Almanac 2012: Cardiovascular risk scores. The national society journals present selected research that has driven recent advances in clinical cardiology

Hellenic Journal of Cardiology

Volumn 53, Issue 6, 2012, Pages 412-419

  Pell, Jill P ^a  

^a UNIVERSITY OF GLASGOW   (United Kingdom)

Author keywords

Defibrillation; Epidemiology; Obstetrics; Public health

Indexed keywords

1 ALKYL 2 ACETYLGLYCEROPHOSPHOCHOLINE ESTERASE; ADIPONECTIN; ANTIHYPERTENSIVE AGENT; ARYLDIALKYLPHOSPHATASE; BIOLOGICAL MARKER; BRAIN NATRIURETIC PEPTIDE; C REACTIVE PROTEIN; CALCIUM; COPEPTIN; CYSTATIN C; ENDOTHELIN 1; FIBRINOGEN; GLUCOSE; MYELOPEROXIDASE; NEUTROPHIL GELATINASE ASSOCIATED LIPOCALIN; PROADRENOMEDULLIN; SECRETORY PHOSPHOLIPASE A2; SODIUM; TROPONIN I;

ACUTE CORONARY SYNDROME; ANGIOGRAPHY; ARTICLE; BLOOD VESSEL INJURY; CARDIOVASCULAR PROCEDURE; CARDIOVASCULAR RISK; CAROTID ATHEROSCLEROSIS; CHRONIC OBSTRUCTIVE LUNG DISEASE; COHORT ANALYSIS; COMPUTER ASSISTED TOMOGRAPHY; CORONARY ARTERY BYPASS GRAFT; COST EFFECTIVENESS ANALYSIS; DIABETES MELLITUS; DRUG ELUTING STENT; FAMILY HISTORY; GENETIC MARKER; HEART ATRIUM FIBRILLATION; HEART FAILURE; HEART INFARCTION; HEART RATE; HUMAN; IMPLANTABLE CARDIOVERTER DEFIBRILLATOR; ISCHEMIC HEART DISEASE; NON INSULIN DEPENDENT DIABETES MELLITUS; NON ST SEGMENT ELEVATION MYOCARDIAL INFARCTION; RACE; SCORING SYSTEM; SENSITIVITY AND SPECIFICITY; SOCIOECONOMICS; ST SEGMENT ELEVATION MYOCARDIAL INFARCTION; SYSTEMATIC REVIEW (TOPIC); SYSTOLIC DYSFUNCTION; UREA NITROGEN BLOOD LEVEL;

BIOLOGICAL MARKERS; BIOMEDICAL RESEARCH; CARDIOVASCULAR DISEASES; HUMANS; RISK ASSESSMENT;

EID: 84870498157     PISSN: 11099666     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (43)

1. Parkes G. Predicting cardiovascular risk. Using risk scores with patients. BMJ. 2010; 340: c3327.
2. Cooper A, Nherera L, Calvert N, et al. Clinical Guidelines and Evidence Review for Lipid Modification: Cardiovascular Risk Assessment and the Primary and Secondary Prevention of Cardiovascular Disease. London: National Collaborating Centre for Primary Care and Royal College of General Practitioners, 2008.
3. Tunstall-Pedoe H. Cardiovascular Risk and Risk Scores: ASSIGN, Framingham, QRISK and others: how to choose. Heart. 2011; 97: 442-444.
4. de la Iglesia B, Potter JF, Poulter NR, Robins MM, Skinner J. Performance of the ASSIGN cardiovascular disease risk score on a UK cohort of patients from general practice. Heart. 2011; 97: 491-499.
5. Collins GS, Altman DG. An independent and external vali-dation of QRISK2 cardiovascular disease risk score: a prospective open cohort study. BMJ. 2010; 340: c3442.
6. Sheridan SL, Crespo E. Does the routine use of global coro-nary heart disease risk scores translate into clinical benefits or harms? A systematic review of the literature. BMC Health Serv Res. 2008; 8: 60.
7. Liew SM, Doust J, Glasziou P. Cardiovascular risk scores donot account for the effect of treatment: a review. Heart. 2011;97: 689-697.
8. Hippisley-Cox J, Coupland C, Robson J, Brindle P. Derivation, validation, and evaluation of a new QRISK model to es-timate lifetime risk of cardiovascular disease: cohort study using QResearch database. BMJ. 2010; 341: c6624.
9. Bueno H, Fernández-Avilés F. Use of risk scores in acutecoronary syndromes. Heart. 2012; 98: 162-168.
10. Fox KA, Eagle KA, Gore JM, Steg PG, Anderson FA; GRACE and GRACE2 Investigators. The Global Registry ofacute coronary events, 1999 to 2009 - GRACE. Heart. 2010; 96: 1095-1101.
11. O'Connor CM, Whellan DJ, Wojdyla D, et al. Factors relat-ed to morbidity and mortality in patients with chronic heartfailure with systolic dysfunction: the HF-ACTION predictive risk score model. Circ Heart Fail. 2012; 5: 63-71.
12. Peterson PN, Rumsfeld JS, Liang L, et al. A validated riskscore for in-hospital mortality in patients with heart failurefrom the American Heart Association get with the guidelines program. Circ Cardiovasc Qual Outcomes. 2010; 3: 25-32.
13. Van Dieren S, Beulens JW, Kengne AP, et al. Predictionmodels for the risk of cardiovascular disease in patients with type 2 diabetes: a systematic review. Heart. 2012; 98: 360-369.
14. Melander O, Newton-Cheh C, Almgren P, et al. Novel andconventional biomarkers for prediction of incident cardiovascular events in the community. JAMA. 2009; 302: 49-57.
15. Rana JS, Cote M, Després JP, et al. Inflammatory biomark-ers and the prediction of coronary events among people at intermediate risk: the EPIC-Norfolk prospective population study. Heart. 2009; 95: 1682-1687.
16. Zethelius B, Berglund L, Sundström J, et al. Use of multiple biomarkers to improve the prediction of death from cardiovascular causes. N Engl J Med. 2008; 358: 2107-2116.
17. Lorgis L, Zeller M, Dentan G, et al. Prognostic value of N-terminal pro-brain natriuretic peptide in elderly people with acute myocardial infarction: prospective observational study. BMJ. 2009; 338: b1605.
18. Lorgis L, Cottin Y, Danchin N, et al. Impact of obesity onthe prognostic value of the N-terminal pro-B-type natriureticpeptide (NT-proBNP) in patients with acute myocardial infarction. Heart. 2011; 97: 551-556.
19. Tello-Montoliu A, Marín F, Roldán V, Lip GY. The additivevalue of biomarkers to clinical risk scores in acute coronarysyndrome. Are biomarkers really ready for real world usage? Heart. 2010; 96: 227-8; author reply 228.
20. Damman P, Beijk MA, Kuijt WJ, et al. Multiple biomarkersat admission significantly improve the prediction of mortality in patients undergoing primary percutaneous coronary intervention for acute ST-segment elevation myocardial infarction. J Am Coll Cardiol. 2011; 57: 29-36.
21. Brugts JJ, Akin S, Helming AM, Loonstra S, van den Bos EJ, Kofflard MJ. The predictive value of cardiac biomarkers inprognosis and risk stratification of patients with atrial fibrillation. Curr Opin Cardiol. 2011; 26: 449-456.
22. Avellino A, Collins SP, Fermann GJ. Risk stratification andshort-term prognosis in acute heart failure syndromes: a review of novel biomarkers. Biomarkers. 2011; 16: 379-392.
23. Smith JG, Newton-Cheh C, Almgren P, et al. Assessmentof conventional cardiovascular risk factors and multiple biomarkers for the prediction of incident heart failure and atrial fibrillation. J Am Coll Cardiol. 2010; 56: 1712-1719.
24. Ketchum ES, Levy WC. Multivariate risk scores and patient outcomes in advanced heart failure. Congest Heart Fail. 2011; 17: 205-212.
25. Haines DE, Wang Y, Curtis J. Implantable cardioverter-defibrillator registry risk score models for acute procedural complications or death after implantable cardioverter-defibrillator implantation. Circulation. 2011; 123: 2069-2076.
26. Wilson SR, Lin FY, Min JK. Role of coronary artery calcium score and coronary CT angiography in the diagnosis and risk stratification of individuals with suspected coronary artery disease. Curr Cardiol Rep. 2011; 13: 271-279.
27. Xie W, Liang L, Zhao L, et al. Combination of carotid intima-media thickness and plaque for better predicting risk ofischaemic cardiovascular events. Heart. 2011; 97: 1326-1331.
28. Henriksson M, Palmer S, Chen R, et al. Assessing the costeffectiveness of using prognostic biomarkers with decisionmodels: case study in prioritising patients waiting for coronary artery surgery. BMJ. 2010; 340: b5606.
29. Ripatti S, Tikkanen E, Orho-Melander M, et al. A multilocusgenetic risk score for coronary heart disease: case-control andprospective cohort analyses. Lancet. 2010; 376: 1393-1400.
30. Paynter NP, Chasman DI, Paré G, et al. Association between a literature-based genetic risk score and cardiovascular events in women. JAMA. 2010; 303: 631-637.
31. Qi L, Ma J, Qi Q, Hartiala J, Allayee H, Campos H. Geneticrisk score and risk of myocardial infarction in Hispanics. Circulation. 2011; 123: 374-380.
32. Thanassoulis G, Peloso GM, Pencina MJ, et al. A genetic riskscore is associated with incident cardiovascular disease and coronary artery calcium: the Framingham Heart Study. Circ Cardiovasc Genet. 2012; 5: 113-121.
33. Farooq V, Brugaletta S, Serruys PW. Utilizing risk scores indetermining the optimal revascularization strategy for complexcoronary artery disease. Curr Cardiol Rep. 2011; 13: 415-423.
34. Farooq V, Brugaletta S, Serruys PW. Contemporary andevolving risk scoring algorithms for percutaneous coronary intervention. Heart. 2011; 97: 1902-1913.
35. Capodanno D, Tamburino C. Integrating the Synergy be-tween percutaneous coronary intervention with Taxus and Cardiac Surgery (SYNTAX) score into practice: use, pitfalls, and new directions. Am Heart J. 2011; 161: 462-470.
36. de Mulder M, Gitt A, van Domburg R, et al. EuroHeartscore for the evaluation of in-hospital mortality in patients undergoing percutaneous coronary intervention. Eur Heart J. 2011; 32: 1398-1408.
37. Garg S, Sarno G, Garcia-Garcia HM, et al. A new tool forthe risk stratification of patients with complex coronary ar-tery disease: the Clinical SYNTAX Score. Circ Cardiovasc Interv. 2010; 3: 317-326.
38. Capodanno D, Caggegi A, Miano M, et al. Global risk clas-sification and clinical SYNTAX (synergy between percuta-neous coronary intervention with TAXUS and cardiac surgery) score in patients undergoing percutaneous or surgical left main revascularisation. JACC Cardiovasc Interv. 2011; 4: 287-297.
39. Chen SL, Chen JP, Mintz G, et al. Comparison between theNERS (New Risk Stratification) score and the SYNTAX(Synergy between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery) score in outcome prediction for unprotected left main stenting. JACC Cardiovasc Interv. 2010; 3: 632-641.
40. Chakravarty T, Buch MH, Naik H, et al. Predictive accuracyof SYNTAX score for predicting long-term outcomes of un-protected left main coronary artery revascularization. Am J Cardiol. 2011; 107: 360-366.
41. Peterson ED, Dai D, DeLong ER, et al. Contemporary mortality risk prediction for percutaneous coronary intervention: results from 588,398 procedures in the National Cardiovascular Data Registry. J Am Coll Cardiol. 2010; 55: 1923-1932.
42. Singh M, Holmes DR, Lennon RJ, Rihal CS. Developmentand validation of risk adjustment models for long-term mortality and myocardial infarction following percutaneous coronary interventions. Circ Cardiovasc Interv. 2010; 3: 423-430.
43. Stolker JM, Kennedy KF, Lindsey JB, et al. Predicting restenosis of drug-eluting stents placed in real-world clinical practice. Derivation and validation of a risk model from the EVENT Registry. Circ Cardiovasc Interv. 2010; 3: 327-334.