Front. Neurol. Frontiers in Neurology Front. Neurol. 1664-2295 Frontiers Media S.A. 10.3389/fneur.2023.1268438 Neurology Systematic Review Risk factors for the rupture of intracranial aneurysms: a systematic review and meta-analysis Ma Jinyuan 1 † Zheng Yuehua 2 † Li Puxian 1 Zhou Tao 2 Sun Zhen 1 Ju Tongze 1 Li Aijun 1 * 1Department of Neurosurgery, Qingdao Binhai University Affiliated Hospital, Qingdao, China 2Department of Neurosurgery, Weifang People’s Hospital Shandong Province, Weifang, China

Edited by: Paolo Aridon, University of Palermo, Italy

Reviewed by: Qin Fei Yun, The First Affiliated Hospital of Wannan Medical College, China; Paolo Ragonese, University of Palermo, Italy

 *Correspondence: Aijun Li, aijunli69@sina.com

†These authors have contributed equally to this work

 11 12 2023 2023 14 1268438 01 08 2023 09 11 2023 Copyright © 2023 Ma, Zheng, Li, Zhou, Sun, Ju and Li. 2023 Ma, Zheng, Li, Zhou, Sun, Ju and Li

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 Purpose

The study aimed to identify potential risk factors for aneurysm rupture by performing a systematic review and meta-analysis.

 Materials and methods

We systematically searched the PubMed, Embase, and Cochrane Library electronic databases for eligible studies from their inception until June 2023.

 Results

Eighteen studies involving 17,069 patients with unruptured intracranial aneurysm (UIA) and 2,699 aneurysm ruptures were selected for the meta-analysis. Hyperlipidemia [odds ratio (OR): 0.47; 95% confidence interval (CI): 0.39–0.56; p < 0.001] and a family history of subarachnoid hemorrhage (SAH) (OR: 0.81; 95% CI: 0.71–0.91; p = 0.001) were associated with a reduced risk of aneurysm rupture. In contrast, a large-size aneurysm (OR: 4.49; 95% CI: 2.46–8.17; p < 0.001), ACA (OR: 3.34; 95% CI: 1.94–5.76; p < 0.001), MCA (OR: 2.16; 95% CI: 1.73–2.69; p < 0.001), and VABA (OR: 2.20; 95% CI: 1.24–3.91; p = 0.007) were associated with an increased risk of aneurysm rupture. Furthermore, the risk of aneurysm rupture was not affected by age, sex, current smoking, hypertension, diabetes mellitus, a history of SAH, and multiple aneurysms.

 Conclusion

This study identified the predictors of aneurysm rupture in patients with UIAs, including hyperlipidemia, a family history of SAH, a large-size aneurysm, ACA, MCA, and VABA; patients at high risk for aneurysm rupture should be carefully monitored.

 Systematic Review Registration

Our study was registered in the INPLASY platform (INPLASY202360062).

 risk factors rupture intracranial aneurysms systematic review meta-analysis section-at-acceptance Neuroepidemiology Introduction

Unruptured intracranial aneurysm (UIA) was considered a “ticking time bomb” and always diagnosed at routine checkups, with an estimated prevalence of 2.3% to 3.2% in the general population (1, 2). The rupture of an intracranial aneurysm can cause aneurysmal subarachnoid hemorrhage (aSAH), with an annual incidence of nearly 9 per 100,000 cases of UIA and 1.4% of UIA rupture annually (3–5). Considering that aSAH is a serious complication of UIA, and the mortality rate has reached 67%, with nearly 50% of the survivors remaining disabled, clinicians should elucidate the risk of rupture (6). Although UIA can be prophylactically treated to prevent aneurysm rupture, nearly 5% of patients are at risk of complications (7). Therefore, in the management of UIAs, the risk of rupture should be balanced with the risk of UIA.

The 5 years risk of aneurysm rupture in UIA can be evaluated using the PHASES scores, which are based on geographic location, hypertension, age, a history of aSAH, and the aneurysm size and location (5). However, the analysis of risk factors based on PHASES scores was restricted because the analysis relies on published articles. Numerous patient and aneurysm characteristics are associated with the rupture risk or are hypothesized to predispose patients to rupture (8). Follow-up imaging could be used to monitor UIA growth, and preventive aneurysm treatment should be administered when aneurysmal growth is observed (7). Several studies have addressed the predictors of aneurysm rupture in patients with UIA; however, these studies only focused on a single factor (5, 9–11). Additional risk factors should be identified to further prevent the aneurysm rupture risk.

In this study, we aimed to identify the risk factors for aneurysm rupture in patients with UIA by conducting a systemic review and meta-analysis.

 Methods Literature search and selection criteria

This study was conducted and reported following the meta-analysis of observational studies in epidemiology protocol (12), which indicates that the predictors of aneurysm rupture in patients with UIA were eligible for our study, and no restrictions were placed on the publication language and status. Our study was registered in the INPLASY platform (INPLASY202360062). We systematically searched the PubMed, Embase, and Cochrane Library databases for potentially eligible studies through June 2023 using the following search terms: [intracranial aneurysm(s) OR cerebral aneurysm(s)] AND (risk of rupture OR aneurysm rupture OR risk factors OR rupture OR unruptured OR subarachnoid hemorrhage) AND (follow-up OR natural history OR natural course). Reference lists of relevant reviews and original articles were manually searched to identify eligible studies that met the inclusion criteria.

Two reviewers independently performed the literature search and study selection. Any disagreements between the reviewers were resolved by a group discussion until a consensus was reached. The inclusion criteria were as follows:

Patients: all of the patients diagnosed with UIA.

Exposure: the predictors for aneurysm rupture reported ≥3 times.

Outcomes: the study should report the effect estimate for the risk of aneurysm rupture or data could transform into effect estimate.

Study design: no restriction for study design, including prospective and retrospective studies.

 Data extraction and quality assessment

Two reviewers performed data collection and quality assessment including the first author’s surname, publication year, region, study design, sample size, mean age, male proportion, disease status, a family history of aSAH, hypertension, diabetes mellitus (DM), smoking, location of UIA, follow-up, and the number of aneurysm ruptures. The methodological quality of the included studies was assessed using the Newcastle–Ottawa scale (NOS), which was partially validated to assess the quality of observational studies in the meta-analysis (13). The NOS contained selection (four items), comparability (one item), and outcome (three items), and the “star system” for each study ranged from 0 to 9. Inconsistent results between the reviewers were resolved by an additional reviewer by referring to the original article.

 Statistical analysis

The risk factors for aneurysm rupture in each study were assigned odds ratios (ORs) with 95% confidence intervals (CIs), and pooled analysis was performed using the random-effects model considering the underlying variations among the included studies (14, 15). Heterogeneity among the included studies was assessed using I2 and Cochran Q statistics, and significant heterogeneity was defined as I2 ≥ 50.0% or a p-value of <0.10 (16, 17). The robustness of the pooled conclusions was assessed using sensitivity analysis through the sequential removal of a single study (18). Subgroup analyses were performed according to region, study design, follow-up, and study quality, and the differences between subgroups were compared using the interaction P test (19). Funnel plots and Egger–Begg test results were used to assess publication bias (20, 21). The inspection level for pooled effect estimates was two-sided, and a p-value of <0.05 was considered statistically significant. The STATA software (version 12.0; Stata Corporation, College Station, TX, United States) was used for all statistical analyses.

 Results Literature search

We initially identified 3,742 articles from the electronic searches, and 2,415 articles were retained after duplicates were removed. Subsequently, 2,279 studies were excluded owing to irrelevant titles or abstracts. Five additional articles were identified by reviewing the reference lists of the relevant reviews and original articles. A total of 141 studies were retrieved for detailed evaluation, and 123 studies were excluded because of insufficient data (n = 51), case reports (n = 42), or intervention studies (n = 30). The remaining 18 studies were included in the final meta-analysis (Figure 1) (22–39).

Literature search and study selection.

 Characteristics of the included studies

The baseline characteristics of the identified studies and patients with UIA are summarized in Table 1. In total, 17,069 patients with UIA were included, and the sample sizes ranged from 70 to 5,720. Eight studies were designed as prospective cohorts, and the remaining eight were designed as retrospective cohorts. Nine studies were conducted in Western countries, eight were performed in Eastern countries, and the remaining one was conducted in multiple countries. These studies reported 2,699 aneurysm ruptures. The methodological quality of the individual studies was assessed using the NOS as follows: six studies with eight stars, seven studies with seven stars, and five studies with six stars. Studies with 7–9 stars were regarded as high quality, while 4–6 stars were considered moderate quality.

Baseline characteristics of included studies and involved patients.

Study Region Study design Sample size Age (years) Male (%) No. of UIA Family history of aSAH Hypertension (%) DM (%) Smoking (%) Location of UIA Follow-up No. of aneurysm rupture NOS scale
Ishibashi et al. (22) Japan Pro 419 60.8 33.0 529 NA NA NA NA ICA (41%), ACA (20%), MCA (27%), VABA (12%) 2.5 years 19 8
Sonobe et al. (23) Japan Pro 374 61.9 36.4 448 8.3 24.9 6.1 NA ICA (38.6%), MCA (35.3%), Acom (13.4%), distal ACA (2.7%), BA (7.4%), VA (0.9%) 3.5 years 18 8
Morita et al. (24) Japan Pro 5,720 62.5 33.5 6,697 12.9 43.4 6.3 NA MCA (36.2%), Acom (15.5%), ICA (18.6%), ICPcom (15.5%), BA (6.6%), VA (1.8%) 1.7 years 111 8
Guresir et al. (25) Germany Pro 263 55.0 22.4 384 3.0 42.6 5.3 52.1 ACA (46%), MCA (33%), Acom (14%), distal ACA (7%) 4.0 years 3 7
Juvela et al. (26) Finland Pro 142 41.8 46.0 181 NA 36.0 NA 47.0 ICA (42%), ACA (4%), Acom (6%), MCA (45%), VABA (3%) 21.0 years 34 7
Korja et al. (27) Finland Pro 118 43.5 48.3 146 NA 25.0 NA 39.0 NA 13.6 years 38 7
Gross et al. (28) United States Retro 747 53.9 17.0 1,013 NA 39.0 NA 32.0 Acom (17%), MCA (16%), VA (5%), BA (8%), ICA (6%) 7.0 years 303 6
Hishikawa et al. (29) Japan Pro 1,896 74.3 27.1 2,227 9.3 53.6 NA 8.1 MCA (33.9%), Acom (17.9%), ICA (11.6%), ICPcom (19.9%), BA (8.7%), VA (2.6%) 2.2 years 68 7
Murayama et al. (30) Japan Pro 2,252 65.0 32.4 2,897 NA 46.5 5.7 13.5 MCA (27.3%), ACA (16.8%), ICA (26.8%), ICPcom (20.5%), VABA (8.6%) 2.6 years 56 8
Teo et al. (31) United Kingdom Retro 94 53.0 21.3 152 NA NA NA NA MCA (38%), ICA (21%), Pcom (16%), Acom (9%), BA (7%) 3.4 years 4 6
Mocco et al. (32) United States Pro 255 NA 23.9 NA NA NA NA NA ICA (25.5%), ACA/Acom (5.9%), MCA (14.9%), BA (18.0%), Pcom (26.3%), PCA (2.4%) 7.0 years 57 7
Hostettler et al. (33) United Kingdom Retro 2,334 54.2 29.7 2,942 12.4 35.3 4.6 42.5 MCA (22.9%), ICA (12.8%), ACA/Acom (24.5%), Pcom (18.1%), PCA (11.4%) 4.0 years 1,729 8
Funakoshi et al. (34) Japan Retro 595 63.9 27.1 595 NA NA NA NA ICA (58.2%), MCA (1.7%), Acom (20.7%), VA (3.9%), BA (11.9%) 6.2 years 169 6
Wang et al. (35) China Pro 1,087 60.3 53.3 1,087 NA 53.4 19.9 21.4 ICA (65.6%), MCA (8.5%), ACA (3.1%), Acom (7.2%), Pcom (4.0%), BA (4.3%), VA (3.3%), PCA (2.1%) 2.8 years 11 8
van der Kamp et al. (36) Canada, Europe, China, and Japan Retro 312 61.0 29.0 329 NA NA NA 41.0 ICA (25%), MCA (32%), Pcom (8%), Acom (15%), ACA (5%), BA (8%), VABA (7%) 2.8 years 24 7
Lee et al. (37) Korea Retro 117 52.8 57.3 117 4.3 42.7 11.1 28.2 VA (100%) 3.0 years 34 6
Dmytriw et al. (38) Canada Retro 70 51.7 55.7 78 NA 54.2 10.9 30.9 VA (38.5%), BA (30.8%), PCA (19.2%), PICA (10.3%), AICA (1.3%) 3.0 years 6 6
Spencer et al. (39) UK Retro 274 54.8 24.1 445 17.2 45.3 7.3 55.1 MCA (74.5%), ICA (24.8%), Acom (17.5%), Pcom (13.1%), ACA (5.8%), BA (5.8%), PCA (2.6%) 3.8 years 15 7

ACA, anterior cerebral artery; Acom, anterior communicating artery; BA, basilar artery; DM, diabetes mellitus; ICA, internal carotid artery; ICPcom, internal carotid-posterior communicating artery; MCA, middle cerebral artery; NA, not available; PCA, posterior cerebral artery; Pro, prospective; Retro, retrospective; UIA, unruptured intracranial aneurysm; VA, vertebral artery; VABA, vertebrobasilar artery.

 Age and sex

A total of 11 and 14 studies reported the roles of age and sex on the risk of aneurysm rupture in UIA patients, respectively (Figure 2). Age (OR: 1.06; 95% CI: 0.74–1.54; p = 0.740) and sex (OR: 1.08; 95% CI: 0.91–1.30; p = 0.382) were not associated with the aneurysm rupture risk in patients with UIA. There was significant heterogeneity in age (I2 = 70.1%; p < 0.001); in contrast, no significant heterogeneity was observed in sex (I2 = 28.1%; p = 0.154). Sensitivity analyses indicated that the pooled conclusions regarding the roles of age and sex were not changed by the sequential removal of individual studies (Supplementary File 1). Subgroup analyses indicated that younger patients had a reduced risk of aneurysm rupture compared to older patients if the follow-up duration was <3.0 years and the role of age in the risk of aneurysm rupture could be affected by region (p = 0.002) and follow-up (p < 0.001) (Table 2). No evidence of publication bias for age was observed (p-value for Egger: 0.622; p-value for Begg: 0.350; Supplementary File 2). Although the Begg test indicated no significant publication bias for sex (p = 0.324), a potentially significant publication bias was observed using the Egger test (p = 0.035) (Supplementary File 2).

Effect of age and sex on the risk of aneurysm rupture in patients with unruptured intracranial aneurysms (UIA). (A) Younger vs. elder. (B) Female vs. male.

Subgroup analyses for the risk factors of aneurysm rupture in UIA patients.

Outcomes Factors Subgroups No. of studies OR and 95% CI p value I2 (%) Q statistic Interaction p-value
Age (younger vs. elder) Region Eastern 5 0.74 (0.50–1.09) 0.128 41.2 0.147 0.002
Western 6 1.47 (0.84–2.56) 0.173 70.1 0.005
Study design Prospective 9 0.94 (0.65–1.35) 0.727 65.5 0.003 0.057
Retrospective 2 1.81 (0.38–8.61) 0.454 84.9 0.010
Follow-up (years) ≥3.0 6 1.82 (0.99–3.37) 0.056 70.8 0.004 <0.001
<3.0 5 0.71 (0.55–0.92) 0.010 0.0 0.568
Study quality High 11 1.06 (0.74–1.54) 0.740 70.1 <0.001 —
Moderate 0 — — — —
Gender (female vs. male) Region Eastern 7 1.11 (0.81–1.52) 0.501 50.0 0.062 0.653
Western 7 1.04 (0.88–1.23) 0.647 0.0 0.438
Study design Prospective 8 1.31 (1.03–1.66) 0.026 0.0 0.511 0.012
Retrospective 6 0.92 (0.77–1.09) 0.321 10.4 0.349
Follow-up (years) ≥3.0 9 0.98 (0.79–1.20) 0.821 27.9 0.197 0.016
<3.0 5 1.39 (1.05–1.86) 0.024 0.0 0.883
Study quality High 11 1.12 (0.97–1.30) 0.128 0.0 0.494 0.011
Moderate 3 0.80 (0.60–1.06) 0.119 9.6 0.331
Current smoker Region Eastern 5 1.01 (0.52–1.95) 0.988 59.1 0.044 0.273
Western 7 1.40 (1.13–1.72) 0.002 2.9 0.404
Study design Prospective 6 1.33 (0.63–2.83) 0.456 67.5 0.009 0.948
Retrospective 6 1.31 (1.11–1.56) 0.002 0.0 0.883
Follow-up (years) ≥3.0 8 1.49 (1.04–2.15) 0.031 36.3 0.139 0.226
<3.0 4 1.06 (0.58–1.91) 0.858 36.1 0.195
Study quality High 9 1.30 (0.87–1.94) 0.193 52.3 0.033 0.679
Moderate 3 1.46 (0.87–2.47) 0.153 0.0 0.898
Hypertension Region Eastern 6 1.44 (0.86–2.41) 0.167 74.3 0.002 0.393
Western 6 1.53 (0.64–3.67) 0.343 95.8 <0.001
Study design Prospective 8 1.75 (1.12–2.73) 0.014 79.3 <0.001 <0.001
Retrospective 4 1.04 (0.49–2.19) 0.928 81.3 0.001
Follow-up (years) ≥3.0 8 1.62 (0.78–3.40) 0.199 94.6 <0.001 0.370
<3.0 4 1.31 (0.79–2.16) 0.292 67.1 0.028
Study quality High 10 1.66 (0.94–2.93) 0.079 93.5 <0.001 0.338
Moderate 2 1.00 (0.36–2.77) 0.994 40.9 0.193
DM Region Eastern 3 0.77 (0.27–2.20) 0.619 35.7 0.211 0.362
Western 2 1.69 (0.18–15.99) 0.646 88.5 0.003
Study design Prospective 2 0.33 (0.08–1.37) 0.128 0.0 0.760 0.230
Retrospective 3 1.39 (0.48–4.05) 0.544 81.9 0.004
Follow-up (years) ≥3.0 3 1.39 (0.48–4.05) 0.544 81.9 0.004 0.230
<3.0 2 0.33 (0.08–1.37) 0.128 0.0 0.760
Study quality High 3 0.57 (0.39–0.85) 0.005 0.0 0.703 0.003
Moderate 2 2.49 (0.61–10.24) 0.205 66.8 0.082
Hyperlipidemia Region Eastern 4 0.59 (0.37–0.93) 0.023 0.0 0.904 0.291
Western 2 0.45 (0.37–0.55) <0.001 0.0 0.712
Study design Prospective 3 0.55 (0.33–0.92) 0.022 0.0 0.880 0.499
Retrospective 3 0.46 (0.38–0.56) <0.001 0.0 0.575
Follow-up (years) ≥3.0 3 0.46 (0.38–0.56) <0.001 0.0 0.575 0.499
<3.0 3 0.55 (0.33–0.92) 0.022 0.0 0.880
Study quality High 4 0.46 (0.38–0.56) <0.001 0.0 0.844 0.322
Moderate 2 0.75 (0.29–1.91) 0.545 0.0 0.907
History of SAH Region Eastern 4 3.17 (1.51–6.66) 0.002 41.6 0.162 0.005
Western 3 0.90 (0.42–1.92) 0.778 0.0 0.613
Study design Prospective 4 3.17 (1.51–6.66) 0.002 41.6 0.162 0.005
Retrospective 3 0.90 (0.42–1.92) 0.778 0.0 0.613
Follow-up (years) ≥3.0 3 0.85 (0.34–2.10) 0.728 0.0 0.595 0.021
<3.0 4 2.75 (1.22–6.23) 0.015 59.8 0.058
Study quality High 6 2.08 (1.03–4.22) 0.041 57.3 0.039 0.143
Moderate 1 0.28 (0.02–4.45) 0.367 — —
Family history of SAH Region Eastern 3 0.91 (0.67–1.24) 0.545 0.0 0.654 0.418
Western 1 0.79 (0.69–0.90) 0.001 — —
Study design Prospective 3 0.91 (0.67–1.24) 0.545 0.0 0.654 0.418
Retrospective 1 0.79 (0.69–0.90) 0.001 — —
Follow-up (years) ≥3.0 2 0.83 (0.70–0.98) 0.028 21.4 0.259 0.629
<3.0 2 0.69 (0.35–1.35) 0.273 0.0 0.983
Study quality High 4 0.81 (0.71–0.91) 0.001 0.0 0.681 —
Moderate 0 — — — —
Large size of aneurysm Region Eastern 6 7.99 (5.00–12.76) <0.001 74.2 0.002 <0.001
Western 6 2.32 (1.19–4.52) 0.013 77.3 0.001
Study design Prospective 9 4.99 (2.41–10.34) <0.001 93.5 <0.001 0.498
Retrospective 3 3.53 (2.13–5.86) <0.001 0.0 0.695
Follow-up (years) ≥3.0 6 2.51 (1.21–5.19) 0.013 78.6 <0.001 <0.001
<3.0 6 7.27 (4.45–11.85) <0.001 78.5 <0.001
Study quality High 11 4.69 (2.53–8.68) <0.001 92.0 <0.001 0.407
Moderate 1 1.62 (0.17–15.18) 0.673 — —
Multiple aneurysm Region Eastern 4 1.51 (0.99–2.30) 0.056 37.7 0.186 0.041
Western 3 0.97 (0.79–1.19) 0.755 0.0 0.414
Study design Prospective 5 1.39 (0.93–2.06) 0.107 35.8 0.183 0.084
Retrospective 2 1.16 (0.54–2.46) 0.703 35.9 0.212
Follow-up (years) ≥3.0 4 1.33 (0.73–2.41) 0.354 60.4 0.055 0.303
<3.0 3 1.28 (0.89–1.85) 0.186 5.9 0.345
Study quality High 6 1.23 (0.89–1.69) 0.214 47.6 0.089 0.267
Moderate 1 2.55 (0.56–11.64) 0.227 — —
ACA vs. ICA Region Eastern 6 2.46 (1.58–3.84) <0.001 22.2 0.267 <0.001
Western 3 5.35 (3.04–9.43) <0.001 41.3 0.182
Study design Prospective 6 3.30 (1.91–5.70) <0.001 13.7 0.327 0.803
Retrospective 3 3.58 (1.34–9.57) 0.011 92.2 <0.001
Follow-up (years) ≥3.0 5 3.95 (1.87–8.33) <0.001 85.0 <0.001 0.676
<3.0 4 2.61 (1.18–5.79) 0.018 36.3 0.194
Study quality High 7 4.06 (2.33–7.07) <0.001 48.7 0.069 <0.001
Moderate 2 2.14 (1.64–2.80) <0.001 0.0 0.662
MCA vs. ICA Region Eastern 6 1.96 (1.28–3.02) 0.002 0.0 0.547 0.615
Western 4 2.23 (1.73–2.89) <0.001 0.0 0.826
Study design Prospective 6 2.07 (1.32–3.24) 0.001 0.0 0.551 0.831
Retrospective 4 2.19 (1.70–2.82) <0.001 0.0 0.770
Follow-up (years) ≥3.0 5 2.17 (1.70–2.78) <0.001 0.0 0.929 0.910
<3.0 5 2.10 (1.24–3.53) 0.005 6.7 0.368
Study quality High 8 2.14 (1.68–2.72) <0.001 0.0 0.728 0.849
Moderate 2 2.27 (1.27–4.08) 0.006 0.0 0.405
VABA vs. ICA Region Eastern 6 2.20 (1.10–4.40) 0.025 53.5 0.044 0.332
Western 1 2.43 (1.02–5.78) 0.045 — —
Study design Prospective 6 2.91 (1.78–4.75) <0.001 0.0 0.586 0.002
Retrospective 1 1.07 (0.70–1.63) 0.752 — —
Follow-up (years) ≥3.0 3 1.40 (0.78–2.51) 0.262 28.7 0.246 0.009
<3.0 4 3.22 (1.72–6.03) <0.001 5.4 0.376
Study quality High 6 2.91 (1.78–4.75) <0.001 0.0 0.586 0.002
Moderate 1 1.07 (0.70–1.63) 0.752 — —
Smoking status and hypertension

Overall, 12 and 12 studies reported the roles of smoking status and hypertension on the risk of aneurysm rupture in UIA patients, respectively (Figure 3). Current smoking (OR: 1.34; 95% CI: 0.99–1.81; p = 0.059) and hypertension (OR: 1.56; 95% CI: 0.94–2.59; p = 0.087) were not associated with the risk of aneurysm rupture. There was no significant heterogeneity for current smoking (I2 = 35.9%; p = 0.103); in contrast, significant heterogeneity was observed for hypertension (I2 = 92.2%; p < 0.001). Sensitivity analyses revealed that current smoking and hypertension were associated with an elevated risk of aneurysm rupture (Supplementary File 1). Subgroup analyses showed current smoking was associated with an increased risk of aneurysm rupture when pooled studies were conducted in Western countries, studies with a retrospective cohort, and a follow-up of ≥3.0 years. Hypertension induced excess risk of aneurysm rupture in pooled prospective cohort studies. Moreover, the role of hypertension in the risk of aneurysm rupture was affected by the study design (p < 0.001) (Table 2). There was no significant publication bias for current smoking (p-value for Egger: 0.840; p-value for Begg: 0.451) or hypertension (p-value for Egger: 0.276; p-value for Begg: 0.451; Supplementary File 2).

Effect of smoking status and hypertension on the risk of aneurysm rupture in patients with unruptured intracranial aneurysms (UIA). (A) Current smoker. (B) Hypertension.

 Diabetes mellitus and hyperlipidemia

Overall, 5 and 6 studies reported the roles of diabetes mellitus (DM) and hyperlipidemia in the risk of aneurysm rupture in patients with UIA, respectively (Figure 4). Notably, DM was not associated with the risk of aneurysm rupture (OR: 0.97; 95% CI: 0.42–2.25; p = 0.940); in contrast, hyperlipidemia was associated with a reduced risk of aneurysm rupture (OR: 0.47; 95% CI: 0.39–0.56; p < 0.001). There was significant heterogeneity for DM (I2 = 68.3%; p = 0.013); in contrast, no evidence of heterogeneity was observed for hyperlipidemia (I2 = 0.0%; p = 0.874). Sensitivity analyses indicated that the pooled conclusions for DM and hyperlipidemia were robust after excluding one study (Supplementary File 1). Subgroup analysis indicated that DM was associated with a reduced risk of aneurysm rupture when pooled studies were of high quality, and study quality could affect the role of DM in the risk of aneurysm rupture (p = 0.003). Moreover, hyperlipidemia was associated with a lower risk of aneurysm rupture in most subgroups; in contrast, there was no significant association between hyperlipidemia and the risk of aneurysm rupture if the pooled studies were of moderate quality (Table 2). There was no significant publication bias for DM (p-value for Egger: 0.619; p-value for Begg: 0.806). Although the Begg test indicated no significant publication bias for hyperlipidemia (p = 0.452), the Egger test suggested a potentially significant publication bias for hyperlipidemia (p = 0.016) (Supplementary File 2).

Effect of diabetes mellitus (DM) and hyperlipidemia on the risk of aneurysm rupture in patients with unruptured intracranial aneurysms (UIA). (A) DM. (B) Hyperlipidemia.

 History of SAH and family history of SAH

Seven and four studies reported the roles of a history of SAH and a family history of SAH on the risk of aneurysm rupture in patients with UIA, respectively (Figure 5). Notably, patients with a history of SAH were not associated with the risk of aneurysm rupture (OR: 1.87; 95% CI: 0.92–3.80; p = 0.085); in contrast, a family history of SAH was associated with a reduced risk of aneurysm rupture (OR: 0.81; 95% CI: 0.71–0.91; p = 0.001). There was significant heterogeneity in the history of SAH (I2 = 56.7%; p = 0.031); in contrast, there was no evidence of heterogeneity in the family history of SAH (I2 = 0.0%; p = 0.681). The pooled conclusions regarding the role of a history of SAH and a family history of SAH on the risk of aneurysm rupture were variable (Supplementary File 1). Subgroup analysis showed that patients with a history of SAH were associated with an increased risk of aneurysm rupture when pooled studies were conducted in Eastern countries, prospective cohort studies, a follow-up of <3.0 years, and high-quality studies, and the association between a history of SAH and aneurysm rupture risk was affected by region (p = 0.005), study design (p = 0.005), and follow-up (p = 0.021). Moreover, a family history of SAH was associated with a reduced risk of aneurysm rupture if pooled studies were conducted in Western countries, retrospective cohort studies, a follow-up of ≥3.0 years, and studies with high quality (Table 2). There was no significant publication bias for a history of SAH (p-value for Egger: 0.161; p-value for Begg: 0.548) or a family history of SAH (p-value for Egger: 0.940; p-value for Begg: 0.734; Supplementary File 2).

Effect of a history of subarachnoid hemorrhage (SAH) and a family history of SAH on the risk of aneurysm rupture in patients with unruptured intracranial aneurysms (UIA). (A) History of SAH. (B) Family history of SAH.

 Aneurysm size and multiple aneurysms

Twelve and seven studies reported the roles of aneurysm size and multiple aneurysms on the risk of aneurysm rupture in patients with UIA, respectively (Figure 6). Large-size aneurysm was associated with an increased risk of aneurysm rupture (OR: 4.49; 95% CI: 2.46–8.17; p < 0.001); in contrast, multiple aneurysms were not associated with the risk of aneurysm rupture (OR: 1.26; 95% CI: 0.92–1.73; p = 0.149). There was significant heterogeneity in aneurysm size (I2 = 91.2%; p < 0.001) and multiple aneurysms (I2 = 44.3%; p = 0.096). The summary results for the role of aneurysm size and multiple aneurysms on the risk of aneurysm rupture were stable and were not altered by removing a single study (Supplementary File 1). Subgroup analyses showed that a large aneurysm size was associated with an increased risk of aneurysm rupture in most subgroups; in contrast, no significant association between a large-size aneurysm and the risk of aneurysm rupture was found in a moderate-quality pooled study. Moreover, the role of a large-size aneurysm in the risk of aneurysm rupture was affected by the region (p < 0.001) and follow-up (p < 0.001). Although the role of multiple aneurysms in the risk of aneurysm rupture was affected by the region (p = 0.041), none of the subgroups showed significant associations between multiple aneurysms and the risk of aneurysm rupture (Table 2). There was no significant publication bias for a large-size aneurysm (p-value for Egger: 0.784; p-value for Begg: 0.451) and multiple aneurysms (p-value for Egger: 0.099; p-value for Begg: 0.548; Supplementary File 2).

Effect of aneurysm size and multiple aneurysms on the risk of aneurysm rupture in patients with unruptured intracranial aneurysms (UIA). (A) Large size of aneurysm. (B) Multiple aneurysm.

 Aneurysm location

Nine, ten, and eight studies reported the roles of the ACA, MCA, and VABA versus the ICA, respectively, in the risk of aneurysm rupture in patients with UIA (Figure 7). ACA (OR: 3.34; 95% CI: 1.94–5.76; p < 0.001), MCA (OR: 2.16; 95% CI: 1.73–2.69; p < 0.001), and VABA (OR: 2.20; 95% CI: 1.24–3.91; p = 0.007) were associated with an increased risk of aneurysm rupture. There was significant heterogeneity in ACA (I2 = 74.7%; p < 0.001) and VABA (I2 = 49.5%; p = 0.054); in contrast, there was no heterogeneity in the MCA (I2 = 0.0%; p = 0.819). Sensitivity analyses indicated that the pooled conclusions regarding the roles of ACA, MCA, and VABA in the risk of aneurysm rupture were stable (Supplementary File 1). The subgroup analyses indicated that the roles of ACA and MCA in the risk of aneurysm rupture were consistent with the overall analysis of all subgroups. VABA was not associated with the risk of aneurysm rupture when pooled studies were designed as retrospective cohorts, a follow-up of ≥3.0 years, and high-quality studies (Table 2). There was no significant publication bias for ACA (p-value for Egger: 0.811; p-value for Begg: 0.602), MCA (p-value for Egger: 0.845; p-value for Begg: 0.858), or VABA (p-value for Egger: 0.146; p-value for Begg: 0.386; Supplementary File 2).

Effect of aneurysm location on the risk of aneurysm rupture in patients with unruptured intracranial aneurysms (UIA).

 Discussion

The predictors of aneurysm rupture in patients with UIA should be further identified to screen patients at high risk of aneurysm rupture. Here, we performed a large quantitative study to identify 17,069 patients with UIA and 2,699 aneurysm ruptures in 18 studies and reviewed the characteristics of studies or patients across a broad range. We determined that large aneurysms, ACA, MCA, and VABA were associated with an increased risk of aneurysm rupture; in contrast, hyperlipidemia and a family history of SAH played a protective role in the risk of aneurysm rupture. Furthermore, age, sex, current smoking status, hypertension, DM, a history of SAH, and multiple aneurysms were not associated with the risk of aneurysm rupture. Finally, the region, study design, follow-up, and study quality could predict the risk of aneurysm rupture in patients with UIA.

Several meta-analyses have investigated potential predictors of aneurysm rupture risk in patients with UIA (5, 9–11). Greving et al. (5) identified six prospective studies and found that the predictors of aneurysm rupture included age, hypertension, a history of SAH, aneurysm size, aneurysm location, and geographic region. Han et al. (9) identified 15 studies and found that wall shear stress, oscillatory shear index, and low shear index could affect the risk of aneurysm rupture in patients. Shu et al. (10) identified four studies reporting machine learning algorithms for rupture risk in patients with UIA and found that the diagnostic value of machine learning algorithms was excellent, with sensitivity and specificity of 84% and 78%, respectively. Guo et al. (11) identified eight studies and found that aspirin plays a protective role against the risk of growth and rupture of aneurysms in patients with UIA. However, these studies did not perform exploratory analyses, and the predictors of aneurysm rupture in patients with UIA should be further explored.

The study indicates that age and sex were not associated with aneurysm rupture risk in patients with UIA. However, subgroup analyses showed that younger age was associated with a lower risk of aneurysm rupture when the follow-up was <3.0 years, inconsistent with the findings of a prior meta-analysis (5). This discrepancy could be explained by variations in the reference age group, which may have affected the estimated effect of age on the risk of aneurysm rupture. Moreover, female patients were associated with an increased risk of aneurysm rupture as compared with male patients when pooled from prospective cohort studies and a follow-up of <3.0 years; this might be due to the higher prevalence of UIA in women compared to men and the accelerated growth rate in women, which was associated with an increased risk of aneurysm rupture (40). Additionally, the risk of aneurysm rupture was not affected by smoking status, hypertension, and DM. Exploratory analysis revealed that current smoking was associated with an increased risk of aneurysm rupture when pooled studies were conducted in Western countries, studies with retrospective cohorts, and a follow-up of ≥3.0 years. This observation could be because smoking is associated with an acute increase in blood pressure for nearly 3 h, and this transient increase might play an important role in the risk of aneurysm rupture (41). Moreover, long-term smoking can change the formation of aneurysms by weakening the vessel walls of cerebral arteries (42). Hypertension was associated with an increased risk of aneurysm rupture in pooled prospective cohort studies, inconsistent with a previous meta-analysis (5), which could be explained by the use of antihypertensive agents, which is associated with a reduced risk of aneurysm rupture (43). Finally, the subgroup analyses showed that DM plays a protective role in the risk of aneurysm rupture when pooled with high-quality studies, which might be affected by hypoglycemic drugs in patients with DM.

This study showed that hyperlipidemia was associated with a reduced risk of aneurysm rupture, which could be explained by the use of statins that reduce the risk of aneurysm rupture through lipid-lowering effects, anti-inflammation of the vasculature, and the ability to stimulate ECM production of extracellular matrix (44–46). Moreover, a history of SAH was not associated with the risk of aneurysm rupture, indicating that aneurysm rupture did not interact with other aneurysms in patients with multiple aneurysms. Notably, we determined that a family history of SAH was associated with a reduced risk of aneurysm rupture, which could be explained by careful monitoring to prevent rupture. Furthermore, the risk of aneurysm rupture can be affected by the size and location of the aneurysm, consistent with prior meta-analyses (5).

This study has some limitations. First, both prospective and retrospective cohort studies were included, and the results may have been affected by selection and recall biases. Second, the reference groups for age and aneurysm size differed across the included studies, which might have affected the estimates for these predictors. Third, the analyses included both crude data and adjusted results, and the adjusted variables might have affected the risk of aneurysm rupture. Fourth, the risk of aneurysm rupture differed according to the location and morphology of aneurysms. Fifth, the heterogeneity among the included studies was not fully explained by sensitivity and subgroup analyses, which could be explained by the different disease statuses of UIA. Finally, there was inevitable publication bias and a restricted detailed meta-analysis of published articles.

This study showed that the predictors of aneurysm rupture in patients with UIA included hyperlipidemia, a family history of SAH, a large-size aneurysm, ACA, MCA, and VABA. However, age, sex, smoking status, hypertension, DM, a history of SAH, and multiple aneurysms did not affect the risk of aneurysm rupture in patients with UIA. The roles of these predictors for the aneurysm rupture risk could be affected by the region, study design, follow-up, and study quality.

 Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

 Ethics statement

All analyses were based on previous published studies, thus no ethical approval and patient consent are required.

 Author contributions

JM: Conceptualization, Data curation, Formal analysis, Writing – original draft. YZ: Conceptualization, Data curation, Formal analysis, Writing – original draft. PL: Data curation, Formal analysis, Writing – original draft. TZ: Data curation, Formal analysis, Writing – original draft. ZS: Data curation, Formal analysis, Writing – original draft. TJ: Data curation, Formal analysis, Writing – original draft. AL: Conceptualization, Formal analysis, Project administration, Writing – review & editing.

 Conflicts of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

 Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

 Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fneur.2023.1268438/full#supplementary-material

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