scholarly journals A Multivariate Logistic Regression Equation to Screen for Diabetes : Development and validation

Diabetes Care ◽  
2002 ◽  
Vol 25 (11) ◽  
pp. 1999-2003 ◽  
Author(s):  
B. P. Tabaei ◽  
W. H. Herman
Keyword(s):  
Logistic Regression ◽  
Regression Equation ◽  
Multivariate Logistic Regression ◽  
Diabetes Development ◽  
Development And Validation ◽  
Logistic Regression Equation

scholarly journals Evaluation of Prognostic Factors for Clinical Pregnancy Rate Following Artificial Insemination by Husband in the Chinese Population

2021 ◽  
Vol 8 ◽  
Author(s):  
Yumei Luo ◽  
Shunhong Wu ◽  
Jingru Yuan ◽  
Hua Zhou ◽  
Yufang Zhong ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Prognostic Factors ◽  
Normal Form ◽  
Pregnancy Rate ◽  
Influencing Factors ◽  
Artificial Insemination ◽  
Regression Equation ◽  
Multivariate Logistic Regression ◽  
Successful Pregnancy ◽  
Logistic Regression Equation

Background: To determine the independent prognostic factors and develop a multivariate logistic regression model for predicting successful pregnancy following artificial insemination by husband (AIH) in infertile Chinese couples.Methods: A total of 3,015 AIH cycles with superovulation from 1,853 infertile Chinese couples were retrospectively analyzed. The clinical characteristics and sperm parameters were compared between the pregnant and non-pregnant groups. Multivariate logistic regression analysis was performed to remove the confounding factors and create an equation to predict the successful pregnancy. Receiver operating characteristic (ROC) curves were constructed for evaluating the abilities for prognostic classification of the independent predictors and the equation.Results: The overall pregnancy rate was 13.0%. The pregnancy rate of double intrauterine insemination (IUI) (18.9%) was significantly higher than that of single IUI (11.4%). The pregnancy rate of the stimulated cycle (14.4%) was significantly higher than that of the natural cycle (9.0%). The pregnancy rates of the age groups <40 years are ~3 times higher than that of the ≥40 years age group. Among sperm parameters, the influencing factors included straight-line velocity (VSL), sperm deformity index (SDI), and normal form rate (all P < 0.05). A multivariate logistic regression equation was created based on the above influencing factors. ROC analysis showed that the prognostic power of the equation is better than those of individual predictors.Conclusion: Cycle treatment options, single/double IUI, female age, sperm VSL, SDI, and normal form rate could predict successful pregnancy following AIH in China. The multivariate logistic regression equation exhibited a greater value for prognostic classification than single predictors.

scholarly journals Logistic regression model to predict acute uncomplicated and complicated appendicitis

2019 ◽  
Vol 101 (2) ◽  
pp. 107-118 ◽  
Author(s):  
MMR Eddama ◽  
KC Fragkos ◽  
S Renshaw ◽  
M Aldridge ◽  
G Bough ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Odds Ratio ◽  
Web Application ◽  
Univariate Analysis ◽  
Complicated Appendicitis ◽  
Regression Equation ◽  
Normal Appendix ◽  
Uncomplicated Appendicitis ◽  
Logistic Regression Equation

Introduction While patients with acute uncomplicated appendicitis may be treated conservatively, those who suffer from complicated appendicitis require surgery. We describe a logistic regression equation to calculate the likelihood of acute uncomplicated appendicitis and complicated appendicitis in patients presenting to the emergency department with suspected acute appendicitis. Materials and methods A cohort of 895 patients who underwent appendicectomy were analysed retrospectively. Depending on the final histology, patients were divided into three groups; normal appendix, acute uncomplicated appendicitis and complicated appendicitis. Normal appendix was considered the reference category, while acute uncomplicated appendicitis and complicated appendicitis were the nominal categories. Multivariate and univariate regression models were undertaken to detect independent variables with significant odds ratio that can predict acute uncomplicated appendicitis and complicated appendicitis. Subsequently, a logistic regression equation was generated to produce the likelihood acute uncomplicated appendicitis and complicated appendicitis. Results Pathological diagnosis of normal appendix, acute uncomplicated appendicitis and complicated appendicitis was identified in 188 (21%), 525 (59%) and 182 patients (20%), respectively. The odds ratio from a univariate analysis to predict complicated appendicitis for age, female gender, log2 white cell count, log2 C-reactive protein and log2 bilirubin were 1.02 (95% confidence interval, CI, 1.01, 1.04), 2.37 (95% CI 1.51, 3.70), 9.74 (95% CI 5.41, 17.5), 1.57 (95% CI 1.40, 1.74), 2.08 (95% CI 1.56, 2.76), respectively. For the same variable, similar odds ratios were demonstrated in a multivariate analysis to predict complicated appendicitis and univariate and multivariate analysis to predict acute uncomplicated appendicitis. Conclusions The likelihood of acute uncomplicated appendicitis and complicated appendicitis can be calculated by using the reported predictive equations integrated into a web application at www.appendistat.com. This will enable clinicians to determine the probability of appendicitis and the need for urgent surgery in case of complicated appendicitis.

scholarly journals A multivariable logistic regression equation to evaluate prostate cancer

2011 ◽  
Vol 110 (11) ◽  
pp. 695-700 ◽  
Author(s):  
Jhih-Cheng Wang ◽  
Steven K. Huan ◽  
Jinn-Rung Kuo ◽  
Chin-Li Lu ◽  
Hung Lin ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Logistic Regression ◽  
Regression Equation ◽  
Multivariable Logistic Regression ◽  
Logistic Regression Equation

A Predictive Logistic Regression Equation for Neck Pain in Helicopter Aircrew

2012 ◽  
Vol 83 (6) ◽  
pp. 604-608 ◽  
Author(s):  
Michael F. Harrison ◽  
J. Patrick Neary ◽  
Wayne J. Albert ◽  
James C. Croll
Keyword(s):  
Logistic Regression ◽  
Neck Pain ◽  
Regression Equation ◽  
Logistic Regression Equation

scholarly journals Pengaruh Jumlah Anggota, Size, Likuiditas, dan Rentabilitas Koperasi terhadap Permintaan Jasa Audit Eksternal

2019 ◽  
Vol 8 (2) ◽  
pp. 125
Author(s):  
Fikri Rizki Utama
Keyword(s):  
Logistic Regression ◽  
Significant Influence ◽  
Sampling Method ◽  
Regression Equation ◽  
External Audit ◽  
Purposive Sampling ◽  
The City ◽  
Size Variable ◽  
Logistic Regression Equation

The purpose of this research is to empirically examine the influence of the number of members of the cooperative, size, liquidity, and rentability of cooperatives to demand external audit services. This study uses a sample of Cooperative Employees (Kopkar) in the city of Bandar Lampung during 2009-2011 using purposive sampling method. The analysis in this study uses logistic regression equation. The result of this study found that the size variable has a significant influence on the demand for external audit services. While the variable of a number of cooperative members, liquidity, and rentability do not significantly influence the demand for external audit services.Keywords: Request for External Audit Services, Cooperative of Employees,�Number of cooperative members, Size, Liquidity, and Rentability.

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