scholarly journals Development and Validation of an Objective Risk Scoring System for Assessing the Likelihood of Virus Introduction in Porcine Reproductive and Respiratory Syndrome Virus-Free Sow Farms in the US

2013 ◽  
Vol 03 (02) ◽  
pp. 168-175 ◽  
Author(s):  
Derald J. Holtkamp ◽  
Hui Lin ◽  
Chong Wang ◽  
Dale D. Polson
2016 ◽  
Vol 14 (11) ◽  
pp. 1562-1570.e2 ◽  
Author(s):  
Tomonori Aoki ◽  
Naoyoshi Nagata ◽  
Takuro Shimbo ◽  
Ryota Niikura ◽  
Toshiyuki Sakurai ◽  
...  

Heart ◽  
2014 ◽  
Vol 100 (Suppl 3) ◽  
pp. A39-A40 ◽  
Author(s):  
Nikesh Malik ◽  
Amerjeet Banning ◽  
Anthony Gershlick

Hepatology ◽  
2019 ◽  
Vol 69 (5) ◽  
pp. 2120-2135 ◽  
Author(s):  
Elizabeth C. Goode ◽  
Allan B. Clark ◽  
George F. Mells ◽  
Brijesh Srivastava ◽  
Kelly Spiess ◽  
...  

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S35-S36
Author(s):  
Styliani Karanika ◽  
Theodoros Karantanos ◽  
Herman Carneiro ◽  
Sabrina A Assoumou

Abstract Background HIV-infected individuals are at higher risk for developing cardiovascular disease (CVD). We aimed to develop a model to predict 10-year cardiovascular (CV) risk given that commonly used CVD risk assessment tools might not be accurate for HIV-infected patients. Methods We conducted a retrospective cohort study of HIV-infected patients seen at Boston Medical Center between March 2012 and January 2017. Exclusion criteria are shown in Figure 1. Patients were divided into model development and validation cohorts. Logistic regression was used to create a risk model for CV events using data from the development cohort. The relationship between risk factors and CVD risk was summarized using a point-based risk-scoring system. Areas under the receiver-operating-characteristics curve (AUC) were used to evaluate model discrimination. The model was subsequently tested using the validation cohort. Results Of 3,867 eligible HIV-infected patients, 1,914 individuals met inclusion criteria (Figure 1). There were 256 CV events in the development cohort. Ten independent prognostic factors were incorporated into the prediction function (Pmodel < 0.001). The model had excellent discrimination for CVD risk [AUC 0.94; (95% CI:0.93–0.96)] (Figure 2) and included the following variables: male sex (P < 0.001), African-American ethnicity (P = 0.023), current age (P = 0.020), age at HIV diagnosis (P = 0.006), peak HIV viral load (P = 0.012), nadir CD4 lymphocyte count (P < 0.001), hypertension (P < 0.001), hyperlipidemia (P = 0.001), diabetes (P < 0.001), and chronic kidney disease (P < 0.001). Scoring system and score sheets of risk estimates were developed to predict CV events in a 10-year follow-up period (Figures 3 and 4). The 10-parameter multiple logistic regression model also had excellent discrimination [AUC 0.96; (95% CI: 0.89–0.99)] when applied to the validation cohort. Conclusion We developed and validated a risk-scoring system based on 10 clinical factors that accurately predict the 10-year risk for CV events in an HIV-infected population. This assessment tool may provide clinicians with a rapid assessment of cardiovascular disease risk among HIV-infected patients and inform prevention measures during the era of effective antiretroviral therapy. Disclosures All Authors: No reported Disclosures.


2020 ◽  
Vol 35 (2) ◽  
pp. 435-442
Author(s):  
Sunghwan Suh ◽  
Tae Sik Goh ◽  
Yun Hak Kim ◽  
Sae-Ock Oh ◽  
Kyoungjune Pak ◽  
...  

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