scholarly journals The effect of patient weight and amiodarone use on the energy of a successful shock in cardioversion of atrial arrhythmias – single-center experience study

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
O Jiravsky ◽  
L Rucki ◽  
J Chovancik ◽  
R Spacek ◽  
A Svobodnik ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Published Data ◽  
Atrial Arrhythmias ◽  
Funding Sources ◽  
Single Center Experience ◽  
Regression Parameters ◽  
Patient Weight ◽  
Level Of Significance

Abstract Background Electrical cardioversion (DCCV) is an effective method of sinus rhythm restitution. Recently published data suggest higher efficiencies of higher discharge energies. The influence of individual parameters on the success of cardioversion is still studying. Purpose To evaluate the influence of individual patient parameters on the energy of a successful external defibrillator shock during cardioversion of atrial arrhythmias Methods The retrospective analysis cohort of all patients treated by DCCV due to atrial arrhythmias between 10/2015 and 1/2020. To evaluate potential predictors for the choice of a higher initial discharge using one-dimensional logistic regression and to include parameters significant at the 10% level of significance (p<0.1) in the multidimensional logistic regression model. Results 1986 electrical cardioversions of 984 patients (382 repeated procedures of the same patients in a cohort). 1292 (65.1%) men and 694 (34.9%) women aged 67.0 (±10.2) years. Mean energy of the first shock 118.9 (±19.2) J with a success rate of 77.8%, energy of the second shock 154.0 (±26.3) J, which increased the overall success to 80.0%, and mean high of the third shock 173.9 (±25.6) J, when the total efficacy of DCCV in sinus rhytm restitution reached 89.8%. From the univariate binary regression, parameters significant at the 10% level of significance (p<0.1) were selected and included in a multidimensional logistic regression model. Only the patient's weight and the use of amiodarone proved to be statistically significant. Weight with OR 1.21 and use of amiodarone with OR 1.43. Conclusion Patient weight and amiodarone use are predictors of the need to use higher energy electric cardioversion. Discussion Amiodarone medication does not appear to increase the defibrillation threshold, but rather is a feature that represents the group of patients treated with more aggressive antiarrhythmic therapy for advanced atrial arrhythmias with more significant structural impairment, but this attitude requires further study. FUNDunding Acknowledgement Type of funding sources: Private hospital(s). Main funding source(s): VAVIA: IGS202009 - Racionální algoritmus při elektivní elektrické kardioverzi fibrilace síní.

Establishment of Prediction Models for venous thromboembolism in non-oncological urological inpatients--a single center experience

2020 ◽  
Author(s):  
Kaixuan Li ◽  
Haozhen Li ◽  
Quan Zhu ◽  
Ziqiang Wu ◽  
Zhao Wang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Venous Thromboembolism ◽  
Prediction Model ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Prediction Models ◽  
Predictive Ability ◽  
Multivariate Logistic Regression Model ◽  
Single Center Experience

Abstract Background To establish prediction models for venous thromboembolism (VTE) in non-oncological urological inpatients. Methods A retrospective analysis of 1453 inpatients was carried out and the risk factors for VTE had been clarified our previous studies. Results Risk factors included the following 5 factors: presence of previous VTE (X1), presence of anticoagulants or anti-platelet agents treatment before admission (X2), D-dimer value (≥ 0.89 µg/ml, X3), presence of lower extremity swelling (X4), presence of chest symptoms (X5). The logistic regression model is Logit (P) = − 5.970 + 2.882 * X1 + 2.588 * X2 + 3.141 * X3 + 1.794 * X4 + 3.553 * X5. When widened the p value to not exceeding 0.1 in multivariate logistic regression model, two addition risk factors were enrolled: Caprini score (≥ 5, X6), presence of complications (X7). The prediction model turns into Logit (P) = − 6.433 + 2.696 * X1 + 2.507 * X2 + 2.817 * X3 + 1.597 * X4 + 3.524 * X5 + 0.886 * X6 + 0.963 * X7. Internal verification results suggest both two models have a good predictive ability, but the prediction accuracy turns to be both only 43.0% when taking the additional 291 inpatients’ data in the two models. Conclusion We built two similar novel prediction models to predict VTE in non-oncological urological inpatients. Trial registration: This trial was retrospectively registered at http://www.chictr.org.cn/index.aspx under the public title“The incidence, risk factors and establishment of prediction model for VTE n urological inpatients” with a code ChiCTR1900027180 on November 3, 2019. (Specific URL to the registration web page: http://www.chictr.org.cn/showproj.aspx?proj=44677).

scholarly journals Cumulative live birth rates for women returning to ART treatment for a second ART-conceived child

2020 ◽  
Vol 35 (6) ◽  
pp. 1432-1440 ◽  
Author(s):  
Repon C Paul ◽  
Oisin Fitzgerald ◽  
Devora Lieberman ◽  
Christos Venetis ◽  
Georgina M Chambers
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Live Birth ◽  
Ovarian Stimulation ◽  
Financial Support ◽  
Logistic Regression Model ◽  
Published Data ◽  
Success Rates ◽  
Cumulative Live Birth ◽  
Number Of Patients

Abstract STUDY QUESTION What are the success rates for women returning to ART treatment in the hope of having a second ART-conceived child. SUMMARY ANSWER The cumulative live birth rate (LBR) for women returning to ART treatment was between 50.5% and 88.1% after six cycles depending on whether women commenced with a previously frozen embryo or a new ovarian stimulation cycle and the assumptions made regarding the success rates for women who dropped-out of treatment. WHAT IS KNOWN ALREADY Previous studies have reported the cumulative LBR for the first ART-conceived child to inform patients about their chances of success. However, most couples plan to have more than one child to complete their family and, for that reason, patients commonly return to ART treatment after the birth of their first ART-conceived child. To our knowledge, there are no published data to facilitate patient counseling and clinical decision-making regarding the success rates for these patients. STUDY DESIGN, SIZE, DURATION A population-based cohort study with 35 290 women who commenced autologous (using their own oocytes) ART treatment between January 2009 and December 2013 and achieved their first treatment-dependent live birth from treatment performed during this period. These women were then followed up for a further 2 years of treatment to December 2015, providing a minimum of 2 years and a maximum of 7 years of treatment follow-up. PARTICIPANTS/MATERIALS, SETTING, METHODS Cycle-specific LBR and cumulative LBR were calculated for up to six complete ART cycles (one ovarian stimulation and all associated transfers). Three cumulative LBR were calculated based on the likelihood of success in women who dropped-out of treatment (conservative, optimal and inverse probability-weighted (IPW)). A multivariable logistic regression model was used to predict the chance of returning to ART treatment for a second ART-conceived child, and a discrete time logistic regression model was used to predict the chance of achieving a second ART-conceived child up to a maximum of six complete cycles. The models were adjusted for patient characteristics and previous and current treatment characteristics. MAIN RESULTS AND THE ROLE OF CHANCE Among the women who had their first ART-conceived live birth, 15 325 (43%) returned to treatment by December 2015. LBRs were consistently better in women who recommenced treatment with a previously frozen embryo, compared to women who underwent a new ovarian stimulation cycle. After six complete cycles, plus any surplus frozen embryos, the cumulative LBR was between 60.9% (95% CI: 60.0–61.8%) (conservative) and 88.1% (95% CI: 86.7–89.5%) (optimal) [IPW 87.2% (95% CI: 86.2–88.2%)] for women who recommenced treatment with a frozen embryo, compared to between 50.5% (95% CI: 49.0–52.0%) and 69.8% (95% CI: 67.5–72.2%) [IPW 68.1% (95% CI: 67.3–68.9%)] for those who underwent a new ovarian stimulation cycle. The adjusted odds of a second ART-conceived live birth decreased for women ≥35 years, who waited at least 3 years before returning to treatment, or who required a higher number of ovarian stimulation cycles or double embryo transfer to achieve their first child. LIMITATIONS, REASONS FOR CAUTION Our estimates do not fully account for a number of individual prognostic factors, including duration of infertility, BMI and ovarian reserve. WIDER IMPLICATIONS OF THE FINDINGS This is the first study to report success rates for women returning to ART treatment to have second ART-conceived child. These age-specific success rates can facilitate individualized counseling for the large number of patients hoping to have a second child using ART treatment. STUDY FUNDING/COMPETING INTEREST(S) No funding was received to undertake this study. R. Paul and O. Fitzgerald have nothing to declare. D. Lieberman reports being a fertility specialist and receiving non-financial support from MSD and Merck outside the submitted work. C. Venetis reports being a fertility specialist and receiving personal fees and non-financial support from MSD, personal fees and non-financial support from Merck Serono and Beisins and non-financial support from Ferring outside the submitted work. G.M. Chambers reports being a paid employee of the University of New South Wales, Sydney (UNSW) and Director of the National Perinatal Epidemiology and Statistics Unit (NPESU), UNSW. The Fertility Society of Australia (FSA) contracts UNSW to prepare the Australian and New Zealand Assisted Reproductive Technology Database (ANZARD) annual report series and benchmarking reports. TRIAL REGISTRATION NUMBER NA.

scholarly journals APPLICATION OF LOGISTIC REGRESSION IN CALCULATION OF DAMAGEABILITY OF SOLID DEFORMABLE BODY

2021 ◽  
Vol 1 (54) ◽  
pp. 46-53
Author(s):  
Dzianis E. MARMYSH ◽  
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Roc Curve ◽  
Logistic Regression Model ◽  
Deformable Body ◽  
Training Sample ◽  
Likelihood Method ◽  
System Of Nonlinear Equations ◽  
Estimation Algorithms ◽  
Regression Parameters

The paper proposes a logistic regression model for estimating the damageability of a solid deformable body. A training sample is randomly generated from a uniform distribution over the area containing the dangerous volume. For linear separability of the training sample, a classifying kernel is used in the form of a radial basis function. The regression parameters were estimated using the maximum likelihood method, then the system of nonlinear equations was solved by the Newton–Raphson method. To determine the quality of the classifier, a ROC analysis was performed, which consists in constructing the ROC curve and calculating the area between the ROC curve and the specificity axis. For adequate assessment of the work, the logistic regression model is used to calculate the damage of a half-plane when a normally distributed load acts on its boundary. The paper also analyzes the stability of the model parameter estimation algorithms when generating a random sample of training sample.

scholarly journals Work absence and multimorbidity in Portugal: results from the 1st National Health Examination Survey

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
J Matos ◽  
C Matias Dias ◽  
A Félix
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Chronic Diseases ◽  
National Health ◽  
Logistic Regression Model ◽  
Health Examination ◽  
Work Absence ◽  
Health Examination Survey ◽  
Absence From Work ◽  
The Impact

Abstract Background Studies on the impact of patients with multimorbidity in the absence of work indicate that the number and type of chronic diseases may increase absenteeism and that the risk of absence from work is higher in people with two or more chronic diseases. This study analyzed the association between multimorbidity and greater frequency and duration of work absence in the portuguese population between the ages of 25 and 65 during 2015. Methods This is an epidemiological, observational, cross-sectional study with an analytical component that has its source of information from the 1st National Health Examination Survey. The study analyzed univariate, bivariate and multivariate variables under study. A multivariate logistic regression model was constructed. Results The prevalence of absenteeism was 55,1%. Education showed an association with absence of work (p = 0,0157), as well as professional activity (p = 0,0086). It wasn't possible to verify association between the presence of chronic diseases (p = 0,9358) or the presence of multimorbidity (p = 0,4309) with absence of work. The prevalence of multimorbidity was 31,8%. There was association between age (p < 0,0001), education (p < 0,001) and yield (p = 0,0009) and multimorbidity. There is no increase in the number of days of absence from work due to the increase in the number of chronic diseases. In the optimized logistic regression model the only variables that demonstrated association with the variable labor absence were age (p = 0,0391) and education (0,0089). Conclusions The scientific evidence generated will contribute to the current discussion on the need for the health and social security system to develop policies to patients with multimorbidity. Key messages The prevalence of absenteeism and multimorbidity in Portugal was respectively 55,1% and 31,8%. In the optimized model age and education demonstrated association with the variable labor absence.

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