Development of MIF/IL-1β Biosensors for Discovery of Critical Quality Attributes and Allergic Rhinitis Targets from Clinical Real-world data by Intelligent Algorithm coupled with in Vitro and Vivo Mechanism Validation

2021 ◽  
pp. 113608
Author(s):  
Lijuan Ma ◽  
Yanfei Zheng ◽  
Ji Wang ◽  
Qianqian Li ◽  
Jingqi Zeng ◽  
...  
Keyword(s):  
Allergic Rhinitis ◽  
Real World ◽  
Quality Attributes ◽  
Intelligent Algorithm ◽  
Real World Data ◽  
Critical Quality Attributes ◽  
World Data

scholarly journals Treatment of allergic rhinitis using mobile technology with real-world data: The MASK observational pilot study

Allergy ◽  
2018 ◽  
Vol 73 (9) ◽  
pp. 1763-1774 ◽  
Author(s):  
J. Bousquet ◽  
P. Devillier ◽  
S. Arnavielhe ◽  
A. Bedbrook ◽  
G. Alexis-Alexandre ◽  
...  
Keyword(s):  
Allergic Rhinitis ◽  
Pilot Study ◽  
Mobile Technology ◽  
Real World ◽  
Real World Data ◽  
World Data

scholarly journals Drugs in COVID19 clinical trials: Predicting transporter‐mediated drug‐drug interactions using in vitro assays and real‐world data

2021 ◽  
Author(s):  
Sook Wah Yee ◽  
Bianca Vora ◽  
Tomiko T Oskotsky ◽  
Ling Zou ◽  
Sebastian Jakobsen ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Drug Interactions ◽  
Real World ◽  
In Vitro Assays ◽  
Real World Data ◽  
World Data

Estimate of the total costs of allergic rhinitis in specialized care based on real-world data: the FERIN Study

Allergy ◽  
2017 ◽  
Vol 72 (6) ◽  
pp. 959-966 ◽  
Author(s):  
C. Colás ◽  
M. Brosa ◽  
E. Antón ◽  
J. Montoro ◽  
A. Navarro ◽  
...  
Keyword(s):  
Allergic Rhinitis ◽  
Real World ◽  
Real World Data ◽  
World Data ◽  
Specialized Care

scholarly journals Evaluation of Ovarian Reserve Tests and Age in the Prediction of Poor Ovarian Response to Controlled Ovarian Stimulation—A Real-World Data Analysis of 89,002 Patients

2021 ◽  
Vol 12 ◽  
Author(s):  
Xue Wang ◽  
Lei Jin ◽  
Yun-dong Mao ◽  
Juan-zi Shi ◽  
Rui Huang ◽  
...  
Keyword(s):  
Real World ◽  
Ovarian Reserve ◽  
Ovarian Stimulation ◽  
Retrospective Cohort ◽  
Prediction Accuracy ◽  
Single Factor ◽  
Real World Data ◽  
Predictive Values ◽  
World Data

AimsThis study aimed to explore the value of ovarian reserve tests (ORTs) for predicting poor ovary response (POR) and whether an age cutoff could improve this forecasting, so as to facilitate clinical decision-making for women undergoing in vitro fertilization (IVF).MethodsA retrospective cohort study was conducted on poor ovary response (POR) patients using real-world data from five reproductive centers of university-affiliated hospitals or large academic hospitals in China. A total of 89,002 women with infertility undergoing their first traditional ovarian stimulation cycle for in vitro fertilization from January 2013 to December 2019 were included. The receiver operating characteristic (ROC) curve was performed to estimate the prediction value of POR by the following ORTs: anti-Mullerian hormone (AMH), antral follicle count (AFC), basal FSH (bFSH), as well as patient age.ResultsIn this retrospective cohort, the frequency of POR in the first IVF cycle was 14.8%. Age, AFC, AMH, and bFSH were used as predicting factors for POR, of which AMH and AFC were the best indicators when using a single factor for prediction (AUC 0.862 and 0.842, respectively). The predictive values of the multivariate model included age and AMH (AUC 0.865), age and AFC (AUC 0.850), age and all three ORTs (AUC 0.873). Compared with using a single factor alone, the combinations of ORTs and female age can increase the predictive value of POR. Adding age to single AMH model improved the prediction accuracy compared with AMH alone (AUC 0.865 vs. 0.862), but the improvement was not significant. The AFC with age model significantly improved the prediction accuracy of the single AFC model (AUC 0.846 vs. 0.837). To reach 90% specificity for POR prediction, the cutoff point for age was 38 years old with a sensitivity of 40.7%, 5 for AFC with a sensitivity of 55.9%, and 1.18 ng/ml for AMH with a sensitivity of 63.3%.ConclusionAFC and AMH demonstrated a high accuracy when using ROC regression to predict POR. When testing is reliable, AMH can be used alone to forecast POR. When AFC is used as a prediction parameter, age is suggested to be considered as well. Based on the results of the cutoff threshold analysis, AFC ≤ 5 and AMH ≤ 1.18 ng/ml should be recommended to predict POR more accurately in IVF/ICSI patients.

Abstract #946: Assessment of Acromegaly Patients with and Without Diabetes Treated with Lanreotide Depot: 2-Year Real World Data

2016 ◽  
Vol 22 ◽  
pp. 219
Author(s):  
Roberto Salvatori ◽  
Olga Gambetti ◽  
Whitney Woodmansee ◽  
David Cox ◽  
Beloo Mirakhur ◽  
...  
Keyword(s):  
Real World ◽  
Real World Data ◽  
World Data

Real world data of Type 2 Diabetes Mellitus (T2DM) obese patients using another GLP1 receptor agonist (GLP1–RA) and switching to Semaglutide in Spain

2020 ◽  
Author(s):  
Jersy Cardenas ◽  
Gomez Nancy Sanchez ◽  
Sierra Poyatos Roberto Miguel ◽  
Luca Bogdana Luiza ◽  
Mostoles Naiara Modroño ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Real World ◽  
Receptor Agonist ◽  
Obese Patients ◽  
Real World Data ◽  
World Data
Sign in / Sign up

Export Citation Format

Share Document