Impact of Kidney Function and Kidney Volume on Intracranial Aneurysms in Patients with Autosomal Dominant Polycystic Kidney Disease

doi:10.21203/rs.3.rs-1739950/v1

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Research Article

Impact of Kidney Function and Kidney Volume on Intracranial Aneurysms in Patients with Autosomal Dominant Polycystic Kidney Disease

https://doi.org/10.21203/rs.3.rs-1739950/v1

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Background

To date, only a personal or family history of intracranial aneurysm/subarachnoid hemorrhage (IA/SAH) has been established as a risk factor for IA in autosomal dominant polycystic kidney disease (ADPKD). Recently, an association between splicing/frameshift mutations, which are reportedly associated with declining kidney function/increased total kidney volume (TKV), and IAs in patients with ADPKD was reported.

Objective

To confirm the association between kidney function/volume and IAs in patients with ADPKD.

Methods

This study included 519 patients with ADPKD. Kidney function, TKV, and general risk factors for IA were assessed for associations with IA formation.

Results

At baseline IA screening, the median age, estimated glomerular filtration rate, and TKV were 44 years, 54.5 mL/min/1.73 m², and 1054.3 mL, respectively. A family IA/SAH history was confirmed in 18.1% patients, and 54.3% patients had hypertension. IA point prevalence was 12.5%. During a clinical follow-up of 3104 patient-years, de novo IA was detected in 29 patients (0.93% patient-years). IA period prevalence was 18.1% (median age, 60 years). Multivariable logistic regression analyses demonstrated that TKV ≥ 1000 mL (odds ratio [OR] = 2.81), height-adjusted TKV ≥ 500 mL (OR = 2.81), Mayo 1D–1E (OR = 2.52), and chronic kidney disease stages 3–5 (OR = 2.31) were significantly associated with IA formation.

Conclusions

IAs in patients with ADPKD may be associated with risk factors for IAs in the general population as well as declining kidney function and increased kidney volume. Kidney disease progression may contribute to effective IA screening and treatment planning in patients with ADPKD.

autosomal dominant polycystic kidney disease

intracranial aneurysm

kidney dysfunction

kidney volume

Mayo imaging classification

subarachnoid hemorrhage

The prevalence of intracranial aneurysm (IA) is higher in patients with autosomal dominant polycystic kidney disease (ADPKD) (9–23%) [1–6] than in the general population (2–4%) [7, 8]. Female sex, increased age, subarachnoid hemorrhage (SAH) history, and ADPKD [9, 10] have been identified as IA risk factors in the general population; nonetheless, to date, only a personal or family IA/SAH history has been established as a risk factor for IA in patients with ADPKD [11]. Until recently, universal IA screening in patients with ADPKD was not recommended by nephrologists [12, 13]. Therefore, in regions where targeted screening is performed, understanding the overall IA picture in patients with ADPKD can be difficult because it is strongly affected by selection bias. In contrast, universal IA screening for patients with ADPKD has generally been conducted and recommended in Japan [14, 15]. ADPKD itself is a risk factor for IA formation in the general population [9, 10], and and mutation in PKD1 and PKD2 and its genotypes affect total kidney volume (TKV) [16], kidney disease severity [17–21], and IA [22, 23], which suggests that factors associated with ADPKD, including mutations in PKD1 and PKD2, TKV, and kidney function are also probable risk factors for IA in patients with ADPKD. We hypothesized that due to its genetic etiology, increased kidney volume and declining kidney function are more responsible for IA formation in patients with ADPKD than are general IA risk factors (such as female sex, increased age, and hypertension). In this study, we analyzed the IA/SAH point and period prevalence, novel IA/SAH incidence, and risk factors for IA in a relatively large cohort of patients with ADPKD at a single Japanese institution.

Study Design

We reviewed the records of 586 outpatients with ADPKD who visited the Kidney Center, Tokyo Women’s Medical University Hospital (Tokyo, Japan), between July 2003 and July 2019. Our facility has been conducting universal IA screening since the 2000s. Universal screenings have been conducted every 3–5 years in patients with ADPKD; if IAs are detected, follow-up magnetic resonance angiography (MRA) is performed every 1–2 years [14, 15, 24]. After excluding 67 patients who did not undergo an MRA intracranial examination, 519 patients were included in the study (Fig. 1; screening ratio, 88.6%). All procedures were approved by the Research Ethics Committee of Tokyo Women’s Medical University (No. 5118) and were in accordance with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Passive informed consent (opt-outs) was obtained from the patients. All data were analyzed anonymously. The participants were followed up until October 31, 2020.

Covariate Assessments

During a regular outpatient clinic visit, anthropometric and physical examinations were conducted, including blood-pressure, height, and weight assessments. All biochemical analyses were performed on samples obtained from patients after overnight fasting. The estimated glomerular filtration rate (eGFR) for Japanese patients was calculated using a previously described formula [25]. IA and TKV assessments and comorbidity definitions are presented in Online Resource 1.

Outcome Evaluations

The primary endpoint was IA formation/SAH confirmed by universal MRA screening or medical records. The risk of de novo IA formation was calculated as follows: de novo saccular aneurysm formation in MRA screening divided by the mean follow-up in years. Similarly, SAH risk per patient-year was calculated as follows: SAH incidence in the entire population divided by the mean follow-up in years.

Statistical Analyses

Continuous variables are expressed as means ± standard deviations or medians (range), while discrete variables are expressed as percentages. The Mann–Whitney U-test or unpaired t-test was performed for continuous variables after assessing data normality. The chi-square or Fisher’s exact test was used to analyze categorical variables. Logistic regression analyses were performed to determine factors associated with IA diagnosis. Multivariable logistic regression models were used to estimate the associated risk of IA diagnosis. The variables of interest and general risk factors for outcomes based on existing knowledge were included in the multivariable model. Since kidney volume, Mayo imaging classification, and kidney function demonstrated strong correlations [26, 27], we constructed four multivariate logistic models separately, considering multicollinearity [28]. Standard methods were used to estimate the sample size for multivariable logistic regression with ≥ 5 outcomes required for each independent variable [29, 30]. Discriminatory ability was measured using the area under the receiver operating characteristic curve (AUC). Goodness-of-fit was assessed using McFadden’s pseudo-R-squared (pseudo-R²) [31] and small-sample-corrected Akaike’s information criterion [32]. The time from birth to IA diagnosis was computed using the Kaplan–Meier method and evaluated using the log-rank test. Considering the study’s exploratory nature, we did not adjust for multiplicity. Statistical significance at 5% was considered a marker for potential further investigation. All statistical tests were two-tailed, and all statistical analyses were performed using JMP Pro software (version 15.0.0; SAS Institute, Cary, NC, USA).

Patient Characteristics

The entire cohort’s patient characteristics are summarized in Table 1 and Online Resource 2. During baseline IA screening, the median age, eGFR, and TKV were 44 years, 54.5 mL/min/1.73 m², and 1054.3 mL, respectively. A family IA/SAH history was confirmed in 94 (18.1%) patients, and 282 (54.3%) patients had hypertension. IA and SAH point prevalence among the 519 patients with ADPKD at baseline screening was 12.5% (65 patients) and 3.1% (16 patients), respectively. During a clinical follow-up of 3104 patient-years in these 519 patients, de novo IAs were detected in 29 patients (0.93% [95% confidence interval (CI), 0.62–1.34%] patient-years for saccular IAs), and three patients had IA rupture (0.10% [95% CI, 0.02–0.28%] patient-years). Accordingly, at the time of the last follow-up (median, 60 years), IA and SAH period prevalence among the 519 patients with ADPKD was 18.1% (94 patients) and 3.7% (19 patients), respectively.

Comparative analyses with and without IA revealed that the frequency of family IA/SAH history was higher among patients with IAs than among those without (28.7% vs. 15.8%, P=0.0032). Baseline hypertension (70.2% for patients with IA vs. 50.8% for those without, P=0.0006) was more frequent and the age was older (47.5 vs. 43 years, P=0.0052) in the aneurysm group. Regarding kidney findings during baseline IA screening, eGFR was significantly lower in patients with IA (35.2 mL/min/1.73 m²) than in those without (59.0 mL/min/1.73 m²; P<0.0001), and TKV was significantly higher in patients with IA than in those without (1459.0 mL with IA vs. 947.9 mL without IA; P<0.0001). The proportions of patients with chronic kidney disease (CKD) stages 3–5 (73.4% with IA vs. 51.3% without IA, P<0.0001) and those with Mayo imaging classification Class 1D–1E (38.0% with IA vs. 24.6% without IA, P=0.0154) were higher in the aneurysm group.

Characteristics of Patients with IAs

IA-associated patient and aneurysm characteristics are shown in Table 2. Ninety-four patients were diagnosed at a median age of 46 (range, 18–81) years, and 24 (25.5% of patients with IA) presented with multiple aneurysms. All IAs were small (maximum IA diameter <10 mm), with a median maximum IA diameter of 3.5 (range, 2.0–8.3) mm. The most frequent IA site was the middle cerebral artery in the anterior circulation. Nineteen patients (20.2%) experienced aneurysm rupture, and the median age at the time of rupture was 39 (range, 29–71) years. Treatment included neurosurgical procedures with IA clipping or coiling in 51 (54.3%) patients (clipping, 42 patients; coiling, nine patients).

IA/SAH and Risk-Factor Associations

First, we investigated the relationship between the progression of ADPKD-related factors and IA/SAH. Thus, risk factors for IA in the general population as well as ADPKD-related factors, including TKV (<1000 mL, 1000–1500 mL, and ≥1500 mL), height-adjusted TKV (htTKV) (<500 mL, 500–1000 mL, and ≥1000 mL), Mayo imaging classification (Classes 1A, 1B–1C, and 1D–1E), and CKD stages (1–2, 3, and 4–5), were examined using age-adjusted logistic regression analyses (Online Resource 3, Figure 2). As the TKV (Figure 2A–2B) and htTKV increased (Figure 2C–2D), and as the Mayo class (Figure 2E–2F) and CKD stage advanced (Figure 2G–2H), the odds ratios for IA/SAH increased.

Multivariable logistic regression analyses using the general risk factors for IA, as well as TKV, htTKV, Mayo classification, or CKD stage, were performed for IA formation (Table 3 and Online Resource 4, upper part). In the model using general risk factors for IA, hypertension (OR=2.58, P=0.0006) and family history of IA/SAH (OR=2.41, P=0.0013) were significantly associated with IA formation (McFadden’s pseudo-R²=0.06, AUC=0.66). Adding TKV to the model of general risk factors increased the AUC to 0.72 and the pseudo-R² value to 0.11. The TKV (100 mL increase; OR=1.05, P<0.0001) was significantly associated with IA formation, indicating that adding TKV improved the model’s discriminatory ability and goodness-of-fit to predict IAs. Similarly, adding htTKV, Mayo 1D–1E, and eGFR to the model of general risk factors also increased the AUC (0.72, 0.71, and 0.70, respectively) and pseudo-R² value (0.11, 0.10, and 0.08, respectively). The htTKV (100-mL increase; OR=1.09, P<0.0001), Mayo 1D–1E (OR=2.90, P=0.0012), and eGFR (10 mL/min/1.73 m² decrease; OR=1.21, P=0.0004) were significantly associated with IA diagnosis. Therefore, adding htTKV, Mayo 1D–1E, and eGFR improved the model’s discriminatory ability and goodness-of-fit to predict IAs. Similarly, multivariable logistic regression analyses based on binary data confirmed ADPKD-related factors, including TKV ≥1000 mL (OR=2.81, P=0.0006), htTKV ≥500 mL (OR=2.81, P=0.0018), Mayo 1D–1E (OR=2.52, P=0.0037), and CKD stages 3–5 (OR=2.31, P=0.0062) to be significantly associated with IA formation (Table 3; Online Resource 4, lower part; Online Resource 5).

In the age-specific Kaplan–Meier model, which was based on the age at IA confirmation (Figure 3), the IA-free survival rates demonstrated no differences between men and women, especially before the age of 50 years (Figure 3A). In contrast, the IA-free survival rates in patients with a family history of IA/SAH and Mayo 1D–1E were significantly lower than those in patients without a family history of IA/SAH and without Mayo 1D–1E, even before the age of 50 years (Figure 3B–C; log-rank, P=0.00025, log-rank, P<0.0001, respectively).

ADPKD, the most common progressive hereditary kidney disease [20, 27], causes cyst formation in the kidneys, leading to various extrarenal complications, including liver cysts [33], hypertension, and IAs. Generally, patients with ADPKD carry a germline mutation in one allele of either PKD1 or PKD2 [17–19]. This study revealed multiple IA risk factors in patients with ADPKD. To the best of our knowledge, this is the first study to confirm the association between IA/SAH and kidney function in patients with ADPKD. Multivariable analyses demonstrated that a family history of IA/SAH, hypertension, TKV/htTKV increase (or TKV ≥ 1000 mL/htTKV ≥ 500 mL), Mayo 1D–1E, and decrease in eGFR (or CKD stages 3–5) were significantly associated with IA diagnosis.

Thus far, as IA prevalence and the risk of small IA ruptures have been considered to be low, indications for IA screening in patients with ADPKD have been limited to those with a family history of IA/SAH, previous IA rupture, a high-risk profession (e.g., airline pilots), and anxiety despite adequate information [12, 13]. However, the considerable variability in IA prevalence (9–23%) in patients with ADPKD [1–3] indicates the need for more information regarding this issue. First, it is difficult to determine accurate IA prevalence and risk levels in patients with ADPKD who have undergone targeted screening, which is theoretically prone to selection bias. Furthermore, accurate information regarding family history of IA/SAH is indeterminable without universal IA screening. Therefore, research reports from regions where universal IA screenings are conducted may be useful.

Recently reported risk factors for IA in patients with ADPKD based on the results of multivariable analyses include: family history of hemorrhagic stroke or IA (355 patients in China)[1]; TKV (265 patients in Japan) [5]; age, female sex, dolichoectasia, and mitral inflow deceleration time for a limited subgroup of high-risk aneurysms (926 patients in Korea) [6]; and age > 45 years (83 patients in Poland) [3]. However, no reports have confirmed the association between kidney function and IA/SAH in patients with ADPKD. In this study, age, female sex, hypertension, TKV, htTKV, Mayo imaging classification of ADPKD, and kidney function showed independent associations with IAs in patients with ADPKD, and our cohort’s large size probably contributed to the results. Hypertension, TKV, htTKV, Mayo imaging classification of ADPKD, and kidney function showed independent associations with IA in all evaluated models, while associations of age or female sex with IA were model dependent. As adding ADPKD-related risk factors to general IA risk factors improved the model’s discriminatory ability and goodness-of-fit to predict IAs, ADPKD-related risk factors such as kidney function/volume could be potentially more important IA risk factors in patients with ADPKD than are general IA risk factors.

We recently conducted a detailed analysis of genetic factors, including mutation types, in ADPKD patients with IA and found an association between mutation type such as splicing/frameshift mutations and IAs in patients with ADPKD [23]. As splicing/frameshift mutations are significantly associated with large TKV [16], advanced classes of the Mayo imaging classification [16], and a poor renal prognosis [20], patients with ADPKD with progressive kidney dysfunction or increasing TKV could have splicing/frameshift mutations, and consequently, be at risk of IA formation.

Limitations

This study has some limitations. First, it was an observational study, and a causal relationship could not be proven for our observations. TKV values were calculated using an ellipsoid formula instead of manual planimetry. Furthermore, although this study’s strength was its ability to evaluate the vast amount of data stored in the electronic medical records, smoking history was not evaluated. However, on analyzing 135 patients with ADPKD who underwent genetic testing as part of a subgroup analysis in this study, smoking was not observed to be associated with IA in patients with ADPKD [23].

In this study, IA in patients with ADPKD was associated with general risk factors for IA as well as declining kidney function and increased kidney volume. The factors observed to be associated with IA in our study may contribute to effective IA screening and treatment planning in patients with ADPKD.

Funding: This study was supported in part by a Grant-in-Aid for Intractable Renal Diseases Research and Research on Rare and Intractable Diseases as well as by Health and Labor Sciences Research Grants from the Ministry of Health, Labor and Welfare of Japan.

Competing Interests

Toshio Mochizuki received honoraria for lectures from Otsuka Pharmaceutical Co. Toshio Mochizuki, and Hiroshi Kataoka belonged to an endowed department sponsored by Otsuka Pharmaceutical Co., Chugai Pharmaceutical Co., Kyowa Hakko Kirin Co., and JMS Co. The remaining authors have no relevant financial or non-financial interests to disclose.

Ethics Approval

This retrospective chart review study involving human participants was in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Research Ethics Committee of Tokyo Women’s Medical University (No. 5118).

Consent to Participate

Passive informed consent (opt-outs) was obtained from the patients.

Consent to Publish
Not applicable

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available because they contain information that could compromise the privacy of research participants.

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Table 1. Patients’ characteristics according to the presence or absence of intracranial aneurysm

Variables	Entire cohort n = 519	Patients with IAs n = 94	Patients without IAs n = 425	P–value
*Clinical Findings*
Age at the time of first screening (years)	44 (12–86) [519]	47.5 (18–77)	43 (12–86)	0.0052*
Follow-up duration (years)	5.98 ± 4.78 [519]	5.92 ± 4.86	5.99 ± 4.76	0.8971
Age at the time of last follow-up (years)	50 (13–88) [519]	53 (19–83)	49 (13–88)	0.0089*
Female sex., n (%)	284 (54.7) [519]	55 (58.5)	229 (53.9)	0.4146
Family history of IA or SAH, n (%)	94 (18.1) [519]	27 (28.7)	67 (15.8)	0.0032*
*Brain Findings*
Total IA, n (%)	94 (18.1) [519]	94 (100.0)	0 (0.0)	NA
Baseline IA, n (%)	65 (12.5) [519]	65 (69.2)	0 (0.0)	NA
IA during follow-up, n (%)	29 (5.6) [519]	29 (30.9)	0 (0.0)	NA
Total SAH, n (%)	19 (3.7) [519]	19 (20.2)	0 (0.0)	NA
Baseline SAH, n (%)	16 (3.1) [519]	16 (17.0)	0 (0.0)	NA
SAH during follow-up, n (%)	3 (0.6) [519]	3 (3.2)	0 (0.0)	NA
*Kidney Findings*
eGFR (mL/min/1.73 m²)	54.5 (3.0–150.1) [519]	35.2 (3.1–125.8)	59.0 (3.0–150.1)	<0.0001*
Blood urea nitrogen (mg/dL)	18.4 (2.9–109.4) [518]	23.7 (9.9–91.3)	17.1 (2.9–109.4)	<0.0001*
CKD3–5, n (%)	287 (55.3) [519]	69 (73.4)	218 (51.3)	<0.0001*
U-Prot (g/g･Cre)	0.07 (0.00–10.32) [517]	0.15 (0.00–7.14)	0.06 (0.00–10.32)	0.0030*
TKV (mL)	1054.3 (196.4–8695.2) [449]	1459.1 (431.2–8695.2)	947.9 (196.4–5920.4)	<0.0001*
TKV ≥1000 mL	237 (52.8) [449]	59 (73.8)	178 (48.2)	<0.0001*
htTKV (mL)	652.4 (129.2–5023.2) [436]	963.8 (288.5–5023.2)	599.6 (129.2–3482.6)	<0.0001*
htTKV ≥500 mL	271 (62.2) [449]	64 (81.1)	207 (59.7)	<0.0001*
Mayo imaging classification Class1D–1E, n (%)	116 (27.0) [429]	30 (38.0)	86 (24.6)	0.0154*
*Comorbidities*
Hypertension, n (%)	282 (54.3) [519]	66 (70.2)	216 (50.8)	0.0006*
Hyperuricemia, n (%)	157 (30.3) [519]	42 (44.7)	115 (27.1)	0.0008*
Low HDL cholesterol, n (%)	73 (14.1) [519]	21 (22.3)	52 (12.2)	0.0108*

*P < 0.05. Continuous values are expressed as the mean ± standard deviation or median (range). Discrete data are expressed as n (%). Values for numbers of subjects are shown in [].

Abbreviations: IA, intracranial aneurysm; n, number; %, percentage; SAH, subarachnoid hemorrhage; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; U-Prot, urinary protein excretion; TKV, total kidney volume; htTKV, height-adjusted total kidney volume; HDL, high-density lipoprotein

Table 2 Characteristics of aneurysms and patients with IAs (n=94)

Patient characteristics associated with IA/SAH
IA
Age at diagnosis of IAs (years)	46 (18–81)
Multiple IAs at baseline screening, n (%)	14 (14.9)
Multiple IAs during follow-up, n (%)	10 (10.6)
Numbers of IAs	1 (1–6)
Size of the largest aneurysm: maximum IA diameter (mm)	3.5 (2.0–8.3)
Treatments, n (%)	51 (54.3)
Clipping, n (%)	42 (44.7)
Coiling, n (%)	9 (9.6)
SAH
SAH, n (%)	19 (20.2)
Age at SAH (years)	39 (29–71)

Location of the IAs
Anterior circulation, n (%)	73 (66.4) {110}
A-com, n (%)	10 (9.1) {110}
ACA, n (%)	8 (7.3) {110}
MCA, n (%)	34 (30.9) {110}
ICA, n (%)	21 (19.1) {110}
Posterior communicating artery, n (%)	16 (14.5) {110}
IC-PC, n (%)	16 (14.5) {110}
Posterior circulation, n (%)	21 (19.1) {110}
BA, n (%)	9 (8.2) {110}
VA, n (%)	7 (6.4) {110}
PICA, n (%)	3 (2.7) {110}
PCA, n (%)	2 (1.8) {110}

Continuous values are expressed as the median (range). Discrete data are expressed as n (%). Values of numbers of IAs where the location were identified are shown in {}.

Abbreviations: IA, intracranial aneurysm; SAH, subarachnoid hemorrhage; n, number; %, percentage; A-com, anterior communicating artery; ACA, anterior cerebral artery; MCA, middle cerebral artery; ICA, internal carotid artery; IC-PC, internal carotid-posterior communicating artery; BA, basilar artery; VA, vertebral artery; PICA, posterior inferior cerebellar artery; and PCA, posterior cerebral artery

Table 3. Multivariable logistic regression analyses for correlations between a diagnosis of intracranial aneurysm and risk factors

	General Risk Factors (n = 519)		General Risk Factors With TKV (n = 449)		General Risk Factors With eGFR (n = 519)
	(AICc = 472.8, pseudo-R²=0.06, AUC=0.66)		(AICc = 385.9, pseudo-R²=0.11, AUC=0.72)		(AICc = 461.8, pseudo-R²=0.08, AUC=0.70)
Variables	Odds Ratio (95% CI)	P-Value	Odds Ratio (95% CI)	P-Value	Odds Ratio (95% CI)	P-Value
Female (vs. male)	1.58 (0.97–2.58)	0.0677	1.93 (1.08–3.46)	0.0270*	1.91 (1.15–3.17)	0.0128*
Hypertension	2.58 (1.50–4.43)	0.0006*	2.15 (1.16–3.99)	0.0154*	2.05 (1.17–3.57)	0.0116*
Family history of IA or SAH	2.41 (1.41–4.14)	0.0013*	2.91 (1.59–5.31)	0.0005*	2.46 (1.42–4.25)	0.0013*
Age (10-year increments)	1.14 (0.96–1.36)	0.1224	1.16 (0.95–1.42)	0.1496	0.91 (0.73–1.13)	0.3967
TKV (100 mL increase)	NA	NA	1.05 (1.03–1.08)	<0.0001*	NA	NA
eGFR (10 mL/min/1.73 m² decrease)	NA	NA	NA	NA	1.21 (1.09–1.35)	0.0004*
	General Risk Factors (n = 519)		General Risk Factors With TKV ≥1000 mL (n = 449)		General Risk Factors With CKD3–5 (n = 519)
	(AICc = 473.5, pseudo-R²=0.06, AUC=0.66)		(AICc = 391.9, pseudo-R²=0.10, AUC=0.72)		(AICc = 467.8, pseudo-R²=0.07, AUC=0.69)
Variables	Odds Ratio (95% CI)	P-Value	Odds Ratio (95% CI)	P-Value	Odds Ratio (95% CI)	P-Value
Female (vs. male)	1.55 (0.95–2.54)	0.0786	1.64 (0.94–2.86)	0.0786	1.76 (1.06–2.92)	0.0278*
Hypertension	2.70 (1.58–4.60)	0.0003*	2.30 (1.25–4.22)	0.0071*	2.25 (1.30–3.89)	0.0037*
Family history of IA or SAH	2.45 (1.43–4.19)	0.0011*	3.04 (1.68–5.49)	0.0002*	2.35 (1.36–4.05)	0.0021*
Age ≥ 50 years	1.38 (0.85–2.33)	0.1889	1.27 (0.74–2.18)	0.3769	0.97 (0.57–1.66)	0.9178
TKV ≥1000 mL	NA	NA	2.81 (1.56–5.09)	0.0006*	NA	NA
CKD3–5	NA	NA	NA	NA	2.31 (1.27–4.19)	0.0062*

*P < 0.05. Variables of general risk factors for intracranial aneurysms and TKV, and eGFR were included in the multivariable models. Abbreviations: n, number; TKV, total kidney volume; eGFR, estimated glomerular filtration rate; CI, confidence interval; P, calculated probability; AICc, small-sample corrected Akaike Information Criterion; pseudo-R², McFadden’s pseudo-R-squared; AUC, area under the receiver operating characteristic curve; IA, intracranial aneurysm; SAH, subarachnoid hemorrhage; NA, not applicable

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Impact of Kidney Function and Kidney Volume on Intracranial Aneurysms in Patients with Autosomal Dominant Polycystic Kidney Disease

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