Web-Based Malignancy Risk Estimation for Thyroid Nodules Using Ultrasonography Characteristics: Development and Validation of a Predictive Model

Thyroid ◽  
2015 ◽  
Vol 25 (12) ◽  
pp. 1306-1312 ◽  
Author(s):  
Young Jun Choi ◽  
Jung Hwan Baek ◽  
Seung Hee Baek ◽  
Woo Hyun Shim ◽  
Kang Dae Lee ◽  
...  
2020 ◽  
Vol 93 (6) ◽  
pp. 729-738
Author(s):  
Bin Zhang ◽  
Shufang Pei ◽  
Qiuying Chen ◽  
Yuhao Dong ◽  
Lu Zhang ◽  
...  

2018 ◽  
Vol 8 (2) ◽  
pp. 83-89 ◽  
Author(s):  
Bülent Öcal ◽  
Mehmet Hakan Korkmaz ◽  
Demet Yılmazer ◽  
Tuğba Taşkın Türkmenoğlu ◽  
Ömer Bayır ◽  
...  

2021 ◽  
Vol 9 (3) ◽  
pp. 486
Author(s):  
Mi Seon Kang ◽  
Jin Hwa Park ◽  
Hyun Jung Kim

The objective of the study was to develop a predictive model of Salmonella spp. growth in pasteurized liquid egg white (LEW) and to estimate the salmonellosis risk using the baseline model and scenario analysis. Samples were inoculated with six strains of Salmonella, and bacterial growth was observed during storage at 10–37 °C. The primary models were developed using the Baranyi model for LEW. For the secondary models, the obtained specific growth rate (μmax) and lag phase duration were fitted to a square root model and Davey model, respectively, as functions of temperature (R2 ≥ 0.98). For μmax, the values were satisfied within an acceptable range (Af, Bf: 0.70–1.15). The probability of infection (Pinf) due to the consumption of LEW was zero in the baseline model. However, scenario analysis suggested possible salmonellosis for the consumption of LEW. Because Salmonella spp. proliferated much faster in LEW than in egg white (EW) during storage at 20 and 30 °C (p < 0.01), greater Pinf may be obtained for LEW when these products are stored at the same conditions. The developed predictive model can be applied to the risk management of Salmonella spp. along the food chain, including during product storage and distribution.


2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
P Codina ◽  
M De Antonio ◽  
E Santiago-Vacas ◽  
M Domingo ◽  
E Zamora ◽  
...  

Abstract Background Heart failure (HF) contemporary management has significantly improved over the past two decades leading to better survival. How application of the contemporary HF management guidelines affects the risk of death estimated by available web-based risk scores is not elucidated. Objective To assess changes in mortality risk prediction after a after a 12-month management period in a multidisciplinary HF Clinic. Methods Out of 1,689 consecutive patients with HF admitted at our ambulatory HF Clinic from May 2006 to November 2018, those who completed one year follow-up were considered for the study. Patients without NTproBNP measurement or with more than 3 missing variables for risk estimation were excluded. Three contemporary web-based HF risk scores were evaluated: MAGGIC-HF, Seattle HF Model (SHFM) and the Barcelona Bio-HF Calculator containing NTproBNP (BCN Bio-HF). Risk of all-cause death at one year and at 3 years were calculated at baseline and re-evaluated after 12-month management in a multidsisciplinary HF Clinic. Wilcoxon paired data test was used to compare changes in mortality risk estimation over time and test equality of matched pairs for comparing estimated change among tools. 442 patients used to derive the Barcelona Bio-HF Calculator were excluded for discrimination purposes. Results 1,157 patients were included (age 65.7±12.7 years, 70.4% men). A significant reduction in mortality risk estimation was observed with the three HF risk scores evaluated at 12-months (Table). The BCN Bio-HF model showed significantly different changes in risk estimation, fact that indeed was partnered with numerically better discrimination. AUC at 1 and 3 years, respectively, were: BCN Bio-HF (0.773 and 0.775), MAGGIC HF (0.686 and 0.748) and SHFM (0.773 and 0.739). Conclusions The three web-based risk scores evaluated showed a significant reduction in mortality risk estimation after 12 month management in a multidisciplinary HF Clinic. The BCN Bio-HF score showed higher reduction in estimated risk, together with better discrimination, likely because it incorporates contemporary treatment and use of biomarkers. Funding Acknowledgement Type of funding source: None


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