Development and external validation of a post-discharge bleeding risk score in patients with acute coronary syndrome: The BleeMACS score

Raposeiras‐Roubín, Sergio; Faxén, Jonas; Íñiguez‐Romo, Andrés; Henriques, José P.S.; D’Ascenzo, Fabrizio; Saucedo, Jorge; Szummer, Karolina; Jernberg, Tomas; James, Stefan; González-Juanatey, José Ramón; Wilton, Stephen B.; Kikkert, Wouter J.; Núñez‐Gil, Iván J.; Arizá-Solé, Albert; Song, Xiantao; Alexopoulos, Dimitrios; Liebetrau, Christoph; Kawaji, Tetsuma; Moretti, Claudio; Huczek, Zenon; Nie, Shaoping; Fujii, Toshiharu; Correia, Luis; Kawashiri, Masa‐aki; Caneiro‐Queija, Berenice; Paz, Rafael Cobas; Acuña, José María García; Southern, Danielle; Alfonso, Emilio; Terol, Belén; Garay, Alberto; Zhang, Dongfeng; Chen, Yalei; Xanthopoulou, Ioanna; Osman, Neriman; Möllmann, Helge; Shiomi, Hiroki; Giordana, Francesca; Gaïta, Fiorenzo; Kowara, Michał; Filipiak‬, Krzysztof J.; Wang, Xiao; Yan, Yan; Fan, Jingyao; Ikari, Yuji; Nakahayshi, Takuya; Sakata, Kenji; Yamagishi, Masakazu; Kalpak, Oliver; Kedev, Saško; Rivera-Asenjo, Daniel; Abu‐Assi, Emad

doi:10.1016/j.ijcard.2017.10.103

Cited by 75 publications

(55 citation statements)

References 32 publications

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“…The score includes seven predictors: age; hypertension; vascular disease; history of bleeding; malignancy; creatinine; and haemoglobin. The BleeMACS risk score exhibited good performance in the derivation (c-statistic: 0.71) and internal validation (c-statistic: 0.72) cohorts.The c-statistic in the external validation cohort, performed in the SWEDEHEART registry, was slightly lower (c-statistic of 0.65 for PCItreated patients and 0.63 for patients who did not undergo PCI) 55. Selecting a Risk Scoring System in Daily Clinical PracticeUndoubtedly, the marked increase in the number of risk scores available to interventional cardiologists, as well as the presence of overlapping risk scores in the same clinical scenarios, make it difficult to select the best risk scoring system in daily clinical practice.In the growing arena of risk assessment tools, however, only a limited number of risk scoring systems have been extensively, rigorously and externally validated.…”

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confidence: 89%

Risk Stratification in Patients with Coronary Artery Disease: a Practical Walkthrough in the Landscape of Prognostic Risk Models

Buccheri

D’Arrigo

Franchina

et al. 2018

Interventional Cardiology Review

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Although a combination of multiple strategies to prevent and treat coronary artery disease (CAD) has led to a relative reduction in cardiovascular mortality over recent decades, CAD remains the greatest cause of morbidity and mortality worldwide. A variety of individual factors and circumstances other than clinical presentation and treatment type contribute to determining the outcome of CAD. It is increasingly understood that personalised medicine, by taking these factors into account, achieves better results than “one-size-fitsall” approaches. In recent years, the multiplication of risk scoring systems for CAD has generated some degree of uncertainty regarding whether, when and how predictive models should be adopted when making clinical decisions. Against this background, this article reviews the most accepted risk models for patients with evidence of CAD to provide practical guidance within the current landscape of tools developed for prognostic risk stratification.

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confidence: 89%

Risk Stratification in Patients with Coronary Artery Disease: a Practical Walkthrough in the Landscape of Prognostic Risk Models

Buccheri

D’Arrigo

Franchina

et al. 2018

Interventional Cardiology Review

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“…Этот регистр интересен тем, что пациенты по основным клиническим характеристикам близки к пациентам, включенным в наше исследование. Также и шкала риска кровотечений, разработанная на основе регистра BleeMACS оказалась близка по набору факторов к модели оценки риска, полученной на основании исследова- Шкала ОРАКУЛ ния ОРАКУЛ [26]. Обе модели включают такие факторы, как возраст, уровень креатинина, уровень гемоглобина.…”

Section: материал и методыunclassified

Bleeding risk factors in patients with acute coronary syndrome: data from observational studies ORACUL II

Бражник¹,

Минушкина²,

Гулиев³

et al. 2019

Russ J Cardiol

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Aim.To identify the risk factors for bleeding of BARC scale 2-5 types in patients after acute coronary syndrome (ACS).Material and methods.The data of 1502 patients from the open multicenter study, ORACUL II, were used — 894 men (59,5%) and 608 women (40,5%), mean age — 65,7±12,9 years. Five hundred sixty (37,3%) patients had ACS with ST-segment elevation and 942 (62,7%) — ACS without ST-segment elevation. Bleeding was recorded in 164 patients (10,9%), including index admission — in 39 (2,6%) patients, of which severe (types 3-5) — 0,5%, significant — 1,7% (types 2-5).Results.Within a year after discharge, bleeding was observed in 126 (8,4%) patients, large — 0,8%, significant — 2,4%. The development of bleeding type 2-5 was associated with the presence of gastric ulcer and duodenal ulcer, gastrointestinal bleeding in history, decreased creatinine, hemoglobin clearance, age of patients, the use of anticoagulants in the composition of triple or double antithrombotic therapy, conducting of percutaneous interventional procedures, the presence of heart failure 2-4 Killip class at admission. ROC analysis showed that the predictive value of the ORACLE bleeding risk scale is 0,762, sensitivity — 62%, specificity — 78%.Conclusion.Thus, we based on routine clinical practice have created a simple scale for assessing the risk of bleeding in patients with ACS.

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“…To date, HBR patients had not been well defined and the eligibility criteria of HBR patients were different among contemporary clinical trials [8][9][10]. Although several bleeding prediction scores are currently available to estimate the bleeding risks of the individual patient [11][12][13][14], they have moderate accuracy for predicting bleeding, with an average C statistics about 0.7. With this in mind, the Academic Research Consortium for HBR (ARC-HBR) developed a consensus definition of patients at HBR based on review of the available evidence in clinical trials [15].…”

Section: Introductionmentioning

confidence: 99%

Contribution of ESC DAPT guideline-endorsed high thrombotic risk features to long-term clinical outcomes among patients with and without high bleeding risk after PCI

Wang

Dou

Yin

et al. 2020

BMC Cardiovasc Disord

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Background: Whether the underlying risk of high bleeding risk (HBR) influences the relationship of high thrombotic risk (HTR) features with adverse events after drug-eluting stent implantation remains unclear. The purpose of this study was to evaluate (1) the prognostic effect of ESC guideline-endorsed HTR features on longterm clinical outcomes and (2) whether the outcomes of HTR versus non-HTR features vary by HBR status. Methods: Ten thousand one hundred sixty-seven consecutive patients who underwent percutaneous coronary intervention between January 2013 and December 2013 were prospectively enrolled in Fuwai PCI Registry. Patients who are at HTR were defined as: diffuse multivessel disease in diabetic patients, chronic kidney disease, at least three stents implanted, at least three stents lesions treated, bifurcation with two stents implanted, total stent length > 60 mm, or treatment of chronic total occlusion. The definition of HBR was based on the Academic Research Consortium for HBR criteria. The primary ischemic outcome was major adverse cardiac event (MACE), a composite of cardiac death, myocardial infarction, target vessel revascularization and stent thrombosis. The primary bleeding outcome was clinically relevant bleeding, defined according to Bleeding Academic Research Consortium (BARC) type 2, 3 or 5 bleeding.

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Development and external validation of a post-discharge bleeding risk score in patients with acute coronary syndrome: The BleeMACS score

Cited by 75 publications

References 32 publications

Risk Stratification in Patients with Coronary Artery Disease: a Practical Walkthrough in the Landscape of Prognostic Risk Models

Risk Stratification in Patients with Coronary Artery Disease: a Practical Walkthrough in the Landscape of Prognostic Risk Models

Bleeding risk factors in patients with acute coronary syndrome: data from observational studies ORACUL II

Contribution of ESC DAPT guideline-endorsed high thrombotic risk features to long-term clinical outcomes among patients with and without high bleeding risk after PCI

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