P845Comparison of the performance of the five validated risk scores in acute myocardial infarction patients undergoing primary PCI

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
Z Mehmedbegovic ◽  
D Milasinovic ◽  
D Jelic ◽  
V Zobenica ◽  
V Dedovic ◽  
...  

Abstract Background Several risk scores have been developed to predict mortality of patients with acute myocardial infarction (AMI) undergoing primary percutaneous coronary intervention (pPCI), with limited data on the comparative prognostic value of these models. Purpose We aimed to compare the prognostic value of five validated risk scores for in-hospital and one-year mortality of patients with AMI undergoing pPCI. ume catheterization laboratory in a period from January 2009 to December 2017, a total of 3868 consecutive patients who underwent pPCI were available for analysis. For each patient, the Thrombolysis In Myocardial Infarction (TIMI), Controlled Abciximab and Device Investigation to Lower Late Angioplasty complications (CADILLAC), ACTION Registry-GWTG in-hospital mortality risk score (ACTION), Age, Creatinine, and Ejection Fraction (ACEF), and ZWOLLE risk scores were calculated using required clinical and angiographic characteristics. In-hospital and one-year mortality were assessed (follow-up available for 92% of pts). Calibration and discrimination of the three risk models were evaluated by the Hosmer-Lemeshow (H-L) goodness-of-fit test and C-statistic, respectively. Results Mortality rates for in-hospital and one-year mortality were 1.8% and 6.9% respectively. All five scores showed good model calibration as assessed by the H-L test and very good discriminative power for in-hospital and one-year mortality as assessed by C-statistics (Table 1 & Figure 1): Table 1 Risk score H-L H-L p AUC in-hospital 95% CI Significant p AUC one-year 95% CI Significant p ZWOLLE 1.3 0.7 0.90 0.89–0.91 vs. CADILLAC <0.05 0.75 0.74–0.77 vs. TIMI <0.005 ACTION 13.1 0.1 0.87 0.86–0.88 vs. TIMI <0.005 0.79 0.77–0.80 CADILLAC 5.5 0.2 0.85 0.84–0.86 vs. TIMI <0.01 0.81 0.80–0.83 vs. ZWOLLE <0.000 vs. TIMI <0.000 ACEF 9.9 0.3 0.814 0.83–0.85 0.80 0.78–0.81 vs. ZWOLLE <0.000 vs. TIMI <0.05 TIMI 7.1 0.3 0.79 0.78–0.80 0.76 0.75–0.78 Figure 1 Conclusion Risk stratification of patients with AMI undergoing pPCI using the ZWOLLE, ACTION, CADILLAC, ACEF or TIMI risk scores enables accurate identification of high-risk patients for in-hospital and one-year mortality in an all-comers population. Among evaluated scores, ZWOLLE model was better fitted for prediction of in-hospital mortality while CADILLAC and ACEF better predicted late events.

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
D Jelic ◽  
Z Mehmedbegovic ◽  
D Milasinovic ◽  
V Dedovic ◽  
V Zobenica ◽  
...  

Abstract Background The Acute Coronary Treatment and Intervention Outcomes Network (ACTION) Registry-Get With The Guidelines (GWTG) AMI mortality model and risk score (ACTION) were introduced in 2011 to predict in-hospital mortality. In 2016 score was updated to enable a more accurate assessment, but, up-to-date, external validation in direct comparison was not performed. Purpose We aimed to externally validate and compare the prognostic value of original and updated ACTION score for in-hospital and one-year mortality. Method From a prospective electronic registry of a high-volume catheterization laboratory in a period from January 2009 to December 2017, a total of 5615 consecutive patients who underwent pPCI were available for analysis. For each patient, original (O-) and updated (U-) ACTION scores were calculated using required clinical and angiographic characteristics. In-hospital and one-year mortality (follow-up available for 91%) were assessed. Calibration and discrimination of the three risk models were evaluated by the Hosmer-Lemeshow (H-L) goodness-of-fit test and C-statistic, respectively. Results Mortality rates for in-hospital and one-year mortality were 4.2% and 9.6%, respectively. Both scores showed good model calibration as assessed by the H-L test and very good discriminative power for in-hospital and one-year mortality as assessed by C-statistics (Table 1 & Figure 1). Net reclassification index (NRI=1.06) showed that 48% of patients with in-hospital event and 58% without event, had their risk recalculated with U-ACTION with Integrated Discrimination Improvement slope 9.1% higher than in first model. Table 1 Risk score H-L H-L p value AUC 95% CI p value AUC 95% CI Significant p value O-ACTION 9.4 0.3 0.829 0.819 to 0.839 p<0.0001 0.781 0.769 to 0.792 p<0.0001 U-ACTION 10.9 0.2 0.918 0.911 to 0.925 0.838 0.827 to 0.848 Figure 1 Conclusion Updated ACTION score enables better prediction of in-hospital and one-year mortality in patients undergoing pPCI for acute myocardial infarction, thus it can be used preferentially over the original ACTION score for assessment of short and long-term mortality risks of this population.


2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
Z Mehmedbegovic ◽  
D Milasinovic ◽  
D Jelic ◽  
V Zobenica ◽  
D Matic ◽  
...  

Abstract Background Considering clinical importance of bleeding complications in patients with acute myocardial infarction (AMI), bleeding risk stratification is a key part of the management of these patients. CRUSADE, ACTION and ACUITY-HORIZONS bleeding risk scores are available for predicting in-hospital major bleeding events in patients with acute myocardial infarction. Purpose We aimed to evaluate performance of the three above mentioned risk scores for predicting in-hospital bleeding events defined according to The Bleeding Academic Research Consortium (BARC) criteria. Methods From a prospective electronic registry of a high-volume catheterization laboratory in a period from January 2009 to December 2017, a total of 6505 consecutive patients with acute myocardial infarction who underwent pPCI were included in analysis. Calibration and discrimination of the three risk models were evaluated by the Hosmer-Lemeshow (H-L) goodness-of-fit test and C-statistic, respectively. Results Overall there were 372 (5.7%) bleeding events out of which 117 (1.8%) fulfilled stage BARC 3 or higher bleeding criteria. All three scores showed good model calibration as assessed by the H-Ls test and very good discriminative power for BARC 3 of higher bleeding events detection as assessed by C-statistics (Table 1 & Figure 1): Bleeding events stage BARC 3 or higher were statistically highly related with higher in-hospital mortality (13.7% vs. 3.5%; p<0.000). Table 1 Risk score H-L H-L p AUC 95% CI p CRUSADE 11.46 0.177 0.761 0.750–0.771 vs. ACUITY = ns vs. ACTION <0.000 ACUITY-HORIZONS 10.47 0.236 0735 0.724–0.745 vs. ACTION = ns ACTION 5.74 0.677 0.701 0.698–0.712 Figure 1 Conclusions All three evaluated scores showed very good discriminative capacity for predicting BARC 3 or higher bleeding events in patients undergoing pPCI for AMI.


Author(s):  
D. V. Zhehestovska ◽  
◽  
M. V. Hrebenyk ◽  

Among the tools presented today for predicting the risk of death from acute myocardial infarction (AMI) the most popular one is GRACE risk score. Along with it, due to the improvement of the prognostic value of the score, a number of parameters are displayed, the main features of which are the availability and ease of interpretation on early stages of hospitalization. The most promising among those are leukocyte parameters. While most studies evaluate the long-term prognosis of AMI, our work focused on potential precursors of in-hospital events. Among 228 patients diagnosed with AMI, 18 died at the hospital. They had a significantly higher GRACE and Gensini scores (p < 0.001). Also, patients of this group had s higher levels of leukocytes, granulocytes, lymphocytes and the neutrophil to lymphocyte ratio (NLR) (p < 0,05). According to the regression analysis, the NLR index along with GRACE was strongly connected to in-hospital mortality (OR = 1,364, 95 % CI 1,119-1,664, p = 0.002). To determine the prognostic value of these indicators, ROC analysis was performed. When evaluating the sensitivity (Se) and specificity (Sp) of parameters, the following results were obtained: GRACE score (Se = 80.0 %, Sp = 77.8 %, AUC 0.854), NLR (Se = 73.3 %, Sp = 73, 4 %, AUC 0.758), GRACE + NLR (Se = 80.0 %, Sp = 84.1 %, AUC 0.91). Thus, the combination of the GRACE risk score and NLR is more effective for predicting in-hospital mortality among patients with AMI.


Author(s):  
Christos Iliadis ◽  
Maximilian Spieker ◽  
Refik Kavsur ◽  
Clemens Metze ◽  
Martin Hellmich ◽  
...  

Abstract Background Reliable risk scores in patients undergoing transcatheter edge-to-edge mitral valve repair (TMVR) are lacking. Heart failure is common in these patients, and risk scores derived from heart failure populations might help stratify TMVR patients. Methods Consecutive patients from three Heart Centers undergoing TMVR were enrolled to investigate the association of the “Get with the Guidelines Heart Failure Risk Score” (comprising the variables systolic blood pressure, urea nitrogen, blood sodium, age, heart rate, race, history of chronic obstructive lung disease) with all-cause mortality. Results Among 815 patients with available data 177 patients died during a median follow-up time of 365 days. Estimated 1-year mortality by quartiles of the score (0–37; 38–42, 43–46 and more than 46 points) was 6%, 10%, 23% and 30%, respectively (p < 0.001), with good concordance between observed and predicted mortality rates (goodness of fit test p = 0.46). Every increase of one score point was associated with a 9% increase in the hazard of mortality (95% CI 1.06–1.11%, p < 0.001). The score was associated with long-term mortality independently of left ventricular ejection fraction, NYHA class and NTproBNP, and was equally predictive in primary and secondary mitral regurgitation. Conclusion The “Get with the Guidelines Heart Failure Risk Score” showed a strong association with mortality in patients undergoing TMVR with additive information beyond traditional risk factors. Given the routinely available variables included in this score, application is easy and broadly possible. Graphic abstract


2015 ◽  
pp. 142-158 ◽  
Author(s):  
Marek Gierlotka ◽  
Tomasz Zdrojewski ◽  
Bogdan Wojtyniak ◽  
Lech Poloński ◽  
Jakub Stokwiszewski ◽  
...  

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