scholarly journals Addition of routine blood biomarkers to TIMI risk score improves predictive performance of 1-year mortality in patients with ST-segment elevation myocardial infarction

2020 ◽  
Author(s):  
Pyung Chun Oh ◽  
Young Sil Eom ◽  
Jeonggeun Moon ◽  
Ho-Jun Jang ◽  
Tae-Hoon Kim ◽  
...  

Abstract Background: Several biomarkers have been proposed as independent predictors of poor outcomes in ST-segment elevation myocardial infarction (STEMI). We investigated whether adding information obtained from routine blood tests including hypoxic liver injury (HLI), dysglycemia, anemia, and high neutrophil to lymphocyte ratio (NLR) could improve the prognostic performance of the TIMI risk score for the prediction of 1-year mortality. Methods: A total of 1057 patients with STEMI undergoing primary percutaneous coronary intervention (PCI) between 2007 and 2014 were retrospectively enrolled from 4-regional hospitals. HLI and dysglycemia were defined as serum transaminase >twice the normal upper limit and glucose <90 or >250 mg/dL, respectively. The effect of adding biomarkers to the TIMI risk score on its discriminative ability was assessed using c-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: The 1-year mortality rate was 7.1%. The best cutoff value of NLR for the prediction of 1-year mortality was 4.3 (sensitivity, 67%; specificity, 65%). HLI (HR, 2.019; 95% CI, 1.104-3.695), dysglycemia (HR, 2.535; 95% CI, 1.324-3.923), anemia (HR, 2.071; 95% CI, 1.093-3.923), and high NLR (HR, 3.651; 95% CI, 1.927-6.918) were independent predictors of 1-year mortality. When these 4 parameters were added to the TIMI risk score, the c-statistic significantly improved from 0.841 to 0.876 (p<0.001), and the NRI and IDI were estimated at 0.203 (95% CI, 0.130-0.275; p<0.001) and 0.089 (95% CI, 0.060-0.119; p<0.001), respectively. Conclusions: The addition of HLI, dysglycemia, anemia, and high NLR to the TIMI risk score may be useful for very early risk stratification in patients with STEMI receiving primary PCI.

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Pyung Chun Oh ◽  
Young Sil Eom ◽  
Jeonggeun Moon ◽  
Ho-Jun Jang ◽  
Tae-Hoon Kim ◽  
...  

Abstract Background Several biomarkers have been proposed as independent predictors of poor outcomes in ST-segment elevation myocardial infarction (STEMI). We investigated whether adding information obtained from routine blood tests including hypoxic liver injury (HLI), dysglycemia, anemia, and high neutrophil to lymphocyte ratio (NLR) could improve the prognostic performance of the TIMI risk score for the prediction of 1-year mortality. Methods A total of 1057 patients with STEMI undergoing primary percutaneous coronary intervention (PCI) between 2007 and 2014 were retrospectively enrolled from 4-regional hospitals. HLI and dysglycemia were defined as serum transaminase > twice the normal upper limit and glucose < 90 or > 250 mg/dL, respectively. The effect of adding biomarkers to the TIMI risk score on its discriminative ability was assessed using c-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results The 1-year mortality rate was 7.1%. The best cutoff value of NLR for the prediction of 1-year mortality was 4.3 (sensitivity, 67%; specificity, 65%). HLI (HR 2.019; 95% CI 1.104–3.695), dysglycemia (HR 2.535; 95% CI 1.324–3.923), anemia (HR 2.071; 95% CI 1.093–3.923), and high NLR (HR 3.651; 95% CI 1.927–6.918) were independent predictors of 1-year mortality. When these 4 parameters were added to the TIMI risk score, the c-statistic significantly improved from 0.841 to 0.876 (p < 0.001), and the NRI and IDI were estimated at 0.203 (95% CI 0.130–0.275; p < 0.001) and 0.089 (95% CI 0.060–0.119; p < 0.001), respectively. Conclusions The addition of HLI, dysglycemia, anemia, and high NLR to the TIMI risk score may be useful for very early risk stratification in patients with STEMI receiving primary PCI.


2020 ◽  
Author(s):  
Pyung Chun Oh ◽  
Young Sil Eom ◽  
Jeonggeun Moon ◽  
Ho-Jun Jang ◽  
Tae-Hoon Kim ◽  
...  

Abstract Background: Several biomarkers have been proposed as independent predictors of poor outcomes in ST-segment elevation myocardial infarction (STEMI). We investigated whether adding information obtained from routine blood tests including hypoxic liver injury (HLI), dysglycemia, anemia, and high neutrophil to lymphocyte ratio (NLR) could improve the prognostic performance of the TIMI risk score for the prediction of 1-year mortality. Methods: A total of 1057 patients with STEMI undergoing primary percutaneous coronary intervention (PCI) between 2007 and 2014 were retrospectively enrolled from 4-regional hospitals. HLI and dysglycemia were defined as serum transaminase >twice the normal upper limit and glucose <90 or >250 mg/dL, respectively. The effect of adding biomarkers to the TIMI risk score on its discriminative ability was assessed using c-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: The 1-year mortality rate was 7.1%. The best cutoff value of NLR for the prediction of 1-year mortality was 4.3 (sensitivity, 67%; specificity, 65%). HLI (HR, 2.019; 95% CI, 1.104-3.695), dysglycemia (HR, 2.535; 95% CI, 1.324-3.923), anemia (HR, 2.071; 95% CI, 1.093-3.923), and high NLR (HR, 3.651; 95% CI, 1.927-6.918) were independent predictors of 1-year mortality. When these 4 parameters were added to the TIMI risk score, the c-statistic significantly improved from 0.841 to 0.876 (p<0.001), and the NRI and IDI were estimated at 0.203 (95% CI, 0.130-0.275; p<0.001) and 0.089 (95% CI, 0.060-0.119; p<0.001), respectively. Conclusions: The addition of HLI, dysglycemia, anemia, and high NLR to the TIMI risk score may be useful for very early risk stratification in patients with STEMI receiving primary PCI.


2020 ◽  
Author(s):  
Pyung Chun Oh ◽  
Young Sil Eom ◽  
Jeonggeun Moon ◽  
Ho-Jun Jang ◽  
Tae-Hoon Kim ◽  
...  

Abstract Background: Several biomarkers have been proposed as independent predictors of poor outcomes in ST-segment elevation myocardial infarction (STEMI). We investigated whether adding information obtained from routine blood tests including hypoxic liver injury (HLI), dysglycemia, anemia, and high neutrophil to lymphocyte ratio (NLR) could improve the prognostic performance of the TIMI risk score for the prediction of 1-year mortality. Methods: A total of 1057 patients with STEMI undergoing primary percutaneous coronary intervention (PCI) between 2007 and 2014 were retrospectively enrolled from 4-regional hospitals. HLI and dysglycemia were defined as serum transaminase >twice the normal upper limit and glucose <90 or >250 mg/dL, respectively. The effect of adding biomarkers to the TIMI risk score on its discriminative ability was assessed using c-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: The 1-year mortality rate was 7.1%. The best cutoff value of NLR for the prediction of 1-year mortality was 4.3 (sensitivity, 67%; specificity, 65%). HLI (HR, 2.019; 95% CI, 1.104-3.695), dysglycemia (HR, 2.535; 95% CI, 1.324-3.923), anemia (HR, 2.071; 95% CI, 1.093-3.923), and high NLR (HR, 3.651; 95% CI, 1.927-6.918) were independent predictors of 1-year mortality. When these 4 parameters were added to the TIMI risk score, the c-statistic significantly improved from 0.841 to 0.876 (p<0.001), and the NRI and IDI were estimated at 0.203 (95% CI, 0.130-0.275; p<0.001) and 0.089 (95% CI, 0.060-0.119; p<0.001), respectively. Conclusions: The addition of HLI, dysglycemia, anemia, and high NLR to the TIMI risk score may be useful for very early risk stratification in patients with STEMI receiving primary PCI.


Author(s):  
Victor Marcos-Garces ◽  
Jose Gavara ◽  
Maria P. Lopez-Lereu ◽  
Jose V. Monmeneu ◽  
Cesar Rios-Navarro ◽  
...  

Background Cardiac magnetic resonance (CMR) permits robust risk stratification of discharged ST-segment–elevation myocardial infarction patients, but its indiscriminate use in all cases is not feasible. We evaluated the utility of left ventricular ejection fraction (LVEF) by echocardiography for a selective use of CMR after ST-segment–elevation myocardial infarction. Methods Echocardiography and CMR were performed in 1119 patients discharged for ST-segment–elevation myocardial infarction included in a multicenter registry. The prognostic power of CMR beyond echocardiography-LVEF was assessed using adjusted C statistic, net reclassification improvement index, and integrated discrimination improvement index. Results During a 4.8-year median follow-up, 136 (12%) first major adverse cardiac events (MACE) occurred (47 cardiovascular deaths and 89 readmissions for acute heart failure). In the entire group, CMR-LVEF (but not echocardiography-LVEF) independently predicted MACE occurrence. The MACE rate significantly increased only in patients with CMR-LVEF<40% (≥50%: 7%, 40%–49%: 9%, <40%: 27%, P <0.001). Most patients displayed echocardiography-LVEF≥50% (629, 56%), and they had a low MACE rate (57/629, 9%). In patients with echocardiography-LVEF<50% (n=490, 44%), the MACE rate was also low in those with CMR-LVEF≥40% (24/278, 9%) but significantly increased in patients with CMR-LVEF<40% (55/212, 26%; P <0.001). Compared with echocardiography-LVEF, CMR-LVEF significantly improved MACE prediction in the group of patients with echocardiography-LVEF<50% (C statistic, 0.80 versus 0.72; net reclassification improvement index, 0.73; integrated discrimination improvement index, 0.10) but not in those with echocardiography-LVEF≥50% (C statistic 0.66 versus 0.66; net reclassification improvement index, 0.17; integrated discrimination improvement index, 0.01). Conclusions A straightforward strategy based on a selective use of CMR for risk prediction in ST-segment–elevation myocardial infarction patients with echocardiography-LVEF<50% can provide insights into patient care. The cost-effectiveness of this approach, as well as the direct implications in clinical management, should be further explored.


2008 ◽  
Vol 10 (1) ◽  
pp. 26-29 ◽  
Author(s):  
Anne Vorlat ◽  
Marc J. Claeys ◽  
Herbert De Raedt ◽  
Sofie Gevaert ◽  
Yves Vandekerckhove ◽  
...  

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Song-jian He ◽  
Jian-xin Weng ◽  
Hai-jun Chen ◽  
Hua-qiu Li ◽  
Wen-qin Guo ◽  
...  

Abstract Background The model for end-stage liver disease excluding international normalized ratio (MELD-XI) is a simple score for risk assessment. However, the prognostic role of MELD-XI and its additional value to current risk assessment in elderly patients with ST-segment elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention (PCI) is uncertain. Methods In all, 1029 elderly patients with STEMI undergoing PCI were consecutively included and classified into three groups according to the TIMI risk score: low-risk (≤ 3, n = 251); moderate-risk (4–6, n = 509); and high-risk (≥ 7, n = 269) groups. Multivariate analysis was performed to identify risk factors for adverse events. Results The overall in-hospital mortality was 5.3% and was significantly higher in the high-risk group (1.2% vs. 3.3% vs. 13.0%, p < 0.001). The optimal cut-off of the TIMI risk score and MELD-XI for in-hospital death was 7 and 13, respectively. MELD-XI was associated with in-hospital (adjusted odds ratio = 1.09, 95% CI = 1.04–1.14, p = 0.001) and one-year (adjusted hazard ratio = 1.05, 95% CI = 1.01–1.08, p = 0.005) mortality independently of the TIMI risk score. Combining TIMI risk score and MELD-XI exhibited better predictive power for in-hospital death than TIMI risk score (area under the curve [AUC] = 0.810 vs. 0.753, p = 0.008) or MELD-XI alone (AUC = 0.810 vs. 0.750, p = 0.018). Patients with TIMI risk score ≥ 7 and MELD-XI ≥ 13 had the worst prognosis. Conclusion MELD-XI could be considered as a risk-stratified tool for elderly patients with STEMI undergoing PCI. It had an additive prognostic value to TIMI risk score.


PLoS ONE ◽  
2012 ◽  
Vol 7 (7) ◽  
pp. e40249 ◽  
Author(s):  
Sharmini Selvarajah ◽  
Alan Yean Yip Fong ◽  
Gunavathy Selvaraj ◽  
Jamaiyah Haniff ◽  
Cuno S. P. M. Uiterwaal ◽  
...  

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