scholarly journals Prediction of spontaneous resolution of primary vesicoureteral reflux in children

2021 ◽  
Vol 10 (224) ◽  
Author(s):  
Vitaly Dubrov ◽  
◽  
Alexander Strotsky ◽  
Tatiana Pavlovich ◽  
Alexander Sukalo ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Prognostic Model ◽  
Conservative Therapy ◽  
Cox Regression ◽  
Binary Logistic Regression ◽  
Spontaneous Resolution ◽  
Factors Influencing ◽  
Primary Vesicoureteral Reflux ◽  
Optimal Treatment Strategy

The retrospective study is based on a database of 871 patients who received conservative therapy for primary VUR. A one-way survival analysis was used to assess the factors influencing the likelihood of spontaneous resolution of VUR. Cox regression was performed for multivariate analysis. The construction of the predictive model was carried out using binary logistic regression. The developed prognostic model is highly reliable, its application can facilitate the adoption of an optimal treatment strategy.

scholarly journals The Predictive Role of NLR, d-NLR, MLR, and SIRI in COVID-19 Mortality

Diagnostics ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 122
Author(s):  
Cosmin Citu ◽  
Florin Gorun ◽  
Andrei Motoc ◽  
Ioan Sas ◽  
Oana Maria Gorun ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cox Regression ◽  
Binary Logistic Regression ◽  
Hospital Death ◽  
Optimal Cutoff ◽  
Inflammatory Index ◽  
Cell Counts ◽  
Risk Of Mortality ◽  
Predictive Role

(1) Background: Since its discovery, COVID-19 has caused more than 256 million cases, with a cumulative death toll of more than 5.1 million, worldwide. Early identification of patients at high risk of mortality is of great importance in saving the lives of COVID-19 patients. The study aims to assess the utility of various inflammatory markers in predicting mortality among hospitalized patients with COVID-19. (2) Methods: A retrospective observational study was conducted among 108 patients with laboratory-confirmed COVID-19 hospitalized between 1 May 2021 and 31 October 2021 at Municipal Emergency Clinical Hospital of Timisoara, Romania. Blood cell counts at admission were used to obtain NLR, dNLR, MLR, PLR, SII, and SIRI. The association of inflammatory index and mortality was assessed via Kaplan–Maier curves univariate Cox regression and binominal logistic regression. (3) Results: The median age was 63.31 ± 14.83, the rate of in-hospital death being 15.7%. The optimal cutoff for NLR, dNLR, MLR, and SIRI was 9.1, 9.6, 0.69, and 2.2. AUC for PLR and SII had no statistically significant discriminatory value. The binary logistic regression identified elevated NLR (aOR = 4.14), dNLR (aOR = 14.09), and MLR (aOR = 3.29), as independent factors for poor clinical outcome of COVID-19. (4) Conclusions: NLR, dNLR, MLR have significant predictive value in COVID-19 mortality.

scholarly journals Comprehensive Analysis of the Functions, Prognostic and Diagnostic Values of RNA Binding Proteins in Head and Neck Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Xueping Ke ◽  
Zhen Fu ◽  
Jingjing Yang ◽  
Shijin Yu ◽  
Tingyuan Yan ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cell Carcinoma ◽  
Prognostic Model ◽  
Rna Binding ◽  
Cox Regression ◽  
Validation Cohort ◽  
Characteristic Curve ◽  
Training Cohort

Abstract Background: Increasing evidence has suggested that RNA binding protein (RBP) dysregulation plays an important part in tumorigenesis. Here, we sought to explore the potential molecular functions and clinical significance of RBP and develop diagnostic and prognostic signatures based on RBP in patients with head and neck squamous cell carcinoma (HNSCC). Methods: The Limma package was applied to identify the differently expressed RBPs between HNSCC and normal samples with |log2 fold change (FC)|≥1 and false discovery rate (FDR)<0.05. the immunohistochemistry images from the Human Protein Atlas database The diagnostic signature based on RBP was built by LASSO-logistic regression and random forest and the prognostic signature based on RBP was constructed by LASSO and stepwise Cox regression analysis in training cohort and validated in validation cohort. All these analyses were performed using the R software.Results: A total of 84 aberrantly expressed RBPs were obtained, comprising 41 up-regulated and 43 down-regulated RBPs. Seven RBP genes (CPEB3, PDCD4, ENDOU, PARP12, DNMT3B, IGF2BP1, EXO1) were identified as diagnostic related hub gene and were used to establish a diagnostic RBP signature risk score (DRBPS) model by the coefficients in LASSO-logistic regression analysis and shown high specificity and sensitivity in the training (area under the receiver operating characteristic curve [AUC] = 0.998), and in all validation cohorts (AUC > 0.95 for all). Similarly, seven RBP genes (MKRN3, ZC3H12D, EIF5A2, AFF3, SIDT1, RBM24 and NR0B1) were identified as prognosis associated hub genes by least absolute shrinkage and selection operator (LASSO) and stepwise multiple Cox regression analyses and were used to construct the prognostic model named as PRBPS. The area under the curve of the time-dependent receiver operator characteristic curve of the prognostic model were 0.664 at 3 years and 0.635 at 5 years in training cohort and 0.720, 0.777 in the validation cohort, showing a favorable predictive effificacy for prognosis in HNSCC.Conclusions: Our results demonstrate the values of consideration of RBP in the diagnosis and prognosis for HNSCC and provide a novel insights to understand potential role of dysregulated RBP in HNSCC.

scholarly journals Estimating seroprevalence of SARS-CoV-2 antibodies using three self-reported symptoms: Development of a prediction model based on data from Ischgl, Austria

2020 ◽  
Author(s):  
Jens Lehmann ◽  
Johannes M Giesinger ◽  
Gerhard Rumpold ◽  
Wegene Borena ◽  
Ludwig Knabl ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Prediction Model ◽  
Regression Model ◽  
Web Application ◽  
Binary Logistic Regression ◽  
Population Level ◽  
Limb Pain ◽  
The Past ◽  
Model Based

We report the development of a regression model to predict prevalence of SARS-CoV-2 antibodies on a population level based on self-reported symptoms.We assessed participant-reported symptoms in the past twelve weeks, as well as presence of SARS-CoV-2 antibodies during a study conducted in April 2020 in Ischgl, Austria. We conducted multivariate binary logistic regression to predict seroprevalence in the sample. Participants (n=451) were on average 47.4 years old (SD 16.8) and 52.5% female. SARS-CoV-2 antibodies were found in n=197 (43.7%) participants. In the multivariate analysis, three significant predictors were included: Odds ratios (OR) for the most predictive categories were: cough (OR 3.34, CI 1.70 - 6.58), gustatory/olfactory alterations (OR 13.78, CI 5.90 - 32.17), and limb pain (OR 2.55, CI 1.20 - 6.50). The AUC was 0.773 (95% CI: 0.727-0.820).Our regression model may be used to estimate seroprevalence on a population-level and a web application is being developed to facilitate use of the model.

scholarly journals Factors influencing nurses' knowledge and skills in the prevention and management of postpartum haemorrhage

2019 ◽  
Vol 13 (4) ◽  
Author(s):  
Joho A. Angelina ◽  
Stephen M. Kibusi ◽  
Ipyana Mwampagatwa
Keyword(s):  
Logistic Regression ◽  
Professional Training ◽  
Postpartum Haemorrhage ◽  
Binary Logistic Regression ◽  
Reduced Model ◽  
Sociodemographic Characteristics ◽  
Maternity Unit ◽  
Knowledge And Skills ◽  
Factors Influencing ◽  
Nurses Knowledge

Background: Postpartum haemorrhage (PPH) is one of the main causes of maternal death. In Tanzania, 25% of maternal deaths are the result of PPH. Gaps in practitioner knowledge in the prevention and management of this issue may lead to severe maternal complications and death. Little has been documented about nurses' knowledge and skills regarding PPH prevention and management. Objective: To determine the factors influencing nurses' knowledge and skill in the prevention and management of PPH in the Dodoma Region, Central Tanzania. Method: A cross-sectional study was conducted involving 172 nurses working in Dodoma, Tanzania. Data on the sociodemographic characteristics of the nurses was collected using a structured questionnaire. Knowledge on PPH was assessed using a validated questionnaire and skills were assessed using an observational checklist. The chi-squared test was used to find associations between sociodemographic characteristics and knowledge and skills. Binary logistic regression (both reduced and full models) was used to identify significant predictors of knowledge and skills. Results: The findings indicated that being ≥40 years old (OR=2.87, P=0.004), being a registered nurse (OR=2.73, P=0.002), having >3 years of professional training (OR=2.38, P=0.01), and having ≥5 years of experience in a maternity unit (OR=3.06, P<0.00) were significant predictors for knowledge in the prevention and management of PPH in a reduced model of binary logistic regression. Being ≥40 years old (OR=11.5, P=0.00), having >3 years of professional training (OR=4.58, P<0.00), and having ≥5 years of experience in a maternity unit (OR=9.14, P<0.00) were significant predictors for skills in the reduced model. After adjusting to control for possible confounders, being a registered nurse was the only significant predictor of nurses' knowledge (AOR=3.35, P=0.001), while having ≥5 years experience in a maternity unit was the only significant predictor of nurses' skills (AOR=3.89, P=0.01). Conclusion: Professional qualification and experience in a maternity unit are significant factors influencing nurses' knowledge and skills, respectively, in the prevention and management of PPH.

Low Tibial Valgization Osteotomy for More Severe Varus Ankle Arthritis

2020 ◽  
Vol 41 (9) ◽  
pp. 1122-1132
Author(s):  
Jun Young Choi ◽  
Kun Woo Kim ◽  
Jin Soo Suh
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Ankle Arthritis ◽  
Level Of Evidence ◽  
Opening Wedge ◽  
Hindfoot Alignment ◽  
Factors Influencing

Background: Low tibial valgization osteotomy with medial opening wedge (LTO) is generally indicated for ankle arthritis with a small talar tilt (TT). We addressed the following research questions: the efficacy of LTO for more significant varus ankle arthritis, the effect of additional inframalleolar correction followed by LTO, and the preoperative or operation-related factors influencing postoperative TT decrease. Methods: We retrospectively reviewed the radiographic and clinical findings of 31 patients with more significant varus ankle arthritis (≥8 degrees) who underwent LTO or LTO plus inframalleolar correction. We grouped the included patients according to combination with inframalleolar correction and postoperative decreased TT. Furthermore, a binary logistic regression analysis was performed to determine the factors influencing postoperative TT decrease. Results: Even though the mean TT was unchanged postoperatively (from 12.1 to 9.9 degrees, P = .052), clinical parameters were significantly increased. In the group with concomitant inframalleolar correction, we found that TT was more corrected (3.9 vs 1.8 degrees, P = .023) with a greater lateralization of the talar center and a greater correction of the hindfoot alignment to valgus. The results of the binary logistic regression analysis showed a significant relationship between postoperative decreased TT and preoperative talar center migration ( P = .016), hindfoot alignment angle ( P = .033), hindfoot moment arm ( P = .041), and hindfoot alignment ratio ( P = .016). Conclusion: LTO in more significant varus ankle arthritis could result in clinical improvement, although TT was not significantly changed. We recommend adding inframalleolar correction after LTO for the patients with more significant varus ankle arthritis. Level of Evidence: Level III, comparative series.

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI MINAT PETANI DALAM BERUSAHATANI PADI DI KECAMATAN KEBAKKRAMAT KABUPATEN KARANGANYAR

2016 ◽  
Vol 12 (2) ◽  
pp. 205
Author(s):  
Ardiyono Muhammad ◽  
Agustono Agustono ◽  
Arip Wijianto
Keyword(s):  
Logistic Regression ◽  
Data Analysis ◽  
Commodity Prices ◽  
Secondary Data ◽  
Binary Logistic Regression ◽  
Real Variable ◽  
Efficiency Analysis ◽  
Sample Collection ◽  
Factors Influencing ◽  
Farm Efficiency

The research aims are (1) Analyse cost, revenue and income (2) Efficiency farming (3) Analyse the factors influencing interest farmers in the cultivation of rice in Kebakkramat  district  Karanganyar.  The  basic  method  of  this  research  used  the explanatory  method.  Research  locations  are  Kebakkramat  district  Karanganyar. Method of the sample collection that is purposive sampling with the sample of the 60 farmers. The data used in this research are primary and secondary data. Methods of data analysis used in this research are (1) Analysis of cost, Revenue and Income (2) Efficiency  Analysis  (3)  Binary  Logistic  Regression.  The  results  showed  that  (1) Average cost of seeking Rp 4.457.348 per UT or Rp  9.682.870 per Ha, revenue of Rp 12.749.167 per UT or Rp 27.695.510 per Ha, earn an income of Rp 8.291.819 per UT or  Rp  18.012.641  per  Ha  (2)  Farm  efficiency  of  2.89  (3)  Variables  influential  real with an odd ratio: Variable commodity prices , variable price seed , variable the price of  fertilizer  and  variable  the  availability  of  water.  While  variables  which  not influential  real:  Variable  area  of  land,  variable  experience,  variable  age,  variable education, variable government assistance, and variable alternation planting.

scholarly journals Factors Affecting the Consumer's Branded Tea Purchase Decision: A Case Study in the Western Province, Sri Lanka

2021 ◽  
pp. 67-73
Author(s):  
A. M. K. R. Bandara ◽  
H. M. M. Gayathri ◽  
A. I. Y. Lankapura
Keyword(s):  
Factor Analysis ◽  
Logistic Regression ◽  
Sri Lanka ◽  
Brand Loyalty ◽  
Binary Logistic Regression ◽  
Purchase Decision ◽  
Western Province ◽  
Factors Influencing ◽  
Main Factors ◽  
Product Marketing

Aims: The purpose of this paper is to identify the factors influencing on consumers' purchasing decisions for branded tea in Sri Lanka. This study investigated the relationship between the factors influencing a consumer's purchase decision on branded tea and the consumer's loyalty behavior. The study concentrated primarily on the socioeconomic factors that influence consumer brand loyalty for tea. Study Design: Multi-stage quota sampling. Place and Duration of Study: The study was carried out in the Western province, the most densely populated province, and the main administrative and commercial center of Sri Lanka in 2016 - 2017. Methodology: Both primary and secondary data were used in the study. Primary data were mainly collected from a survey using a pre-tested, structured questionnaire. Descriptive analytical techniques, factor analysis, and binary logistic regression analysis were used for data analysis. Statistical analysis was performed using both SPSS and SAS software. Results: According to the factor analysis, three main factors were recognized, such as product, marketing, and lifestyle. The product factor contributes 31 percent to the total variation that implies the prominence of product-oriented variables over the other variables considered. Among the related variables of the product, the highest factor loading (0,963) was received by the taste of the product, while the price (0,946) was the next. The results of the binary logistic regression revealed that both the level of education (ED) and the level of income (IL) had a significant impact on tea brand loyalty. Conclusion: The study concludes that both income and education have a significant impact on brand loyalty for tea, while product, marketing, and life-style attributes are the main factors influencing the purchase decision of the branded tea by the consumer. As product-related attributes contribute more to the purchase decision of branded tea, firms can increase their market share by planning their marketing strategies, focusing mainly on product-related aspects.

Genetic profile of polyps and risk of advanced metachronous lesions.

2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 555-555
Author(s):  
Oscar Murcia ◽  
Miriam Juárez ◽  
Maria Rodriguez-Soler ◽  
Eva Hernández-Illán ◽  
Cecilia Egoavil ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Cox Regression ◽  
Univariate Analysis ◽  
Colonic Polyps ◽  
Rank Test ◽  
Genetic Profile ◽  
Braf Mutations ◽  
Allelic Discrimination ◽  
Kras Mutations

555 Background: The role of genetic profile of polyps to predict advanced metachronous lesions (AML) remains unknown. The aim is to study the relation between genetic profile of polyps and both risk of AMLs and time to develop them in surveillance. Methods: 308 patients with colonic polyps were consecutively enrolled between 2007 and 2009 for this cohort study, and followed up to 2014 (median 26 months, range 63). Variables as age, sex, smoking, weight, number of colonoscopies and number and characteristics of polyps were collected. 995 polyps were analyzed for somatic mutations on BRAF and KRAS genes using allelic discrimination by real-time PCR and direct DNA sequenciation, respectively. High level of methylation on CpG islands (CIMP-H) was also tested using MS-MLPA. AML was defined by a size higher than 9mm, high grade dysplasia or villous component. Risk of developing AML for individual genetic markers was studied using Chi-square tests and logistic regression. Log-rank test with Kaplan Meier survival curves and Cox-regression model were also performed. Multivariate analysis were adjusted by sex, age, familial colorectal cancer, smoking and features of AML in first colonoscopy. Results: 21% of polyps in first colonoscopy were CIMP-H. KRAS and BRAF mutations accounted for 25% and 17% of polyps, respectively. In univariate analysis, KRAS-mutated polyps were related to higher risk of AML in surveillance (52% KRAS-mutated polyps vs 31% non-mutated; p = 0.01). Similar results were obtained regarding CIMP-H (77% CIMP-H polyps vs 38% non-CIMP; p = 0.005). Logistic regression showed CIMP-H as the unique genetic marker of risk for AML (OR 11.41, 95% CI 2.04-63.70; p = 0.006). Regarding time to develop AML, shorter intervals were found related to CIMP-H (median of 31 vs 48 months in non-CIMP-H; p = 0.002) and KRAS-mutations (median of 36 vs 49 months in non-mutated; p = 0.029) in univariate analysis. Multivariate analysis highlighted CIMP-H as the unique independent marker associated to shorter time to develop AML (HR 4.01, 95% CI 1.36-10.46; p = 0.01). Conclusions: Presence of CIMP-H in polyps associates higher risk of subsequent AML and shorter interval to their development. Genetic profile of polyps emerges as useful tool for colonoscopy surveillance.

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