Objective To investigate the effect of gender on the long-term prognosis in the elderly acute coronary syndrome (ACS) patients over 80 years old. Methods All 664 consecutive ACS octogenarians (28.31% women) admitted and undergoing coronary angiography in our department from January 2006 to December 2011 were enrolled in this study. They were assigned into male and female groups. Clinical data were collected and compared between the 2 groups. The occurrence of major adverse cardiac events (MACE) was recorded. Kaplan-Meier survival analysis was performed for the effect of gender on long-term survival in the cohort. Cox multivariate regression analysis was carried out to study the independent predictors for long-term prognosis. Results The follow-up period ranged from 13 to 79 months (median 28 months). The women had higher hyperlipidemia incidence, larger left ventricular ejection fraction, higher body mass index, and elevated fasting blood glucose than the men (P＜0.05). But diastolic blood pressure, serum uric acid, percentages of smoking history and previous myocardial infarction, and incidences of stroke and chronic renal failure were higher in the male than in the female groups (P＜0.05). There were no significant differences in clinical classification of ACS, medicine and treatment strategies between the 2 groups (P＞0.05). Kaplan-Meier survival analysis showed that no significant differences were observed in long-term survival (P=0.619) and event-free survival (P=0.365) between the 2 groups. Cox multivariate regression analysis revealed that non-high density lipoprotein cholesterol (non-HDL-C) and systolic blood pressure level were independent predictors for long-term all-cause mortality (HR=1.73, 95%CI: 1.09-2.75, P=0.019; HR=0.98, 95%CI: 0.97-1.00, P=0.015) and MACE (HR=1.80, 95%CI: 1.22-2.63, P=0.003; HR=0.98, 95%CI: 0.97-0.99, P=0.003). ConclusionGender is not a risk factor for long-term prognosis in ACS octogenarians, but non-HDL-C and systolic blood pressure are independent predictors for long-term all-cause mortality and MACE.