{"title":"The novel risk score model for predicting the poor anticoagulation control in patients with atrial fibrillation taking warfarin.","authors":"Komsing Methavigul, Rungroj Krittayaphong","doi":"10.2478/abm-2025-0013","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Previous trials have shown that the C-statistics of SAMe-TT<sub>2</sub>R<sub>2</sub> score in the prediction of suboptimal time in therapeutic range (TTR) is very low.</p><p><strong>Objectives: </strong>To propose the novel risk score model for predicting the poor anticoagulation control in atrial fibrillation (AF) patients compared with the SAMe-TT<sub>2</sub>R<sub>2</sub> score.</p><p><strong>Methods: </strong>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<sub>2</sub>R<sub>2</sub> score. Net Reclassification Index (NRI) and Integrated Discrimination Index (IDI) were performed.</p><p><strong>Results: </strong>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<sub>2</sub>AF score was created. The C-statistics of SHOB-D<sub>2</sub>AF score was greater than the SAMe-TT<sub>2</sub>R<sub>2</sub> score (0.584 vs 0.506, <i>P</i> < 0.001). NRI of the SHOB-D<sub>2</sub>AF score was 17.82% compared with the SAMe-TT<sub>2</sub>R<sub>2</sub> score.</p><p><strong>Conclusions: </strong>SHOB-D<sub>2</sub>AF score was the novel risk score which was better than the SAMe-TT<sub>2</sub>R<sub>2</sub> score in predicting poor anticoagulation control.</p>","PeriodicalId":8501,"journal":{"name":"Asian Biomedicine","volume":"19 2","pages":"106-113"},"PeriodicalIF":0.4000,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189168/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Biomedicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2478/abm-2025-0013","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Previous trials have shown that the C-statistics of SAMe-TT2R2 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-TT2R2 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-TT2R2 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-D2AF score was created. The C-statistics of SHOB-D2AF score was greater than the SAMe-TT2R2 score (0.584 vs 0.506, P < 0.001). NRI of the SHOB-D2AF score was 17.82% compared with the SAMe-TT2R2 score.
Conclusions: SHOB-D2AF score was the novel risk score which was better than the SAMe-TT2R2 score in predicting poor anticoagulation control.
背景：已有研究表明，SAMe-TT2R2评分预测治疗范围次优时间（TTR）的c统计量很低。目的：与SAMe-TT2R2评分相比，提出预测房颤（AF）患者抗凝控制不良的新型风险评分模型。方法：我们前瞻性地从泰国COOL AF登记处的27家医院招募了2014年至2017年的AF患者。以TTR 2R2评分为抗凝控制不良。采用净重分类指数（NRI）和综合区分指数（IDI）进行分析。结果：在3461例患者中，有2233例服用华法林的患者有可用的TTR数据。抗凝控制不良1432例（TTR < 65%），抗凝控制良好801例（TTR≥65%）。有症状的房颤、糖尿病、心力衰竭和出血史与房颤风险增加相关，而肥胖、房颤持续时间和阵发性房颤与抗凝控制不良风险降低相关。创建了SHOB-D2AF分数。SHOB-D2AF评分的c统计量大于SAMe-TT2R2评分（0.584 vs 0.506, P < 0.001）。SHOB-D2AF评分与SAMe-TT2R2评分相比，NRI为17.82%。结论：SHOB-D2AF评分是较SAMe-TT2R2评分更能预测抗凝控制不良的新型风险评分。
期刊介绍：
Asian Biomedicine: Research, Reviews and News (ISSN 1905-7415 print; 1875-855X online) is published in one volume (of 6 bimonthly issues) a year since 2007. [...]Asian Biomedicine is an international, general medical and biomedical journal that aims to publish original peer-reviewed contributions dealing with various topics in the biomedical and health sciences from basic experimental to clinical aspects. The work and authorship must be strongly affiliated with a country in Asia, or with specific importance and relevance to the Asian region. The Journal will publish reviews, original experimental studies, observational studies, technical and clinical (case) reports, practice guidelines, historical perspectives of Asian biomedicine, clinicopathological conferences, and commentaries
Asian biomedicine is intended for a broad and international audience, primarily those in the health professions including researchers, physician practitioners, basic medical scientists, dentists, educators, administrators, those in the assistive professions, such as nurses, and the many types of allied health professionals in research and health care delivery systems including those in training.
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