Predicting Blood in the Real World
Kevin S. Attenhofer, MD
You can’t discuss stroke prevention without talking about antiplatelet drugs. Drugs like Aspirin and Clopidigrel are frequently used by stroke neurologists as the secondary prevention treatment of choice for patients with TIA and non-cardioembolic ischemic strokes. However, we must remember that bleeding is a clinically important and potentially life-threatening side effect of these agents. Reliably predicting who is most likely to bleed would dramatically inform the clinician’s decision-making process and likely result in improved patient outcomes.
To that end, the S2TOP-BLEED score was derived from patient data from six randomized trials (CAPRIE, ESPS-2, MATCH, CHARISMA, ESPRIT, and PRoFESS). It is a 28-point score that incorporates readily available patient characteristics: Sex, Smoking history, Type of antiplatelet, Outcome (mRS), Prior stroke, Blood pressure, Low BMI, Elderly, Ethnicity, Diabetes. It was validated in the PERFORM trial (Prevention of Cerebrovascular and Cardiovascular Events of Ischemic Origin Terutroban in Patients with a History of Ischemic Stroke or Transient Ischemic Attack Study). In this paper, Hilkens et al. externally validate the S2TOP-BLEED score in observational data from a real-world setting.