@article{JTD28558,
author = {Yibo He and Yuming Huang and Junqing Yang and Jin Liu and Guoli Sun and Feier Song and Shiqun Chen and Ning Tan and Zhonghan Ni and Yong Liu and Jiyan Chen},
title = {Novel risk model for predicting acute adverse drug reactions following cardiac catheterization from TRUST study (The Safety and toleRability of UltraviSt in Patients Undergoing Cardiac CaTheterization)},
journal = {Journal of Thoracic Disease},
volume = {11},
number = {4},
year = {2019},
keywords = {},
abstract = {Background: Acute drug reactions (ADRs) are common complications of contrast administration following cardiac catheterization. Serious reactions may be life threatening. However, few risk models for predicting ADRs exist. The study aims to develop a novel tool for predicting the risk of ADRs [occurring within 1 hour in patients undergoing coronary angiography or percutaneous coronary intervention (PCI)].
Methods: A total of 17,139 consecutive patients included in the TRUST study were randomly (2:1) assigned to a development data set (n=11,426) or a validation data set (n=5,713). Multivariate logistic regression was applied to identify independent predictors of contrast-induced nephropathy (CIN), including age, contrast dose, premedication, and prehydration. The performance of our model was assessed using the c-statistic for discrimination and the Hosmer-Lemeshow test for calibration.
Results: The overall incidence of ADRs was 42 (0.37%) in the development data set: 0.09% in the low-risk category (score: 0–2), 0.36% in the moderate-risk category (score: 3–4), and 1.78% in the high-risk category (score ≥5). The risk score across the subgroup of the study population exhibited good discrimination and predictive ability for ADRs (c-statistic: 0.694). Meanwhile, the calibration was also demonstrated to be accurate by the Hosmer-Lemeshow goodness-of-fit test (P=0.305).
Conclusions: Our data showed that our simple risk model showed good discrimination and predictive ability of ADRs following cardiac catheterization.},
issn = {2077-6624}, url = {https://jtd.amegroups.org/article/view/28558}
}