Urinary tract infections (UTI) are among the most prevalent microbial diseases and their financial burden on society is substantial. The continuing increase of antibiotic resistance worldwide is alarming. Thus, well-tolerated, highly effective therapeutic alternatives are urgently needed. Although there is evidence indicating that bacteriophage therapy may be effective and safe for treating UTIs, the number of investigated patients is low and there is a lack of randomized controlled trials. This study is the first randomized, placebo-controlled, double-blind trial investigating bacteriophages in UTI treatment. Patients planned for transurethral resection of the prostate are screened for UTIs and enrolled if in urine culture eligible microorganisms ≥104 colony forming units/mL are found. Patients are randomized in a double-blind fashion to the 3 study treatment arms in a 1:1:1 ratio to receive either: a) bacteriophage (i.e. commercially available Pyo bacteriophage) solution, b) placebo solution, or c) antibiotic treatment according to the antibiotic sensitivity pattern. All treatments are intended for 7 days. No antibiotic prophylaxes will be given to the double-blinded treatment arms a) and b). As common practice, the Pyo bacteriophage cocktail is subjected to periodic adaptation cycles during the study. Urinalysis, urine culture, bladder and pain diary, and IPSS questionnaire will be completed prior to and at the end of treatment (i.e. after 7 days) or at withdrawal/drop out from the study. Patients with persistent UTIs will undergo antibiotic treatment according to antibiotic sensitivity pattern. Based on the high lytic activity and the potential of resistance optimization by direct adaptation of bacteriophages, and considering the continuing increase of antibiotic resistance worldwide, bacteriophage therapy is a very promising treatment option for UTIs. Thus, our randomized controlled trial investigating bacteriophages for treating UTIs will provide essential insights into this potentially revolutionizing treatment option. This study has been registered at clinicaltrials.gov ( www.clinicaltrials.gov/ct2/show/NCT03140085 ). April 27, 2017.

There are no reliable signs or symptoms that differentiate Mycoplasma pneumoniae (Mp) infection in community-acquired pneumonia (CAP) from other etiologies. Additionally, current diagnostic tests do not reliably distinguish between Mp infection and carriage. We previously determined that the measurement of Mp-specific immunoglobulin M antibody-secreting cells (ASCs) by enzyme-linked immunospot assay allowed for differentiation between infection and carriage. Using this new diagnostic test, we aimed to identify clinical and laboratory features associated with Mp infection. This is a prospective cohort study of children, 3–18 years of age, with CAP from 2016 to 2017. Clinical features and biomarkers were compared between Mp-positive and -negative groups by Mann-Whitney U test or Fisher exact test, as appropriate. Area under the receiver operating characteristic curve (AUC) differences and optimal thresholds were determined by using the DeLong test and Youden J statistic, respectively. Of 63 CAP patients, 29 were Mp-positive (46%). Mp positivity was statistically associated with older age (median, 8.6 vs 4.7 years), no underlying disease, family with respiratory symptoms, prior antibiotic treatment, prolonged prodromal respiratory symptoms and fever, and extrapulmonary (skin) manifestations. Lower levels of C-reactive protein, white blood cell count, absolute neutrophil count, and procalcitonin (PCT), specifically PCT 5 years (AUC = 0.77), prodromal fever and respiratory symptoms >6 days (AUC = 0.79), and PCT <0.25 μg/L (AUC = 0.81) improved diagnostic performance (AUC = 0.90) (P = .05). A combination of clinical features and biomarkers may aid physicians in identifying patients at high risk for Mp CAP.

Objective The number of mobile applications addressing health topics is increasing. Whether these apps underwent scientific evaluation is unclear. We comprehensively assessed papers investigating the diagnostic value of available diagnostic health applications using inbuilt smartphone sensors. Methods Systematic Review—MEDLINE, Scopus, Web of Science inclusive Medical Informatics and Business Source Premier (by citation of reference) were searched from inception until 15 December 2016. Checking of reference lists of review articles and of included articles complemented electronic searches. We included all studies investigating a health application that used inbuilt sensors of a smartphone for diagnosis of disease. The methodological quality of 11 studies used in an exploratory meta-analysis was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool and the reporting quality with the ’STAndards for the Reporting of Diagnostic accuracy studies' (STARD) statement. Sensitivity and specificity of studies reporting two-by-two tables were calculated and summarised. Results We screened 3296 references for eligibility. Eleven studies, most of them assessing melanoma screening apps, reported 17 two-by-two tables. Quality assessment revealed high risk of bias in all studies. Included papers studied 1048 subjects (758 with the target conditions and 290 healthy volunteers). Overall, the summary estimate for sensitivity was 0.82 (95 % CI 0.56 to 0.94) and 0.89 (95 %CI 0.70 to 0.97) for specificity. Conclusions The diagnostic evidence of available health apps on Apple’s and Google’s app stores is scarce. Consumers and healthcare professionals should be aware of this when using or recommending them. PROSPERO registration number 42016033049.