title: Risk prediction in stable angina pectoris.
abstract: BACKGROUND
  Although stable angina pectoris often carries a favourable prognosis, it remains important to identify patients with an increased risk of cardiovascular (CV) complications. Many new markers of disease activity and prognosis have been described. We evaluated whether common and easily accessible markers in everyday care provide sufficient prognostic information.
  
  
  METHODS
  The Angina Pectoris Prognosis Study in Stockholm treated 809 patients (248 women) with stable angina pectoris with metoprolol or verapamil double blind during a median follow-up of 3·4 years, with a registry-based extended follow-up after 9·1 years. Clinical and mechanistic variables, including lipids and glucose, renal function, ambulatory and exercise-induced ischaemia, heart rate variability, cardiac and vascular ultrasonography, and psychosocial variables were included in an integrated analysis. Main outcome measures were nonfatal myocardial infarction (MI) and CV death combined.
  
  
  RESULTS
  In all, 139 patients (18 women) suffered a main outcome. Independent predictive variables were (odds ratio [95% confidence intervals]), age (1·04 per year [1·00;1·08], P = 0·041), female sex (0·33 [0·16;0·69], P = 0·001), fasting blood glucose (1.29 per mM [1.14; 1.46], P < 0·001), serum creatinine (1·02 per μM [1·00;1·03], P < 0·001) and leucocyte counts (1·21 per 10(6)  cells/L [1·06;1·40], P = 0·008). Smoking habits, lipids and hypertension or a previous MI provided limited additional information. Impaired fasting glucose was as predictive as manifest diabetes and interacted adversely with serum creatinine. Sexual problems were predictive among men.
  
  
  CONCLUSIONS
  Easily accessible clinical and demographic variables provide a good risk prediction in stable angina pectoris. Impaired glucose tolerance and an elevated serum creatinine are particularly important.
authors.affiliation: Division of Cardiovascular Medicine, Department of Clinical Sciences, Danderyd Hospital, Karolinska Institutet, SE-182 88, Stockholm, Sweden. thomas.kahan@ds.se
authors.forename: Thomas
authors.initials: T
authors.lastname: Kahan
authors.forename: Lennart
authors.initials: L
authors.lastname: Forslund
authors.forename: Claes
authors.initials: C
authors.lastname: Held
authors.forename: Inge
authors.initials: I
authors.lastname: Björkander
authors.forename: Ewa
authors.initials: E
authors.lastname: Billing
authors.forename: Sven V
authors.initials: SV
authors.lastname: Eriksson
authors.forename: Per
authors.initials: P
authors.lastname: Näsman
authors.forename: Nina
authors.initials: N
authors.lastname: Rehnqvist
authors.forename: Paul
authors.initials: P
authors.lastname: Hjemdahl
mesh_terms: D000368:Aged; D060050:Angina, Stable / Q000150:complications* / Q000188:drug therapy; D000889:Anti-Arrhythmia Agents / Q000627:therapeutic use; D001786:Blood Glucose / Q000378:metabolism; D003404:Creatinine / Q000097:blood; D004311:Double-Blind Method; D005260:Female; D005951:Glucose Tolerance Test; D006339:Heart Rate / Q000187:drug effects / Q000502:physiology; D006801:Humans; D008297:Male; D008790:Metoprolol / Q000627:therapeutic use; D008875:Middle Aged; D009203:Myocardial Infarction / Q000175:diagnosis* / Q000209:etiology*; D012307:Risk Factors; D014700:Verapamil / Q000627:therapeutic use
chemical_list: D000889:Anti-Arrhythmia Agents; D001786:Blood Glucose; D003404:Creatinine; D014700:Verapamil; D008790:Metoprolol