| Objective To explore the factors associated with the restoration of spontaneous circulation (ROSC) in patients with out-ofhospital cardiac arrest (OHCA), and to construct a nomogram prediction model.Methods A retrospective analysis was conducted on the clinical data of 902 OHCA patients treated in the Emergency Department of the Second People’s Hospital of Hefei city, Anhui province from January 2021 to June 2024. The patients were stratified into the ROSC group and non-ROSC group based on resuscitation outcomes, and further allocated into a training set and a validation set at a 7∶3 ratio using stratified random sampling. Univariate analysis and multivariate logistic regression analysis were used for variable screening. A nomogram was applied to visualize the risk prediction model. The receiver operating characteristic (ROC) curve, calibration curve, and clinical decision curve (DCA) were employed to assess the performance of the model respectively.Results No statistical differences were observed in all baseline variables between the training set (n=633) and validation set (n=269) (P> 0.05), confirming group comparability. The number of defibrillation attempts, the dosage of epinephrine administered, the use of cardiotonic drugs, and whether the cardiopulmonary resuscitation (CPR) duration exceeded 30 minutes were identified as predictive variables for ROSC in OHCA patients (P＜0.05). A nomogram model was constructed based on the above indicators. The area under the curve (AUC) of the ROC curve in both the training set and the testing set was 0.881, and the threshold probability in the clinical decision curve analysis was 16% to 85%.Conclusion The number of defibrillation attempts, the dosage of epinephrine, the use of cardiotonic drugs, and whether the CPR duration ≥ 30 minutes are the risk factors for ROSC in OHCA patients. The constructed combined prediction model exhibits good predictive value. |
