Risk factors for intracranial hemorrhage after mechanical thrombectomy: a systematic review and meta-analysis

ABSTRACT

Background: Intracerebral hemorrhage (ICH) is the most feared complication of mechanical thrombectomy (MT). This study aims to provide a comprehensive overview of ICH risk factors.

Methods: The authors systematically searched Pubmed and Embase (from inception to November 2018) for studies evaluating independent predictors for symptomatic ICH (sICH), parenchymal hematoma (PH), hemorrhagic infarction (HI), and any ICH after MT.

Results: This analysis included a total of 42 studies involving 10,001 patients. The combined rate was 8% (7–10%) for sICH, 13% (10–15%) for PH, 25% (20–29%) for HI, and 35% (31–39%) for any ICH. Meta-analysis identified the following predictors of sICH: female sex (OR 2.98, 95%CI 1.23–7.25, I² = 26.3%), treatment interval (OR 1.01, 95%CI 1–1.03, I² = 69.20%), tirofiban use (OR 3.16, 95%CI 2.11–4.73, I² = 0%), and ASPECTS score on admission (OR 0.63, 95%CI 0.54–0.74, I² = 0%). Predictors of any ICH were diabetes mellitus (OR 1.95, 95%CI 1.29–2.94, I² = 35.7%), deep white matter on diffusion-weighted imaging (OR 3.11, 95%CI 1.56–6.20, I² = 0%), and intravenous recombinant tissue plasminogen activator (rt-PA) (OR 2.57, 95%CI 1.28–5.17, I² = 0%).

Conclusion: Many predictors of ICH were identified, however, given the lack of robust evidence, larger cohort studies should be prioritized to confirm these predictors.

KEYWORDS:

• Mechanical thrombectomy
• endovascular treatment
• intracerebral hemorrhage
• risk factors

Author contributions

Z Hao designed the review, developed the search strategy, carried out the analysis and drafted the manuscript. C Yang undertook searches, selected trials for inclusion, appraised the quality of studies; extracted data from papers and carried out analysis and interpretation of the data. L Xiang selected trials for inclusion, extracted data from studies and checked the data. B Wu appraised the quality of studies, checked the data and revised the manuscript. M Liu designed the review, carried out interpretation of the data, and drafted the manuscript. All authors reviewed and revised the manuscript and provided their approval of the final version of the manuscript. All authors agree to be accountable for all aspects of the work.

Article highlights

• MT is a proven, effective therapy for AIS. ICH is the most severe complication of MT. In this study, we perform a systematic review and meta-analysis of ICH predictors after thrombectomy in AIS patients.

• There were five ICH criteria (ECASS I, ECASS II, ECASS III, Heidelberg Bleeding, SITS-MOST) and 13 cut-off time points for MT treatment among the different studies. A cut-off of 24 h after stroke onset was used in 35.7% of studies.

• Meta-analysis showed that the overall incidence of ICH was 8% (sICH), 13% (PH), 25% (HI), and 35% (any ICH) based on observational clinical studies.

• Many factors have been reported as predictors of ICH risk, but study methodologies vary widely. Meta-analysis showed that female sex, treatment interval, tirofiban, and ASPECTS score were predictive of sICH incidence, but no significant predictor was identified for PH.

• Many ICH predictors were identified for improving risk stratification of patients, but the evidence is still weak, and larger cohort studies should be prioritized to confirm these results.

Data availability

This is a systematic review and meta-analysis based on published results from individual studies. The data were extracted from the published studies, so individual patient data cannot be obtained. All data from this study are available from the corresponding author upon reasonable request.

Declaration of interest

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or conflict with the subject matter or materials discussed in this manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (81601012), Key Research and Development Programme, Science & Technology Department of Sichuan Province (Grant No. 2017SZ0007), the National Key Development Plan for Precision Medicine Research (2017YFC0910004), and 1·3·5 project for disciplines of excellence, West China Hospital, Sichuan University (ZYGD18009).