scholarly journals ANALYSIS OF SKIN DISEASE INFECTION AFTER THE PALU EARTHQUAKE USING BINARY LOGISTIC REGRESSION

2021 ◽  
Vol 2 (1) ◽  
pp. 40-46
Author(s):  
Selvia Anggun Wahyuni ◽  
Lilies Handayani ◽  
Muhammad Akriyaldi Masdin ◽  
Salmia
Keyword(s):  
Logistic Regression ◽  
Skin Disease ◽  
Genetic Factors ◽  
Skin Diseases ◽  
Subcutaneous Tissue ◽  
Binary Logistic Regression ◽  
Significant Problem ◽  
Health Profile ◽  
Profile Data ◽  
The Third

The incidence of skin disease in Indonesia is still relatively high and is a significant problem. This is evidenced by the 2010 Indonesian Health Profile data which shows that skin and subcutaneous tissue diseases are the third rank of the 10 most common diseases among outpatients in hospitals throughout Indonesia. Skin disease is growing, as evidenced by data from the Indonesian Ministry of Health, the prevalence of skin disease throughout Indonesia in 2012 was 8.46%, then increased in 2013 by 9 %. Palu City is an area that has a high skin disease problem. According to the 2016 BPS of Palu City, skin diseases are among the top 10 diseases in Palu City with a total of 11,363 sufferers. The method used in this research is binary logistic regression. Based on the analysis that has been done, it can be concluded that the best model is formed as follows:. Based on the best model, it is found that the factors that influence the transmission of skin diseases after the Palu earthquake are genetic factors.

scholarly journals Implementasi Model Finansial Distres Pada Perusahaan Manufaktur Yang Terdaftar di IDX Tahun 2015-2017

2020 ◽  
Vol 9 (1) ◽  
pp. 61-74
Author(s):  
Tuti Zakiyah ◽  
Wahyuni Windasari
Keyword(s):  
Logistic Regression ◽  
Financial Distress ◽  
Binary Logistic Regression ◽  
Z Score ◽  
Working Capital ◽  
Binary Variable ◽  
The Third ◽  
A Value ◽  
Univariate Model ◽  
Score Model

Manufacturing Company is a sample of this study, the dependent variable used in this study is a binary variable, namely whether the company is in financial distress or non-financial distress. Hypothesis testing uses binary logistic regression (Binary Logistic Regression) because the dependent variable is a combination of metric and non-metric (nominal). The model used is the Altman Z-Score model, Springate S-Score, Grover G-Score, Zmijewski X-Score, and univariate models. Of the five models, the best model is the Springate S-Score with a Nagelkerke R2 value of 0.582. the second is, Zmijewski X-Score with a value of 0.227 and the third best is the Univariate Model with a value of 0.042. Of the three best models, namely the Springate S-Score, Zmijewski X-Score and the Univariate Model. The implementation is that the ratios in these models are very important to be considered by companies as a sensitivity tool so that companies do not experience financial distress. ratios that are often used are ratios related to the company's ability to manage and produce net working capital, sales, debt and ability to generate profits from sales and profits from assets.

scholarly journals Prevalence and Pattern of Diseases of The Skin and Subcutaneous Tissue in A Primary Care Area in Thailand

2021 ◽  
Vol 73 (6) ◽  
pp. 357-362
Author(s):  
Sakchai Chaiyamahapurk ◽  
Prateep Warnnissorn
Keyword(s):  
Primary Care ◽  
Atopic Dermatitis ◽  
Skin Disease ◽  
Skin Diseases ◽  
Subcutaneous Tissue ◽  
Seborrheic Dermatitis ◽  
Decubitus Ulcer ◽  
Population Based ◽  
University Hospital ◽  
Period Prevalence

Objective: Information on the population-based prevalence study of skin diseases is still lacking.  The study explores the prevalence and pattern of diagnosed skin diseases of the population in a primary care area of a university hospital in Thailand.Materials and Methods: Skin disease patients were identified using the International Statistical Classification of Diseases and Related Health Problems 10th Revision codes (L00-L99).  Retrospective data were obtained from the hospital electronic medical record between 2015-2019.  The number of clinic visits and the number of skin disease diagnoses were counted.  The five-year period prevalence was calculated by dividing the number of cases by the population in the primary care area.Results: During the five-year period, in a population of 29,969, we found 3,770 patients (12.6% of 29,969 population) who made 7,433 outpatient visits with the diagnoses of skin diseases.  Infections of the skin and subcutaneous tissues were the most common (37.3%), followed by dermatitis (29.7%), urticaria and erythema (13.9%), other disorders of the skin and subcutaneous tissue (8.6%), and papulosquamous disorders (1.7%).  The five-year period prevalence of skin diseases per 100,000 persons was as following: cellulitis (2,296), urticaria (1,682), psoriasis (177), atopic dermatitis (420), seborrheic dermatitis (227), alopecia areata (50), vitiligo (23), and pemphigus (10).Conclusion: Infection and dermatitis were the two most common skin diseases in the primary care area population.  Atopic dermatitis, psoriasis, seborrheic dermatitis, and decubitus ulcer were less commonly found.  Our prevalence data should be the “at least” prevalence of skin diseases due to possible underreporting.

scholarly journals Effect of leptin genetic polymorphism on lameness prevalence in Tunisian Holstein cows

2018 ◽  
Vol 61 (3) ◽  
pp. 305-310 ◽  
Author(s):  
Mohamed Amine Ferchichi ◽  
Bayrem Jemmali ◽  
Sihem Amiri ◽  
Abderrahmane Ben Gara ◽  
Boulbaba Rekik
Keyword(s):  
Logistic Regression ◽  
Genetic Polymorphism ◽  
Restriction Enzyme ◽  
Logistic Regression Model ◽  
Genetic Factors ◽  
Holstein Cows ◽  
Blood Samples ◽  
The Third ◽  
Pcr Rflp ◽  
Calving Season

Abstract. Lameness is the third most important infection affecting dairy cattle in modern stabling barns. Environmental (food, stables and injuries) and genetic factors are responsible for this pathology. This study aims to investigate the screening of leptin genetic polymorphism and its effect on lameness prevalence. DNA was extracted from 412 blood samples from Holstein cows (lame and healthy). Genotyping was performed by the PCR-RFLP using the Sau3AI restriction enzyme. Prevalence of parity, calving season, age at calving, test-day milk yields, calving year and leptin/Sau3AI genotype was evaluated by the logistics procedure. Results showed that allelic frequencies are 0.68 and 0.32 respectively for the A and B allele. Frequencies for the AA, AB and BB genotypes are 0.52, 032 and 0.16 respectively. All factors included in the logistic regression model significantly affect the prevalence of lameness in Holstein cows (P<0.01). The probability of lameness incidence varied between 37 % and 99 % respectively for the second and the third parity. The lameness incidence recorded in multiparous is higher than primiparous cows. This recorded incidence is greater in winter and autumn than in the summer and spring. The genetic polymorphism affects the prevalence of lameness in Holstein cows. The incidence of lameness in AB genotype is lower than that in BB and AA genotype. These results can be a way to improve length of productive life for cattle breeds in Tunisia.

Evaluating the implementation potential of a transcultural tool for Tamil migrants with gestational diabetes mellitus living in Switzerland

2017 ◽  
Vol 2 (2) ◽  
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Online Survey ◽  
Healthcare Professionals ◽  
Binary Logistic Regression ◽  
Private Practices ◽  
Populations At Risk ◽  
Management Procedures

Background: Gestational diabetes mellitus is a condition that affects many pregnancies and ethnicity appears to be a risk factor. Data indicate that approximately 18% of Tamil women are diagnosed with gestational diabetes mellitus. Today, approximately 50,000 of Tamils live in Switzerland. To date, there is no official tool available in Switzerland that considers the eating and physical activity habits of this migrant Tamil population living in Switzerland, while offering a quick overview of gestational diabetes mellitus and standard dietetics management procedures. The NutriGeD project led by Bern University of Applied Sciences in Switzerland aimed at closing this gap. The aim of this present study was to evaluate the implementation potential of the tools developed in the project NutriGeD for dietetic counseling before their wide scale launch in Swiss hospitals, clinics and private practices. Method: An online survey was developed and distributed to 50 recruited healthcare professionals working in the German speaking region of Switzerland from October – December 2016 (31% response rate). The transcultural tools were sent to participants together with the link to the online survey. The evaluation outcome was analysed using binary logistic regression and cross tabulation analysis with IBM SPSS version 24.0, 2016. Results: 94% (N=47) respondents believed that the transcultural tools had good potential for implementation in hospitals and private practices in Switzerland. A binary logistic regression analysis revealed that the age of participants had a good correlation (42.1%) on recommending the implementation potential of the transcultural tool. The participants with age group 34- 54 years old where the highest group to recommend the implementation potential of the transcultural tool and this was found to be statistically significant (p=0.05). 74% (34 out of 50) of the respondents clearly acknowledged the need for transcultural competence knowledge in healthcare practices. 80% (N =40) of the respondents agreed that the information presented in the counseling display folder was important and helpful while 60% (N= 30) agreed to the contents being clinically applicable. 90% (N=45) participants recommended the availability of the evaluated transcultural tools in healthcare settings in Switzerland. Conclusion: The availability in healthcare practice of the evaluated transcultural tools was greatly encouraged by the Swiss healthcare practitioners participating in the survey. While they confirmed the need for these transcultural tools, feed-backs for minor adjustments were given to finalize the tools before their official launch in practice. The developed materials will be made available for clinical visits, in both hospitals and private practices in Switzerland. The Migmapp© transcultural tool can serve as a good approach in assisting healthcare professionals in all fields, especially professionals who practice in areas associated with diet - related diseases or disorders associated with populations at risk.

Intimate Partner Violence and its Association With Contraceptive Use Among Women in Pakistan

2019 ◽  
Vol 34 (Spring 2019) ◽  
pp. 157-173
Author(s):  
Kashif Siddique ◽  
Rubeena Zakar ◽  
Ra’ana Malik ◽  
Naveeda Farhat ◽  
Farah Deeba
Keyword(s):  
Intimate Partner Violence ◽  
Logistic Regression ◽  
Partner Violence ◽  
Contraceptive Use ◽  
Binary Logistic Regression ◽  
Intimate Partner ◽  
Married Women ◽  
Reproductive Age ◽  
Outcome Variable ◽  
Odds Ratios

The aim of this study is to find the association between Intimate Partner Violence (IPV) and contraceptive use among married women in Pakistan. The analysis was conducted by using cross sectional secondary data from every married women of reproductive age 15-49 years who responded to domestic violence module (N = 3687) of the 2012-13 Pakistan Demographic and Health Survey. The association between contraceptive use (outcome variable) and IPV was measured by calculating unadjusted odds ratios and adjusted odds ratios with 95% confidence intervals using simple binary logistic regression and multivariable binary logistic regression. The result showed that out of 3687 women, majority of women 2126 (57.7%) were using contraceptive in their marital relationship. Among total, 1154 (31.3%) women experienced emotional IPV, 1045 (28.3%) women experienced physical IPV and 1402 (38%) women experienced both physical and emotional IPV together respectively. All types of IPV was significantly associated with contraceptive use and women who reported emotional IPV (AOR 1.44; 95% CI 1.23, 1.67), physical IPV (AOR 1.41; 95% CI 1.20, 1.65) and both emotional and physical IPV together (AOR 1.49; 95% CI 1.24, 1.72) were more likely to use contraceptives respectively. The study revealed that women who were living in violent relationship were more likely to use contraceptive in Pakistan. Still there is a need for women reproductive health services and government should take initiatives to promote family planning services, awareness and access to contraceptive method options for women to reduce unintended or mistimed pregnancies that occurred in violent relationships.

Development of Dermatological Skin Disease Detection and Classification based on Wavelet and ANN

2018 ◽  
Vol 8 (5) ◽  
pp. 10
Author(s):  
Revati Kadu ◽  
U. A. Belorkar
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Skin Disease ◽  
Skin Diseases ◽  
Screening Method ◽  
Phase Detection ◽  
Statistical Measures ◽  
The World ◽  
Artificial Neural ◽  
Wavelet Techniques

One of the most common and augmenting health problems in the world are related to skin. The most  unpredictable and one of the most difficult entities to automatically detect and evaluate is the human skin disease because of complexities of texture, tone, presence of hair and other distinctive features. Many cases of skin diseases in the world have triggered a need to develop an effective automated screening method for detection and diagnosis of the area of disease. Therefore the objective of this work is to develop a new technique for automated detection and analysis of the skin disease images based on color and texture information for skin disease screening. In this paper, system is proposed which detects the skin diseases using Wavelet Techniques and Artificial Neural Network. This paper presents a wavelet-based texture analysis method for classification of five types of skin diseases. The method applies tree-structured wavelet transform on different color channels of red, green and blue dermoscopy images, and employs various statistical measures and ratios on wavelet coefficients. In all 99 unique features are extracted from the image. By using Artificial Neural Network, the system successfully detects different types of dermatological skin diseases. It consists of mainly three phases image processing, training phase, detection  and classification phase.

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

scholarly journals Characteristics and outcomes of children with dissociative (conversion) disorders in western China: a retrospective study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhixu Fang ◽  
Yuhang Li ◽  
Lingling Xie ◽  
Min Cheng ◽  
Jiannan Ma ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Environmental Variables ◽  
Binary Logistic Regression ◽  
Junior College ◽  
Conversion Disorder ◽  
Psychological Characteristics ◽  
Western China ◽  
Left Behind ◽  
Conversion Disorders ◽  
Close Relationship

Abstract Background Dissociative (conversion) disorder in children is a complex biopsychosocial disorder with high rates of medical and psychiatric comorbidities. We sought to identify the characteristics and outcomes of children with dissociative (conversion) disorders in western China. Methods We conducted a retrospective cohort study of 66 children admitted with dissociative (conversion) disorders from January 2017 to July 2019, and analyzed their clinical characteristics, socio-cultural environmental variables, and personality and psychiatric/psychological characteristics. Binary logistic regression was used to analyze the variables associated with clinical efficacy. Results Of these 66 patients, 38 (57.6%) were male and 28 (42.4%) were female, 46 (69.7%) had an antecedent stressor, 30 (45.5%) were left-behind adolescents, and 16 (24.2%) were from single-parent families. In addition, 30 patients (45.5%) were not close to their parents, 38 patients (59.4%) had an introverted personality, and 34 (53.1%) had unstable emotions. Thirteen families (19.7%) were uncooperative with the treatment. Patients who had cormorbid anxiety or depression exhibited significantly lower cognitive ability (P < 0.01). Logistic regression found that better treatment outcomes were positively associated with having a close relationship with parents, parental cooperation with treatment, and having a father with a lower level of education (i.e., less than junior college or higher). Conclusions The characteristics and outcomes of children with dissociative (conversion) disorders are related to socio-cultural environmental variables and psychiatric/psychological factors. Timely recognition and effective treatment of dissociative (conversion) disorders are important.

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