Effect of the need for preoperative dialysis on perioperative outcomes on patients undergoing laparoscopic nephrectomy: an analysis of the National Surgical Quality Improvement Program database

Objective: To investigate whether patients requiring dialysis are a higher risk surgical population and would experience more perioperative adverse events even when undergoing a perceived less invasive operation as a laparoscopic radical nephrectomy (LRN). LRN is generally a well-tolerated surgical procedure with minimal morbidity and mortality. Prior to transplantation, dialysis patients will often have to undergo a LRN to remove a native kidney with a suspicious mass. Materials and Methods: Patients in the American College of Surgeons National Surgical Quality Improvement Program who underwent a LRN between 2011 and 2016 were included. Patients were stratified by the need for preoperative dialysis 2 weeks prior to surgery, and perioperative outcomes were compared. A multivariable logistic regression analysis was performed to test the association between the need for preoperative dialysis and perioperative risk. Results: There were 8315 patients included in this analysis of which 445 (5.4%) patients required preoperative dialysis. Patients who required preoperative dialysis had more minor (

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