scholarly journals Adverse events associated with incretin-based drugs in Japanese spontaneous reports: a mixed effects logistic regression model

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1753 ◽  
Author(s):  
Daichi Narushima ◽  
Yohei Kawasaki ◽  
Shoji Takamatsu ◽  
Hiroshi Yamada
Keyword(s):  
Logistic Regression ◽  
Adverse Events ◽  
Regression Model ◽  
Fixed Effects ◽  
Logistic Regression Model ◽  
Random Effect ◽  
Mixed Effects ◽  
Information Criteria ◽  
Drug Event ◽  
Receptor Agonists

Background:Spontaneous Reporting Systems (SRSs) are passive systems composed of reports of suspected Adverse Drug Events (ADEs), and are used for Pharmacovigilance (PhV), namely, drug safety surveillance. Exploration of analytical methodologies to enhance SRS-based discovery will contribute to more effective PhV. In this study, we proposed a statistical modeling approach for SRS data to address heterogeneity by a reporting time point. Furthermore, we applied this approach to analyze ADEs of incretin-based drugs such as DPP-4 inhibitors and GLP-1 receptor agonists, which are widely used to treat type 2 diabetes.Methods:SRS data were obtained from the Japanese Adverse Drug Event Report (JADER) database. Reported adverse events were classified according to the MedDRA High Level Terms (HLTs). A mixed effects logistic regression model was used to analyze the occurrence of each HLT. The model treated DPP-4 inhibitors, GLP-1 receptor agonists, hypoglycemic drugs, concomitant suspected drugs, age, and sex as fixed effects, while the quarterly period of reporting was treated as a random effect. Before application of the model, Fisher’s exact tests were performed for all drug-HLT combinations. Mixed effects logistic regressions were performed for the HLTs that were found to be associated with incretin-based drugs. Statistical significance was determined by a two-sided p-value <0.01 or a 99% two-sided confidence interval. Finally, the models with and without the random effect were compared based on Akaike’s Information Criteria (AIC), in which a model with a smaller AIC was considered satisfactory.Results:The analysis included 187,181 cases reported from January 2010 to March 2015. It showed that 33 HLTs, including pancreatic, gastrointestinal, and cholecystic events, were significantly associated with DPP-4 inhibitors or GLP-1 receptor agonists. In the AIC comparison, half of the HLTs reported with incretin-based drugs favored the random effect, whereas HLTs reported frequently tended to favor the mixed model.Conclusion:The model with the random effect was appropriate for analyzing frequently reported ADEs; however, further exploration is required to improve the model. The core concept of the model is to introduce a random effect of time. Modeling the random effect of time is widely applicable to various SRS data and will improve future SRS data analyses.

Relationship between childhood obesity and socioeconomic status among primary school children in Costa Rica

2021 ◽  
pp. 1-24
Author(s):  
Tatiana Gamboa-Gamboa ◽  
Romain Fantin ◽  
Jeancarlo Cordoba ◽  
Ivannia Caravaca ◽  
Ingrid Gómez-Duarte
Keyword(s):  
Socioeconomic Status ◽  
Logistic Regression ◽  
Childhood Obesity ◽  
Costa Rica ◽  
Regression Model ◽  
Primary Schools ◽  
Logistic Regression Model ◽  
Mixed Effects ◽  
Overweight And Obesity ◽  
Public And Private

Abstract Objective: This article analyzes the relationship between socioeconomic status and the prevalence of overweight and obesity in the primary school population in Costa Rica. Design: A National School Weight/Height Census was disseminated across Costa Rica in 2016. The percentage of children who were overweight or obese was calculated by sex, age, and socioeconomic indicators (type of institution: private, public, mix; type of geographic location: rural, urban; and the level of development of the district of residence: quartiles). A mixed effects multinomial logistic regression model and mixed effects logistic regression model were used to analyze the association between the prevalence of being overweight or obese and district socioeconomic status. Setting: The survey was carried out in public and private primary schools across Costa Rica in 2016. Participants: 347,366 students from 6 to 12 years old, enrolled in public and private primary schools. Results: The prevalence of overweight and obesity among children was 34.0%. Children in private schools were more likely to be overweight or obese than students in public schools (OR=1.10 [1.07, 1.13]). Additionally, children were less likely to be overweight or obese if attending a school in a district of the lowest socioeconomic quartile compared to the highest socioeconomic quartile (OR=0.79 [0.75, 0.83]), and in a rural area compared to the urban area (OR=0.92 [0.87, 0.97]). Conclusions: Childhood obesity in Costa Rica continues to be a public health problem. Prevalence of overweight and obesity in children was associated with indicators of higher socioeconomic status.

scholarly journals Quantifying the Robustness of the English Sibilant Fricative Contrast in Children

2015 ◽  
Vol 58 (3) ◽  
pp. 622-637 ◽  
Author(s):  
Jeffrey J. Holliday ◽  
Patrick F. Reidy ◽  
Mary E. Beckman ◽  
Jan Edwards
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Mixed Effects ◽  
Vocabulary Size ◽  
Phonological Contrast ◽  
Different Types ◽  
Centroid Frequency ◽  
The Relationship ◽  
Children's Speech

Purpose Four measures of children's developing robustness of phonological contrast were compared to see how they correlated with age, vocabulary size, and adult listeners' correctness ratings. Method Word-initial sibilant fricative productions from eighty-one 2- to 5-year-old children and 20 adults were phonetically transcribed and acoustically analyzed. Four measures of robustness of contrast were calculated for each speaker on the basis of the centroid frequency measured from each fricative token. Productions that were transcribed as correct from different children were then used as stimuli in a perception experiment in which adult listeners rated the goodness of each production. Results Results showed that the degree of category overlap, quantified as the percentage of a child's productions whose category could be correctly predicted from the output of a mixed-effects logistic regression model, was the measure that correlated best with listeners' goodness judgments. Conclusions Even when children's productions have been transcribed as correct, adult listeners are sensitive to within-category variation quantified by the child's degree of category overlap. Further research is needed to explore the relationship between the age of a child and adults' sensitivity to different types of within-category variation in children's speech.

scholarly journals Impact of Transcatheter Aortic Valve Replacement on Hospitalization Rates: Insights From Nationwide Readmission Database

2021 ◽  
Author(s):  
Ahmed Elkaryoni ◽  
Adnan K. Chhatriwalla ◽  
Kevin F. Kennedy ◽  
John T. Saxon ◽  
John J. Lopez ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Aortic Valve ◽  
Aortic Valve Replacement ◽  
Regression Model ◽  
Transcatheter Aortic Valve Replacement ◽  
Logistic Regression Model ◽  
Mixed Effects ◽  
Transcatheter Aortic Valve ◽  
Hospitalization Rates ◽  
Before And After

Background Hospitalization rates after transcatheter aortic valve replacement (TAVR) remain high, given the age and comorbidities of patients undergoing TAVR. To better understand the impact of TAVR on hospitalization, we sought to compare hospitalization rates before and after TAVR and to examine if underlying patient comorbidities are associated with a differential effect of TAVR on hospitalizations. Methods and Results We used the Nationwide Readmissions Database to identify patients who underwent TAVR. As Nationwide Readmissions Database data do not cross over calendar years, we limited our index admission to hospitalizations during April to September of each calendar year to allow 90 days of observation before and after TAVRs. We calculated the daily risk of all‐cause hospitalization and used a mixed‐effects logistic regression model to explore interactions between patient characteristics, TAVR, and hospitalization risk. Among 39 249 patients who underwent TAVR in 2014 to 2017 (median age, 82 years [interquartile range, 76–87 years]; 45.7% women), 32.0% had at least one hospitalization in the 90 days before TAVR compared with 23.2% in the 90 days post‐TAVR (relative reduction, 27.5%; P <0.001). In the mixed‐effects logistic regression model, TAVR was associated with decreased all‐cause hospitalization rate after TAVR in all comorbidity subgroups. However, younger patients and those with heart failure and reduced ejection fraction appeared to have more robust reduction in hospitalizations. Conclusions Although patients who are treated with TAVR have high rates of rehospitalization, TAVR is associated with an overall reduction in all‐cause hospitalizations regardless of underlying patient comorbidities.

scholarly journals Household overcrowding and risk of SARS-CoV-2: analysis of the Virus Watch prospective community cohort study in England and Wales

2021 ◽  
Author(s):  
Robert W Aldridge ◽  
Helen Pineo ◽  
Ellen Fragaszy ◽  
Max Eyre ◽  
Jana Kovar ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Fixed Effects ◽  
Respiratory Infections ◽  
Random Effect ◽  
Mixed Effects ◽  
P Value ◽  
England And Wales ◽  
Logistic Regression Models ◽  
Household Level ◽  
Increased Risk

Background: Household overcrowding is associated with increased risk of infectious diseases across cultures and countries. Limited data exist in England and Wales linking household overcrowding and risk of COVID-19. We used data collected from the Virus Watch cohort to examine the association between overcrowded households and infection to pandemic coronavirus SARS-CoV-2. Methods: The Virus Watch study is a household community cohort of acute respiratory infections in England & Wales that began recruitment in June 2020. We calculated the persons per room for each household and classified accommodation as overcrowded when the number of rooms was fewer than the number of people. We considered two primary outcomes - PCR-confirmed positive SARS-CoV-2 antigen tests and laboratory confirmed SARS-CoV-2 antibodies (Roche Elecsys anti-N total immunoglobulin assay). We used mixed effects logistic regression models that accounted for household structure to estimate the association between household overcrowding and SARS-CoV-2 infection. Results: The proportion of participants with a positive SARS-CoV-2 PCR result was highest in the overcrowded group (6.6%; 73/1,102) and lowest in the under-occupied group (2.9%; 682/23,219). In a mixed effects logistic regression model that included age, sex, ethnicity, household income and geographical region as fixed effects, and a household-level random effect, we found strong evidence of an increased odds of having a positive PCR SARS-CoV-2 antigen result (Odds Ratio 3.67; 95% CI: 1.91, 7.06; p-value < 0.001) and increased odds of having a positive SARS-CoV-2 antigen result in individuals living in overcrowded houses (2.99; 95% CI: 1.14, 7.81; p-value =0.03) compared to people living in under-occupied houses. Discussion: Public health interventions to prevent and stop the spread of SARS-CoV-2 should consider the much greater risk of infection for people living in overcrowded households and pay greater attention to reducing household transmission. There is an urgent need to better recognise housing as a leading determinant of health in the context of a pandemic and beyond.

The morphosyntactic characteristics of null subjects in Old English

2019 ◽  
pp. 93-122
Author(s):  
Kristian A. Rusten
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Old English ◽  
Logistic Regression Model ◽  
Mixed Effects ◽  
Linguistic Variables ◽  
Null Subjects ◽  
Null Subject ◽  
Structural Variables ◽  
The Individual

Chapter 4 provides an in-depth quantitative investigation of the morpohsyntactic characteristics of null subjects in Old English. The distribution of overt and null subjects is presented according to the structural variables of clause type, the position of the finite verb, person, and number. Attempts are made to fit an explanatory generalized mixed-effects logistic regression model incorporating these linguistic variables, as well as those non-linguistic variables which emerged as significant in Chapter 3. It is demonstrated that correlations between the occurrence of null subjects and such variables are extremely weak when both genre and the individual text are taken into account: only minuscule influence on the odds of having a null subject instead of an overt one is exercised by these variables. It is argued that this strengthens the view of null subjects in Old English as linguistic ‘residue’.

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