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Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study

Xin Feng, Xin Tong, Fei Peng, Hao Niu, Peng Qi, Jun Lu, Yang Zhao, Weitao Jin, Zhongxue Wu, Yuanli Zhao, Aihua Liu, Daming Wang
DOI: 10.1136/svn-2020-000480 Published 28 September 2021
Xin Feng
1 Neurosurgery Department, Beijing Hospital, Beijing, Beijing, China
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Xin Tong
2 Neurointervention Center, Beijing Neurosurgical Institute, Beijing, China
3 Neurointervention Center, Beijing Tiantan Hospital, Beijing, China
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  • ORCID record for Xin Tong
Fei Peng
2 Neurointervention Center, Beijing Neurosurgical Institute, Beijing, China
3 Neurointervention Center, Beijing Tiantan Hospital, Beijing, China
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Hao Niu
2 Neurointervention Center, Beijing Neurosurgical Institute, Beijing, China
3 Neurointervention Center, Beijing Tiantan Hospital, Beijing, China
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Peng Qi
1 Neurosurgery Department, Beijing Hospital, Beijing, Beijing, China
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Jun Lu
1 Neurosurgery Department, Beijing Hospital, Beijing, Beijing, China
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Yang Zhao
4 Neurosurgery Department, Peking University International Hospital, Beijing, China
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Weitao Jin
4 Neurosurgery Department, Peking University International Hospital, Beijing, China
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Zhongxue Wu
2 Neurointervention Center, Beijing Neurosurgical Institute, Beijing, China
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Yuanli Zhao
4 Neurosurgery Department, Peking University International Hospital, Beijing, China
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Aihua Liu
2 Neurointervention Center, Beijing Neurosurgical Institute, Beijing, China
3 Neurointervention Center, Beijing Tiantan Hospital, Beijing, China
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Daming Wang
1 Neurosurgery Department, Beijing Hospital, Beijing, Beijing, China
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  • Figure 1
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    Figure 1

    Distribution of survey respondents by country, region, occupation and by hospital context. AR, aspect ratio; AUC, area under the curve; PC, posterior circulation; SAH, subarachnoid haemorrhage.

  • Figure 2
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    Figure 2

    Calibration curves of the CMB-MIAs nomogram in the derivation (A) and validation (B) set. The predicted probabilities and the actual observed probability of aneurysm rupture were divided into ten groups to create a bar chart for in the derivation (C) and validation (D) set. CMB, clinical and morphological; MIA, multiple intracranial aneurysms.

  • Figure 3
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    Figure 3

    Decision curve analysis of CMB-MIAs nomogram in derivation and validation cohort.

Tables

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  • Table 1

    Univariate analysis between unruptured and ruptured groups in the derivation and validation set

    CharacteristicDerivation cohort
    (n=1171)
    Validation cohort
    (n=500)
    Unruptured
    N (%)
    Ruptured
    N (%)
    P valueUnruptured
    N (%)
    Ruptured
    N (%)
    P value
    No of aneurysm1067 (91.1)104 (8.9)446 (89.2)54 (10.8)
    Female sex734 (68.8)79 (76.0)0.130294 (65.9)40 (74.1)0.229
    Age (years)
     <50214 (20.1)23 (22.1)0.17880 (17.9)12 (22.2)0.205
     50–70728 (68.2)63 (60.6)307 (68.8)31 (57.4)
     ≥70125 (11.7)18 (17.3)59 (13.2)11 (20.4)
    History of SAH56 (5.2)23 (22.1)<0.00122 (4.9)12 (22.2)<0.001
    No of aneurysms
     2636 (59.6)65 (62.5)0.830271 (60.8)37 (68.5)0.442
     3–4382 (35.8)35 (33.7)155 (34.8)16 (29.6)
     >449 (4.6)4 (3.8)20 (4.4)1 (1.9)
    Comorbidities
     Hypertension562 (52.7)62 (59.6)0.175234 (52.5)35 (64.8)0.086
     Diabetes128 (12.0)8 (7.7)0.19142 (9.4)2 (3.7)0.207
     Hypercholesterolaemia111 (10.4)10 (9.6)0.80150 (11.2)7 (13.0)0.702
     Heart diseases113 (10.6)5 (4.8)0.06136 (8.1)6 (11.1)0.436
     History of stroke123 (11.5)8 (7.7)0.23653 (11.9)7 (13.0)0.818
     Smoking199 (18.7)20 (19.2)0.88584 (18.8)15 (27.8)0.119
     Drinking141 (13.2)18 (17.3)0.14570 (15.7)14 (25.9)0.058
    Morphological characterises
    Size, mm
     <3291 (27.3)14 (13.5)0.012127 (28.5)135 (27.0)0.102
     3–7573 (53.7)65 (62.5)235 (52.7)34 (63.0)
     7–15170 (15.9)23 (22.1)84 (18.8)12 (22.2)
     >1533 (3.1)2 (1.9)
    Neck >3.9379 (35.5)41 (39.4)0.428168 (37.7)21(389)0.861
    AR >1.5196 (18.4)41 (39.4)<0.00195 (21.3)23 (46.2)0.001
    Branching to parent ratio >1.2187 (17.5)33 (31.7)<0.00186 (19.3)17 (31.5)0.036
    Neck to parent ratio >1.2325 (30.5)41 (39.4)0.060138 (30.9)14 (25.9)0.449
    SR >1.7204 (19.1)42 (40.4)<0.00195 (21.3)21 (38.9)0.004
    Location of PC109 (10.2)23 (22.1)<0.00142 (9.4)10 (18.5)0.039
    Irregular shape357 (33.5)53 (51.0)<0.001155 (34.8)35 (64.8)<0.001
    Bifurcation location236 (22.1)41 (39.4)<0.001109 (24.4)24 (44.4)0.002
    Inflow angle, mean (SD)96 (35)103 (33)0.05599 (31)104 (31)0.351
    Outflow angle, mean (SD)102 (31)102 (29)0.866100 (30)106 (29)0.172
    Branching angle, mean (SD)137 (34)128 (36)0.021137 (35)134 (33)0.045
    • AR, aspect ratio; PC, posterior circulation; SAH, subarachnoid haemorrhage; SR, size ratio.

  • Table 2

    Multivariate analysis of all 1671 multiple aneurysms in 700 patients and 400 multiple aneurysms in 158 patients who presented with SAH

    Model 1*OR (95% CI)P valueVIFModel 2*OR (95% CI)P valueVIF
    SAH history5.094 (2.848 to 8.929)<0.0011.026AR >1.552.449 (1.302 to 4.641)0.0061.218
    Irregular shape1.883 (1.225 to 2.897)0.0041.025Irregular shape1.886 (1.070 to 3.336)0.0281.120
    Alcohol use2.022 (1.016 to 3.920)0.0401.400Neck >4 mm1.994 (1.015 to 3.944)0.0461.307
    Female1.852 (1.053 to 3.3950.0381.419PC2.522 (1.156 to 5.667)0.0221.007
    AR >1.52.371 (1.507 to 3.698)<0.0011.021Size
    Bifurcation location1.762 (1.118 to 2.745)0.0131.026<3 mmRefRef
    PC2.722 (1.561 to 4.460)<0.0011.0283 to 7 mm1.494 (0.738 to 3.093)0.2701.617
     >7 mm3.240 (1.090 to 10.114)0.0381.803
    • *Model one was developed by all 1671 multiple aneurysms in patients with or without SAH; model 2 was developed by 400 multiple aneurysms in 158 patients with SAH.

    • AR, aspect ratio; PC, posterior circulation; SAH, subarachnoid haemorrhage; VIF, variation inflation factors.

  • Table 3

    Evaluation of discrimination and calibration abilities of the models

    Model 1*Model 2*
    Derivation GroupValidation GroupTotal group (1671 IAs)Derivation GroupValidation GroupTotal group (400 IAs)
    Overall performance
    Brier score0.0730.0850.0830.1990.2070.202
    Discrimination
    AUC (95%)0.743 (0.690 to 0.796)0.772 (0.686 to 0.858)0.753 (0.712 to 0.794)0.739 (0.677 to 0.801)0.717 (0.632 to 0.802)0.730 (0.683 to 0.782)
    Calibration, goodness of fit
    P value of Hosmer-Lemeshow test0.91460.46540.9830.8930.2690.3663
    • *Model 1 was developed by all 1671 multiple aneurysms in patients with or without SAH; model 2 was developed by 400 multiple aneurysms in 158 patients with SAH.

    • AUC, areas under curve; IA, intracranial aneurysm; SAH, subarachnoid haemorrhage.

Supplementary Materials

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  • Supplementary data

    [svn-2020-000480supp001.pdf]

Additional Files

  • Figures
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  • Supplementary Data

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

    • Data supplement 1
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Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study
Xin Feng, Xin Tong, Fei Peng, Hao Niu, Peng Qi, Jun Lu, Yang Zhao, Weitao Jin, Zhongxue Wu, Yuanli Zhao, Aihua Liu, Daming Wang
Stroke and Vascular Neurology Sep 2021, 6 (3) 433-440; DOI: 10.1136/svn-2020-000480

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Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study
Xin Feng, Xin Tong, Fei Peng, Hao Niu, Peng Qi, Jun Lu, Yang Zhao, Weitao Jin, Zhongxue Wu, Yuanli Zhao, Aihua Liu, Daming Wang
Stroke and Vascular Neurology Sep 2021, 6 (3) 433-440; DOI: 10.1136/svn-2020-000480
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Development and validation of a novel nomogram to predict aneurysm rupture in patients with multiple intracranial aneurysms: a multicentre retrospective study
Xin Feng, Xin Tong, Fei Peng, Hao Niu, Peng Qi, Jun Lu, Yang Zhao, Weitao Jin, Zhongxue Wu, Yuanli Zhao, Aihua Liu, Daming Wang
Stroke and Vascular Neurology Sep 2021, 6 (3) 433-440; DOI: 10.1136/svn-2020-000480
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