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Does anemia affect the predictive ability of bleeding risk scores in patients with acute coronary syndromes?
Alberto Garay1, Albert Ariza-Solé1, Francesc Formiga1
1Bellvitge University Hospital, L'Hospitalet de Llobregat, Barcelona, Spain.
Insights
Anemia is common in acute coronary syndrome (ACS) patients. Bleeding risk scores adequately predict major bleeding in ACS patients with mild anemia, showing similar predictive ability.
Area of Science:
- Cardiology
- Internal Medicine
- Clinical Research
Background:
- Anemia is a frequent comorbidity in patients with acute coronary syndromes (ACS).
- Anemia in ACS patients is linked to increased risks of both bleeding and ischemic complications.
- Assessing bleeding risk is crucial for managing ACS patients.
Purpose of the Study:
- To evaluate the predictive performance of established bleeding risk scores in ACS patients with anemia.
- To compare the accuracy of CRUSADE, Mehran, and ACTION scores in predicting major bleeding in anemic versus non-anemic ACS populations.
Main Methods:
- Prospective inclusion of consecutive ACS patients.
- Definition of anemia as hemoglobin <130 g/l (men) or <120 g/l (women).
- Assessment of bleeding risk scores (CRUSADE, Mehran, ACTION) using logistic regression and ROC curve analysis (AUC).
Main Results:
- 2255 ACS patients were included; 24.4% had anemia and higher comorbidity rates.
- All three scores (CRUSADE, ACTION, Mehran) adequately predicted major bleeding in the overall cohort.
- No significant differences in predictive ability were found between anemic and non-anemic patients for CRUSADE and ACTION scores.
Conclusions:
- Anemia is a common condition among ACS patients.
- Current bleeding risk scores demonstrate adequate predictive ability for major bleeding in ACS patients with mild anemia.
- The Mehran score showed reduced predictive accuracy in patients with severe anemia (hemoglobin <11 g/dl).
Introduction And Objective:
Anemia is a common comorbidity in patients with acute coronary syndromes (ACS), and is associated with higher risk for both bleeding and ischemic complications. We aimed to assess the predictive ability of bleeding risk scores (Can Rapid risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the ACC/AHA guidelines [CRUSADE], Mehran and Acute Coronary Treatment and Intervention Outcomes Network [ACTION]) in ACS patients with anemia.
Methods:
All consecutive ACS patients were prospectively included. The primary outcome was in-hospital major bleeding according to the CRUSADE, Mehran and ACTION definitions. Anemia was defined as hemoglobin <130 g/l in men and <120 g/l in women. The predictive ability of the bleeding risk scores was assessed by binary logistic regression, calculating receiver operating characteristic (ROC) curves and their corresponding area under the curve (AUC).
Results:
We included 2255 patients, mean age 62.4 years. Anemia was present in 550 patients (24.4%). Patients with anemia had a significantly higher prevalence of comorbidities. The three bleeding risk scores adequately predicted major bleeding in the whole cohort. No significant differences were observed regarding the predictive ability of each of the scores in patients with and without anemia (CRUSADE: AUC 0.73 without anemia vs. 0.74 with anemia, p=0.913; ACTION: AUC 0.68 without anemia vs. 0.73 with anemia, p=0.353; Mehran: AUC 0.69 without anemia vs. 0.61 with anemia, p=0.210). Only the Mehran score showed significantly lower predictive ability in patients with hemoglobin <11 g/dl (AUC 0.51, p=0.044).
Conclusions:
Anemia was a common comorbidity in patients with ACS from our series. Currently available bleeding risk scores showed an adequate predictive ability in patients with mild anemia.
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