| Objective:Based on the serological indicators,relevant scale scores,and general information of the patient within24 hours of admission.1.To evaluate the independent risk factors of delayed cerebral ischemia(DCI)after surgery(within 2weeks)in patients with aneurysmal subarachnoid hemorrhage(aSAH)complicated with acute hydrocephalus before admission.2.To evaluate the independent risk factors for poor prognosis of patients at 6 months post-operatively and design a nomogram prediction model.This model was used to predict the probability of a patient having a poor prognosis 6 months after surgery based on indicators within 24 hours of admission.In addition,the model is evaluated and validated.The aim is to use this as a reference to develop the best treatment plan and optimise the allocation of medical resources.Method:The clinical data of 227 patients with pre-admission aSAH complicated with acute hydrocephalus admitted to our hospital from April 2017 to December 2020 were retrospectively analyzed.Divide patients into DCI group and non-DCI group based on whether they have DCI after surgery;According to the mRS score at 6 months after surgery,the patients were divided into good prognosis group(mRS=0-2)and poor prognosis group(mRS=3-6).Firstly,the univariate analysis of the indicators was carried out,and the indicators with statistical significance in the univariate analysis were included in the multivariate Logistic regression analysis to generate the final independent risk factors.Based on independent risk factors,the receiver operating curve(ROC)was established to calculate the AUC,sensitivity,specificity and cutoff value of each index.In addition,for the good prognosis group and the poor prognosis group,the independent risk factors within 24 hours of admission were combined to draw a nomogram prediction model,and the ROC curve was used to evaluate the model discrimination,the DCA curve was used to evaluate the clinical availability of the model,and 1000 Bootstrap samples for internal validation to measure the calibration of the model.Results:A total of 227 patients were included,there were 74 cases(32.60%)in the DCI group and 153 cases(67.40%)in the non-DCI group;there were 103 cases(45.37%)in the good prognosis group and 124 cases(54.63%)in the poor prognosis group.1.Analysis of DCI group and non-DCI group:Based on the results of univariate analysis,multivariate Logistic regression analysis showed that high Hunt-Hess grade and clipping were independent risk factors for postoperative DCI(P<0.05);ROC curve analysis showed that the AUC of“Hunt-Hess grade”and“surgical method”were 0.665 and 0.593,respectively.The sensitivity was 89.2%and 50%respectively,and the specificity was 36.6%and 68.6%respectively.The optimal cut-off value of“Hunt-Hess grade”was 2.5.2.Analysis of Good prognosis group and poor prognosis group:Based on the results of univariate analysis,multivariate logistic regression analysis showed that advanced age,high Hunt-Hess grade,elevated CRP and neutrophil levels were independent risk factors for poor prognosis at 6 months after surgery(P<0.05);The ROC curve showed that the area under the curve(AUC)of“CRP”,“neutrophil”,“age”and“Hunt-Hess grade”were 0.804,0.735,0.596 and 0.869,respectively.The sensitivity was 74.2%,73.4%,74.2%and46.8%,respectively.The specificity was 76.7%,68%,42.7%and 92.2%,respectively.The optimal cut-off value were 11.4,9.06,61.5 and 3.5,respectively.The nomogram prediction model showed that the AUC of the model constructed by the combination of“CRP+neutrophils+age+Hunt-Hess grade”was 0.879,indicating that the discrimination was good;The DCA results suggest that the model has good clinical usability.Through the bootstrap method,the calibration curve constructed by 1000 repeated samples shows that the prediction model has good calibration.Conclusion:1、Hunt-Hess grade>2 on admission and surgical method of clipping are independent risk factors for delayed cerebral ischemia after surgery.2、CRP>11.4mg/L,neutrophil>0.06×10~9/L,age>61.5 years,Hunt-Hess grade>3 were independent risk factors for poor clinical prognosis in patients.Combined with the above four indicators,development of a risk prediction model for poor prognosis at 6 months postoperatively in patients with aSAH complicated by acute hydrocephalus before admission.The prediction model is clear and simple,with high clinical usability,and can accurately predict the patient’s prognosis within 24 hours of admission,helping the clinic to select reasonable interventions early and improve the prognosis. |
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