Risk adjustment for in-hospital mortality of contemporary patients with acute myocardial infarction: The Acute Coronary Treatment and Intervention Outcomes Network (ACTION) Registry®–Get With The Guidelines (GWTG)™ acute myocardial infarction mortality model and risk score

2011 ◽  
Vol 161 (1) ◽  
pp. 113-122.e2 ◽  
Author(s):  
Chee Tang Chin ◽  
Anita Y. Chen ◽  
Tracy Y. Wang ◽  
Karen P. Alexander ◽  
Robin Mathews ◽  
...  
2007 ◽  
Vol 35 (5) ◽  
pp. 590-596 ◽  
Author(s):  
K Hayashida ◽  
Y Imanaka ◽  
M Sekimoto ◽  
H Kobuse ◽  
H Fukuda

This study aimed to develop a new risk-adjustment method to assess acute myocardial infarction (AMI) in-hospital mortality. Risk-adjustment was based on variables obtained from administrative data from Japanese hospitals, and included factors such as age, gender, primary diagnosis and co-morbidity. The infarct location was determined using the criteria of the International Classification of Diseases (10th version). Potential co-morbidity risk factors for mortality were selected based on previous studies and their critical influence analysed to identify major co-morbidities. The remaining minor co-morbidities were then divided into two groups based on their medical implications. The major co-morbidities included shock, pneumonia, cancer and chronic renal failure. The two minor co-morbidity groups also demonstrated a substantial impact on mortality. The model was then used to assess clinical performance in the participating hospitals. Our model reliably employed the available data for the risk-adjustment of AMI mortality and provides a new approach to evaluating clinical performance.


2013 ◽  
Vol 34 (suppl 1) ◽  
pp. P1207-P1207
Author(s):  
A. Gudjoncik ◽  
S. Richet ◽  
A. Derrou ◽  
J. Hamblin ◽  
L. Mock ◽  
...  

BMJ Open ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. e030772 ◽  
Author(s):  
Chenxi Song ◽  
Rui Fu ◽  
Sidong Li ◽  
Jingang Yang ◽  
Yan Wang ◽  
...  

ObjectivesTo simplify our previous risk score for predicting the in-hospital mortality risk in patients with non-ST-segment elevation myocardial infarction (NSTEMI) by dropping laboratory data.DesignProspective cohort.SettingMulticentre, 108 hospitals across three levels in China.ParticipantsA total of 5775 patients with NSTEMI enrolled in the China Acute Myocardial Infarction (CAMI) registry.Primary outcome measuresIn-hospital mortality.ResultsThe simplified CAMI-NSTEMI (SCAMI-NSTEMI) score includes the following nine variables: age, body mass index, systolic blood pressure, Killip classification, cardiac arrest, ST-segment depression on ECG, smoking status, previous angina and previous percutaneous coronary intervention. Within both the derivation and validation cohorts, the SCAMI-NSTEMI score showed a good discrimination ability (C-statistics: 0.76 and 0.83, respectively); further, the SCAMI-NSTEMI score had a diagnostic performance superior to that of the Global Registry of Acute Coronary Events risk score (C-statistics: 0.78 and 0.73, respectively; p<0.0001 for comparison). The in-hospital mortality increased significantly across the different risk groups.ConclusionsThe SCAMI-NSTEMI score can serve as a useful tool facilitating rapid risk assessment among a broader spectrum of patients admitted owing to NSTEMI.Trial registration numberNCT01874691.


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.


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