Logistic Regression Analysis of Catheter Fixation Defects and Their Influencing Factors

[Objectives] To analyze the influencing factors of fixed defects in patients with catheter fixation in clinical nursing work, in order to provide the best catheter fixation nursing plan for patients.[Methods] 176 inpatients with indwelling catheter from surgical system of Taihe Hospital in Shiyan City from August 2022 to March 2023 were selected. Using a retrospective analysis method, the influencing factors of catheter fixation defects in the study subjects were divided into two categories based on objective characteristics: type I non modifiable influencing factors and type II modifiable influencing factors. Using the standard for catheter fixation defects, whether the patient had catheter fixation defects was determined. After classified and statistically analyzed item by item, binary Logistic multiple regression analysis was used to identify the influencing factors.[Results] The occurrence of catheter fixation defects in patients with catheter fixation was related to factors such as whether the patient was evaluated before fixation, whether the fixation method was standardized and systematic, whether there was sufficient communication between nurses and patients, and the patient s knowledge of catheter fixation. It was also influenced by factors such as the patient s age, catheterization site, catheterization number, catheterization duration, where there was a consciousness disorder, educational level, and external environmental temperature.[Conclusions] Early attention to the key factors affecting patients with catheter fixation defects can effectively prevent adverse factors and provide patients with the best catheter fixation nursing plan to improve nursing quality.

Regression analysis and its application to oil and gas exploration:A case study of hydrocarbon loss recovery and porosity prediction,China

In oil and gas exploration,elucidating the complex interdependencies among geological variables is paramount.Our study introduces the application of sophisticated regression analysis method at the forefront,aiming not just at predicting geophysical logging curve values but also innovatively mitigate hydrocarbon depletion observed in geochemical logging.Through a rigorous assessment,we explore the efficacy of eight regression models,bifurcated into linear and nonlinear groups,to accommodate the multifaceted nature of geological datasets.Our linear model suite encompasses the Standard Equation,Ridge Regression,Least Absolute Shrinkage and Selection Operator,and Elastic Net,each presenting distinct advantages.The Standard Equation serves as a foundational benchmark,whereas Ridge Regression implements penalty terms to counteract overfitting,thus bolstering model robustness in the presence of multicollinearity.The Least Absolute Shrinkage and Selection Operator for variable selection functions to streamline models,enhancing their interpretability,while Elastic Net amalgamates the merits of Ridge Regression and Least Absolute Shrinkage and Selection Operator,offering a harmonized solution to model complexity and comprehensibility.On the nonlinear front,Gradient Descent,Kernel Ridge Regression,Support Vector Regression,and Piecewise Function-Fitting methods introduce innovative approaches.Gradient Descent assures computational efficiency in optimizing solutions,Kernel Ridge Regression leverages the kernel trick to navigate nonlinear patterns,and Support Vector Regression is proficient in forecasting extremities,pivotal for exploration risk assessment.The Piecewise Function-Fitting approach,tailored for geological data,facilitates adaptable modeling of variable interrelations,accommodating abrupt data trend shifts.Our analysis identifies Ridge Regression,particularly when augmented by Piecewise Function-Fitting,as superior in recouping hydrocarbon losses,and underscoring its utility in resource quantification refinement.Meanwhile,Kernel Ridge Regression emerges as a noteworthy strategy in ameliorating porosity-logging curve prediction for well A,evidencing its aptness for intricate geological structures.This research attests to the scientific ascendancy and broad-spectrum relevance of these regression techniques over conventional methods while heralding new horizons for their deployment in the oil and gas sector.The insights garnered from these advanced modeling strategies are set to transform geological and engineering practices in hydrocarbon prediction,evaluation,and recovery.

Composition Analysis and Identification of Ancient Glass Products Based on L1 Regularization Logistic Regression

In view of the composition analysis and identification of ancient glass products, L1 regularization, K-Means cluster analysis, elbow rule and other methods were comprehensively used to build logical regression, cluster analysis, hyper-parameter test and other models, and SPSS, Python and other tools were used to obtain the classification rules of glass products under different fluxes, sub classification under different chemical compositions, hyper-parameter K value test and rationality analysis. Research can provide theoretical support for the protection and restoration of ancient glass relics.

Variance Inflation Factor: As a Condition for the Inclusion of Suppressor Variable(s) in Regression Analysis

Suppression effect in multiple regression analysis may be more common in research than what is currently recognized. We have reviewed several literatures of interest which treats the concept and types of suppressor variables. Also, we have highlighted systematic ways to identify suppression effect in multiple regressions using statistics such as: R2, sum of squares, regression weight and comparing zero-order correlations with Variance Inflation Factor (VIF) respectively. We also establish that suppression effect is a function of multicollinearity;however, a suppressor variable should only be allowed in a regression analysis if its VIF is less than five (5).

Biological stability in drinking water: a regression analysis of influencing factors

Some parameters, such as assimilable organic carbon(AOC), chloramine residual, water temperature, and water residence time, were measured in drinking water from distribution systems in a northern city of China. The measurement results illustrate that when chloramine residual is more than 0.3 mg/L or AOC content is below 50 μg/L, the biological stability of drinking water can be controlled. Both chloramine residual and AOC have a good relationship with Heterotrophic Plate Counts(HPC)(log value), the correlation coefficient was -0.64 and 0.33, respectively. By regression analysis of the survey data, a statistical equation is presented and it is concluded that disinfectant residual exerts the strongest influence on bacterial growth and AOC is a suitable index to assess the biological stability in the drinking water.

Multiple regression analysis of risk factors related to radiation pneumonitis

BACKGROUND Radiation pneumonitis(RP)is a severe complication of thoracic radiotherapy that may lead to dyspnea and lung fibrosis,and negatively affects patients’quality of life.AIM To carry out multiple regression analysis on the influencing factors of radiation pneumonitis.METHODS Records of 234 patients receiving chest radiotherapy in Huzhou Central Hospital(Huzhou,Zhejiang Province,China)from January 2018 to February 2021,and the patients were divided into either a study group or a control group based on the presence of radiation pneumonitis or not.Among them,93 patients with radiation pneumonitis were included in the study group and 141 without radiation pneumonitis were included in the control group.General characteristics,and radiation and imaging examination data of the two groups were collected and compared.Due to the statistical significance observed,multiple regression analysis was performed on age,tumor type,chemotherapy history,forced vital capacity(FVC),forced expiratory volume in the first second(FEV1),carbon monoxide diffusion volume(DLCO),FEV1/FVC ratio,planned target area(PTV),mean lung dose(MLD),total number of radiation fields,percentage of lung tissue in total lung volume(vdose),probability of normal tissue complications(NTCP),and other factors.RESULTS The proportions of patients aged≥60 years and those with the diagnosis of lung cancer and a history of chemotherapy in the study group were higher than those in the control group(P<0.05);FEV1,DLCO,and FEV1/FVC ratio in the study group were lower than those in the control group(P<0.05),while PTV,MLD,total field number,vdose,and NTCP were higher than in the control group(P<0.05).Logistic regression analysis showed that age,lung cancer diagnosis,chemotherapy history,FEV1,FEV1/FVC ratio,PTV,MLD,total number of radiation fields,vdose,and NTCP were risk factors for radiation pneumonitis.CONCLUSION We have identified patient age,type of lung cancer,history of chemotherapy,lung function,and radiotherapy parameters as risk factors for radiation pneumonitis.Comprehensive evaluation and examination should be carried out before radiotherapy to effectively prevent radiation pneumonitis.

Clinical feature and predictive factor analysis for spontaneous regression of retinopathy of prematurity in a Chinese population

AIM:To investigate the ratio of spontaneous regression of retinopathy of prematurity(ROP)and to explore the possible relevant predictive factors.METHODS:A retrospective review of 405 infants who were diagnosed with ROP and mother during pregnancy were collected.Stage,zone,and duration of ROP were recorded.Statistical analysis was performed on 51 possible predictive factors.RESULTS:Totally 356 infants showed spontaneous regression.The incidence was 100%,95.3%,and 22.7%in stage 1,2,and 3,respectively.The 13.4%of the ROP with plus disease eventually resolved spontaneously.All affected eyes of aggressive posterior retinopathy of prematurity(APROP)failed to spontaneously regress.The mean duration of ROP was 7.2wk in patients with spontaneous resolution of ROP.Days of mechanical ventilation(OR=0.981,95%CI,0.965-0.997,P=0.021),retinal hemorrhage(OR=0.173,95%CI,0.064-0.470,P=0.001),delivery pattern(OR=2.750,95%CI,1.132-6.681,P=0.025),maternal anemia in pregnancy(OR=0.142,95%CI,0.036-0.563,P=0.005),the stages(at initial diagnosis OR=0.183,95%CI,0.041-0.816,P=0.026;at final diagnosis OR=0.031,95%CI,0.006-0.167,P<0.001),and with plus disease or not(OR=0.005,95%CI,0.001-0.031,P<0.001)were independent predictive factors of the spontaneous regression of ROP.CONCLUSION:Most mild ROP can spontaneously resolve.Active treatment is still recommended for stage 3 ROP,zone I ROP,AP-ROP,and ROP with plus disease.Prolonged mechanical ventilation and concurrent retinal hemorrhage reduce the likelihood of spontaneous ROP resolution.The pattern of delivery and the mother's anemia during pregnancy can also affect the prognosis of ROP.

Association between Macroscopic-factors and Identified HIV/AIDS Cases among Injecting Drug Users: An Analysis Using Geographically Weighted Regression Model

Drug use （DU）, particularly injecting drug use （IDU） has been the main route of transmission and spread of Human Immunodeficiency Virus （HIV）/Acquired Immune Deficiency Syndrome （AIDSJ among injecting drug users （IDUs）[1]. Previous studies have proven that needles or cottons sharing during drug injection were major risk factors for HIV/AIDS transmission at the personal level[z4]. Being a social behavioral issue, HIV/AIDS related risk factors should be far beyond the personal level. Therefore, studies on HIV/AIDS related risk factors should focus not only on the individual factors, but also on the association between HIV/AIDS cases and macroscopic-factors, such as economic status, transportation, health care services, etc[1]. The impact of the macroscopic-factors on HIV/AIDS status might be either positive or negative, which are potentially reflected in promoting, delaying or detecting HIV/AIDS epidemics.

COX MULTIVARIATE REGRESSION ANALYSIS OF RECURRENCE FACTORS FOR COLONIC CARCINOMA

Objective: To determine the independent prognostic factors in the recurrence of colonic carcinoma after curative resection. Methods: Two hundred and one patients undergoing curative resections for colonic carcinoma were investigated by univariate and Cox multivariate regression analyses. Ten factors contributed to the rate were analyzed. Results: Dukes stages, obstruction, postoperative chemotherapy as well as the growth manner of the tumor were significantly associated with the recurrence rate of colonic carcinoma (P<0.05) by univariate analysis, while Dukes stages, obstruction, and postoperative chemotherapy were significant factors by the multivariate analysis. Conclusion: Dukes stages, obstruction, and postoperative chemotherapy are independent prognostic factors in the recurrence of colonic carcinoma.

Risk Factors for Birth Defects: A Conditional LogisticRegression Analysis of a Case-Control Study in Guang-dong Province of China

Information was obtained from the same questionnaire (23 risk factors listed) of cases and controls. We used a multivariate logistic model, which described variables significantly increased risk of birth defects. The risk factors included maternal educational levels, medicine taken during pregnancy and antenatal care. It was suggested to strengthen antenatal care was the main preventive measure against birth defects.

Factors Affecting Minimum Foot Clearance in the Elderly Walking: A Multiple Regression Analysis

Because falls among the elderly can cause serious injury leading to a bedridden state, methods to maintain motor function in the elderly and prevent falls are important. Among falls by the elderly are tripping falls, in which the forefoot gets caught on the floor to cause the fall. Minimum foot clearance (MFC), the smallest distance between the floor and the foot during the swing phase of gait, has been given attention as a cause of tripping falls, as elderly people at risk of falling have been reported to have low MFC. No research has been done, however, to examine what geriatric factors determine MFC. In this study, various measurements were taken on muscle strength, joint angles, and other characteristics as factors possibly influencing the height of MFC, a multiple regression analysis was performed with MFC as the dependent variable, and those factors with high degrees of influence were extracted. The results revealed that the height of MFC is highly influenced by strength of the hip flexors and angle of ankle dorsiflexion. The results of this study should be taken into consideration when having elderly people do fall prevention training.

Logistic Regression Analysis the Risk Factors of Peripherally Inserted Central Catheter Related Blood Stream Infection of Tumor Patients

Objective: Our object is to study risk factors of tumor patients’ PICC catheter-related blood stream infection. Method: a retrospective analysis of data of 586 PICC catheterized patients was implemented, a univariate analysis of general data and catheterizing data of tumor patients was then carried out, and data of single factors with statistical significance were incorporated into multi-factor Logistic regression model for analysis. Results: PICC catheter-related blood stream infection occurred to 16 patients, and occurrence rate was 2.73%. Multi-factor Logistic regression analysis results showed that number of puncturing times, positioning method and maintenance frequency were risk factors for tumor patients’ peripherally inserted central catheter catheter-related blood stream infection, and odds risk values were respectively 8.762, 9.253 and 10.324. Conclusion: for tumor patients implanted with peripherally inserted central catheters, using ECG positioning during strict sterile operation and catheterizing process to avoid repeated puncturing and increasing maintenance frequency could effectively reduce occurrence of PICC catheter-related blood stream infection.

Multiple Regression Analysis of Influencing Factors on Yield of New Sugarcane Variety Yuetang 03-373

[Objectives]The purpose of this study was to provide reference for cultivation and promotion of a new sugarcane variety Yuetang 03-373,on the basis of analyzing and summarizing the characters of the variety.[Methods]Correlation,multiple regression and path analyses were performed for the yield and yield components of Yuetang 03-373.[Results]Correlation analysis shows that cane yield was significantly correlated with millable stalk number,stalk length and stalk diameter,and among them,the correlation with millable stalk number was the strongest.Multiple regression and path analyses show that millable stalk number contributed the most to cane yield,followed by stalk length,and stalk diameter contributed the least.The regression equation of cane yield against the three yield components was y=-2.8713+1.5497x1+5.8990x2-395.4294x3(R=0.9672**).[Conclusions]Millable stalk number and stalk length were the important and major factors for high yield of Yuetang 03-373,indicating that Yuetang 03-373 is a sugarcane variety of millable stalk type.In cultivation,full play should be given to the advantage of Yuetang 03-373 in millable stalk number,as well as stalk length(plant height),in order to achieve the purpose of increasing yield.

Purified protein derivative skin testing on HIV/AIDS patients and logistic regression analysis of its risk factors

Objective： To understand the reactivity of purified protein derivative skin test（PPD test） in HIV-infected persons and to determine the influential factors associated with PPD. Methods： 174 HIV/AIDS patients registered in the local center for disease control and prevention（CDC） participated this study from April to June in 2006. Questionnaire,CD4 count and thoracic roentgenogram were performed for all participants. Results： In this study, response rate of questionnaires was 83.65%. The majority of these participants had a different degree of immunodeficiency that accounted for 93.64%. Female patients had a higher CD4 count than that of males. The total positive rate of PPD was 38.15%. Analysis of single factor in our study indicated that CD4 count, previous tubereulosis history, tuberculosis contact history and thoracic roentgenogram manifestation of patients were related to their PPD diameters. Further analysis of multiple factors also supports the previous conclusion that CD4 count and previous tuberculosis history of patients were risk factors in the PPD test. Conclusion： The PPD test of HIV/AIDS patients could be affected by several factors. For persons infected with HIV, the confirmation of latent tuberculosis infection （LTBI） should be considered the combination effect of previous MTB infection and body cellular immune function.

Influencing factor analysis of interception probability and classification-regression neural network based estimation

The interception probability of a single missile is the basis for combat plan design and weapon performance evaluation,while its influencing factors are complex and mutually coupled.Existing calculation methods have very limited analysis of the influence mechanism of influencing factors,and none of them has analyzed the influence of the guidance law.This paper considers the influencing factors of both the interceptor and the target more comprehensively.Interceptor parameters include speed,guidance law,guidance error,fuze error,and fragment killing ability,while target performance includes speed,maneuverability,and vulnerability.In this paper,an interception model is established,Monte Carlo simulation is carried out,and the influence mechanism of each factor is analyzed based on the model and simulation results.Finally,this paper proposes a classification-regression neural network to quickly estimate the interception probability based on the value of influencing factors.The proposed method reduces the interference of invalid interception data to valid data,so its prediction accuracy is significantly better than that of pure regression neural networks.

Application of cluster analysis and stepwise regression in predicting the traffic volume of lanes

Because of the difficulty to obtain the traffic flow information of lanes at non-detector intersections in most metropolises of the world,based on the relationships between the lanes of signal-controlled intersections,cluster analysis and stepwise regression are integrated to predict the traffic volume of lanes at non-detector isolated controlled intersections.First cluster analysis is used to cluster the lanes of non-detector isolated signal-controlled intersections and the lanes of all signal-controlled intersections with detectors.Then, by the results of cluster analysis,the traffic volume samples are selected randomly and stepwise regression is used to predict the traffic volume of lanes at non-detector isolated signal-controlled intersections.The method is tested by the traffic volume data of lanes of the road network of Nanjing city.The problem of predicting the traffic volume of lanes at non-detector isolated signal-controlled intersections was resolved and can be widely used in urban traffic flow guidance and urban traffic control in cities without enough intersections equipped with detectors.

Factor Decomposition and Regression Analysis of the Energy Related Carbon Emissions in Shandong, China: A Perspective of Industrial Structure

An in-depth study of the energy related carbon emissions has important practical significance for carbon emissions reduction and structural adjustment in Shandong Province and throughout China.Based on the perspective of industrial structure,the expanded KAYA equation to measure the energy related carbon emissions of the primary industries(Resources and Agriculture)and secondary industries(Manufacturing and Construction)and tertiary industries(Retail and Service)was utilized in Shandong Province from 2011 to 2017.The carbon emissions among industries in Shandong Province were empirically analyzed using the Logarithmic Mean Divisia Index decomposition approach.The results were follows:(1)Under the three industrial dimensions,the energy structure effect and the energy intensity effect have a restraining influence on the carbon emissions of the three industries.(2)The development level effect and the employment scale effect play a pulling role in carbon emissions.(3)From the perspective of the employment structure effect of the primary industry,there is a restraining effect on carbon emissions,while the employment structure effects of the secondary and tertiary industries play a pulling role in carbon emissions,and the employment structure effect of the tertiary industry has a greater pulling effect on carbon emissions than the secondary industry.

Logistic Regression Analysis of Influencing Factors on Serum ALT and HCV RNA Changes in Patients with Chronic Hepatitis C

Objective This study was undertaken to investigate the influencing factors on serum ALT level and hepatitis C virus(HCV)RNA titer in chronic hepatitis C(CHC)patients.Methods All patients enrolled into this study were anti-HCV positive.Retrospective tracing method was applied to detect serum ALT level and HCV RNA titer and to collect general information of the patients such as genders,age groups,interferon medication history,infection pathways,height and weight.Then the multi-factor analysis was adopted with the application of binominal logistic regression mode.Results The abnormal rate of ALT level was positively correlated to HCV RNA and gender while negatively correlated to interferon medication history and age group,with Wald value of the 4 factors as 39.604,11.823,18.991 and 7.389,respectively.The positive rate of HCV RNA was negatively correlated to interferon medication history and gender while positively correlated to ALT level,with corresponding Wald value of the 3 factors as81.394,7.618 and 27.562,respectively.Conclusions The normal ALT level in HCV infected patients was associated with viral load,age,gender and interferon medication history,while the normal rate of HCV RNA titer was closely associated with gender,interferon medication history and ALT level.

Impact Analysis of Macroeconomic Factors on Stock Value of Shanghai Pudong Development Bank under PCA Regression

When we consider the factors affecting the stock market,we often consider the impact of macroeconomic factors on it.On the basis of the academic achievements of predecessor scholars on macroscopic factors affecting the overall stocks,this article selects six macroeconomic influencing factors:money supply,USDCNY exchange rate,GDP,national fiscal revenue,price index and interest rate,and uses PAC regression analysis method to construct a regression model.Analyze the influencing factors of Shanghai Pudong Development Bank stock;then conduct heteroscedasticity,autocorrelation,and multicollinearity tests to modify and adjust the regression model;finally,make relevant recommendations based on the analysis results.

A Study on the Effect Factors of Community Participation in Tourism:Based on the Logistic Regression Analysis of Xingwen World Geopark

In order to find out the factors which influence community participation in tourism,several effect factors are summed up through the investigation of the local residents and the analysis of the logistic regression of the data gained from Xingwen world Geopark.Results indicated there are several main influencing factors of community participation such as the comparative benefit of tourist industry,participant residents' subjective wishes,preference consciousness of working opportunity obtainment in the tourist enterprise and participant skills.Based on above investigation data and field travel,the paper put forward several methods about how to enhance the residents' participant degree:increasing the comparative benefit of tourist industry,enhancing the attraction of tourism for boosting participant wishes,improving the preference consciousness on obtaining working opportunity in tourism industry and cultivating residents' participant skills through training.