Reproductive risk factors assessment for anaemia among pregnant women in India using a multinomial logistic regression model

2014 ◽  
Vol 19 (7) ◽  
pp. 841-851 ◽  
Author(s):  
Vanamail Perumal
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Model ◽  
Pregnant Women ◽  
Logistic Regression Model ◽  
Multinomial Logistic Regression ◽  
Multinomial Logistic Regression Model ◽  
Reproductive Risk ◽  
Reproductive Risk Factors ◽  
Women In India

scholarly journals A comprehensive, contemporary assessment of the association between hepatosteatosis and coronary artery calcium scoring

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
T Heseltine ◽  
SW Murray ◽  
RL Jones ◽  
M Fisher ◽  
B Ruzsics
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Coronary Artery ◽  
Regression Model ◽  
Coronary Artery Calcium ◽  
Logistic Regression Model ◽  
Prediction Models ◽  
Multinomial Logistic Regression ◽  
Cvd Risk ◽  
Male Sex

Abstract Funding Acknowledgements Type of funding sources: None. onbehalf Liverpool Multiparametric Imaging Collaboration Background Coronary artery calcium (CAC) score is a well-established technique for stratifying an individual’s cardiovascular disease (CVD) risk. Several well-established registries have incorporated CAC scoring into CVD risk prediction models to enhance accuracy. Hepatosteatosis (HS) has been shown to be an independent predictor of CVD events and can be measured on non-contrast computed tomography (CT). We sought to undertake a contemporary, comprehensive assessment of the influence of HS on CAC score alongside traditional CVD risk factors. In patients with HS it may be beneficial to offer routine CAC screening to evaluate CVD risk to enhance opportunities for earlier primary prevention strategies. Methods We performed a retrospective, observational analysis at a high-volume cardiac CT centre analysing consecutive CT coronary angiography (CTCA) studies. All patients referred for investigation of chest pain over a 28-month period (June 2014 to November 2016) were included. Patients with established CVD were excluded. The cardiac findings were reported by a cardiologist and retrospectively analysed by two independent radiologists for the presence of HS. Those with CAC of zero and those with CAC greater than zero were compared for demographic and cardiac risks. A multivariate analysis comparing the risk factors was performed to adjust for the presence of established risk factors. A binomial logistic regression model was developed to assess the association between the presence of HS and increasing strata of CAC. Results In total there were 1499 patients referred for CTCA without prior evidence of CVD. The assessment of HS was completed in 1195 (79.7%) and CAC score was performed in 1103 (92.3%). There were 466 with CVD and 637 without CVD. The prevalence of HS was significantly higher in those with CVD versus those without CVD on CTCA (51.3% versus 39.9%, p = 0.007). Male sex (50.7% versus 36.1% p= <0.001), age (59.4 ± 13.7 versus 48.1 ± 13.6, p= <0.001) and diabetes (12.4% versus 6.9%, p = 0.04) were also significantly higher in the CAC group compared to the CAC score of zero. HS was associated with increasing strata of CAC score compared with CAC of zero (CAC score 1-100 OR1.47, p = 0.01, CAC score 101-400 OR:1.68, p = 0.02, CAC score >400 OR 1.42, p = 0.14). This association became non-significant in the highest strata of CAC score. Conclusion We found a significant association between the increasing age, male sex, diabetes and HS with the presence of CAC. HS was also associated with a more severe phenotype of CVD based on the multinomial logistic regression model. Although the association reduced for the highest strata of CAC (CAC score >400) this likely reflects the overall low numbers of patients within this group and is likely a type II error. Based on these findings it may be appropriate to offer routine CVD risk stratification techniques in all those diagnosed with HS.

scholarly journals Burden and predictors ofStaphylococcus aureusandS. pseudintermediusinfections among dogs presented at an academic veterinary hospital in South Africa (2007–2012)

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3198 ◽  
Author(s):  
Daniel N. Qekwana ◽  
James Wabwire Oguttu ◽  
Fortune Sithole ◽  
Agricola Odoi
Keyword(s):  
South Africa ◽  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Multinomial Logistic Regression ◽  
Risk Of Infection ◽  
Multinomial Logistic Regression Model ◽  
Tract Infections ◽  
Veterinary Hospital ◽  
Isolated Species

BackgroundStaphylococci are commensals of the mucosal surface and skin of humans and animals, but have been implicated in infections such as otitis externa, pyoderma, urinary tract infections and post-surgical complications. Laboratory records provide useful information to help investigate these infections. Therefore, the objective of this study was to investigate the burdens of these infections and use multinomial regression to examine the associations between variousStaphylococcusinfections and demographic and temporal factors among dogs admitted to an academic veterinary hospital in South Africa.MethodsRecords of 1,497 clinical canine samples submitted to the bacteriology laboratory at a veterinary academic hospital between 2007 and 2012 were included in this study. Proportions of staphylococcal positive samples were calculated, and a multinomial logistic regression model was used to identify predictors of staphylococcal infections.ResultsTwenty-seven percent of the samples tested positive forStaphylococcusspp. The species ofStaphylococcusidentified wereS. pseudintermedius(19.0%),S. aureus(3.8%),S. epidermidis(0.7%) andS. felis(0.1%). The remaining 2.87% consisted of unspeciatedStaphylococcus. Distribution of the species by age of dog showed thatS. pseudintermediuswas the most common (25.6%) in dogs aged 2–4 years whileS. aureuswas most frequent (6.3%) in dogs aged 5–6 years.S. pseudintermedius(34.1%) andS. aureus(35.1%) were the most frequently isolated species from skin samples. The results of the multivariable multinomial logistic regression model identified specimen, year and age of the dog as significant predictors of the risk of infection withStaphylococcus. There was a significant temporal increase (RRR = 1.17; 95% CI [1.06–1.29]) in the likelihood of a dog testing positive forS. pseudintermediuscompared to testing negative. Dogs ≤ 8 years of age were significantly more likely to test positive forS. aureusthan those >8 years of age. Similarly, dogs between 2–8 years of age were significantly more likely to test positive forS. pseudintermediusthan those >8 years of age. In addition, dogs 2–4 years of age (RRR = 1.83; 1.09–3.06) were significantly more likely to test positive forS. pseudintermediuscompared to those <2 years of age. The risk of infection withS. pseudintermediusorS. aureuswas significantly higher in ear canal and skin specimens compared to other specimens.ConclusionsThe findings suggest thatS. pseudintermediusandS. aureuswere the most commonly isolated species from dogs presented at the study hospital. Age of the dog and the location of infection were significant predictors of infection with bothStaphylococcusspecies investigated. Significant increasing temporal trend was observed forS. pseudintermediusbut notS. aureus. This information is useful for guiding clinical decisions as well as future research.

Diachronic frame analysis

2019 ◽  
Vol 11 (1) ◽  
pp. 43-78
Author(s):  
James Law
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Multinomial Logistic Regression ◽  
Frame Analysis ◽  
Semantic Change ◽  
Frame Semantics ◽  
Multinomial Logistic Regression Model ◽  
Grammatical Category

Abstract Frame Semantics offers a valuable perspective on mechanisms of semantic change, particularly metonymy. However, corpus-based frame analysis has rarely been applied to diachronic data. The potential of this approach is illustrated with a diachronic description of the Purpose frame in French, based on 1,429 tokens of 17 frame-evoking words. Metonymic mappings in the frame allow Means and Medium to replace Agent. A multinomial logistic regression model shows that usage of these mappings has increased since 1600 and is conditioned by genre and the frequency and grammatical category of the frame-evoking word. The approach may inform how metonymy leads to lexicalized semantic change.

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