scholarly journals Persistence of Fatigue among COVID-19 Survivors in Bangladesh: A Two-month after Follow-up Study

2021 ◽  
Vol 33 (1) ◽  
pp. 57-63
Author(s):  
Md Khairul Islam ◽  
Mohammad Murad Hossain ◽  
Md Monowar Hossain ◽  
Md Mohiuddin Sharif ◽  
Fahima Sharmin Hossain ◽  
...  
Keyword(s):  
Logistic Regression Model ◽  
Telephone Interview ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Follow Up Study ◽  
Laboratory Markers ◽  
Study Participants ◽  
Prevalent Symptom ◽  
D Dimer

Background: A limited number of studies have exclusively assessed fatigue among post-COVID patients. Our study aimed to assess the persistence and associations of fatigue among COVID-19 survivors after two months of recovery from their primary illness. Methods: During hospital admission from August to September, 2020, a total of 400 patients were diagnosed to be suffering from fatigue using Chalder fatigue scale. After obtaining informed written consent, patients were followed up two months later over telephone. A total of 332 participants participated in the interview (63 patients could not be traced and another 5 patient died within two months). Patients were asked to categorize their present fatigue condition based on a simplified questionnaire developed for telephone interview. Results: Among study participants, 62.9% (n=207) were found to be still suffering from fatigue two months after their hospital discharge. A significant association of fatigue was found with age (p=0.000), hypertension (RR: 1.51; CI: 1.15-1.99; p=0.002), diabetes mellitus (RR: 1.45; CI: 1.08-1.95; p=0.010), ischemic heart disease (RR: 2.04; CI: 1.15-3.64; p=0.011), on admission SpO2 (p=0.000), on admission serum ferritin (p=0.000), d-dimer (p=0.000), CRP (p=0.000), and Hb% (p=0.019). Binary logistic regression model revealed significant association of age and onadmission SpO2 with persistence of fatigue. Conclusions: Fatigue is a highly prevalent symptom among the COVID-19 survivors with significant association between fatigue and patients clinical and laboratory markers. Bangladesh J Medicine July 2022; 33(1) : 57-63

scholarly journals Differential Effects of Fingolimod and Natalizumab on Magnetic Resonance Imaging Measures in Relapsing–Remitting Multiple Sclerosis

2021 ◽  
Author(s):  
S. Grahl ◽  
M. Bussas ◽  
B. Wiestler ◽  
P. Eichinger ◽  
C. Gaser ◽  
...  
Keyword(s):  
Regression Models ◽  
Logistic Regression Model ◽  
White Matter Lesions ◽  
Binary Logistic Regression ◽  
Resonance Imaging ◽  
Binary Logistic Regression Model ◽  
Relapsing Remitting ◽  
Multiple Regression Models ◽  
Relapsing Remitting Multiple Sclerosis

AbstractFingolimod and natalizumab are approved disease-modifying drugs in relapsing–remitting multiple sclerosis (RRMS). The two drugs have different modes of action and may therefore influence different aspects of MS-related tissue damage. In this retrospective cohort study, we longitudinally compared patients treated with fingolimod and patients treated with natalizumab by measures based on structural magnetic resonance imaging (MRI). We included patients with RRMS given that two standardized MRI scans under the same drug were available with an interval of at least 6 months both from therapy start to baseline scan and from baseline scan to follow-up scan. After matching for age, baseline and follow-up scans from 93 patients (fingolimod, 48; natalizumab, 45) were investigated. Mean follow-up time was 1.9 years. We determined the number of new white matter lesions as well as thalamic, cortical, and whole-brain atrophy. After scaling for time of the interscan interval, measures were analyzed by group comparisons and, to account for demographic and clinical characteristics, by multiple regression models and a binary logistic regression model. Compared to natalizumab, fingolimod treatment went along with more new white matter lesions (median [interquartile range, IQR] 0.0 [0.0; 0.7] vs. 0.0 [0.0; 0.0] /year; p < 0.01) whereas whole-brain atrophy was lower (median [IQR] 0.2 [0.0; 0.5] vs. 0.5 [0.2; 1.0] %/year; p = 0.01). These significant differences were confirmed by multiple regression models and the binary logistic regression model. In conclusion, our observation is compatible with stronger neuroprotective properties of fingolimod compared to natalizumab.

Seven-Year Follow-Up of Screening for Hypertension and Diabetes at a Dental Clinic

2019 ◽  
Author(s):  
Göran Friman
Keyword(s):  
Antihypertensive Drugs ◽  
Study Data ◽  
Initial Screening ◽  
Pharmacological Treatments ◽  
Medical Screening ◽  
Follow Up Study ◽  
Undiagnosed Hypertension ◽  
Dental Setting ◽  
Study Participants

Objective: To describe the distribution of risk, diagnosis and pharmacological treatments for diabetes and hypertension after seven years among patients provided with opportunistic medical screening in a dental setting. Material and Methods: The initial screening’s 170 participants were asked to take part in a seven-year follow-up study. Data were collected through self-reported information in a written health declaration. Outcome measures: • Number of study participants who had passed away • Prescription of antidiabetics or antihypertensives • Changes in weight and height to calculate body mass index (BMI) Results: The follow-up study consisted of 151 participants. Twenty had passed away. The risk needs for medicating with antihypertensive drugs after seven years for those not receiving pharmacological treatment at the initial screening was 3.7 times greater (p=0.025 CI 1.2-11.3) for participants with a diastolic blood pressure (BP) ≥ 90 mm Hg (85 for diabetics) than for the others. The risk was 3.9 times greater (p=0.020 CI 1.2-12.6) for those with a systolic BP of 140-159 mm Hg and 54.2 times greater (p<0.0001 CI 9.8-300.3) for those with a systolic BP ≥ 160 mm Hg than for those with a systolic BP 140 mm Hg. There were no changes in BMI. Conclusion: At least one in ten cases of incorrect medication or undiagnosed hypertension may be identifiable through opportunistic medical screening

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI PEROLEHAN KREDIT OLEH PENGUSAHA MIKRO

2018 ◽  
Vol 4 (3) ◽  
Author(s):  
Abdul Azis Safii ◽  
Tri Suwarno
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Large Scale ◽  
Logistic Regression Model ◽  
Banking Sector ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Access To Credit ◽  
The Poor ◽  
Micro Enterprises

Abstract: The number of micro-entrepreneurs and the dominant number of micro enterprises compared to medium and large-scale enterprises in Indonesia are not balanced by the provision of access to credit and venture capital for micro businesses. This resulted in a micro-sector sector identical to the poor being vulnerable to exploitation by moneylenders who exploit the difficulties of micro entrepreneurs accessing credit from the banking sector. This study examines the factors that determine the accessibility of credit by micro entrepreneur in Bojonegoro regency. A total sum of 270 micro entrepreneurs who have applied for banking loan were sampled from the study area. With an binary logistic regression model the research resulting that education, skill on entrepreneur, and monthly net profits generated by the microenterprise are significant in determining the accessibility of microcredit. Keywords: micro entrepreneur, microcredit, credit accessibility Abstrak: Perkembangan jumlah pengusaha mikro serta dominannya jumlah usaha mikro dibandingkan dengan usaha menengah dan usaha besar di Indonesia, tidak diimbingi dengan penyediaan akses kredit dan modal usaha bagi para pelaku usaha mikro. Hal tersebut mengakibatkan sektor usaha mikro yang identik dengan masyarakat miskin rentan dieksploitasi oleh rentenir yang memanfaatkan sulitnya para pengusaha mikro mengakses kredit dari sektor perbankan. Penelitian ini menggunakan data primer yang di ambil langsung dari pengusaha mikro dengan teknik kuesioner. Analisis data dengan metode binary logistic regression mendapatkan hasil variabel yang berpengaruh signifikan terhadap akses kredit para pengusaha mikro adalah variabel usia pengusaha, laba bersih usaha tiap bulan, dan jumlah karyawan yang di pekerjakan. Kata kunci : usaha mikro, microcredit, akses kredit

scholarly journals Using the Econometric Models for Identification of Risk Factors for Albanian Smes (Case Study: Smes of Gjirokastra Region)

2021 ◽  
Vol 18 ◽  
pp. 163-170
Author(s):  
Lorenc Koçiu ◽  
Kledian Kodra
Keyword(s):  
Logistic Regression ◽  
Statistical Models ◽  
Logistic Regression Model ◽  
Qualitative Data ◽  
Linear Models ◽  
Binary Logistic Regression ◽  
Random Variable ◽  
Econometric Models ◽  
Binary Logistic Regression Model

Using the econometric models, this paper addresses the ability of Albanian Small and Medium-sizedEnterprises (SMEs) to identify the risks they face. To write this paper, we studied SMEs operating in theGjirokastra region. First, qualitative data gathered through a questionnaire was used. Next, the 5-level Likertscale was used to measure it. Finally, the data was processed through statistical software SPSS version 21,using the binary logistic regression model, which reveals the probability of occurrence of an event when allindependent variables are included. Logistic regression is an integral part of a category of statistical models,which are called General Linear Models. Logistic regression is used to analyze problems in which one or moreindependent variables interfere, which influences the dichotomous dependent variable. In such cases, the latteris seen as the random variable and is dependent on them. To evaluate whether Albanian SMEs can identifyrisks, we analyzed the factors that SMEs perceive as directly affecting the risks they face. At the end of thepaper, we conclude that Albanian SMEs can identify risk

scholarly journals ESTIMATION OF THE BINARY LOGISTIC REGRESSION MODEL PARAMETER USING BOOTSTRAP RE-SAMPLING

2018 ◽  
Vol 48 (3) ◽  
pp. 199-204 ◽  
Author(s):  
R. LI ◽  
J. ZHOU ◽  
L. WANG
Keyword(s):  
Logistic Regression ◽  
Parameter Estimation ◽  
Maximum Likelihood ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Parametric Bootstrap ◽  
Binary Logistic Regression Model ◽  
Bayesian Bootstrap ◽  
Non Parametric

In this paper, the non-parametric bootstrap and non-parametric Bayesian bootstrap methods are applied for parameter estimation in the binary logistic regression model. A real data study and a simulation study are conducted to compare the Nonparametric bootstrap, Non-parametric Bayesian bootstrap and the maximum likelihood methods. Study results shows that three methods are all effective ways for parameter estimation in the binary logistic regression model. In small sample case, the non-parametric Bayesian bootstrap method performs relatively better than the non-parametric bootstrap and the maximum likelihood method for parameter estimation in the binary logistic regression model.

Die Flexion der Indefinita jemand und niemand

2021 ◽  
Vol 49 (2) ◽  
pp. 209-243
Author(s):  
Linnéa Weitkamp
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Influencing Factors ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Corpus Study ◽  
Frequent Use ◽  
Current Variation ◽  
Reference Corpus

Abstract This article investigates the inflection of the German indefinite pronouns jemand and niemand in the accusative and dative. The pronouns are used both with inflectional suffix (jemanden/jemandem, niemanden/niemandem) and without (jemand, niemand) and are thus an example of current variation in contemporary German. The grammars take an unusually liberal stance and describe both forms as correct, partially even with preference to the uninflected form. A corpus study which examines conceptually written data of the DeReKo (German reference corpus) and conceptually oral data of the DECOW16B (German web corpus), shows that over 90 % of occurrences are inflected. But almost 10 % of uninflected forms show that these formations are no arbitrary errors either. To find out what influences the presence or absence of the inflectional ending, a binary logistic regression model was calculated. The following factors proved to be significant influencing factors for inflection: the degree of formality (DeReKo vs. DECOW16B), the lexeme (jemand vs. niemand), the case (acc vs. dat), government by preposition vs. government by verb and the following nominalized adjective (jemand anderen). With regard to the different inflectional suffixes, the frequent use of -en in the dative stood out in particular. Although this form is classified as erroneous in all grammars, almost 30 % of the dative occurrences in informal DECOW16B data are formed in this way.

scholarly journals Sustainable Entrepreneurship in the Transport and Retail Supply Chain Sector

2020 ◽  
Vol 13 (11) ◽  
pp. 267
Author(s):  
Cristian Negrutiu ◽  
Cristinel Vasiliu ◽  
Calcedonia Enache
Keyword(s):  
Supply Chain ◽  
Quantitative Research ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Unique Combination ◽  
Binary Logistic Regression Model ◽  
Online Questionnaire ◽  
Sustainable Entrepreneurship ◽  
Research Gap ◽  
Freight Forwarder

The present study investigated the factors that influence the feasibility and competitive advantage of a digital freight forwarder through a binary logistic regression model. The research is a concrete application of sustainable entrepreneurship in the transport and supply chain sector. The novelty of this topic presents a research gap that needs to be covered with dedicated studies. After the literature review and concept clarification, the article presents quantitative research involving an online questionnaire administered among a sample of transporters in Romania. Through analysis of the data collected from 405 respondents, it was found that the most important factors when selecting a digital freight forwarder are the existence of both sales and dispatch departments. Furthermore, apart from greening the industry, a digital freight forwarder has several other advantages for all stakeholders and society. The study concludes that the concept has the potential to disrupt the entire industry through a unique combination of efficiency, transparency, and sustainability.

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