Influencing Factors of Disease Uncertainty in Patients with Intracranial Aneurysm after Superselective Intra-Arterial Emboligation and Construction of Nomogram Model for Predicting Its Risk
Objective To investigate the influencing factors of disease uncertainty in patients with intracranial aneurysm after superselective intra-arterial emboligation(SIAE),and construct its risk prediction nomogram model.Methods A total of 242 patients with intracranial aneurysm who received SIAE in the First Affiliated Hospital of Nanjing Medical University from September 2022 to April 2024 were retrospectively selected as the research subjects,and according to a 7∶3 ratio,they were assigned into a modeling set(n=169)and a validation set(n=73)via random number table method.General information,disease understanding status,social support,family care and self-perceived burden of patients were collected.The Chinese version of Mishel's Uncertainty In Illness Scale(MUIS)was used to evaluate the patients'disease uncertainty,the Chinese version of MUIS score of 22-66 was low level and the Chinese version of MUIS score of≥67 was medium to high level.Multivariate Logistic regression analysis was used to explore the influencing factors of disease uncertainty in patients with intracranial aneurysm after SIAE.The nomogram model for predicting the risk of medium to high level of disease uncertainty in patients with intracranial aneurysm after SIAE was constructed by using the rms package of R 3.6.3 software.Hosmer-Lemeshow goodness of fit test was performed,calibration curve was drawn.Results In the modeling set of 169 patients,93 patients had a low level of disease uncertainty(low level group)and 76 patients had a medium to high level of disease uncertainty(medium to high level group).The proportion of patients with postoperative complications,the proportion of patients with low social support,the proportion of patients with low family care,and the proportion of patients with severe self-perceived burden in the medium to high level group were higher than those in the low level group(P<0.05).Multivariate Logistic regression analysis showed that postoperative complications,low social support,low family care and severe self-perceived burden were risk factors for medium to high level of disease uncertainty in patients with intracranial aneurysm after SIAE(P<0.05).The nomogram model for predicting medium to high level of disease uncertainty in patients with intracranial aneurysm after SIAE was constructed based on the results of multivariate Logistic regression analysis.If there were postoperative complications,85 points were assigned;when social support was low,93 points were given;if the family care was low,100 points would be awarded;if the self-perceived burden was severe,82 points would be awarded.The Hosmer-Lemeshow goodness of fit test showed that the nomogram model fitted well in the modeling set and validation set(P>0.05).The ROC curve analysis showed that the AUC of the nomogram model for predicting medium to high level of disease uncertainty in patients with intracranial aneurysm after SIAE in the modeling set and validation set was 0.806[95%CI(0.738-0.874)],0.870[95%CI(0.787-0.954)],respectively.Conclusion Postoperative complications,low social support,low family care and severe self-perceived burden are risk factors for medium to high level of disease uncertainty in patients with intracranial aneurysm after SIAE,and the nomogram model constructed based on the above influencing factors has a high degree of discrimination and has certain predictive value for medium to high level of disease uncertainty in patients with intracranial aneurysm after SIAE.
万方数据
维普
