Abstract: OBJECTIVE To investigate the predictive value of peripheral blood CD64, interleukin-1β (IL-1β) and platelet membrane glycoprotein fibrinogen receptor (PAC-1) for the prognosis of patients with severe pneumonia complicated by septic shock. METHODS A total of 180 patients with severe pneumonia who were treated in the hospital from Jul. 2023 to Jul. 2025 were enrolled and divided into a septic shock group and a non-septic shock group (n=92 each) based on the presence or absence of septic shock. Peripheral blood levels of CD64, IL-1β and PAC-1 were compared between the two groups. Logistic regression analysis was performed to identify prognostic factors in patients with severe pneumonia complicated by septic shock. Receiver operating characteristic (ROC) curves were adopted to evaluate the predictive value of peripheral blood CD64, IL-1β and PAC-1 for prognosis. In addition, 50 patients with severe pneumonia complicated by septic shock admitted between Oct. 2024 and Jul. 2025 were selected as an external validation cohort, and the Kappa test was employed to validate the combined model.RESULTS The levels of CD64, IL-1β and PAC-1 in the septic shock group were higher than those in the non-septic shock group (P < 0.05). Among the 92 patients with severe pneumonia complicated by septic shock, 40 died within 28 days (43.48%) and were classified as having a poor prognosis. Logistic regression analysis showed that after adjusting for other factors, peripheral blood CD64, IL-1β and PAC-1 were independently associated with poor prognosis in patients with severe pneumonia complicated by septic shock (P < 0.05). The area under the curve (AUC) for the combined prediction of peripheral blood CD64, IL-1β and PAC-1 was up to 0.903, which was higher than that of each marker alone (P < 0.05). In the external validation cohort, the concordance rate was 86.00%, with a Kappa value of 0.711 (95% CI: 0.434-0.988). CONCLUSIONS CD64, IL-1β and PAC-1 are independent prognostic predictors in patients with severe pneumonia complicated by septic shock. The predictive model developed by combining the three indicators demonstrates excellent discriminatory efficacy, providing a new potential tool for early clinical identification of high-risk patients and precise risk stratification.