title: Routine laboratory tests to risk-stratify patients with chronic coronary artery disease.
abstract: BACKGROUND
  Several biohumoral variables, taken individually, are predictors of prognosis in patients with chronic coronary artery disease (CAD). We hypothesized that taken together, laboratory tests provide prognostic information that is additive to a complete diagnostic work-up.
  
  
  METHODS
  We prospectively examined 2370 consecutive patients with chronic CAD, as shown by a >50% coronary stenosis (in 95% of patients), previous coronary revascularization (in 31% of patients), and/or previous myocardial infarction (MI, in 54% of patients). We tested the ability of laboratory and clinical variables to predict future cardiac events (cardiac death and non-fatal MI).
  
  
  RESULTS
  During follow-up (median, 46 months), 147 patients (6.2%) died from cardiac causes and 81 (3.4%) experienced a non-fatal MI. Using multivariate analysis, after adjustment for clinical variables (including left ventricular ejection fraction and angiographic extent of coronary stenoses), a high-density lipoprotein cholesterol (HDLc) concentration<35 mg/dL (p<0.0001), a neutrophil-to-lymphocyte ratio >2.4 (p=0.0014), and an fT3 serum level<2.1 pg/mL with normal thyrotropin (low-T3 syndrome) (p=0.0260) showed an independent and incremental prognostic value, and were associated with an increase in the rate of cardiac events of 86%, 57% and 41%, respectively. When these variables were added to clinical and instrumental variables, the prognostic power of the model increased significantly (global chi-square improvement: from 157.01 to 185.07, p<0.0001).
  
  
  CONCLUSIONS
  Low HDLc, high neutrophil-to-lymphocyte ratio and low-T3 syndrome, both individually and taken together, provide prognostic information that is independent of and incremental to the main clinical and instrumental findings.
authors.affiliation: Fondazione Toscana Gabriele Monasterio, Pisa, Italy. francesco.sbrana@ftgm.it
authors.forename: Francesco
authors.initials: F
authors.lastname: Sbrana
authors.forename: Franca
authors.initials: F
authors.lastname: Cocci
authors.forename: Angela
authors.initials: A
authors.lastname: Papa
authors.forename: Patrizia
authors.initials: P
authors.lastname: Landi
authors.forename: Tiziana
authors.initials: T
authors.lastname: Sampietro
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Rossi
authors.forename: Daniele
authors.initials: D
authors.lastname: Rovai
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood; D001772:Blood Cell Count; D002097:C-Reactive Protein / Q000032:analysis; D008076:Cholesterol, HDL / Q000097:blood; D002908:Chronic Disease; D003324:Coronary Artery Disease / Q000145:classification* / Q000175:diagnosis* / Q000401:mortality*; D003404:Creatinine / Q000097:blood; D003955:Diagnostic Tests, Routine; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D008214:Lymphocytes / Q000166:cytology; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000175:diagnosis / Q000401:mortality; D009504:Neutrophils / Q000166:cytology; D011379:Prognosis; D011446:Prospective Studies; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors
chemical_list: D015415:Biomarkers; D008076:Cholesterol, HDL; D002097:C-Reactive Protein; D003404:Creatinine