Nonsteroidal anti-inflammatory drug-associated gastropathy: Incidence and risk factor models

1991 ◽  
Vol 91 (3) ◽  
pp. 213-222 ◽  
Author(s):  
James F. Fries ◽  
Catherine A. Williams ◽  
Daniel A. Bloch ◽  
Beat A. Michel
Keyword(s):  
Risk Factor ◽  
Factor Models ◽  
Inflammatory Drug ◽  
Anti Inflammatory ◽  
Risk Factor Models

The Contributions of Propensity, Delinquent Peers, Low Parental Supervision, and Empathy to the Emergence of Antisocial Behavior in Childhood and Adolescence: Testing Developmental Path Models Combining Psychological- and Sociological-Criminological Approaches

2020 ◽  
pp. 1-14
Author(s):  
Susanne Wallner ◽  
Stemmler Mark ◽  
Jost Reinecke
Keyword(s):  
Risk Factor ◽  
Antisocial Behavior ◽  
Action Theory ◽  
Cumulative Risk ◽  
Factor Models ◽  
Individual Risk ◽  
Parental Supervision ◽  
Childhood And Adolescence ◽  
Path Models ◽  
Risk Factor Models

Psychological- and sociological-criminological research refers to, for example, cumulative risk factor models (e.g., Lösel & Bender, 2003) and Situational Action Theory (SAT; e.g., Wikström, 2006). The German longitudinal study “Chances and Risks in the Life Course“ (research project A2, Collaborative Research Center 882; e.g., Reinecke, Stemmler, & Wittenberg, 2016) focuses upon the development of antisocial behavior from a psychological and sociological point of view. Two-wave panel data of two cohorts (children and adolescents) were utilized to test the power of developmental path models investigating the development of antisocial behavior. Individual risk seems to have both direct and indirect influences on antisocial behavior, supporting the ideas of risk factor models; antisocial behavior might be the outcome of the interaction between propensity and criminogenic exposure, so there is evidence for SAT. Additionally, empathy seems to be related to both propensity and low parental supervision. Implications for the study of antisocial behavior in childhood and adolescence are discussed in line with developmental criminology.

scholarly journals Ordering risk bounds in factor models

2018 ◽  
Vol 6 (1) ◽  
pp. 259-287 ◽  
Author(s):  
Jonathan Ansari ◽  
Ludger Rüschendorf
Keyword(s):  
Risk Factor ◽  
Systemic Risk ◽  
Factor Models ◽  
Worst Case ◽  
Sign Changes ◽  
Risk Factor Models ◽  
Risk Bounds ◽  
Derivatives Of ◽  
Dependence Structures

AbstractConditionally comonotonic risk vectors have been proved in [4] to yield worst case dependence structures maximizing the risk of the portfolio sum in partially specified risk factor models. In this paper we investigate the question how risk bounds depend on the specification of the pairwise copulas of the risk components Xiwith the systemic risk factor. As basic toolwe introduce a new ordering based on sign changes of the derivatives of copulas. This together with discretization by n-grids and the theory of supermodular transfers allows us to derive concrete ordering criteria for the maximal risks.

scholarly journals Nonsteroidal anti-inflammatory drug use is a risk factor for early Type II endoleak after endovascular abdominal aortic repair

Vascular ◽  
2019 ◽  
Vol 28 (1) ◽  
pp. 53-58
Author(s):  
Yutaka Matsubara ◽  
Kentaro Inoue ◽  
Kazuki Mori ◽  
Masato Morita ◽  
Satoshi Takebayashi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Body Mass Index ◽  
Risk Factor ◽  
Drug Use ◽  
Type Ii ◽  
Type Ii Endoleak ◽  
Inflammatory Drug ◽  
Postoperative Risk ◽  
Inflammatory Drugs ◽  
Anti Inflammatory

Objectives Type II endoleak is a problem after endovascular abdominal aneurysm repair. Preoperative risk factors for Type II endoleak include anatomical factors in the lumbar artery and inferior mesenteric artery; however, preventable postoperative risk factors are unknown. Postimplantation syndrome is associated with lower incidence of Type II endoleak. Therefore, we focused on inflammation, and our aim was to investigate nonsteroidal anti-inflammatory drugs as a postoperative risk factor for Type II endoleak. Methods This was a retrospective study of patients with aortic aneurysm who underwent endovascular aneurism repair at the Department of Cardiovascular Surgery, Beppu Medical Center, Oita, Japan, from January 2011 to August 2018. Clinical characteristics were retrieved from patients’ medical records and included age, sex, body mass index, smoking history, comorbidities, treatment devices, medications, and perioperative information, including postimplantation syndrome. Postimplantation syndrome was defined as body temperature >38.5°C with 12,000/dL white blood cells or >10.0 mg/dL C-reactive protein. The primary outcome was the presence or absence of Type II endoleak assessed on the first postoperative enhanced computed tomography scan. Risk factors for Type II endoleak were assessed. Results and conclusions: Of the eligible 84 patients, 20 (24%) had Type II endoleak identified in the first enhanced computed tomographic scans after endovascular aneurism repair. Nonsteroidal anti-inflammatory drug use (odds ratio (OR): 21.2; 95% confidence interval (95% CI): 1.5–308.4; P = 0.026), cerebrovascular disease (OR: 7.27; 95% CI: 1.06–49.99; P = 0.044), and body mass index <22 kg/m2 (OR: 17.3; 95% CI: 2.1–141.8; P = 0.008) were independent risk factors for Type II endoleak after endovascular aneurism repair. Comparing the rate of Type II endoleak among patients who did not receive nonsteroidal anti-inflammatory drugs within 24 h after endovascular aneurism repair, patients who first used nonsteroidal anti-inflammatory drugs 12–24 h after endovascular aneurism repair, and those who received nonsteroidal anti-inflammatory drugs within 12 h after endovascular aneurism repair, we found a significant difference among the groups (4%, 18%, 45%, respectively; P = 0.001). Nonsteroidal anti-inflammatory drug use within 24 h after endovascular aneurism repair is a risk factor for Type II endoleak. We should know nonsteroidal anti-inflammatory drugs within 24 h after endovascular aneurism repair can be a risk of Type II endoleak.

Risk models vs characteristic models from an investor’s perspective

2019 ◽  
Vol 20 (2) ◽  
pp. 201-222
Author(s):  
Christian Fieberg ◽  
Armin Varmaz ◽  
Thorsten Poddig
Keyword(s):  
Risk Factor ◽  
Versus Characteristic ◽  
Design Methodology ◽  
Factor Models ◽  
Expected Returns ◽  
Risk Models ◽  
Content Type ◽  
Risk Factor Models ◽  
Mean Variance ◽  
Academic Debate

Purpose The purpose of this paper is to analyze the implications of the risk versus characteristic debate from the perspective of a mean-variance investor. Design/methodology/approach Expected returns and the variance-covariance matrix are estimated based on various characteristic and risk models and evaluated for the purpose of mean-variance portfolios. Findings Return estimates from characteristic models are most informative to investors. Risk-factor models provide the most informative estimates of the risk. A mean-variance investor should rely on combinations of the two model types. Originality/value Although the risk vs characteristic debate is a binary academic debate, our findings from an investor's perspective suggest to make use of the best of both worlds.

Benefits on Sales Generated by Innovation

2021 ◽  
pp. 2140010
Author(s):  
Fernando Henrique Taques ◽  
Nelson Areal ◽  
Leonardo Fernando Cruz Basso
Keyword(s):  
Risk Factor ◽  
Financial Performance ◽  
Abnormal Returns ◽  
Sales Performance ◽  
Factor Models ◽  
Regression Method ◽  
Risk Models ◽  
Risk Factor Models ◽  
Rolling Regression ◽  
D Investment

The object of the research is to assess whether organizations’ ability to innovate may be able to explain abnormal returns to firms by composing risk factor models. Using R&D investment indicators and published patents from a global sample of companies for the period 1992 to 2018, the 3-factor, 4-factor and 5-factor risk models were applied. Partly the case is that increased investment in innovation contributes to better sales performance and, consequently, excess returns. Regarding the rolling-regression method, the results show few scenarios in which the ability to innovate is an explanatory factor for financial performance.

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