International journal of general medicine · 2025
Pan-Immune-Inflammatory Value Predicts the Risk of Myocardial Infarction Among Patients with Unstable Angina Pectoris and the Outcomes After Percutaneous Coronary Intervention.
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Chen Ce, Zhao Bo, Fan Yongyan, Peng Jianjun
Аннотация
OBJECTIVE: This study investigates the potential of the pan-immune-inflammatory value (PIV) as a predictive indicator for myocardial infarction (MI) risk in unstable angina pectoris (UAP) patients and its association with major adverse cardiovascular events (MACE) after percutaneous coronary intervention (PCI).
METHODS: UAP patients diagnosed with MI underwent PCI and were monitored for MACE, including mortality, recurrent MI, revascularization, cerebrovascular accidents, and heart failure admissions. Clinical profiles and PIV levels were recorded. Multivariate logistic regression and receiver operating characteristic (ROC) analyses were conducted to identify variables associated with MI and MACE risk.
RESULTS: MI patients had higher PIV (409.07 ± 127.63 vs 284.44 ± 126.96 × 101 8/L2, P < 0.001) and LDL-C (2.91 ± 1.04 vs 2.31 ± 1.06 mmol/L, P < 0.001) levels. Both PIV (OR = 1.008, P < 0.001) and LDL-C (OR = 1.694, P < 0.001) were significant predictors of MI. ROC analysis showed that PIV had stronger discriminatory capacity (AUC = 0.755) than LDL-C (AUC = 0.661), with their combined model improving predictive performance (AUC = 0.787). In PCI-treated MI patients, those developing MACE had higher PIV (452.66 ± 105.24 vs 378.45 ± 133.53 × 101 8/L2, P = 0.001) and TC levels (4.84 ± 0.39 vs 4.66 ± 0.42 mmol/L, P = 0.010). Both TC (OR = 3.337, P = 0.007) and PIV (OR = 1.005, P = 0.001) were independently associated with MACE. The combined model (AUC = 0.721) outperformed individual markers.
CONCLUSION: PIV is independently associated with MI risk in UAP patients and MACE following PCI. Combining PIV with lipid markers may enhance clinical risk assessment and inform management strategies.
METHODS: UAP patients diagnosed with MI underwent PCI and were monitored for MACE, including mortality, recurrent MI, revascularization, cerebrovascular accidents, and heart failure admissions. Clinical profiles and PIV levels were recorded. Multivariate logistic regression and receiver operating characteristic (ROC) analyses were conducted to identify variables associated with MI and MACE risk.
RESULTS: MI patients had higher PIV (409.07 ± 127.63 vs 284.44 ± 126.96 × 101 8/L2, P < 0.001) and LDL-C (2.91 ± 1.04 vs 2.31 ± 1.06 mmol/L, P < 0.001) levels. Both PIV (OR = 1.008, P < 0.001) and LDL-C (OR = 1.694, P < 0.001) were significant predictors of MI. ROC analysis showed that PIV had stronger discriminatory capacity (AUC = 0.755) than LDL-C (AUC = 0.661), with their combined model improving predictive performance (AUC = 0.787). In PCI-treated MI patients, those developing MACE had higher PIV (452.66 ± 105.24 vs 378.45 ± 133.53 × 101 8/L2, P = 0.001) and TC levels (4.84 ± 0.39 vs 4.66 ± 0.42 mmol/L, P = 0.010). Both TC (OR = 3.337, P = 0.007) and PIV (OR = 1.005, P = 0.001) were independently associated with MACE. The combined model (AUC = 0.721) outperformed individual markers.
CONCLUSION: PIV is independently associated with MI risk in UAP patients and MACE following PCI. Combining PIV with lipid markers may enhance clinical risk assessment and inform management strategies.