Clinical risk factors associated with coronary slow flow: a meta-analysis

Objective To investigate factors associated with coronary slow flow (CSF) using a meta-analysis and to provide evidence-based support for the prevention and management of coronary artery disease. Methods Relevant studies published between January 1, 2015, and December 31, 2025, were retrieved from CNKI, CBM, Wanfang, VIP, PubMed, and Embase using the search terms “coronary slow flow,” “coronary slow flow phenomenon,” “coronary slow flow syndrome,” “related factors,” “influencing factors,” and “risk factors.” Case–control studies that met the predefined inclusion and exclusion criteria were included. Study quality was assessed using the Newcastle–Ottawa Scale (NOS), with studies scoring ≥ 7 considered high quality. Meta-analysis was performed using RevMan version 5.3. This study was registered with PROSPERO (ID: CRD420261334323). Results A total of 41 studies were included in the systematic review. Quantitative meta-analysis was performed only for risk factors reported in a sufficient number of studies with comparable definitions and extractable data. The meta-analysis suggested that smoking (OR = 1.21, 95% CI: 1.13–1.29), higher body mass index (OR = 1.20, 95% CI: 1.06–1.36), male sex (OR = 1.51, 95% CI: 1.26–1.81), hypertension (OR = 2.32, 95% CI: 1.27–4.26), elevated homocysteine (OR = 1.55, 95% CI: 1.13–2.13), elevated high-sensitivity C-reactive protein (OR = 1.62, 95% CI: 1.36–1.94), and higher uric acid levels (OR = 1.90, 95% CI: 1.47–2.46) were associated with higher odds of CSF. In contrast, higher high-density lipoprotein cholesterol (HDL-C) levels were associated with lower odds of CSF (OR = 0.45, 95% CI: 0.38–0.55). Conclusion Coronary slow flow (CSF) may be associated with multiple clinical and biochemical factors. Smoking, increased body mass index, male sex, hypertension, and elevated levels of homocysteine, high-sensitivity C-reactive protein, and uric acid were associated with higher odds of CSF, whereas higher HDL-C levels were associated with lower odds of CSF. These findings suggest that unhealthy lifestyle behaviors, metabolic abnormalities, and inflammatory responses may contribute to the development of CSF. Although many CSF-associated factors are potentially modifiable, early interventions—particularly smoking cessation, blood pressure and weight control, and improvement of metabolic and inflammatory status—may help reduce the likelihood of CSF. However, these associations should be interpreted cautiously because moderate-to-high heterogeneity remained in several pooled analyses. Future high-quality prospective studies are needed to clarify the relative importance of these factors, examine potential causal relationships, and evaluate targeted interventions.