1,721,008 research outputs found

    Drainage fluid LDH and neutrophil to lymphocyte ratio as biomarkers for early detecting anastomotic leakage in patients undergoing colorectal surgery

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    Objectives In this study, we investigated the role of several circulating and drainage fluid biomarkers for detecting postoperative complications (PCs) and anastomotic leakage (AL) in patients undergoing colorectal surgery. Methods All consecutive patients undergoing colorectal surgery between June 2018 and April 2020 were prospectively considered. On postoperative days (POD) 1, 3, and 5, we measured lactate dehydrogenase (LDH) in drainage fluid, C-reactive protein (CRP) in serum and drainage fluid, and neutrophil to lymphocyte ratio (NLR). Results We enrolled 187 patients. POD1 patients with AL had higher serum CRP levels, while on POD3 and on POD5 higher NLR and serum CRP. LDH and CRP in drainage fluid were also significantly higher at both time points. The area under the curves (AUCs) of serum and drainage fluid CRP were 0.752 (0.629–0.875) and 0.752 (0.565–0.939), respectively. The best cut-off for serum and drainage fluid CRP was 185.23 and 76 mg/dL, respectively. The AUC of NLR on POD3 was 0.762 (0.662–0.882) with a sensitivity and specificity of 84 and 63 %, respectively, at a cut-off of 6,6. Finally, drainage fluid LDH showed the best diagnostic performance for AL, with an AUC, sensitivity, and specificity of 0.921 (0.849–0.993), 82 %, and 90 % at a cut-off of 2,186 U/L. Trends in serum parameters between patients with or without PCs or AL were also evaluated. Interestingly, we found that NLR decreased faster in patients without PCs than in patients with PCs and patients with AL. Conclusions Drainage fluid LDH and NLR could be promising biomarkers of PCs and AL

    The multicenter European Biological Variation Study (EuBIVAS): a new glance provided by the Principal Component Analysis (PCA), a machine learning unsupervised algorithms, based on the basic metabolic panel linked measurands

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    Objectives The European Biological Variation Study (EuBIVAS), which includes 91 healthy volunteers from five European countries, estimated high-quality biological variation (BV) data for several measurands. Previous EuBIVAS papers reported no significant differences among laboratories/population; however, they were focused on specific set of measurands, without a comprehensive general look. The aim of this paper is to evaluate the homogeneity of EuBIVAS data considering multivariate information applying the Principal Component Analysis (PCA), a machine learning unsupervised algorithm. Methods The EuBIVAS data for 13 basic metabolic panel linked measurands (glucose, albumin, total protein, electrolytes, urea, total bilirubin, creatinine, phosphatase alkaline, aminotransferases), age, sex, menopause, body mass index (BMI), country, alcohol, smoking habits, and physical activity, have been used to generate three databases developed using the traditional univariate and the multivariate Elliptic Envelope approaches to detect outliers, and different missing-value imputations. Two matrix of data for each database, reporting both mean values, and "within-person BV" (CVP) values for any measurand/subject, were analyzed using PCA. Results A clear clustering between males and females mean values has been identified, where the menopausal females are closer to the males. Data interpretations for the three databases are similar. No significant differences for both mean and CV(P)s values, for countries, alcohol, smoking habits, BMI and physical activity, have been found. Conclusions The absence of meaningful differences among countries confirms the EuBIVAS sample homogeneity and that the obtained data are widely applicable to deliver APS. Our data suggest that the use of PCA and the multivariate approach may be used to detect outliers, although further studies are required

    Prostate Health Index (PHI) as a triage tool for reducing unnecessary magnetic resonance imaging (MRI) in patients at risk of prostate cancer

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    Introduction: The aim of this study is to assess the usefulness of the Prostate Health Index (PHI) as a triage tool for selecting patients at risk of prostate cancer (PCa) who should undergo multiparametric Magnetic Resonance Imaging (mpMRI). Material and methods: We enrolled 204 patients with suspected PCa. For each patient, a blood sample was collected before mpMRI to measure PHI. Findings on mpMRI were assessed according to the Prostate Imaging Reporting & Data System version 2.0 (PI-RADSv2) category scale. Results: According to PI-RADSv2, patients were classified into two groups: PI-RADS < 3 (48 %) and >= 3 (52 %). PHI showed the best performance for predicting PI-RADS >= 3 [AUC: 0,747 (0,679-0,815), 0,680(0,607-0,754), and 0,613 (0,535-0,690) for PHI, PSA ratio, and total PSA, respectively]. The best PHI cut-off was 30, with a sensitivity of 90%. At the univariate logistic regression, total PSA (p = 0.007), PSA ratio (p = 0.001), [-2]proPSA (p = 0.019) and PHI (p < 0.001) were associated with PI-RADS >= 3; however, at the multivariate analysis, only PHI (p < 0.001) was found to be an independent predictor of PI-RADS >= 3. Conclusion: PHI could represent a reliable noninvasive tool for selecting patients to undergo mpMRI

    Lipoprotein profile, lipoprotein-associated phospholipase A2 and cardiovascular risk in hemodialysis patients

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    Cardiovascular disease is the leading cause of morbidity and mortality in hemodialysis patients; the increased risk of cardiovascular disease is due to accelerated atherosclerosis, inflammation and impaired lipoprotein metabolism. We aimed to evaluate lipoprotein-associated phospholipase A2 (Lp-PLA2) and some pro-inflammatory aspects of the lipoprotein profile in dialyzed patients in order to evaluate the relationship with the accelerated atherosclerosis and vascular accidents

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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