scholarly journals Validation and deployment of a direct saliva real-time RT-PCR test on pooled samples for COVID-19 surveillance testing

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261956
Author(s):  
Amanda Rainey ◽  
Austin Pierce ◽  
Xiaoyun Deng ◽  
Luis A. Actis ◽  
Philip Smith ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Real Time ◽  
Nasal Swab ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Rt Pcr ◽  
Confirmatory Tests ◽  
Pooled Samples ◽  
Pcr Test

A direct, real-time reverse transcriptase PCR test on pooled saliva was validated in 2,786 participants against oropharyngeal swabs. Among asymptomatic/pre-symptomatic participants, the test was found to be in 99.21% agreement and 45% more sensitive than contemporaneous oropharyngeal swabs. The test was then used for surveillance testing on 44,242 saliva samples from asymptomatic participants. Those whose saliva showed evidence of SARS-CoV-2 within 50 cycles of amplification were referred for confirmatory testing, with 87% of those tested by nasal swab within 72 hours receiving a positive diagnostic result on Abbott ID NOW or real-time PCR platforms. Median Ct values on the saliva PCR for those with a positive and negative confirmatory tests was 30.67 and 35.92 respectively, however, binary logistic regression analysis of the saliva Ct values indicates that Ct thresholds as high as 47 may be useful in a surveillance setting. Overall, data indicate that direct RT-PCR testing of pooled saliva samples is an effective method of SARS-CoV-2 surveillance.

scholarly journals Predicting Burn Mortality Using a Simple Novel Prediction Model

2021 ◽  
Author(s):  
Sneha Sharma ◽  
Raman Tandon
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Prediction Model ◽  
Receiver Operating Characteristic ◽  
Logistic Regression Analysis ◽  
Operating Characteristic ◽  
Binary Logistic Regression ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Binary Logistic Regression Analysis

Abstract Background Prediction of outcome for burn patients allows appropriate allocation of resources and prognostication. There is a paucity of simple to use burn-specific mortality prediction models which consider both endogenous and exogenous factors. Our objective was to create such a model. Methods A prospective observational study was performed on consecutive eligible consenting burns patients. Demographic data, total burn surface area (TBSA), results of complete blood count, kidney function test, and arterial blood gas analysis were collected. The quantitative variables were compared using the unpaired student t-test/nonparametric Mann Whitney U-test. Qualitative variables were compared using the ⊠2-test/Fischer exact test. Binary logistic regression analysis was done and a logit score was derived and simplified. The discrimination of these models was tested using the receiver operating characteristic curve; calibration was checked using the Hosmer—Lemeshow goodness of fit statistic, and the probability of death calculated. Validation was done using the bootstrapping technique in 5,000 samples. A p-value of <0.05 was considered significant. Results On univariate analysis TBSA (p <0.001) and Acute Physiology and Chronic Health Evaluation II (APACHE II) score (p = 0.004) were found to be independent predictors of mortality. TBSA (odds ratio [OR] 1.094, 95% confidence interval [CI] 1.037–1.155, p = 0.001) and APACHE II (OR 1.166, 95% CI 1.034–1.313, p = 0.012) retained significance on binary logistic regression analysis. The prediction model devised performed well (area under the receiver operating characteristic 0.778, 95% CI 0.681–0.875). Conclusion The prediction of mortality can be done accurately at the bedside using TBSA and APACHE II score.

scholarly journals Predicting organizational performance from motivation in Oromia Seed Enterprise Bale branch

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Askalech Feyisa Jobira ◽  
Abdulnasir Abdulmelike Mohammed
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Intrinsic Motivation ◽  
Organizational Performance ◽  
Logistic Regression Analysis ◽  
Extrinsic Motivation ◽  
Binary Logistic Regression ◽  
Moderate Level ◽  
Binary Logistic Regression Analysis ◽  
Study Results

AbstractMotivation is one of the most researched yet crucial topics in academia from various perspectives. Despite this, researches show mixed results about the effect of extrinsic motivation on intrinsic motivation and organizational performance. Studies in Ethiopia also lack causal analysis and theoretical underpinning that made contributions from academia very little. Hence, this research is important to assess the effect of extrinsic motivation on intrinsic motivation and organizational performance from a cognitive evaluation theory perspective. The researchers adopted an explanatory research design with a quantitative approach. The entire 119 employees of the Oromia Seed Enterprise, Bale branch were included in the study to collect primary data through a close-ended questionnaire. The collected data was processed by SPSS software version 20. The relationship analysis was addressed by correlation and binary logistic regression analysis. Seen from extrinsic and intrinsic motivation aspects, the findings of the study showed that Oromia Seed Enterprise had a moderate level of organizational performance and a moderate level of employees’ motivation. The correlation analysis result indicated that employees’ extrinsic and intrinsic motivation had a positive relationship with organizational performance. The binary logistic regression analysis also indicated that extrinsic and intrinsic motivation had a positive and significant influence on organizational performance. However, the interaction effect of intrinsic and extrinsic motivation on organizational performance was not significant, implying the absence of influence when both intrinsic and extrinsic motivations happen at the same time. Finally, the study results have a theoretical contribution for compensating the lack of actual experience in the Ethiopian organization’s context. Equally, the understanding of the moderated relationship among the study variables may encourage Oromia Seed Enterprise and its managers to develop a practical motivation system, which entertains the complex interaction of motivation variables to improve organizational performance. In addition, studies of this nature can inform policymakers to strengthen an incentive system as well as other motivation veins in the Ethiopian public organizations.

scholarly journals Association between the non-HDL-cholesterol to HDL-cholesterol ratio and non-alcoholic fatty liver disease in Chinese children and adolescents: a large single-center cross-sectional study

2020 ◽  
Author(s):  
Shouxing Yang ◽  
Jinwei Zhong ◽  
Mengsi Ye ◽  
Lei Miao ◽  
Guangrong Lu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Children And Adolescents ◽  
Binary Logistic Regression ◽  
Hdl Cholesterol ◽  
Chinese Children ◽  
Binary Logistic Regression Analysis ◽  
Cross Sectional ◽  
Alcoholic Fatty Liver ◽  
Chinese Children And Adolescents

Abstract Background: The non-HDL-cholesterol to HDL-cholesterol (NHDLC/HDLC) ratio is closely related to a variety of dyslipidemia-related diseases. This study aimed to inspect the relationship between the NHDLC/HDLC ratio and non-alcoholic fatty liver (NAFLD) in children and adolescents.Methods: In this cross-sectional survey, a total of 7,759 eligible Chinese children and adolescents (5,692 boys and 2,067 girls) received routine medical examinations. The anthropometric and laboratory data of the subjects were collected. NAFLD was diagnosed by liver ultrasonography. Binary logistic regression analysis was performed on the NHDLC/HDLC ratio, NHDLC, HDLC and NAFLD. Receiver operating characteristic (ROC) curve analysis was exploited to compare the diagnostic significance of the above parameters for NAFLD.Results: The total prevalence of NAFLD was 4.36%, and the prevalence in boys was higher than that in girls (5.61% vs. 1.9%, P < 0.001). The prevalence of NAFLD was positively correlated with the NHDLC/HDLC ratio (P < 0.001). The binary logistic regression analysis demonstrated that the OR was 8.61 (95% CI, 5.90-12.57, P < 0.001) in tertile 3 (highest NHDLC/HDLC ratio) compared with tertile 1 (lowest NHDLC/HDLC ratio). After adjustment for age, sex, body mass index (BMI), alanine aminotransferase (ALT), uric acid (UA), total bilirubin (TB), fasting plasma glucose (FPG) and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), the OR for tertile 3 (OR=1.83, 95% CI, 1.04-3.22, P = 0.035) was still significantly higher than that of tertile 1. The area under the curve (AUC) of the NHDLC/HDLC ratio of boys was 0.787, which was significantly greater than that of NHDLC and HDLC (0.719 and 0.726, P < 0.001). For girls, the AUC of the NHDLC/HDLC ratio was 0.763, which was also significantly greater than that of NHDLC (0.661, P < 0.001). Furthermore, the cutoff point of the NHDLC/HDLC ratio was 2.475 in boys and 2.695 in girls. In addition, the AUC of the NHDLC/HDLC ratio was 0.761 in subjects with normal ALT levels (ALT ≤ 40 U/L), which was significantly higher than that of NHDLC (0.680, P < 0.001) and HDLC (0.724, P = 0.007). For subjects with elevated ALT levels (ALT > 40 U/L), the AUC of the NHDLC/HDLC ratio (0.746) was also significantly greater than that of NHDLC (0.646, P < 0.001)Conclusions: The NHDLC/HDLC ratio was positively correlated with NAFLD in Chinese children and adolescents. It may serve as an effective indicator to help identify NAFLD in children and adolescents.

scholarly journals PENGARUH KEBUTUHAN BERPRESTASI DAN KARAKTERISTIK PERSONAL TERHADAP KINERJA USAHA WIRAUSAHA WANITA (Survey pada Petani Tanaman Obat Keluarga (TOGA) di Kecamatan Jumantono Kabupaten Karanganyar)

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Setyaningsih SU ◽  
Edi Wibowo
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Women Entrepreneurs ◽  
Business Performance ◽  
Binary Logistic Regression ◽  
Personal Characteristics ◽  
Binary Logistic Regression Analysis ◽  
Entrepreneurship Training ◽  
Analysis Technique ◽  
Business Experience

This study aims to analyze the effect of the needs of achievement and personal characteristics (education, age, experience, training) on business performance. This research is census research, using 63 respondents of women entrepreneurs to Toga farmers in Jumantono District, Karanganyar Regency. Data analysis technique using binary logistic regression analysis. The conclusions from the results of this study indicate that the needs of achievement and personal characteristics of business experience have a significant effect on business performance, while the variables of education, age, and entrepreneurship training have no significant effect on business performance. Based on the results of this study, the odds/probabilities of the performance of women's entrepreneurial business in Toga farmers in Jumantono District, Karanganyar Regency can be predicted by the needs of achievement and business experience. The implication of this finding is that to achieve high business performance, Toga farmers in Jumantono District, Karanganyar Regency need to increase their needs for achievement and business experience.Keywords: needs of achievement, education, age, experience, training, business performance

scholarly journals Determining factors in MSMEs success: An empirical study in Mexico

2022 ◽  
Vol 6 (1) ◽  
pp. e384
Author(s):  
Rubén Molina-Sánchez ◽  
Domingo García-Pérez-de-Lema ◽  
Alejandra López-Salazar ◽  
Roberto Godínez-López
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Empirical Study ◽  
Small And Medium Enterprises ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Technology And Innovation ◽  
Determining Factors ◽  
Quality Technology ◽  
Medium Enterprises

This work empirically analyzes the competitive factors that help make micro, small, and medium enterprises (MSMEs) successful. To do this, an empirical study with a sample of 614 companies in Guanajuato, Mexico, has been carried out. The results of the binary logistic regression analysis show that quality, technology, and innovation are the main variables that determine a company’s success. These findings could provide guidelines to help MSMEs improve their competitiveness, and they could help public administrations better support MSME growth.

scholarly journals Binary Logistic Regression Analysis of Variables That Influence Poverty in Central Java

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Sendi Nugraha Nurdiansah ◽  
Laelatul Khikmah
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Binary Logistic Regression ◽  
Equation Model ◽  
Binary Logistic Regression Analysis ◽  
Poor People ◽  
Regional Government ◽  
Central Java ◽  
The Government

The phenomenon of poverty is a serious problem faced by almost every country in the world. This is because poverty can affect various aspects of people's lives. One of the causes of poverty is due to lack of income and assets to meet basic needs such as food, clothing, housing, health level and acceptable education. In addition, poverty occurs because of the powerlessness of society to get out of the problems it faces. The Central Java regional government incorporated poverty issues into the Regional Medium-Term Development Plan (RPJMD) because Central Java has a high number of poor people. This was done as an effort by the Central Java government to reduce poverty. Therefore, research is needed to find out the variables that most influence poverty in order to assist the government in developing the RPJMD. To find out what factors influence poverty in Central Java with the dichotomous categorical response variable, binary logistic regression analysis was used. The results showed that based on the analysis conducted did not obtain a logistic regression equation model because there were no significant parameters because there were no variables that had a sig value <0.05. Existing variables are Number of Population, Female Head of Household, Number of Children not in School, Number of Disabled Individuals, Number of Chronic Disease Individuals, Unemployment, Non-Electricity Lighting Sources, Unprotected Drinking Water Sources, Kerosene and Wood Cooking Fuels, Location Facilities Defecation (BAB) Not Available, so there are no variables that affect the level of poverty in Central Java Province.

scholarly journals Factors affecting internet use among university students in Sarawak, Malaysia: an empirical study

2020 ◽  
Vol 7 (3) ◽  
pp. 848
Author(s):  
M. Mizanur Rahman ◽  
M. Taha Arif ◽  
Fready Luke ◽  
Santha Letchumi ◽  
Fatin Nabila ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
University Students ◽  
Logistic Regression Analysis ◽  
Internet Use ◽  
Binary Logistic Regression ◽  
Problematic Internet Use ◽  
The Internet ◽  
Binary Logistic Regression Analysis ◽  
Factors Affecting

Background: The internet has become an indispensable tool for communication, academic research, information and entertainment. However, heavy users of the internet lead to less confidence in social skills and the tendency to be isolated. The study aimed to assess the pattern of internet use and factors affecting problematic internet use among university students.Methods: This cross-sectional study conducted among the students of a university in Sarawak, Malaysia. A multistage cluster sampling technique was adapted to select the participants. Data were collected from 463 students by self-administered questionnaire. Hierarchical binary logistic regression analysis was done to determine the potential factors for problematic internet use.Results: The mean age of the students was 22 years, with a standard deviation of 1.6 years. Two-fifths (61.8%) of the students had no problematic internet use. However, 35.4% had moderate and 2.8% had severe problematic internet use. Hierarchical binary logistic regression analysis found that age of the students, year of study, duration of daily internet use and use of social networking like Skype appeared to be potential predictors of problematic internet use (p<0.05).Conclusions: This study was conducted in only one university, thus did not depict the overall scenarios of the country. The implications of the findings are still worth noting in the process of designing internet addiction studies among university students. Overall, this study has unearthed some useful insights which can serve as a guide to more elaborate studies.

Clinical Factors Associated with the Diagnosis of Granulomatosis with Polyangiitis

2017 ◽  
Vol 156 (3) ◽  
pp. 484-488 ◽  
Author(s):  
Erdem Eren ◽  
Toygar Kalkan ◽  
Seçil Arslanoğlu ◽  
Mustafa Özmen ◽  
Kazım Önal ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Nasal Mucosa ◽  
Odds Ratio ◽  
Granulomatosis With Polyangiitis ◽  
Univariate Analysis ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Significant Difference ◽  
History Of

Objective To determine the predictive value of nasal endoscopic findings and symptoms in the diagnosis of granulomatosis with polyangiitis (GPA). Study Design A cross-sectional study. Setting A tertiary university hospital. Subjects and Methods A total of 116 adults were enrolled in the study: 19 patients with GPA, 29 patients with other rheumatic diseases, and 68 healthy volunteers. All patients were examined with a flexible endoscope, and nasal endoscopic images were recorded and evaluated blindly. The medical history of each patient was taken by a physician blinded to the patient’s diagnosis. Results Univariate analysis indicated a statistically significant difference in rhinorrhea ( P = .002), postnasal drip ( P = .015), epistaxis ( P < .001), and saddle nose ( P = .017). However, binary logistic regression analysis demonstrated that only history of epistaxis ( P = .012; odds ratio, 5.6) was statistically significant in predicting GPA. Univariate analysis showed a statistically significant difference in nasal secretion ( P = .028), nasal septal perforation ( P < .017), nasal crusting ( P < .001), nasal adhesion ( P < .001), nasal granuloma ( P = .017), and hemorrhagic fragile nasal mucosa ( P < .001). A binary logistic regression analysis demonstrated that only hemorrhagic fragile nasal mucosa ( P < .001; odds ratio, 52.9) was a statistically significant predictor of GPA. Conclusions Given the results of this study, we believe that hemorrhagic fragile nasal mucosa and history of recurrent epistaxis may put patients at risk for GPA and should be investigated accordingly.

scholarly journals Differential analysis of disease risk assessment using binary logistic regression with different analysis strategies

2018 ◽  
Vol 46 (9) ◽  
pp. 3656-3664 ◽  
Author(s):  
Wenbo Xu ◽  
Yang Zhao ◽  
Shiyan Nian ◽  
Lei Feng ◽  
Xuejing Bai ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Density Lipoprotein ◽  
Binary Logistic Regression ◽  
Lipoprotein Cholesterol ◽  
Binary Logistic Regression Analysis ◽  
Confounding Factors ◽  
Analysis Strategies ◽  
Glutamyl Transferase

Objective To investigate the importance of controlling confounding factors during binary logistic regression analysis. Methods Male coronary heart disease (CHD) patients (n = 664) and healthy control subjects (n = 400) were enrolled. Fourteen indexes were collected: age, uric acid, cholesterol, triglyceride, high density lipoprotein cholesterol, low density lipoprotein cholesterol, apolipoprotein A1, apolipoprotein B100, lipoprotein a, homocysteine, total bilirubin, direct bilirubin, indirect bilirubin, and γ-glutamyl transferase. Associations between these indexes and CHD were assessed by logistic regression, and results were compared by using different analysis strategies. Results 1) Without controlling for confounding factors, 14 indexes were directly inputted in the analysis process, and 11 indexes were finally retained. A model was obtained with conflicting results. 2) According to the application conditions for logistic regression analysis, all 14 indexes were weighed according to their variances and the results of correlation analysis. Seven indexes were finally included in the model. The model was verified by receiver operating characteristic curve, with an area under the curve of 0.927. Conclusions When binary logistic regression analysis is used to evaluate the complex relationships between risk factors and CHD, strict control of confounding factors can improve the reliability and validity of the analysis.

scholarly journals A Welfare Model of Street Vendors: Cases from Denpasar, Bali, Indonesia

2019 ◽  
Vol 9 (3) ◽  
pp. 1
Author(s):  
Desak Putu Eka Nilakusmawati ◽  
Made Susilawati ◽  
Geoffrey Wall
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Employment Status ◽  
Binary Logistic Regression ◽  
Well Being ◽  
Binary Logistic Regression Analysis ◽  
Family Labor ◽  
Street Vendors ◽  
Business Skills ◽  
Welfare Model

This study determines the socio-economic characteristics of street vendors in Denpasar, Bali, Indonesia and proposes a welfare model to examine their well-being. The results showed that street vendors in Denpasar are mostly male, married, with an average age of 39. Most are recent migrants who rent their housing. The majority sell food and beverages from carts and work almost 8 hours per day. Most are self-employed and may be assisted by family labor. Most do not do bookkeeping for their business activities and many are not registered businesses. Most have little access to capital and do not participate in empowerment programs in the form of education/training in business skills. Binary logistic regression analysis shows that the incomes of street vendors are related positively to marital status, age, employment status, physical facilities, and presence of bookkeeping.

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