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Risk factor analysis and prediction model construction of aneurysmal subarachnoid hemorrhage complicated by acute hydrocephalus

Published on Sep. 30, 2024Total Views: 1162 timesTotal Downloads: 362 timesDownloadMobile

Author: ZHANG Long 1 CHUAI Ruiyu 1 WANG Guilin 1 TIAN Yu 2 YANG Dawei 1

Affiliation: 1. Department of Neurosurgery Ward. 1, First Hospital of Qinhuangdao, Qinhuangdao 066000, Hebei Province, China 2. Hand and Foot Display Surgery, First Hospital of Qinhuangdao, Qinhuangdao 066000, Hebei Province, China

Keywords: Aneurysmal subarachnoid hemorrhage Hydrocephalus Ventricular rupture Neuron specific enolase Risk factors Prediction model

DOI: 10.12173/j.issn.1004-5511.202406077

Reference: Zhang L, Chuai RY, Wang GL, Tian Y, Yang DW. Risk factor analysis and prediction model construction of aneurysmal subarachnoid hemorrhage complicated by acute hydrocephalus[J]. Yixue Xinzhi Zazhi, 2024, 34(9): 999-1008. DOI: 10.12173/j.issn.1004-5511.202406077.[Article in Chinese]

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Abstract

Objective  To evaluate the risk factors for the development of acute hydrocephalus (AHC) after aneurysmal subarachnoid hemorrhage (aSAH) and to construct a prediction model.

Methods  The clinical data of patients with aSAH treated in the department of neurosurgery in the First Hospital of Qinhuangdao from January 2015 to January 2024 were retrospectively analyzed. The patients were randomly divided into the training set and the validation set in a 7:3 ratio and were also divided into the AHC group and non-AHC group according to whether they developed AHC or not. The training set was used to construct an AHC risk prediction model, while the validation set was used to validate the AHC risk prediction model. The reliability and stability of the risk prediction model were verified by the receiver operating characteristic curve (ROC), its area under the curve (AUC), calibration curve, and decision curve.

Results  A total of 1,062 patients with aSAH were included, among whom 324 patients developed AHC, with an incidence rate of 30.51%. The training set and validation set had 744 and 318 patients, respectively. Multivariate Logistic regression showed that age ≥60 years [OR=3.067, 95%CI (1.710, 5.499)], entering the ventricles [OR=7.039, 95%CI (3.792, 13.068)], Fisher grade IV [OR=3.371, 95%CI (1.335, 8.514)], Hunt-Hess grade IV [OR=6.198, 95%CI (2.218, 17.324)] and high level of neuron-specific enolase [OR=1.746, 95%CI (1.581, 1.928)] were independent risk factors for aSAH patients developing AHC (P<0.05), while the aneurysm located at anterior circulation [OR=0.397, 95%CI (0.199, 0.790)] was an independent protective factor (P<0.05). The AUC (95%CI) for the training set and validation set were 0.950 (0.932, 0.967) and 0.969 (0.955, 0.982), respectively; the calibration curve showed that the predicted AHC probability and actual AHC probability were consistent; the decision curves both indicated that the AHC risk prediction model had a higher net clinical benefit than the all net clinical benefit.

Conclusion  Clinical attention should be focused on patients with aSAH aged 60 years or older, entering the ventricles, Fisher grade IV, Hunt-Hess grade IV, and high level of neuron-specific enolase, and the AHC prediction model constructed in this study can provide a convenient tool for early identification of AHC.

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References

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