The External Genitalia Score (EGS): A European Multicenter Validation Study

CONTEXT: Standardized description of external genitalia is needed in the assessment of children with atypical genitalia. OBJECTIVES: To validate the External Genitalia Score (EGS), to present reference values for preterm and term babies up to 24 months and correlate obtained scores with anogenital distances (AGDs). DESIGN, SETTING: A European multicenter (n = 8) validation study was conducted from July 2016 to July 2018. PATIENTS AND METHODS: EGS is based on the external masculinization score but uses a gradual scale from female to male (range, 0-12) and terminology appropriate for both sexes. The reliability of EGS and AGDs was determined by the interclass correlation coefficient (ICC). Cross-sectional data were obtained in 686 term babies (0-24 months) and 181 preterm babies, and 111 babies with atypical genitalia. RESULTS: The ICC of EGS in typical and atypical genitalia is excellent and good, respectively. Median EGS (10th to 90th centile) in males < 28 weeks gestation is 10 (8.6-11.5); in males 28-32 weeks 11.5 (9.2-12); in males 33-36 weeks 11.5 (10.5-12) and in full-term males 12 (10.5-12). In all female babies, EGS is 0 (0-0). The mean (SD) lower/upper AGD ratio (AGDl/u) is 0.45 (0.1), with significant difference between AGDl/u in males 0.49 (0.1) and females 0.39 (0.1) and intermediate values in differences of sex development (DSDs) 0.43 (0.1). The AGDl/u correlates with EGS in males with typical genitalia and in atypical genitalia. CONCLUSIONS: EGS is a reliable and valid tool to describe external genitalia in premature and term babies up to 24 months. EGS correlates with AGDl/u in males. It facilitates standardized assessment, clinical decision-making and multicenter research

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press