Radiographic cortical thickness parameters as predictors of rotational alignment in proximal tibial shaft fractures: a cadaveric study

AIM The treatment of tibial fractures with an intramedullary nail is an established procedure. However, torsional control remains challenging using intraoperatively diagnostic tools. Radiographic tools such as the Cortical Step Sign (CSS) and the Diameter Difference Sign (DDS) may serve as tools for diagnosing a relevant malrotation. The aim of this study was to investigate the effect of torsional malalignment on CSS and DDS parameters and to construct a prognostic model to detect malalignment. METHODS A proximal tibial shaft fracture was set in human tibiae. Torsion was set stepwise from 0° to 30° in external and internal torsion. Images were obtained with a C-arm and transferred to a PC for measuring the medical cortical thickness (MCT), lateral cortical thickness (LCT), tibial diameter (TD) in AP and the anterior cortical thickness (ACT) as well as the posterior cortical thickness (PCT) and the transverse diameter (TD) of the proximal and the distal main fragment. RESULTS There were significant differences between the various degrees of torsion for each of the absolute values of the examined variables. The parameters with the highest correlation were TD, LCT and ACT. A model combining ACT, LCT, PCT and TD lateral was most suitable model in identifying torsional malalignment. The best prediction of clinically relevant torsional malalignment, namely 15°, was obtained with the TD and the ACT. CONCLUSION This study shows that the CSS and DDS are useful tools for the intraoperative detection of torsional malalignment in proximal tibial shaft fractures and should be used to prevent maltorsion

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

Teratom der Zirbeldrüse

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