Evidence map›Paper›PMID 35227316›Full record

ArticleChinese neurosurgical journal2022

Validation of the predictive accuracy of "clinical + morphology nomogram" for the rebleeding risk of ruptured intracranial aneurysms after admission.

Jianfei Sui, Nuochuan Wang, Pengjun Jiang, Jun Wu, Qingzhen Wang, Qiaolin Yuan, Hongwei He

Abstract read
In one paragraph

Article in Chinese neurosurgical journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Jianfei Sui *Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
Nuochuan Wang *Department of Transfusion, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
Pengjun JiangDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
Jun WuDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
Qingzhen WangDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China.
Qiaolin YuanDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China. lqyuan1969@sina.com.
Hongwei HeDepartment of Neurointervention, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing, 100070, China. ttyyhhw@126.com.

Funding

Major special projects in the 14th five-year plan 2021YFC2501100National Natural Science Foundation of China 82071296
6 · The paper itself

Abstract

backgroundRebleeding can cause a catastrophic outcome after aneurysmal subarachnoid hemorrhage. A clinical + morphology nomogram was promoted in our previous study to assist in discriminating the rupture intracranial aneurysms (RIAs) with a high risk of rebleeding. The aim of this study was to validate the predictive accuracy of this nomogram model.

methodThe patients with RIAs in two medical centers from December 2020 to September 2021 were retrospectively reviewed, whose clinical and morphological parameters were collected. The Cox regression model was employed to identify the risk factors related to rebleeding after their admission. The predicting accuracy of clinical + morphological nomogram, ELAPSS score and PHASES score was compared based on the area under the curves (AUCs).

resultsOne hundred thirty-eight patients with RIAs were finally included in this study, 20 of whom suffering from rebleeding after admission. Hypertension (hazard ratio (HR), 2.54; a confidence interval of 95% (CI), 1.01-6.40; P = 0.047), bifurcation (HR, 3.88; 95% CI, 1.29-11.66; P = 0.016), and AR (HR, 2.68; 95% CI, 1.63-4.41; P < 0.001) were demonstrated through Cox regression analysis as the independent risk factors for rebleeding after admission. The clinical + morphological nomogram had the highest predicting accuracy (AUC, 0.939, P < 0.01), followed by the bifurcation (AUC, 0.735, P = 0.001), AR (AUC, 0.666, P = 0.018), and ELAPSS score (AUC, 0.682, P = 0.009). Hypertension (AUC, 0.693, P = 0.080) or PHASES score (AUC, 0.577, P = 0.244) could not be used to predict the risk of rebleeding after admission. The calibration curve for the probability of rebleeding showed a good agreement between the prediction through clinical + morphological nomogram and actual observation.

conclusionHypertension, bifurcation site, and AR were independent risk factors related to the rebleeding of RIAs after admission. The clinical + morphological nomogram could help doctors to identify the high-risk RIAs with a high predictive accuracy.

Indexed as

Intracranial aneurysmsMorphologyPredicting modelRebleedingRupture

Identifiers

PMID35227316
PMCPMC8886787

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