Abstract: OBJECTIVE To observe the related factors for central venous catheter-related thrombosis (CVCRT) in ICU patients with sepsis and establish the nomogram prediction model. METHODS A total of 182 sepsis patients who treated with central venous catheter indwelling in critical care medicine department of Affiliated Hospital of North Sichuan Medical College from Sep. 2024 to Aug. 2025 were recruited as the research subjects and were divided into the CVCRT group with 69 cases and the non-CVCRT group with 113 cases according to the occurrent of CVCRT during the ICU stay. The clinical data were collected from the patients. Univariate analysis and multivariate logistic regression analysis were performed for the related factors for CVCRT in the ICU patients with sepsis. The nomogram prediction model was established based on R software. The internal validation was carried out for the model by Bootstrap repeated sampling, and the predictive efficiency of the model was evaluated by means of receiver operating characteristic (ROC) curves, Hosmer-Lemeshow test, calibration curves, and decision curve analysis. RESULTS The incidence of CVCRT was 37.91%(69/182) among the sepsis patients. The multivariate logistic regression analysis showed that the age, lactic acid, fibrinogen and species of pathogens were the related factors for CVCRT in the ICU patients with sepsis(P＜0.05). The nomogram prediction model that was constructed based on the above variables showed incredible discriminating capability, with the AUC 0.947(95%CI:0.913 to 0.974). The result of Hosmer-Lemeshow test of goodness of fit indicated that the model fit well. The calibration curves showed that the predicted probability of the model approximated the actual probability. The decision curve analysis showed that the model had high clinical net profit. CONCLUSION The nomogram prediction model that is established based on the age, lactic acid, fibrinogen and species of pathogenic bacteria has high accuracy and clinical practice value in prediction of CVCRT among the ICU patients with sepsis.