Dataset Information

Prediction of Uropathogens by Flow Cytometry and Dip-stick Test Results of Urine Through Multivariable Logistic Regression Analysis.

ABSTRACT: PURPOSE:Multidrug-resistant Enterobacteriaceae in urinary tract infection (UTI) has spread worldwide; one cause is overuse of broad-spectrum antimicrobial agents such as fluoroquinolone antibacterials. To improve antimicrobial agent administration, this study aimed to calculate a probability prediction formula to predict the organism strain causing UTI in real time from dip-stick testing and flow cytometry. METHODOLOGY:We examined 372 outpatient spot urine samples with observed pyuria and bacteriuria using dip-stick testing and flow cytometry. We performed multiple logistic-regression analysis on the basis of 11 measurement items and BACT scattergram analysis with age and sex as explanatory variables and each strain as the response variable and calculated a probability prediction formula. RESULTS:The best prediction formula for discrimination of the bacilli group and cocci or polymicrobial group was a model with 5 explanatory variables that included percentage of scattergram dots in an angular area of 0-25° (P<0.001), sex (P<0.001), nitrite (P = 0.002), and ketones (P = 0.133). For a predicted cut-off value of Y = 0.395, sensitivity was 0.867 and specificity was 0.775 (cross-validation group: sensitivity = 0.840, specificity = 0.760). The best prediction formula for P. mirabilis and other bacilli was a model with percentage of scattergram dots in an angular area of 0-20° (P<0.001) and nitrite (P = 0.090). For a predicted cut-off value of Y = 0.064, sensitivity was 0.889 and specificity was 0.788 (cross-validation group: sensitivity = 1.000, specificity = 0.766). CONCLUSION:Simultaneous use of the calculated probability prediction formula with urinalysis results facilitates real-time prediction of organisms causing UTI, thus providing helpful information for empiric therapy.

SUBMITTER: Nakamura A

PROVIDER: S-EPMC6946154 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Prediction of Uropathogens by Flow Cytometry and Dip-stick Test Results of Urine Through Multivariable Logistic Regression Analysis.

Nakamura Akihiro A Kohno Aya A Noguchi Nobuyoshi N Kawa Kenji K Ohno Yuki Y Komatsu Masaru M Yamanishi Hachiro H

PloS one 20200107 1

<h4>Purpose</h4>Multidrug-resistant Enterobacteriaceae in urinary tract infection (UTI) has spread worldwide; one cause is overuse of broad-spectrum antimicrobial agents such as fluoroquinolone antibacterials. To improve antimicrobial agent administration, this study aimed to calculate a probability prediction formula to predict the organism strain causing UTI in real time from dip-stick testing and flow cytometry.<h4>Methodology</h4>We examined 372 outpatient spot urine samples with observed py ...[more]

PMID: 31910242

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Project description:Multivariable logistic regression (MLR) has been increasingly used in Chinese clinical medical research during the past few years. However, few evaluations of the quality of the reporting strategies in these studies are available.To evaluate the reporting quality and model accuracy of MLR used in published work, and related advice for authors, readers, reviewers, and editors.A total of 316 articles published in 5 leading Chinese clinical medical journals with high impact factor from January 2010 to July 2015 were selected for evaluation. Articles were evaluated according 12 established criteria for proper use and reporting of MLR models.Among the articles, the highest quality score was 9, the lowest 1, and the median 5 (4-5). A total of 85.1% of the articles scored below 6. No significant differences were found among these journals with respect to quality score (χ = 6.706, P = .15). More than 50% of the articles met the following 5 criteria: complete identification of the statistical software application that was used (97.2%), calculation of the odds ratio and its confidence interval (86.4%), description of sufficient events (>10) per variable, selection of variables, and fitting procedure (78.2%, 69.3%, and 58.5%, respectively). Less than 35% of the articles reported the coding of variables (18.7%). The remaining 5 criteria were not satisfied by a sufficient number of articles: goodness-of-fit (10.1%), interactions (3.8%), checking for outliers (3.2%), collinearity (1.9%), and participation of statisticians and epidemiologists (0.3%). The criterion of conformity with linear gradients was applicable to 186 articles; however, only 7 (3.8%) mentioned or tested it.The reporting quality and model accuracy of MLR in selected articles were not satisfactory. In fact, severe deficiencies were noted. Only 1 article scored 9. We recommend authors, readers, reviewers, and editors to consider MLR models more carefully and cooperate more closely with statisticians and epidemiologists. Journals should develop statistical reporting guidelines concerning MLR.

Project description:BackgroundMonitoring proteinuria is important for the management of patients with cancer treated with anti-vascular endothelial growth factor (VEGF) or anti-VEGF receptor (VEGFR) inhibitors (VEGF/Ri). Here we investigated the difference between the urine protein/creatinine ratio (UPCR) and a qualitative value test (QV) on the decision making of treatment continuation and the usefulness of UPCR testing in patients with gastrointestinal cancer treated with anti-VEGF/Ri.MethodsFrom January 2017 to December 2018, a survey was conducted based on the medical records of patients with gastrointestinal cancer with a QV of ≥2+ during the use of anti-VEGF/Ri at seven Japanese institutions participating in the Onco-nephrology Consortium. The primary endpoint was the ratio of the worst UPCR < 2.0 (low UPCR) in cases with a QV2+ at the point of the first proteinuria onset. The secondary endpoints were a comparison of low UPCR and worst UPCR ≥2.0 (high UPCR), the concordance rate between UPCR and QV in the Common Terminology Criteria for Adverse Events (CTCAE) grading, and the differences in the decision making for anti-VEGF/Ri continuation.ResultsAmong the 71 patients enrolled, the proportion of low UPCR in onset QV2+ (n = 53) was 66% (n = 35). In a comparison between low (n = 36) and high UPCR cases (n = 24), body weight (P = 0.036), onset QV status (P = 0.0134), and worst QV status (P < 0.0001) were significantly associated with UPCR levels. The concordance rate for CTCAE Grade 2 of both the QV and UPCR was 83%. Regarding the judgment of anti-VEGF/Ri continuation, treatment was continued in 42.4% of cases when the QV became 3+, whereas only 25% continued treatment when the UPCR value became high.ConclusionUrine dipstick test results may overestimate proteinuria, and the UPCR result tended to be more critical than the QV when deciding the treatment policy.Trial registrationThis study is a multiple institutional retrospectively registered observational trial.Clinical trial numberUniversity Hospital Medical Information Network (UMIN) Clinical Trials Registry (protocol ID UMIN000042545 ).

Project description:IntroductionFlow state has been deemed a desirable state for performing musicians given its negative correlations with musical performance anxiety, its relationship to optimal performance, and its possible effect on creativity. In the field of music, there are a few studies that have assessed intervention programmes to promote flow state in performing musicians with varying results in terms of their success. The flow condition-experience model proposes three components that would be the conditions for flow state to occur and six components that describe the experience of being in a flow state. In addition, within the vast academic literature on this experience, other factors that could influence its occurrence have been proposed. The main objective of this research was to detect which are the most suitable predictors from a set of independent variables collected to distinguish performing musicians with a high flow level.MethodsA binary logistic regression analysis was carried out with data from 163 musicians aged between 18 and 65. Independent variables were introduced in the analysis: skill-challenge balance, clear goals and clear feedback (condition-experience model); and also, gender, age, dedication, (musical) style, musical instrument and (performing) situation.ResultsThe results showed that the three conditions of the condition-experience model and the situation variable had positive associations with flow state. The model explained 78% of the variance of the dependent variable and obtained a 90.8% correct classification rate.DiscussionThese variables seem to contribute most to a high flow level, and the importance of keeping in mind the intrinsic reasons why performers dedicate themselves to music is emphasised. The results and their implications for the training of performing musicians are discussed. Future lines of research are proposed, as well as collecting data on personality-related variables to introduce them into the regression model.

Dataset Information

Prediction of Uropathogens by Flow Cytometry and Dip-stick Test Results of Urine Through Multivariable Logistic Regression Analysis.

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Prediction of Uropathogens by Flow Cytometry and Dip-stick Test Results of Urine Through Multivariable Logistic Regression Analysis.

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