Meta-analysis links metabolic and inflammatory markers to coronary slow flow phenomenon risk

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Frontiers in Medicine Published May 7, 2026 Medically reviewed May 7, 2026 DOI ↗ By Dr. Amelia Tan, PhD · Internal Medicine & Chronic Disease

Key Takeaway

Consider these metabolic and inflammatory markers as potential risk factors for coronary slow flow phenomenon in clinical assessment.

A meta-analysis of observational studies investigated clinical risk factors associated with coronary slow flow phenomenon. The analysis synthesized data from a large cohort of patients with the condition and controls. The authors observed that several metabolic and inflammatory markers, including triglycerides, total cholesterol, white blood cell counts, and platelet indices, were significantly associated with an increased risk of coronary slow flow phenomenon. Body mass index and current smoking were also linked to higher risk.

The authors noted key limitations, including the potential for unmeasured confounding and the inability to establish causality from the pooled observational data. The certainty of the evidence was not formally graded in the report. The analysis did not address specific therapeutic interventions.

Clinically, these associations may help refine risk prediction models and suggest potential pathways for future therapeutic targets. However, the findings are preliminary and should not be used to guide individual patient management without further validation.

Study Details

Study typeMeta analysis

EvidenceLevel 1

PublishedMay 2026

View Original Abstract ↓

BackgroundAs coronary angiography becomes more common, more cases of coronary slow flow phenomenon (CSFP) are detected. To identify key clinical predictors of CSFP, we conducted a meta-analysis. This aims to improve treatment decisions for affected patients.MethodsWe searched multiple databases (Embase, Web of Science, PubMed) up to May 2025 for studies on the association between clinical risk factors and CSFP. Study heterogeneity was assessed using Cochran's Q test and I2 statistics, followed by meta-analysis to pool effect estimates. Publication bias was evaluated with funnel plots and Egger's test. All analyses were conducted using R.ResultsWe identified 23 eligible studies, comprising a total of 2,309 patients with CSFP and 3,377 controls. The pooled analysis identified several clinically independent risk factors for CSFP: Triglycerides (TG)[odds ratio (OR) = 1.01, 95% confidence interval (CI): 1.01–1.02)], Totol cholesterol (TC)[OR = 1.008, CI: 1.001–1.015],White blood cell (WBC) counts[OR = 1.07, CI: 1.04–1.10], Platelets/lymphocytes ratio (PLR)[OR = 1.01, CI: 1.01–1.02], Body mass index (BMI)[OR = 1.09, CI: 1.05–1.13], and platelet count (PC) [OR = 1.009, CI: 1.006–1.011], Current smoke (OR = 1.09, 95% CI = 1.07–1.10) were significantly associated with an increased risk of CSFP.ConclusionThis comprehensive meta-analysis identifies seven key modifiable risk factors for CSFP. These findings not only enhance risk prediction models but also suggest potential therapeutic targets through lipid optimization, anti-inflammatory, antiplatelet strategies, weight control and smoking cessation interventions in CSFP management.Systematic Review RegistrationPROSPERO CRD420251057679.