53 research outputs found

    Malignancy risk analysis in patients with inadequate fine needle aspiration cytology (FNAC) of the thyroid

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    Background Thyroid fine needle aspiration cytology (FNAC) is the standard diagnostic modality for thyroid nodules. However, it has limitations among which is the incidence of non-diagnostic results (Thy1). Management of cases with repeatedly non-diagnostic FNAC ranges from simple observation to surgical intervention. We aim to evaluate the incidence of malignancy in non-diagnostic FNAC, and the success rate of repeated FNAC. We also aim to evaluate risk factors for malignancy in patients with non-diagnostic FNAC. Materials and Methods Retrospective analyses of consecutive cases with thyroid non diagnostic FNAC results were included. Results Out of total 1657 thyroid FNAC done during the study period, there were 264 (15.9%) non-diagnostic FNAC on the first attempt. On repeating those, the rate of a non-diagnostic result on second FNAC was 61.8% and on third FNAC was 47.2%. The overall malignancy rate in Thy1 FNAC was 4.5% (42% papillary, 42% follicular and 8% anaplastic), and the yield of malignancy decreased considerably with successive non-diagnostic FNAC. Ultrasound guidance by an experienced head neck radiologist produced the lowest non-diagnostic rate (38%) on repetition compared to US guidance by a generalist radiologist (65%) and by non US guidance (90%). Conclusions There is a low risk of malignancy in patients with a non-diagnostic FNAC result, commensurate to the risk of any nodule. The yield of malignancy decreased considerably with successive non-diagnostic FNAC

    Role of ultrasound, clinical and scintigraphyc parameters to predict malignancy in thyroid nodule

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    Background: This study aimed to evaluate clinical, laboratory, ultrasound (US) and scintigraphyc parameters in thyroid nodule and to develop an auxiliary model for clinical application in the diagnosis of malignancy. Methods: We assessed 143 patients who were surgically treated at a single center, 65% (93) benign vs. 35% (50) malignant lesions at final histology (1998-2008). The clinical, laboratory, scintigraphyc and US features were compared and a prediction model was designed after the multivariate analysis. Results: There were no differences in gender, serum TSH and FT4 levels, thyroid auto-antibodies (TAb), thyroid dysfunction and scintigraphyc results (P = 0.33) between benign and malignant nodule groups. The sonographic study showed differences when the presence of suspected characteristics was found in the nodules of the malignant lesions group, such as: microcalcifications, central flow, border irregularity and hypoechogenicity. After the multivariate analysis the model obtained showed age (>39 years), border irregularity, microcalcifications and nodule size over 2 cm as predictive factors of malignancy, featuring 81.7% of accuracy. Conclusions: This study confirmed a significant increase of risk for malignancy in patients of over 39 years and with suspicious features at US

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

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    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

    SAFTA and AFTA: a comparative welfare analysis of two regional trade agreements

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    Abstract The gravity model is one of the most successful empirical models in economics to evaluate the effects of several factors on international trade or bilateral trade flows. Many factors that are related to trade barriers can influence the bilateral trade between two countries. Regional trade agreements (RTAs) are important factors, which can pave the path of bilateral trades. In this paper, I use GEPPML estimator of Anderson et al. (Estimating general equilibrium trade policy effects: GE PPML. CESifo Working Papers-5592, 2015) to evaluate the counterfactual welfare effect of SAFTA and AFTA on member countries as well as on the non-member countries. After accounting for potential endogeneity of RTAs, removal of AFTA causes 3.08% real GDP loss for member countries, removal of SAFTA causes 6.36% real GDP loss for member countries, and joint agreement of SAFTA and AFTA brings 0.71 real GDP gains for member countries. In all scenarios, trade diversion effect is not remarkable
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