications is available for self-management of diabetes, current results show that there are only nine (5 from Google Play Store, 3 from App Store and 1 from Windows Phone Store) out of 65 reviewed mobile apps that can be versatile and useful for successful self-management of diabetes based on selection criteria. The levels of inclusion of features based on selection criteria in selected mobile apps can be very different. The results of the study can be used as a basis to prvide app developers with certain recommendations. There is a need for mobile apps for self-management of diabetes with more features in order to increase the number of long-term users and thus influence better self-management of the disease.

The objective of this study was to survey health professionals to investigate their knowledge of probiotics. An online survey was conducted to gather data on the knowledge of health professionals. The online survey was distributed via email and social media platforms using snowball sampling. A total of 1066 health professionals (859; 80.6% female) from 30 countries responded to the survey. Most of the respondents evaluated their knowledge of probiotics as medium (36.4%) or good (36.2%). Only 8.9% of the respondents rated it as excellent. No statistical difference in knowledge was found between male and female health professionals. Over 80% of pharmacists, allied health professionals, medical doctors and dentists, and other health professionals knew the correct definition of probiotics as “live microorganisms that, when administered in adequate amounts, confer a health benefit on the host”, whereas three quarters of registered nurses and midwives and less than two thirds of psychologists identified the correct definition. Statistically, more female than male health professionals knew the correct definition of probiotics. The most frequently recognized species of bacteria containing probiotic strains were Lactobacillus acidophilus (92%), Bifidobacterium bifidum (82%), and Lactobacillus rhamnosus (62%). The opinions on when it is best to take probiotics were different (χ2 = 28.375; p < 0.001), with 90.2% of respondents identifying that probiotics have beneficial effects if taken during antibiotic therapy, 83.5% for diarrhea, 70.6% for constipation, 63.3% before traveling abroad, and 60.4% for treating allergies. Almost 79% of health professionals involved in this study have advised their patients to use probiotics and 57.5% of the respondents wanted to learn more about probiotics. All things considered, health professionals have a medium level of knowledge of probiotics, which could be improved by the implementation of targeted learning programs. As probiotics have many beneficial effects in a wide range of health areas, health professionals need to adopt the use of probiotics in clinical practice.

ObjectiveThe aim of the present study was to identify all currently available screening and assessment tools for detection of malnutrition in hospitalised children, and to identify the most useful tools on the basis of published validation studies.DesignSystematic review.Data sourcesPubMed, CINAHL and MEDLINE were searched up to October 2017.Eligibility criteria for selecting studiesStudies in English that reported sensitivity, specificity and positive/negative predictive values (PPVs/NPVs) in the paediatric population were eligible for inclusion.Data extraction and synthesisTwo authors independently screened all of the studies identified, and extracted the data. The methodological qualities of the studies included were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool.ResultsThe 26 validation studies that met the inclusion criteria for this systematic review used eight screening and three assessment tools. The number of participants varied from 32 to 14 477. There was considerable variability in the chosen reference standards, which prevented direct comparisons of the predictive performances of the tools. Anthropometric measurements were used as reference standards in 16 of the identified studies, and full nutritional assessment in 5. The Pediatric Yorkhill Malnutrition Score (PYMS) screening tool performed better than Screening Tool for the Assessment of Malnutrition and Screening Tool for Risk On Nutritional status and Growth when compared in terms of anthropometric measurements, especially for body mass index (Se=90.9, Sp=81.9) and triceps skinfold thickness (Se=80.0, Sp=75.0). However, low PPVs indicated the problem of overprediction of positive cases, which was typical for all of the studies that used anthropometric measurements as the reference standard.ConclusionsThis systematic review identifies the need for definition of the gold standard for validation of screening tools. Anthropometry measurements using WHO or Centers for Disease Control and Prevention growth charts should be considered as the possible reference standard in future validation studies. We would recommend the use of PYMS for hospitalised paediatric patients without chronic conditions, in combination with full nutritional assessment.PROSPERO registration numberCRD42017077477.

Objectives To assess the added value of 3D T2-weighted imaging (T2WI) over conventional 2D T2WI in diagnosing extracapsular extension (ECE). Methods Seventy-five patients undergoing 3-T MRI before radical prostatectomy were included. PI-RADS ≥ 4 lesions were assessed for ECE on 2D T2W images using a 5-point Likert scale (1 = no ECE, 5 = definite ECE) and the length of tumour prostatic capsular contact. A second read using 3D T2W images and reformats evaluated ECE and the maximal 3D capsular contact length and surface. Results One hundred six lesions were identified at MRI. ECE was confirmed by histology in 54% (57/106) of lesions and 64% (48/75) of patients. Sensitivity and specificity for 3D T2 reads were 75.4% versus 64.9% ( p = 0.058), respectively, and 83.7% versus 85.7% ( p = 0.705) for 2D T2 reads, respectively. 3D T2W reads showed significantly higher mean subjective Likert scores of 3.7 ± 1.4 versus 3.3 ± 1.4 ( p = 0.001) in ECE-positive lesions and lower mean Likert score of 1.5 ± 1 versus 1.6 ± 0.9 ( p = 0.27) in ECE-negative lesions compared with 2D T2W reads. 3D contact significantly increased sensitivity from 59.6 to 73.7% ( p = 0.03), whilst maintaining the same specificity of 87.8% ( p = 1). High-grade group tumours (≥ Gleason 4 + 3) showed significantly higher ECE prevalence than low-grade tumours (88% versus 44%, p < 0.001) and a positive predictive value (PPV) for ECE of 90.9% with ≥ 5 mm of contact versus PPV of 90.4% at ≥ 12.5 mm for lower grade tumours. Conclusions 3D T2WI significantly increases sensitivity and confidence in calling ECE. The capsular contact length threshold differed between low- and high-grade cancers. Key Points • 3D capsular contact length and 3D surface contact significantly increased sensitivity in diagnosing ECE. • 3D T2W reads significantly increased reader confidence in calling ECE. • Thresholds for capsular contact length differed between low-grade and high-grade cancers. Electronic supplementary material The online version of this article (10.1007/s00330-019-06070-6) contains supplementary material, which is available to authorized users.

This study describes a novel approach to solve the surgical site infection (SSI) classification problem. Feature engineering has traditionally been one of the most important steps in solving complex classification problems, especially in cases with temporal data. The described novel approach is based on abstraction of temporal data recorded in three temporal windows. Maximum likelihood L1-norm (lasso) regularization was used in penalized logistic regression to predict the onset of surgical site infection occurrence based on available patient blood testing results up to the day of surgery. Prior knowledge of predictors (blood tests) was integrated in the modelling by introduction of penalty factors depending on blood test prices and an early stopping parameter limiting the maximum number of selected features used in predictive modelling. Finally, solutions resulting in higher interpretability and cost-effectiveness were demonstrated. Using repeated holdout cross-validation, the baseline C-reactive protein (CRP) classifier achieved a mean AUC of 0.801, whereas our best full lasso model achieved a mean AUC of 0.956. Best model testing results were achieved for full lasso model with maximum number of features limited at 20 features with an AUC of 0.967. Presented models showed the potential to not only support domain experts in their decision making but could also prove invaluable for improvement in prediction of SSI occurrence, which may even help setting new guidelines in the field of preoperative SSI prevention and surveillance.