The novel risk score model for predicting the poor anticoagulation control in patients with atrial fibrillation taking warfarin
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background Previous trials have shown that the C-statistics of SAMe-TT 2 R 2 score in the prediction of suboptimal time in therapeutic range (TTR) is very low. Objectives To propose the novel risk score model for predicting the poor anticoagulation control in atrial fibrillation (AF) patients compared with the SAMe-TT 2 R 2 score. Methods We prospectively recruited AF patients from 27 hospitals between 2014 and 2017 in the COOL AF Thailand registry. The poor anticoagulation control was defined as TTR <65%. Multivariate logistic regression analysis was performed for the prediction of poor anticoagulation control. The novel risk score model was then generated. Receiver operating characteristic (ROC) curve analysis was performed to calculate the C-statistics and to compare between the novel risk score model and the SAMe-TT 2 R 2 score. Net Reclassification Index (NRI) and Integrated Discrimination Index (IDI) were performed. Results Of 3,461 patients, 2,233 patients taking warfarin having available TTR data were retrieved. There were 1,432 patients having poor anticoagulation control (TTR < 65%) and 801 patients having good anticoagulation control (TTR ≥ 65%). Symptomatic AF, diabetes, heart failure, and a history of bleeding were associated with increased risk while obesity, AF duration, and paroxysmal AF were associated with decreased risk of poor anticoagulation control. SHOB-D 2 AF score was created. The C-statistics of SHOB-D 2 AF score was greater than the SAMe-TT 2 R 2 score (0.584 vs 0.506, P < 0.001). NRI of the SHOB-D 2 AF score was 17.82% compared with the SAMe-TT 2 R 2 score. Conclusions SHOB-D 2 AF score was the novel risk score which was better than the SAMe-TT 2 R 2 score in predicting poor anticoagulation control.
Source: Asian Biomedicine
Authors: Komsing Methavigul, Rungroj Krittayaphong
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4411626556