More than one fourth of pediatric ED patients might rapidly, appropriately, and safely be referred for primary care or sent home by experienced pediatric nurses soon after arrival, thereby facilitating management of urgent and more appropriate patients. Evaluations by physicians were primarily required in young infants and for urgent medical conditions demanding qualified pediatric skills.

Background Positive margins after breast-conserving surgery (BCS) and subsequent second surgery are associated with increased costs and patient discomfort. The aim of this study was to develop a prediction model for positive margins based on risk factors available before surgery. Methods Patients undergoing BCS for in situ or invasive cancer between 2015 and 2016 at site A formed a development cohort; those operated during 2017 in site A and B formed two validation cohorts. MRI was not used routinely. Preoperative radiographic and tumour characteristics and method of operation were collected from patient charts. Multivariable logistic regression was used to develop a prediction model for positive margins including variables with discriminatory capacity identified in a univariable model. The discrimination and calibration of the prediction model was assessed in the validation cohorts, and a nomogram developed. Results There were 432 patients in the development cohort, and 190 and 157 in site A and B validation cohorts respectively. Positive margins were identified in 77 patients (17.8 per cent) in the development cohort. A non-linear transformation of mammographic tumour size and six variables (visible on mammography, ductal carcinoma in situ , lobular invasive cancer, distance from nipple–areola complex, calcification, and type of surgery) were included in the final prediction model, which had an area under the curve of 0.80 (95 per cent c.i. 0.75 to 0.85). The discrimination and calibration of the prediction model was assessed in the validation cohorts, and a nomogram developed. Conclusion The prediction model showed good ability to predict positive margins after BCS and might, after further validation, be used before surgery in centres without the routine use of preoperative MRI. Presented in part to the San Antonio Breast Cancer Symposium, San Antonio, Texas, USA, December 2018 and the Swedish Surgical Society Annual Meeting, Helsingborg, Sweden, August 2018.

BackgroundParental social characteristics influence the use of emergency departments (ED) in the USA, but less is known about paediatric ED care-seeking in countries with national health insurance. This prospective study was designed to evaluate associations between parental care-seeking and social characteristics, with emphasis on impact of non-native origin, at a paediatric ED in Sweden, a European country providing paediatric healthcare free of charge.MethodsParents attending a paediatric ED at a large urban university hospital filled out a questionnaire on social characteristics and reasons for care-seeking. Information on patient characteristics and initial management was obtained from ED registers and patient records. Paediatric ED physicians assessed the medical appropriateness of each patient visit triaged for ED care.ResultsIn total, 962 patient visits were included. Telephone healthline service before the paediatric ED visit was less often used by non-native parents (63/345 vs. 249/544, p < 0.001). Low-aquity visits, triaged away from the ED, were more common among non-native parents (80/368 vs. 67/555, OR = 1.66; p = 0.018), and among those reporting lower abilities in the Swedish language (23/82 vs. 120/837, OR = 2.66; p = 0.003). Children of non-native parents were more often assessed by physicians not to require ED care (122/335 vs. 261/512, OR = 0.70; p = 0.028).ConclusionsThis study confirms more direct and less urgent use of paediatric ED care by parents of non-native origin or with limited abilities in the Swedish language, proposing that parental social characteristics influence paediatric ED care-seeking, also in a country with healthcare free of charge, and that specific needs of these groups should be better met by prehospital medical services.Electronic supplementary materialThe online version of this article (10.1186/s12873-018-0210-5) contains supplementary material, which is available to authorized users.

Newly diagnosed breast cancer (BC) patients with clinical T1–T2 N0 disease undergo sentinel-lymph-node (SLN) biopsy, although most of them have a benign SLN. The pilot noninvasive lymph node staging (NILS) artificial neural network (ANN) model to predict nodal status was published in 2019, showing the potential to identify patients with a low risk of SLN metastasis. The aim of this study is to assess the performance measures of the model after a web-based implementation for the prediction of a healthy SLN in clinically N0 BC patients. This retrospective study was designed to validate the NILS prediction model for SLN status using preoperatively available clinicopathological and radiological data. The model results in an estimated probability of a healthy SLN for each study participant. Our primary endpoint is to report on the performance of the NILS prediction model to distinguish between healthy and metastatic SLNs (N0 vs. N+) and compare the observed and predicted event rates of benign SLNs. After validation, the prediction model may assist medical professionals and BC patients in shared decision making on omitting SLN biopsies in patients predicted to be node-negative by the NILS model. This study was prospectively registered in the ISRCTN registry (identification number: 14341750).