From GWAS to the clinic: risk factors for intracranial aneurysms

Subarachnoid hemorrhage (SAH) from a ruptured intracranial aneurysm is a devastating subset of stroke, occurring in relatively young people (mean age around 50 years) of whom around a third die within the initial weeks after the bleed. Environmental and genetic risk factors both have a role in SAH. A recent genome-wide association study of intracranial aneurysms in Finnish, Dutch and Japanese cohorts totaling 5,891 cases and 14,181 controls identified three new loci strongly associated with intracranial aneurysms on chromosomes 18q11.2 and 10q24.32, and replicated two previously found loci on chromosomes 8q11.23-q12.1 and 9p21.3. However, these five intracranial aneurysm risk loci identified so far explain only up to 5% of the familial risk of intracranial aneurysms, which makes genetic risk prediction tests currently unfeasible for intracranial aneurysms. New approaches, including identification of causal variants, rare variants and copy number variants, such as insertions and deletions, may improve genetic risk prediction for SAH and intracranial aneurysms. This may lead to diagnostic tools for identifying individuals at increased risk for aneurysm formation and rupture of aneurysms. In this way, genetic diagnostic tools will identify the people who will benefit most from screening by imaging studies for aneurysms and those who are most likely to benefit from preventive treatment of incidentally discovered aneurysms

Radiosurgical, neurosurgical, or no intervention for cerebral cavernous malformations: A decision analysis

Introduction We aimed to evaluate the preferred treatment strategy for patients with symptomatic cerebral cavernous malformations (CCM). Methods In a decision model, we compared neurosurgical, radiosurgical, and conservative management. A literature review yielded the risks and outcomes of interventions, intracerebral hemorrhage (ICH), and seizures. Patients with CCM rated their quality of life to determine utilities. We estimated the expected number of quality-adjusted life years (QALYs) and the ICH recurrence risk over five years, according to mode of presentation and CCM location (brainstem vs. other). We performed analyses with a time horizon of five years. Results Using the best available data, the expected number of QALYs for brainstem CCM presenting with ICH or focal neurological deficit was 2.84 (95% confidence interval [CI]: 2.54-3.08) for conservative, 3.01 (95% CI: 2.86-3.16) for neurosurgical, and 3.03 (95% CI: 2.88-3.18) for radiosurgical intervention; those for non-brainstem CCM presenting with ICH or focal neurological deficit were 3.08 (95% CI: 2.85-3.31) for conservative, 3.21 (95% CI: 3.01-3.36) for neurosurgical, and 3.19 (95% CI: 2.98-3.37) for radiosurgical intervention. For CCM presenting with epilepsy, QALYs were 3.09 (95% CI: 3.03-3.16) for conservative, 3.33 (95% CI: 3.31-3.34) for neurosurgical, and 3.27 (95% CI: 3.24-3.30) for radiosurgical intervention. Discussion and conclusion For the initial five years after presentation, our study provides Class III evidence that for CCM presenting with ICH or focal neurological deficit conservative management is the first option, and for CCM presenting with epilepsy CCM intervention should be considered. More comparative studies with long-term follow-up are needed

Aneurysm treatment within 6 h versus 6-24 h after rupture in patients with subarachnoid hemorrhage

BACKGROUND The risk of rebleeding after aneurysmal subarachnoid hemorrhage (aSAH) is the highest during the initial hours after rupture. Emergency aneurysm treatment may decrease this risk, but is a logistic challenge and economic burden. We aimed to investigate whether aneurysm treatment <6 h after rupture is associated with a decreased risk of poor functional outcome compared to aneurysm treatment 6-24 h after rupture. METHODS We used data of patients included in the ULTRA trial (NCT02684812). All patients in ULTRA were admitted within 24 h after aneurysm rupture. For the current study, we excluded patients in whom the aneurysm was not treated <24 h after rupture. We calculated crude and adjusted risk ratios (aRR) with 95% confidence intervals using Poisson regression analyses for poor functional outcome (death or dependency, assessed by the modified Rankin Scale) after aneurysm treatment <6 h versus 6-24 h after rupture. Adjustments were made for age, sex, clinical condition on admission (WFNS scale), amount of extravasated blood (Fisher score), aneurysm location, tranexamic acid treatment, and aneurysm treatment modality. RESULTS We included 497 patients. Poor outcome occurred in 63/110 (57%) patients treated within 6 h compared to 145/387 (37%) patients treated 6-24 h after rupture (crude RR: 1.53, 95% CI: 1.24-1.88; adjusted RR: 1.36, 95% CI: 1.11-1.66). CONCLUSION Aneurysm treatment <6 h is not associated with better functional outcome than aneurysm treatment 6-24 h after rupture. Our results do not support a strategy aiming to treat every patient with a ruptured aneurysm <6 h after rupture

Reliability of intracerebral hemorrhage classification systems: a systematic review

BACKGROUND: Accurately distinguishing non-traumatic intracerebral hemorrhage (ICH) subtypes is important since they may have different risk factors, causal pathways, management, and prognosis. We systematically assessed the inter- and intra-rater reliability of ICH classification systems. METHODS: We sought all available reliability assessments of anatomical and mechanistic ICH classification systems from electronic databases and personal contacts until October 2014. We assessed included studies' characteristics, reporting quality and potential for bias; summarized reliability with kappa value forest plots; and performed meta-analyses of the proportion of cases classified into each subtype. SUMMARY OF REVIEW: We included 8 of 2152 studies identified. Inter- and intra-rater reliabilities were substantial to perfect for anatomical and mechanistic systems (inter-rater kappa values: anatomical 0.78-0.97 [six studies, 518 cases], mechanistic 0.89-0.93 [three studies, 510 cases]; intra-rater kappas: anatomical 0.80-1 [three studies, 137 cases], mechanistic 0.92-0.93 [two studies, 368 cases]). Reporting quality varied but no study fulfilled all criteria and none was free from potential bias. All reliability studies were performed with experienced raters in specialist centers. Proportions of ICH subtypes were largely consistent with previous reports suggesting that included studies are appropriately representative. CONCLUSIONS: Reliability of existing classification systems appears excellent but is unknown outside specialist centers with experienced raters. Future reliability comparisons should be facilitated by studies following recently published reporting guidelines

Intracranial Aneurysm Classifier Using Phenotypic Factors: An International Pooled Analysis

Intracranial aneurysms (IAs) are usually asymptomatic with a low risk of rupture, but consequences of aneurysmal subarachnoid hemorrhage (aSAH) are severe. Identifying IAs at risk of rupture has important clinical and socio-economic consequences. The goal of this study was to assess the effect of patient and IA characteristics on the likelihood of IA being diagnosed incidentally versus ruptured. Patients were recruited at 21 international centers. Seven phenotypic patient characteristics and three IA characteristics were recorded. The analyzed cohort included 7992 patients. Multivariate analysis demonstrated that: (1) IA location is the strongest factor associated with IA rupture status at diagnosis; (2) Risk factor awareness (hypertension, smoking) increases the likelihood of being diagnosed with unruptured IA; (3) Patients with ruptured IAs in high-risk locations tend to be older, and their IAs are smaller; (4) Smokers with ruptured IAs tend to be younger, and their IAs are larger; (5) Female patients with ruptured IAs tend to be older, and their IAs are smaller; (6) IA size and age at rupture correlate. The assessment of associations regarding patient and IA characteristics with IA rupture allows us to refine IA disease models and provide data to develop risk instruments for clinicians to support personalized decision-making