multivariate logistic model
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2022 ◽  
Vol 9 (1) ◽  
pp. 23
Author(s):  
Alexander A. Berezin ◽  
Ivan M. Fushtey ◽  
Alexander E. Berezin

Background: Apelin is a regulatory vasoactive peptide, which plays a pivotal role in adverse cardiac remodeling and heart failure (HF) with reduced ejection fraction. The purpose of the study was to investigate whether serum levels of apelin is associated with HF with preserved election fraction (HFpEF) in patients with T2DM. Methods: The study retrospectively involved 101 T2DM patients aged 41 to 62 years (48 patients with HFpEF and 28 non-HFpEF patients). The healthy control group consisted of 25 individuals with matched age and sex. Data collection included demographic and anthropometric information, hemodynamic performances and biomarkers of the disease. Transthoracic B-mode echocardiography, Doppler and TDI were performed at baseline. Serum levels of N-terminal pro-brain natriuretic peptide (NT-proBNP) and apelin were measured by ELISA in all patients at the study entry. Results: Unadjusted multivariate logistic model yielded the only apelin to NT-proBNP ratio (OR = 1.44; p = 0.001), BMI > 34 кг/м2 (OR = 1.07; p = 0.036), NT-proBNP > 458 pmol/mL (OR = 1.17; p = 0.042), LAVI > 34 mL/m2 (OR = 1.06; p = 0.042) and E/e’ > 11 (OR = 1.04; p = 0.044) remained to be strong predictors for HFpEF. After obesity adjustment, multivariate logistic regression showed that the apelin to NT-proBNP ratio < 0.82 × 10−2 units remained sole independent predictor for HFpEF (OR = 1.44; 95% CI: 1.18–2.77; p = 0.001) HFpEF in T2DM patients. In conclusion, we found that apelin to NT-proBNP ratio < 0.82 × 10−2 units better predicted HFpEF in T2DM patients than apelin and NT-proBNP alone. This finding could open new approach for CV risk stratification of T2DM at higher risk of HF.


2021 ◽  
Vol 10 (21) ◽  
pp. 4911
Author(s):  
Daniela Geisler ◽  
Piotr Nikodem Rudziński ◽  
Waseem Hasan ◽  
Martin Andreas ◽  
Ena Hasimbegovic ◽  
...  

Transcatheter aortic valve replacement (TAVR) offers a novel treatment option for patients with severe symptomatic aortic valve stenosis, particularly for patients who are unsuitable candidates for surgical intervention. However, high therapeutical costs, socio-economic considerations, and numerous comorbidities make it necessary to target and allocate available resources efficiently. In the present study, we aimed to identify risk factors associated with futile treatment following transfemoral (TF) and transapical (TA) TAVR. Five hundred and thirty-two consecutive patients (82 ± 9 years, female 63%) who underwent TAVR between June 2009 and December 2016 at the Vienna Heart Center Hietzing were retrospectively analyzed to identify predictors of futility, defined as all-cause mortality at one year following the procedure for the overall patient cohort, as well as the TF and TA cohort. Out of 532 patients, 91 (17%) did not survive the first year after TAVR. A multivariate logistic model identified cerebrovascular disease, home oxygen dependency, wheelchair dependency, periinterventional myocardial infarction, and postinterventional renal replacement therapy as the factors independently associated with an increased one-year mortality. Our findings underscore the significance of a precise preinterventional evaluation, as well as illustrating the subtle differences in baseline characteristics in the TF and TA cohort and their impact on one-year mortality.


BMJ Open ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. e049135
Author(s):  
Irene Lie ◽  
Siv Stafseth ◽  
Laila Skogstad ◽  
Ingvild Strand Hovland ◽  
Haakon Hovde ◽  
...  

ObjectiveTo survey the healthcare professionals’ background and experiences from work with patients with COVID-19 in intensive care units (ICUs) during the first wave of the COVID-19 pandemic in Norway.DesignObservational cohort study.SettingCOVID-ICUs in 27 hospitals across Norway.ParticipantsHealthcare professionals (n=484): nurses (81%), medical doctors (9%) and leaders (10%), who responded to a secured, web-based questionnaire from 6 May 2020 to 15 July 2020.Primary and secondary measuresHealthcare professionals’: (1) professional and psychological preparedness to start working in COVID-ICUs, (2) factors associated with high degree of preparedness and (3) experience of working conditions.ResultsThe age of the respondents was 44.8±10 year (mean±SD), 78% were females, 92% had previous ICU working experience. A majority of the respondents reported professional (81%) and psychological (74%) preparedness for working in COVID-ICU. Factors significantly associated with high professional preparedness for working in COVID-19-ICU in a multivariate logistic model were previous ICU work experience (p<0.001) and participation in COVID-ICU simulation team training (p<0.001). High psychological preparedness was associated with higher age (p=0.003), living with spouse or partner (p=0.013), previous ICU work experience (p=0.042) and participation in COVID-ICU simulation team training (p=0.001). Working with new colleagues and new professional challenges were perceived as positive in a majority of the respondents, whereas 84% felt communication with coworkers to be challenging, 46% were afraid of being infected and 82% felt discomfort in denying access for patient relatives to the unit. Symptoms of sweating, tiredness, dehydration, headache, hunger, insecurity, mask irritation and delayed toilet visits were each reported by more than 50%.ConclusionsHealthcare professionals working during the first wave of COVID-ICU patients in Norway were qualified and prepared, but challenges and potential targets for future improvements were present.Trial registration numberNCT04372056.


Author(s):  
Ronik S. Bhangoo ◽  
Molly M. Petersen ◽  
Gabriella F. Bulman ◽  
Carlos E. Vargas ◽  
Cameron S. Thorpe ◽  
...  

Abstract Purpose and Objectives With increasing use of hypofractionation and extreme hypofractionation for prostate cancer, rectal dose-volume histogram (DVH) parameters that apply across dose fractionations may be helpful for treatment planning in clinical practice. We present an exploratory analysis of biologically effective rectal dose (BED) and equivalent rectal dose in 2 Gy fractions (EQD2) for rectal bleeding in patients treated with proton therapy across dose fractionations. Materials and Methods From 2016 to 2018, 243 patients with prostate cancer were treated with definitive proton therapy. Rectal DVH parameters were obtained from treatment plans, and rectal bleeding events were recorded. The BED and EQD2 transformations were applied to each rectal DVH parameter. Univariate analysis using logistic regression was used to determine DVH parameters that were significant predictors of grade ≥ 2 rectal bleeding. Youden index was used to determine optimum cutoffs for clinically meaningful DVH constraints. Stepwise model-selection criteria were then applied to fit a “best” multivariate logistic model for predicting Common Terminology Criteria for Adverse Events grade ≥ 2 rectal bleeding. Results Conventional fractionation, hypofractionation, and extreme hypofractionation were prescribed to 117 (48%), 84 (34%), and 42 (17.3%) patients, respectively. With a median follow-up of 20 (2.5-40) months, 10 (4.1%) patients experienced rectal bleeding. On univariate analysis, multiple rectal DVH parameters were significantly associated with rectal bleeding across BED, EQD2, and nominal doses. The BED volume receiving 55 Gy &gt; 13.91% was found to be statistically and clinically significant. The BED volume receiving 55 Gy remained statistically significant for an association with rectal bleeding in the multivariate model (odds ratio, 9.81; 95% confidence interval, 2.4-40.5; P = .002). Conclusion In patients undergoing definitive proton therapy for prostate cancer, dose to the rectum and volume of the rectum receiving the dose were significantly associated with rectal bleeding across conventional fractionation, hypofractionation, and extreme hypofractionation when using BED and EQD2 transformations.


PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254005
Author(s):  
Gyan Chandra Kashyap ◽  
Bal Govind ◽  
Shobhit Srivastava ◽  
Veena R. ◽  
Madhumita Bango ◽  
...  

Introduction Though there are several interventions evaluated over the past 25 years, significant knowledge gaps continue to exist regarding the effective prevention of sexual violence. This study explored the socio-economic and context-specific distinctive characteristics of husbands and wives on sexual autonomy and unwanted sexual experiences of currently married women in India. Methodology We have utilized the recent round of National Family Health Survey (NFHS-4, 2015–16) data for this exploration. The NFHS-4 survey had adopted a stratified two-stage sample design to reach out to the survey households. A total of 63,696 couples are included in the analysis comprising of women of 15–49 years age and men of 15–54 years age. Multivariate techniques have been applied to understand the adjusted effects of socio-economic and demographic variables on control over their sexuality and sexual violence. Results Uneducated women married to uneducated men experienced more sexual violence and had less control over their sexuality than the other categories. The adjusted multivariate logistic model shows that educated husbands were significantly more likely to exercise control over their educated wives’ sexuality (AOR = 0.88; CI:0.78–0.99). Women having older husbands were significantly less likely to be having no-control over own sexuality (AOR = 0.89; CI:0.83–0.95) and experienced sexual violence (AOR = 0.81; CI:0.70–0.95). Women having comparatively more-educated husbands were significantly less likely to experience sexual violence (AOR = 0.62; CI:0.47–0.81). Muslim women were significantly more likely to have no control overown sexuality. SC/ST women were significantly more likely to experience sexual violence (28%). Conclusions This study highlights the factors associated with control over one’s sexuality and preponderance to sexual violence: age, education, spouse working status, wealth status, husband’s alcohol consumption, women autonomy, decision-making, and freedom for mobility. This study suggests that empowering women with education, creating awareness regarding reproductive health, and addressing their socio-economic needs to help them achieve autonomy and derive decision-making power.


Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1285
Author(s):  
Alfonso T. García-Sosa

Substances that can modify the androgen receptor pathway in humans and animals are entering the environment and food chain with the proven ability to disrupt hormonal systems and leading to toxicity and adverse effects on reproduction, brain development, and prostate cancer, among others. State-of-the-art databases with experimental data of human, chimp, and rat effects by chemicals have been used to build machine-learning classifiers and regressors and to evaluate these on independent sets. Different featurizations, algorithms, and protein structures lead to different results, with deep neural networks (DNNs) on user-defined physicochemically relevant features developed for this work outperforming graph convolutional, random forest, and large featurizations. The results show that these user-provided structure-, ligand-, and statistically based features and specific DNNs provided the best results as determined by AUC (0.87), MCC (0.47), and other metrics and by their interpretability and chemical meaning of the descriptors/features. In addition, the same features in the DNN method performed better than in a multivariate logistic model: validation MCC = 0.468 and training MCC = 0.868 for the present work compared to evaluation set MCC = 0.2036 and training set MCC = 0.5364 for the multivariate logistic regression on the full, unbalanced set. Techniques of this type may improve AR and toxicity description and prediction, improving assessment and design of compounds. Source code and data are available on github.


Author(s):  
Alfonso T. García-Sosa

Substances that can modify the androgen receptor pathway in humans and animals are entering the environment and food chain with the proven ability to disrupt hormonal systems and leading to toxicity and adverse effects on reproduction, brain development, and prostate cancer, among others. State-of-the-art databases with experimental data of human, chimp, and rat effects by chemicals have been used to build machine learning classifiers and regressors and evaluate these on independent sets. Different featurizations, algorithms, and protein structures lead to dif- ferent results, with deep neural networks (DNNs) on user-defined physicochemically-relevant features developed for this work outperforming graph convolutional, random forest, and large featurizations. The results show that these user-provided structure-, ligand-, and statistically-based features and specific DNNs provided the best results as determined by AUC (0.87), MCC (0.47), and other metrics and by their interpretability and chemical meaning of the descriptors/features. In addition, the same features in the DNN method performed better than in a multivariate logistic model: validation MCC = 0.468 and training MCC = 0.868 for the present work compared to evalu- ation set MCC = 0.2036 and training set MCC = 0.5364 for the multivariate logistic regression on the full, unbalanced set. Techniques of this type may improve AR and toxicity description and predic- tion, improving assessment and design of compounds. Source code and data are available at https://github.com/AlfonsoTGarcia-Sosa/ML


Author(s):  
Alfonso T. García-Sosa

Substances that can modify the androgen receptor pathway in humans and animals are entering the environment and food chain with the proven ability to disrupt hormonal systems and leading to toxicity and adverse effects on reproduction, brain development, and prostate cancer, among others. State-of-the-art databases with experimental data of human, chimp, and rat effects by chemicals have been used to build machine learning classifiers and regressors and evaluate these on independent sets. Different featurizations, algorithms, and protein structures lead to dif- ferent results, with deep neural networks (DNNs) on user-defined physicochemically-relevant features developed for this work outperforming graph convolutional, random forest, and large featurizations. The results show that these user-provided structure-, ligand-, and statistically-based features and specific DNNs provided the best results as determined by AUC (0.87), MCC (0.47), and other metrics and by their interpretability and chemical meaning of the descriptors/features. In addition, the same features in the DNN method performed better than in a multivariate logistic model: validation MCC = 0.468 and training MCC = 0.868 for the present work compared to evalu- ation set MCC = 0.2036 and training set MCC = 0.5364 for the multivariate logistic regression on the full, unbalanced set. Techniques of this type may improve AR and toxicity description and predic- tion, improving assessment and design of compounds. Source code and data are available at https://github.com/AlfonsoTGarcia-Sosa/ML


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hiroshi Hanamoto ◽  
Hikaru Nakagawa ◽  
Hitoshi Niwa

Abstract Background The insertion of inappropriately sized uncuffed endotracheal tubes (ETTs) with a tight seal or presence of air leakage may be necessary in children. This study aimed to analyze the frequency of the requirement of inappropriately sized uncuffed ETT insertion, air leakage after the ETT was replaced with one of a larger size, and factors associated with air leakage after ETT replacement. Methods Patients under 2 years of age who underwent oral surgery under general anesthesia with uncuffed ETTs between December 2013 and May 2015 were enrolled. The ETT size was selected at the discretion of the attending anesthesiologists. A leak test was performed after intubation. The ETT was replaced when considered necessary. Data regarding the leak pressure (PLeak) and inspiratory and expiratory tidal volumes were extracted from anesthesia records. We considered a PLeak of 10 < PLeak ≤ 30 cmH2O to be appropriate. The frequencies of the requirement of inappropriately sized ETTs, absence of leakage after ETT replacement, ETT size difference, and leak rate were calculated. A logistic regression was performed, with PLeak, leak rate, and size difference included as explanatory variables and presence of leakage after replacement as the outcome variable. Results Out of the 156 patients enrolled, 109 underwent ETT replacement, with the requirement of inappropriately sized ETTs being observed in 25 patients (23%). ETT replacement was performed in patients with PLeak ≤ 10 cmH2O; leakage was absent after replacement (PLeak < 30 cmH2O) in 52% of patients (25/48). In the multivariate logistic model, the leak rate before ETT replacement was significantly associated with the presence of leakage after replacement (p = 0.021). Conclusions Inappropriately sized ETTs were inserted in approximately 23% of the patients. The leak rate may be useful to guide ETT replacement.


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