Angiographic Correlates of the Treadmill Scores in Non-High-Risk Patients with Unstable Angina

Cardiology ◽  
2007 ◽  
Vol 109 (1) ◽  
pp. 1-9 ◽  
Author(s):  
José A. Alvarez Tamargo ◽  
Eugenio Simarro Martín-Ambrosio ◽  
Enrique Romero Tarín ◽  
María Martín Fernández ◽  
Sergio Hevia Nava ◽  
...  
Keyword(s):  
High Risk ◽  
Unstable Angina ◽  
High Risk Patients ◽  
Risk Patients

Usefulness of Positive Troponin-T and Negative Creatine Kinase Levels in Identifying High-Risk Patients With Unstable Angina Pectoris

1997 ◽  
Vol 80 (4) ◽  
pp. 510-511 ◽  
Author(s):  
Trent L Pettijohn ◽  
Thomas Doyle ◽  
A. Michael Spiekerman ◽  
Linley E Watson ◽  
Mark W Riggs ◽  
...  
Keyword(s):  
Creatine Kinase ◽  
High Risk ◽  
Angina Pectoris ◽  
Unstable Angina ◽  
Troponin T ◽  
Unstable Angina Pectoris ◽  
High Risk Patients ◽  
Risk Patients

scholarly journals Identification of high-risk patients with unstable angina

1996 ◽  
Vol 27 (2) ◽  
pp. 332
Author(s):  
Giorgio Ghigliotti ◽  
Claudio Brunelli ◽  
Luca Corsiglia ◽  
Paolo Spallorossa ◽  
Alessandro Iannone ◽  
...  
Keyword(s):  
High Risk ◽  
Unstable Angina ◽  
High Risk Patients ◽  
Risk Patients

scholarly journals Prognostic Significance of the Number of Leads with ST Depression during an Anginal Attack in High Risk Patients with Unstable Angina.

2002 ◽  
Vol 41 (4) ◽  
pp. 270-276 ◽  
Author(s):  
Makoto SAITOH ◽  
Teruo KONDOH ◽  
Kyoko WAKAO ◽  
Kazuhisa KITAMURA ◽  
Shigeru NOMOTO ◽  
...  
Keyword(s):  
High Risk ◽  
Unstable Angina ◽  
Prognostic Significance ◽  
Anginal Attack ◽  
High Risk Patients ◽  
St Depression ◽  
Risk Patients

Abstract 334: Potential Risk Factors for Recurrent Coronary Revascularization and Hospitalization for Unstable Angina Following Acute Myocardial Infarction

2014 ◽  
Vol 7 (suppl_1) ◽  
Author(s):  
Kim Smolderen ◽  
Yan Li ◽  
David Cohen ◽  
Suzanne V Arnold ◽  
Phil G Jones ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
High Risk ◽  
Unstable Angina ◽  
Risk Score ◽  
Coronary Revascularization ◽  
High Risk Patients ◽  
Grace Risk Score ◽  
Increased Risk ◽  
Risk Patients

Background: Subsequent hospitalizations after acute myocardial infarction (AMI) for unstable angina (UA) and coronary revascularization represent common and important clinical events. While numerous studies sought to predict survival, AMI, and all-cause rehospitalization after AMI, there are limited data about how to best risk-stratify patients for UA and subsequent revascularization. Understanding these factors can support the development of more efficient AMI care. Methods: In the multi-center TRIUMPH registry, we used 3,283 patients with detailed baseline and 1-year follow-up information, including adjudicated hospitalizations, following initial AMI admission. An initial prediction model was derived after examining > 60 demographic, socio-economic, comorbidity, AMI severity, treatment, psychosocial and health status characteristics using hierarchical Cox Proportional Hazards for UA or revascularization. Staged PCIs and elective CABGs performed ≤1 month were excluded. Results: A total of 140 (4.3%) patients were readmitted ≤1 year for UA and 158 (4.8%) for revascularization. Independent predictors of UA were female sex (HR=1.88; 95%CI: 1.33, 2.65), prior PCI (HR=1.64; 95%CI: 1.12, 2.39), prior CABG (HR=2.06; 95%CI: 1.28, 3.32), and GRACE risk score (HR per 1 point increase=0.99; 95%CI: 0.98, 0.99). Independent predictors of revascularization were diseased vessels >1 (HR=2.50; 95%CI: 1.74, 3.60), and GRACE risk score (HR=0.99; 95%CI: 0.99, 1.00). While high-risk patients (those with diabetes, peripheral artery and cerebrovascular disease) were at increased risk of being readmitted for UA (HR=1.48; 95%CI 1.04, 2.10) or revascularization (HR=1.35; 95%CI: 0.97, 1.88), there was no interaction between these associations and risk status, suggesting equal prognostic significance in those with and without high-risk characteristics. Conclusion: Unique characteristics are associated with admissions for UA and revascularization. Creating multivariable models, risk scores and prospective risk stratification can support tailoring treatment to those at highest risk, although prospective studies are needed to establish the best management for high-risk patients.

Combination of norfloxacin and cisapride in prevention of SBP in high risk patients: A new approach

2001 ◽  
Vol 120 (5) ◽  
pp. A376-A376
Author(s):  
B JEETSANDHU ◽  
R JAIN ◽  
J SINGH ◽  
M JAIN ◽  
J SHARMA ◽  
...  
Keyword(s):  
High Risk ◽  
New Approach ◽  
High Risk Patients ◽  
Risk Patients

1610: High-Risk Patients Undergoing Radical Prostatectomy Today are Less High-Risk than in the Past

2005 ◽  
Vol 173 (4S) ◽  
pp. 436-436
Author(s):  
Christopher J. Kane ◽  
Martha K. Terris ◽  
William J. Aronson ◽  
Joseph C. Presti ◽  
Christopher L. Amling ◽  
...  
Keyword(s):  
High Risk ◽  
Radical Prostatectomy ◽  
High Risk Patients ◽  
The Past ◽  
Risk Patients

995: Immunohistochemical Analysis of Tumor Polyamines Discriminates High Risk Patients Undergoing Nephrectomy for Renal Cell Carcinoma

2004 ◽  
Vol 171 (4S) ◽  
pp. 263-263
Author(s):  
Nathalie Rioux-Leclercq ◽  
Florence Jouan ◽  
Pascale Bellaud ◽  
Jacques-Philippe Moulinoux ◽  
Karim Bensalah ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Immunohistochemical Analysis ◽  
High Risk Patients ◽  
Risk Patients
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