Most studies indicated that low on-treatment platelet reactivity ( LTPR ) , as measured by several platelet function tests , and the carriage of CYP2C19 * 17 allele were independent risk factors for bleeding .
A bleeding score also proved to be helpful in identifying patients at risk .
Several patient characteristics were also identified as independent predictors of bleeding , such as older age , female sex and renal failure .
Patients with coronary artery disease are usually treated with dual antiplatelet therapy ( DAPT ) after percutaneous coronary intervention .
Patients on DAPT are at risk of both ischaemic and bleeding events .
Although side-lined for a long time , real-life studies have shown that both the incidence and the associated morbidity and mortality of out-of-hospital bleeding are high .
This indicates that prevention of ( post-interventional ) bleeding is as important as prevention of ischaemia .
For this purpose it is crucial to reliably identify patients with a high bleeding risk .
In order to postulate an algorithm , which could help identifying these patients , we performed a systematic review to determine the value of previously proposed prognostic modalities for bleeding .
Simple risk algorithm to predict serious bleeding in patients with ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention: RISK-PCI bleeding score.
BACKGROUND Bleeding is a potentially catastrophic complication after primary percutaneous coronary intervention ( PPCI ) . It occurs most frequently within the first 30 days following the intervention . The aim of this study was to generate a simple and accurate risk model for the prediction of bleeding after PPCI . METHODS AND RESULTS The training set included 2,096 patients enrolled in the RISK-PCI trial . The model was vali date d using a data base of 961 patients enrolled in the ART-PCI trial .  Bleeding was defined as type ≥3a bleeding according to the Bleeding Academic Research Consortium definition . Multivariate logistic regression was used to evaluate the predictors of outcome . A sum of weighted points for specific predictors was calculated to determine the final score . The model included 5 independent predictors of 30-day bleeding : gender ( female ) ; history of peptic ulcer ; creatinine clearance at admission ( < 60 ml/min ) ; hemoglobin at presentation ( < 125 g/dl ) ; and Killip class > 1 heart failure at admission . The model showed good discrimination and calibration for the prediction of bleeding in the derivation set ( C-statistic , 0.79 ; goodness of fit , P=0.12 ) and in the validation set ( C-statistic , 0.76 ; goodness of fit , P=0.37 ) . Patients were classified into 3 risk classes and the observed incidence of 30-day bleeding of 1.0 % , 3.5 % and 10.7 % corresponded to the low- , intermediate- and high-risk classes , respectively . CONCLUSIONS A simple risk model was developed that has a reasonably good capacity for the prediction of 30-day bleeding after PPCI
Most studies indicated that low on-treatment platelet reactivity ( LTPR ) , as measured by several platelet function tests , and the carriage of CYP2C19 * 17 allele were independent risk factors for bleeding .
A bleeding score also proved to be helpful in identifying patients at risk .
Several patient characteristics were also identified as independent predictors of bleeding , such as older age , female sex and renal failure .
Patients with coronary artery disease are usually treated with dual antiplatelet therapy ( DAPT ) after percutaneous coronary intervention .
Patients on DAPT are at risk of both ischaemic and bleeding events .
Although side-lined for a long time , real-life studies have shown that both the incidence and the associated morbidity and mortality of out-of-hospital bleeding are high .
This indicates that prevention of ( post-interventional ) bleeding is as important as prevention of ischaemia .
For this purpose it is crucial to reliably identify patients with a high bleeding risk .
In order to postulate an algorithm , which could help identifying these patients , we performed a systematic review to determine the value of previously proposed prognostic modalities for bleeding .