Algorithm for predicting cardiovascular events in low/moderate risk patients using traditional and new factors: data from 10-year follow-up study

Aim. To create an advanced algorithm for predicting cardiovascular events (CVE) in low/moderate risk patients using a complex of traditional and new factors.

Material and methods. The study included 700 patients with Systematic Coronary Risk Evaluation (SCORE) <5%, examined in 20092010. In addition to standard investigations, blood biochemistry tests, including high-sensitivity C-reactive protein (hsCRP), and sphygmography were carried. In 2019, a follow-up phone call was made to participants to identify recent CVEs: cardiovascular death, myocardial infarction, unstable angina, stroke, revascularization. The response rate was 79,6% (n=557; men, 100; women, 457).

Results. CVEs were observed in 48 (8,6%) patients. The risk of CVEs increases systolic blood pressure (SBP) >130 mmHg (odds ratio (OR), 1,9 (95% confidence interval (CI), 1,0-3,6)), hsCRP >2,3 mg/L (OR, cardio-ankle vascular index (CAVI) >8,05 (OR, 1,25 (95% CI, 1,0-1,6)). In patients with a combination of ≥2 lipid profile abnormalities, SBP >130 mm Hg, hsCRP >2,3 mg/L and pulse wave velocity >13 m/s, the probability of developing CVEs (including cardiovascular death) increases 3,55 times (95% CI, 1,32-7,67).

Conclusion. Levels of pulse wave velocity, CAVI, urea and hsCRP should be considered as additional risk factors for CVE in patients with low/moderate risk, estimated using standard scales. Combinations of traditional and new risk factors demonstrate a cumulative effect.

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