Dialysis-associated peritonitis in children

Peritonitis remains a frequent complication of peritoneal dialysis in children and is the most common reason for technique failure. The microbiology is characterized by a predominance of Gram-positive organisms, with fungi responsible for less than 5% of episodes. Data collected by the International Pediatric Peritonitis Registry have revealed a worldwide variation in the bacterial etiology of peritonitis, as well as in the rate of culture-negative peritonitis. Risk factors for infection include young age, the absence of prophylactic antibiotics at catheter placement, spiking of dialysis bags, and the presence of a catheter exit-site or tunnel infection. Clinical symptoms at presentation are somewhat organism specific and can be objectively assessed with a Disease Severity Score. Whereas recommendations for empiric antibiotic therapy in children have been published by the International Society of Peritoneal Dialysis, epidemiologic data and antibiotic susceptibility data suggest that it may be desirable to take the patient- and center-specific history of microorganisms and their sensitivity patterns into account when prescribing initial therapy. The vast majority of patients are treated successfully and continue peritoneal dialysis, with the poorest outcome noted in patients with peritonitis secondary to Gram-negative organisms or fungi and in those with a relapsing infection

Fast Track Algorithm: How To Differentiate A “Scleroderma Pattern” From A “Non-Scleroderma Pattern”

Objectives: This study was designed to propose a simple “Fast Track algorithm” for capillaroscopists of any level of experience to differentiate “scleroderma patterns” from “non-scleroderma patterns” on capillaroscopy and to assess its inter-rater reliability. Methods: Based on existing definitions to categorise capillaroscopic images as “scleroderma patterns” and taking into account the real life variability of capillaroscopic images described standardly according to the European League Against Rheumatism (EULAR) Study Group on Microcirculation in Rheumatic Diseases, a fast track decision tree, the “Fast Track algorithm” was created by the principal expert (VS) to facilitate swift categorisation of an image as “non-scleroderma pattern (category 1)” or “scleroderma pattern (category 2)”. Mean inter-rater reliability between all raters (experts/attendees) of the 8th EULAR course on capillaroscopy in Rheumatic Diseases (Genoa, 2018) and, as external validation, of the 8th European Scleroderma Trials and Research group (EUSTAR) course on systemic sclerosis (SSc) (Nijmegen, 2019) versus the principal expert, as well as reliability between the rater pairs themselves was assessed by mean Cohen's and Light's kappa coefficients. Results: Mean Cohen's kappa was 1/0.96 (95% CI 0.95-0.98) for the 6 experts/135 attendees of the 8th EULAR capillaroscopy course and 1/0.94 (95% CI 0.92-0.96) for the 3 experts/85 attendees of the 8th EUSTAR SSc course. Light's kappa was 1/0.92 at the 8th EULAR capillaroscopy course, and 1/0.87 at the 8th EUSTAR SSc course. C Conclusion: For the first time, a clinical expert based fast track decision algorithm has been developed to differentiate a “non-scleroderma” from a “scleroderma pattern” on capillaroscopic images, demonstrating excellent reliability when applied by capillaroscopists with varying levels of expertise versus the principal expert and corroborated with external validation.Wo