Spontaneous resolution of atrial and ventricular septal defects in Malta

Congenital heart disease (CHD) is the commonest congenital malformation, and ventricular septal defect (VSD) and atrial septal defect (ASD) are the commonest forms of CHD. This study was undertaken to determine rates or spontaneous closure or lesions diagnosed at echocardiography after detection or a murmur in Maltese patients born in 1990-94. A significant excess or ASD and VSD was found in Malta, and this was attributed to early echocardiographic diagnosis or small defects, prior to spontaneous closure. A high spontaneous closure rate was round for both ASD and VSD. Rate of closure for both defects was initially high, and tapered off at about 5 to 7 years or age for both lesions. ASDs in excess of 8 mm in diameter at presentation also underwent spontaneous resolution, which is contrary to the known natural history or these defects. Larger VSDs were shown to have a smaller likelihood or closing (p=0.04). Parents and patients can be reassured that spontaneous closure is very likely to occur in the vast majority of these conditions.peer-reviewe

A comparison of clinical paediatric murmur assessment with echocardiography

Objective: To compare the clinical acumen of paediatric cardiovascular examination between various hospital paediatrician grades. Design: Prospective data collection of clinical and echocardiography findings on paediatric echocardiography referrals. Setting and patients: All paediatric patients (birth - 14 years) referred for echocardiography, in a regional hospital catering for the island population of Malta. Echocardiography was carried out by three paediatricians with tertiary training in this technique. Main outcome measures: Pre-echocardiography clinical diagnoses were compared with echocardiography results according to grade of referring hospital doctor (ranging from houseman to consultant). Both normal and abnormal hearts at echocardiography were included. Results: Echocardiographers had the highest clinical accuracy and the highest attempts at reaching a clinical diagnosis. Accuracy and attempts at diagnosis decreased as doctor's hospital grade decreased, from consultant to houseman. Ventricular septal defect was the most easily diagnosed lesion. Atrial septal defect was often misdiagnosed as pulmonary stenosis.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 research.Peer reviewe

Two new mutations in the HIF2A gene associated with erythrocytosis

Congenital or familial erythrocytosis/polycythemia can have many causes, and an emerging cause is genetic disruption of the oxygen-sensing pathway that regulates the ERYTHROPOIETIN (EPO) gene. More specifically, recent studies have identified erythrocytosis-associated mutations in the HIF2A gene, which encodes for Hypoxia Inducible Factor-2α (HIF-2α), as well as in two genes that encode for proteins that regulate it, Prolyl Hydroxylase Domain protein 2 (PHD2) and the von Hippel Lindau tumor suppressor protein (VHL). We report here the identification of two new heterozygous HIF2A missense mutations, M535T and F540L, both associated with erythrocytosis. Met-535 has previously been identified as a residue mutated in other patients with erythrocytosis, although the mutation of this particular residue to Thr has not been reported. In contrast, Phe-540 has not been reported as a residue mutated in erythrocytosis, and we present evidence here that this mutation impairs interaction of HIF-2α with both VHL and PHD2

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

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