Early Prediction of Malignant Brain Edema After Ischemic Stroke
Background and Purpose—
Malignant brain edema after ischemic stroke has high mortality but limited treatment. Therefore, early prediction is important, and we systematically reviewed predictors and predictive models to identify reliable markers for the development of malignant edema.
We searched Medline and Embase from inception to March 2018 and included studies assessing predictors or predictive models for malignant brain edema after ischemic stroke. Study quality was assessed by a 17-item tool. Odds ratios, mean differences, or standardized mean differences were pooled in random-effects modeling. Predictive models were descriptively analyzed.
We included 38 studies (3278 patients) with 24 clinical factors, 7 domains of imaging markers, 13 serum biomarkers, and 4 models. Generally, the included studies were small and showed potential publication bias. Malignant edema was associated with younger age (n=2075; mean difference, −4.42; 95% CI, −6.63 to −2.22), higher admission National Institutes of Health Stroke Scale scores (n=807, median 17–20 versus 5.5–15), and parenchymal hypoattenuation >50% of the middle cerebral artery territory on initial computed tomography (n=420; odds ratio, 5.33; 95% CI, 2.93–9.68). Revascularization (n=1600, odds ratio, 0.37; 95% CI, 0.24–0.57) were associated with a lower risk for malignant edema. Four predictive models all showed an overall C statistic >0.70, with a risk of overfitting.
Younger age, higher National Institutes of Health Stroke Scale, and larger parenchymal hypoattenuation on computed tomography are reliable early predictors for malignant edema. Revascularization reduces the risk of malignant edema. Future studies with robust design are needed to explore optimal cutoff age and National Institutes of Health Stroke Scale scores and to validate and improve existing models.
Malignant brain edema is a leading cause of early death after ischemic stroke,1 which occurs in 10% to 78% of patients with ischemic stroke.2 It is characterized by a malignant course of rapid neurological deterioration associated with massive cerebral swelling, leading to transtentorial herniation and death or poor functional outcome.3 Despite its devastating consequences, little evidence is available to inform prevention and management of malignant edema, apart from the decompressive hemicraniectomy.4
Given the lack of effective treatment, better understanding of the underlying pathophysiology and predictive factors for rapid deterioration could inform more accurate and faster prediction and, therefore, inform clinical practice for high-risk patients by the targeted implementation of more intensive monitoring and evidence-based interventions. A systematic review of predictors of life-threatening brain edema in ischemic stroke in 2008 identified 23 studies with 27 potential predictors and concluded that single predictors lacked sufficient predictive value.2 Since then several studies of new predictive factors and models have been published, and thus, we performed a systematic review and critical appraisal of the evidence to determine the clinical utility of the available single predictors and predictive models. In addition, we focused on the time when each potential predictor had been assessed because early identification of patients at risk is important to inform timely clinical decisions.
The data that support the findings of this study are available from the corresponding author on reasonable request. We followed the guidelines for MOOSE (Meta-analyses Of Observational Studies in Epidemiology) to complete and report this study.5 Study protocol is available from http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42017075701.
Search Strategies and Study Selection
We searched Ovid Medline (from 1946) and Embase (from 1974) in September 2017 and updated in March 2018, with search terms ‘ischemic stroke’ AND ‘severe OR malignant OR edema’ AND ‘predict*’ (search strategies in Methods in the online-only Data Supplement). One researcher (Dr S. Wu) reviewed all abstracts, and 2 researchers (Dr S. Wu, R. Yuan) independently reviewed all full texts of potentially eligible studies and scrutinized reference lists of relevant articles. Discrepancies were resolved through joint-reassessment and discussing with another researcher (C. Wei).
We included observational studies of adult patients with acute ischemic stroke, defined malignant edema as a syndrome of clinical worsening (or death or requirement for decompressive hemicraniectomy) with imaging evidence of brain swelling, measured at least 1 potential predictor or developed a predictive model for malignant edema, and published a full-text report in a peer-reviewed journal. Predictive models were defined as a score or scale with ≥2 variables to assess the risk of developing malignant edema, with the overall discrimination performance being reported. There were no language restrictions. Studies were excluded if outcomes were defined as imaging-based edema or as clinical worsening or death not attributable to brain edema, or if the study assessed cross-sectional associations.
For each included study, 2 researchers (Dr S. Wu, Y. Wang) independently assessed 6 domains (study participation, study attrition, potential predictor measurement, outcome measurement, flow and timing, and data analysis) with 17 items of potential biases (Table I in the online-only Data Supplement).
Odds ratios (ORs) and 95% CIs were extracted or calculated as the effect size for dichotomous variables and mean differences or standardized mean differences for continuous variables. Summary estimates of the strength of association were pooled by random-effects modeling. We had planned to estimate summary performance statistics of predictive models, but this was not performed because none of the included models had been externally validated. Heterogeneity was quantified by I2 and was stratified by inclusion criteria on stroke severity and on whether all patients had received reperfusion therapies; for imaging factors, heterogeneity was stratified by imaging modalities and assessment time (subgroup analysis in Methods in the online-only Data Supplement). Publication bias was explored by funnel plots, where the estimate of effect size was plotted on the horizontal axis and the SE of the log-transformed estimate of effect size on a reversed scale of the vertical axis. For predictive models, we descriptively analyzed data according to the CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies).6 For each model, we extracted or calculated C statistic for discrimination performance and sensitivity and specificity of each index score for classification performance. Statistical analyses were conducted in RevMan (Computer program), version 5.3 and Microsoft Office Excel 2007.
Post Hoc Analysis
We performed a post hoc literature search in May 2018 to identify randomized controlled trials (RCTs) to provide more robust evidence for the effect of reperfusion therapies and successful revascularization on the development of malignant edema (Methods in the online-only Data Supplement). Reperfusion therapies included either intravenous thrombolysis (ie, intravenous administration of alteplase or other thrombolytic agents) or endovascular interventions (ie, intraarterial thrombolysis, mechanical clot disruption or retrieval, or both). Revascularization was defined as either recanalization of the arterial occlusion or reperfusion of the downstream territory.7
Figure 1 shows literature search and study selection. We included 38 studies (31 cohort studies8–38 and 7 case-control studies,39–45 in 49 articles) with 3278 patients (mean age 49 to 78 years; male proportion 35%–74%). Study characteristics are summarized in Table II in the online-only Data Supplement. Twenty-five studies reported the assessment time for malignant edema, all within 30 days after stroke (median 6 days; interquartile range, 4–7).9–14,16,17,19,21–23,25,28,29,31–33,35,37,39–43 In 31 cohort studies, 31% (796/2546) of patients developed malignant edema (for individual studies: median 31%; range 10%–78%). We identified 24 clinical factors, 7 domains of imaging markers, 13 serum biomarkers, other physiological biomarkers, and 4 predictive models.
Of 17 items for the risk of bias, the most common bias lied in the inadequate sample size (high risk in all 38 studies), followed by nonprespecified (24 studies) or nonreported assessment time for edema (13 studies), and data presented in inappropriate forms (16 studies; Figure I in the online-only Data Supplement). We found asymmetry of funnel plots for potential predictors, with a trend towards symmetrical as the number of studies increases. For most plots, the individual effect sizes distributed symmetrically aside the pooled effect size, with most studies showed an SE of log(OR) around 0.5 or log(SEM) around 0.25 (Figure II in the online-only Data Supplement).
We identified 11 factors related to demographics or medical history, which could be collected from patients immediately after their admission (Table III in the online-only Data Supplement). Of these factors, only younger age was associated with malignant edema (n=2075; pooled mean difference, −4.42; 95% CI, −6.63 to −2.22 years),8,10,11,13,15,16,20,21,24,26–29,31,32,34–36,40–43 with heterogeneity (df=21, I2=88%, P<0.0001) that could not be explained by stroke severity (Figure 2A) or whether receiving reperfusion therapies (Figure 2B). Four studies each reported a cutoff age ranging from 60 to 75 years.9,18,42,46
We identified 11 stroke characteristics, which could be determined within 24 hours after admission (Table III in the online-only Data Supplement). Patients presenting with higher National Institutes of Health Stroke Scale (NIHSS) scores,8,10,12,15,20,24,26–28,30–33,35,37,43,44,46,47 depressed consciousness,9,21,25,27,36,45 gaze palsy,9,19,25,45 nausea or vomiting,21,41 or receiving ventilation16,19,48 were more likely to develop malignant edema, whereas there was no association with hemispheric lateralization of infarct,9,11–13,16,18,19,24–27,30,31,35–37,40,41,44,45,47 large arterial atherosclerosis,10,12,16,26–28,33,35–37,40,42,43 cardioembolism,10,12,16,19,26–28,33,35–37,40,42,43 headache,21,41 fever,21,41 or osmotic therapies.30,48 Fourteen studies reported median values of admission NIHSS (Table IV in the online-only Data Supplement): in unselected patients regarding stroke severity (n=568)8,12,28,43,44 and all but one study of patients with major artery occlusion (n=239),15,20,37 malignant group (median NIHSS all ≥17: 17–20) had higher NIHSS scores than nonmalignant group (median NIHSS all ≤15: 5.5–15); in all patients with clinically severe stroke (n=526; median NIHSS ≥17 in both groups in all studies)10,24,30,33,35 and 1 study of patients with major artery occlusion (n=52; median NIHSS ≤15 in both groups),27 higher NIHSS scores were not associated with further clinical deterioration. Nine studies reported cutoff values of NIHSS (11–20) with different measures of their predictive values for malignant edema.12,26,27,31,32,37,43,46,47
The post hoc search identified 10 additional studies for thrombolysis, endovascular interventions, and revascularization (Figure III and Table V in the online-only Data Supplement).49–58 Patients who had received intravenous thrombolysis showed a higher risk for developing malignant edema than those received control treatment in RCTs (n=4986; OR, 1.34; 95% CI, 1.01–1.77; df=4; I2=0%)49,52,53,56,58 but a lower risk in observational studies8,12,16,18,27,33–37 (Figure IV in the online-only Data Supplement). After excluding the single RCT reporting a significant association (n=3035; OR, 1.65; 95% CI, 1.12–2.45),58 the pooled association of the remaining RCTs was nonsignificant (n=1951; OR, 1.06; 95% CI, 0.71–1.60).49,52,53,56 RCTs identified no association between endovascular interventions and the development of malignant edema (n=938; OR, 0.94; 95% CI, 0.70–1.27; df=2; I2=0%),51,54,57 consistent with the findings in observational studies (Figure V in the online-only Data Supplement).12,15,16,27,30,33,35–37,43,44,56 Revascularization within 24 hours after onset was associated with a lower risk of malignant edema (n=1600; OR, 0.37; 95% CI, 0.24–0.57; df=12; I2=53%),15,18–20,29,34,35,47,50,54,55,59 where the association was significant regardless whether revascularization was defined as recanalization or reperfusion (Figure 3A) or whether all patients had received reperfusion therapies or not (Figure 3B).
Patients with malignant edema had a larger infarct volume on admission than those without (n=929; standardized mean difference, 2.57; 95% CI, 1.82–3.31; df=12; I2=93%; P<0.0001), where heterogeneity was explained by difference in imaging modalities (computed tomography [CT] versus diffusion-weighted imaging [DWI]; Figure 4A) and the time of DWI assessment (Figure 4B) but not CT time (Figure 4C).8,11,15,18,26,27,29,31,32,36,37,42,44 Five studies (n=335) measured DWI infarct volume within 14 hours after onset in patients with severe stroke and defined a cutoff volume (82–145 cm3), where the volume >145 cm3 showed the best predictive values (Table VI in the online-only Data Supplement).18,31,32,36,37
Six studies investigated parenchymal hypoattenuation on CT within 40 hours after stroke, where the extent >50% of the middle cerebral artery territory was associated with malignant edema (n=420; OR, 5.33; 95% CI, 2.93–9.68; df=3; I2=24%; P=0.27), with the larger extent indicating the stronger association (Figure 5)9,21,22,24,39,41 and the ischemia involving other territory increased the risk than middle cerebral artery alone (n=833; OR, 7.10; 95% CI, 4.53–11.14).16,21,24,29–31,33,41 The association between hypoattenuation >50% of the middle cerebral artery territory and malignant edema was significant both in patients with severe stroke (n=358; OR, 4.27; 95% CI, 2.63–6.94; df=2; I2=0%; P=0.72)21,24,41 and unselected stroke patients (n=62; OR, 20.08; 95% CI, 4.05–99.51)39 and regardless of whether CT was performed within 6 hours (n=157; OR, 5.54; 95% CI, 2.36–13.03),24,41 18 hours (n=62; OR, 20.08; 95% CI, 4.05–99.51),39 or 40 hours (n=201; OR, 3.78; 95% CI, 2.10–6.80)21 after stroke.
Six studies (n=737) reported controversial findings for the ASPECTS (Alberta Stroke Program Early CT Score).15,20,30,33,42,47 Other early infarct signs associated with malignant edema included moderate mass effect (ventricle compression)21,30,39,41,42,45 and major mass effect (midline shift39,42,45 or compression of basal cisterns30,39; 4 studies reported different cutoff values of midline shift17,32,46,48), but not hyperdense artery signs,21,22,30,39,41 minor mass effect (sulcal effacement),21,22,41,42 or basal ganglia involvement21–23,38,41 (Table III in the online-only Data Supplement). Brain atrophy was associated with a lower risk of malignant edema when defined by objective measures.23,32,60 Seven studies investigated hemorrhagic transformation21,28–30,34,35,44 but no association in the study specifically assessing the presence of hemorrhagic transformation before edema (P=0.18).21
In patients with clinically severe stroke, no association was found between the presence of proximal arterial occlusion and malignant edema (n=48; OR, 0.75; 95% CI, 0.10–5.44; df=1; I2=40%; P=0.20).24,59 In patients with arterial occlusion, more proximal site (n=399; OR, 4.89; 95% CI, 2.77–8.64; df=6; I2=19%; P=0.29),15,18,31,33–35,37 longer extent (n=224; OR, 3.78; 95% CI, 1.96–7.28; df=2; I2=0%; P=0.55),19,36,47 and more segments (n=294; OR, 4.05; 95% CI, 2.24–7.34; df=2; I2=0%; P=0.80)20,22,36 of occlusion were each associated with a higher risk of malignant edema. The malignant group had more severe deficits in cerebral blood perfusion within 24 hours after stroke than nonmalignant group, regardless of imaging modalities or measures used (Table VII in the online-only Data Supplement).8,9,12–14,24,25,27,36,59 In addition, patients with malignant edema had increased permeability of blood-brain barrier,8,34 poor collateral circulation,15,19,47 and more severe clot burden.47 Thirteen serum biomarkers were included in meta-analysis (Table III in the online-only Data Supplement),10,11,13,16,21,26,28,30,33,36,41–43,45,47 whereas available data for other physiological biomarkers were limited.11,13,26,28,33,35,42,44,61–64
Of 11 multifactorial models identified,11,20,21,28,30,33,35,36,46,60,65 4 models fulfilled our definition of predictive models,20,21,30,33 all included patients with severe stroke and assessed potential predictors within 24 hours after stroke (Table VIII in the online-only Data Supplement). Kasner index score21 and DASH score (DWI ASPECTS Score, Anterior Cerebral Artery Territory Involvement, M1 Susceptibility Vessel Sign, and Hyperglycemia)33 were development studies, and MBE score (Malignant Brain Edema)20 and EDEMA score (Enhanced Detection of Edema in Malignant Anterior Circulation Stroke)30 were studies of development with internal validation, but none was externally validated. Factors in Kasner score21 and EDEMA score30 were all routinely assessed on admission for stroke patients, whereas DASH score33 required DWI and MBE score20 required CT angiography. All models showed a C statistic of ≥0.70, while with a risk of overfitting because none satisfied the sample size criterion of >10 events per variable (Table IX in the online-only Data Supplement). Within the range of possible scores of each model, cutoff scores of Karsner score ≥2,21 DASH score ≥2,33 MBE score ≥4,20 and EDEMA score ≥330 showed the best classification considering both sensitivity and specificity (Table VIII in the online-only Data Supplement).
We provide a comprehensive review of predictors and predictive models for malignant brain edema after ischemic stroke, particularly focusing on the time when the data would be available for each predictor in practice. Despite that the included studies were generally small and some had methodological flaws, we found that younger age, higher admission NIHSS, and larger parenchymal hypoattenuation on initial CT were consistently associated with an increased risk of the development of malignant course and all routinely available within 6 hours after stroke. A reduced risk of malignant edema was associated with successful revascularization but not with the administration of intravenous thrombolysis or endovascular interventions.
Previous studies found that patients with more severe neurological deficits were more likely to develop malignant edema.2 Our study confirmed this finding and further proposed a narrower range of cutoff score (15–17) to distinguish patients at a risk for malignant edema from general stroke patients. Another predictor is the parenchymal hypoattenuation >50% of the middle cerebral artery territory on initial CT.2 We further clarified that this predictor was reliable when assessed as early as within 6 hours up to 40 hours after stroke and for both general stroke patients and those with severe stroke. Although an absolute volume of infarct might be more accurate than a relative extent, it is difficult to reach consensus on a definite cutoff volume in practice because of various imaging measures used, and some imaging techniques, such as DWI, are not available in many stroke services.
In addition to initial stroke severity assessed clinically or radiologically, younger age is another predictor for which age-related brain atrophy is a possible confounder by providing buffering space for brain swelling. However, the optimal cutoff age for predicting malignant edema is unknown. Among 4 studies reporting cutoff ages,9,18,42,46 a case-control study recruited patients <70 years and matched for stroke severity reported that malignant group had more patients aged <60 years than nonmalignant group42; another study found that whether age ≥70 years did not change the risk for malignant edema46; the other 2 studies (not in meta-analysis because median age was presented) reported that age ≥75 years increased risk of malignant edema.9,18 In addition, in patients with malignant edema, those aged >75 years had larger infarct volume than those <75 years of age, even the age-related brain atrophy was taken into account.18 Furthermore, a study reported that the protective effect of older age no longer existed after controlling for the effect of infarct volume.36 These findings, although from small studies, imply the possibility that patients aged >75 years are prone to more severe infarct that predisposes malignant edema, which worth further investigation.
There is a discrepancy between RCTs and observational studies about the association between intravenous thrombolysis and malignant edema, which could be explained by differences in baseline characteristics. First, apart from the IST-3 study (Third International Stroke Trial) that had relatively broad inclusion,58 all other 4 RCTs had excluded patients with severe stroke syndrome or those with large cerebral infarction; both are important predictors for malignant edema. This difference in inclusion criteria was reflected in the change of the pooled effect size in the sensitivity analysis after excluding the IST-3 study. Therefore, the pooled results of RCTs might have been biased towards less severe stroke patients, whereas most included observational studies had enrolled patients with severe stroke who were more prone to malignant edema. Second, the effect of intravenous thrombolysis on malignant edema might have been confounded by baseline characteristics that influenced the choice of the intervention in the observational studies; for example, patients who had milder stroke and those who had earlier access to medical care were more likely to receive thrombolysis, where these characteristics are often associated with better prognosis. Therefore, we were unable to draw a firm conclusion of this association from either RCTs or observational studies, and future RCTs with broader inclusion are expected.
By performing meta-analysis for individual predictors, we were unable to analyze the effect of confounders. Therefore, we reviewed multifactorial models. where the confounding effects had been adjusted. Existing predictive models for malignant edema showed good discrimination but at a risk of overfitting because of small-sample effect, and none was externally validated. In addition, DASH score33 and MBE score20 showed better discrimination than Kasner score21 and EDEMA score,30 at the cost of feasibility as the former 2 required advanced imaging techniques that may not be available in all stroke services. Furthermore, none of these models included age, an important predictor identified in this review. Large cohort studies are needed to externally validate these models and to improve them by including other important predictors identified in this review and future studies.
This review had several limitations. First, the random-effects modeling is subjected to the loss of efficiency if the assumed effect size is far from the true effect size because of a broad CI; for example, when there are substantial differences in baseline characteristics or only a small number of studies included. However, for variables in the current review, we found consistent results between random-effects modeling and fixed-effect modeling (data not shown). We believe that random-effects modeling used here is appropriate, and we are more confident when the positive inferences are drawn. Second, although we used broad search strategies and inclusion criteria, the asymmetry of funnel plots for some factors indicated potential publication bias because of the lack of large sample studies to provide more precise and reliable results. The included studies were generally small, and the number of studies for individual predictor was limited. Therefore, although some predictors, such as hyperdense artery sign, showed no association with malignant edema in this comprehensive review, they are worth further investigation because the sample size might have been underpowered to detect clinically important differences. Similarly, although we found associations between malignant edema and depressed consciousness, gaze palsy, nausea or vomiting, ventilation, and early mass effect on CT, they were investigated in the limited number of small studies, and these signs often indicate the existence of brain swelling, thus require further investigation.
Younger age, higher admission NIHSS, and larger parenchymal hypoattenuation on initial CT are early predictors for malignant edema after stroke, which are routinely available within 6 hours after stroke to inform timely clinical decisions. Successful revascularization reduces the risk for malignant edema. No firm conclusion could be drawn for other factors because of the limited data and diversity in study characteristics. Future studies with robust design are needed to explore optimal cutoff age and NIHSS scores for predicting malignant edema, to provide more reliable evidence for other potential predictors and to externally validate and improve existing models.
We thank Professor Peter Sandercock for his helpful comments to improve this study.
Sources of Funding
This study was supported by Major International (Regional) Joint Research Project, National Natural Science Foundation of China (81620108009); National Natural Science Foundation of China (81701156); and Key Research and Development Program, Science and Technology Department of Sichuan Province (2017SZ0007).
White OB, Norris JW, Hachinski VC, Lewis A. Death in early stroke, causes and mechanisms.Stroke. 1979; 10:743.LinkGoogle Scholar
Hofmeijer J, Algra A, Kappelle LJ, van der Worp HB. Predictors of life-threatening brain edema in middle cerebral artery infarction.Cerebrovasc Dis. 2008; 25:176–184. doi: 10.1159/000113736CrossrefMedlineGoogle Scholar
Huttner HB, Schwab S. Malignant middle cerebral artery infarction: clinical characteristics, treatment strategies, and future perspectives.Lancet Neurol. 2009; 8:949–958. doi: 10.1016/S1474-4422(09)70224-8CrossrefMedlineGoogle Scholar
Powers WJ, Rabinstein AA, Ackerson T, Adeoye OM, Bambakidis NC, Becker K,; American Heart Association Stroke Council. 2018 Guidelines for the early management of patients with acute ischemic stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke Association.Stroke. 2018; 49:e46–e110. doi: 10.1161/STR.0000000000000158LinkGoogle Scholar
Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D,. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) Group.JAMA. 2000; 283:2008–2012.CrossrefMedlineGoogle Scholar
Moons KG, de Groot JA, Bouwmeester W, Vergouwe Y, Mallett S, Altman DG,. Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist.PLoS Med. 2014; 11:e1001744. doi: 10.1371/journal.pmed.1001744CrossrefMedlineGoogle Scholar
Zaidat OO, Yoo AJ, Khatri P, Tomsick TA, von Kummer R, Saver JL,; Cerebral Angiographic Revascularization Grading (CARG) Collaborators; STIR Revascularization working group; STIR Thrombolysis in Cerebral Infarction (TICI) Task Force. Recommendations on angiographic revascularization grading standards for acute ischemic stroke: a consensus statement.Stroke. 2013; 44:2650–2663. doi: 10.1161/STROKEAHA.113.001972LinkGoogle Scholar
Bektas H, Wu TC, Kasam M, Harun N, Sitton CW, Grotta JC,. Increased blood-brain barrier permeability on perfusion CT might predict malignant middle cerebral artery infarction.Stroke. 2010; 41:2539–2544. doi: 10.1161/STROKEAHA.110.591362LinkGoogle Scholar
Berrouschot J, Barthel H, von Kummer R, Knapp WH, Hesse S, Schneider D. 99m technetium-ethyl-cysteinate-dimer single-photon emission CT can predict fatal ischemic brain edema.Stroke. 1998; 29:2556–2562.LinkGoogle Scholar
Caso V, Agnelli G, Alberti A, Venti M, Acciarresi M, Palmerini F,. High diastolic blood pressure is a risk factor for in-hospital mortality in complete MCA stroke patients.Neurol Sci. 2012; 33:545–549. doi: 10.1007/s10072-011-0767-1CrossrefMedlineGoogle Scholar
Chen R, Deng Z, Song Z. The prediction of malignant middle cerebral artery infarction: a predicting approach using random forest.J Stroke Cerebrovasc Dis. 2015; 24:958–964. doi: 10.1016/j.jstrokecerebrovasdis.2014.12.016CrossrefMedlineGoogle Scholar
Dittrich R, Kloska SP, Fischer T, Nam E, Ritter MA, Seidensticker P,. Accuracy of perfusion-CT in predicting malignant middle cerebral artery brain infarction.J Neurol. 2008; 255:896–902. doi: 10.1007/s00415-008-0802-1CrossrefMedlineGoogle Scholar
Dohmen C, Bosche B, Graf R, Staub F, Kracht L, Sobesky J,. Prediction of malignant course in MCA infarction by PET and microdialysis.Stroke. 2003; 34:2152–2158. doi: 10.1161/01.STR.0000083624.74929.32LinkGoogle Scholar
Firlik AD, Yonas H, Kaufmann AM, Wechsler LR, Jungreis CA, Fukui MB,. Relationship between cerebral blood flow and the development of swelling and life-threatening herniation in acute ischemic stroke.J Neurosurg. 1998; 89:243–249. doi: 10.3171/jns.1998.89.2.0243CrossrefMedlineGoogle Scholar
Flores A, Rubiera M, Ribó M, Pagola J, Rodriguez-Luna D, Muchada M,. Poor collateral circulation assessed by multiphase computed tomographic angiography predicts malignant middle cerebral artery evolution after reperfusion therapies.Stroke. 2015; 46:3149–3153. doi: 10.1161/STROKEAHA.115.010608LinkGoogle Scholar
Foerch C, Otto B, Singer OC, Neumann-Haefelin T, Yan B, Berkefeld J,. Serum S100B predicts a malignant course of infarction in patients with acute middle cerebral artery occlusion.Stroke. 2004; 35:2160–2164. doi: 10.1161/01.STR.0000138730.03264.acLinkGoogle Scholar
Gerriets T, Stolz E, König S, Babacan S, Fiss I, Jauss M,. Sonographic monitoring of midline shift in space-occupying stroke: an early outcome predictor.Stroke. 2001; 32:442–447.LinkGoogle Scholar
Goto Y, Kumura E, Watabe T, Nakamura H, Nishino A, Koyama T,. Prediction of malignant middle cerebral artery infarction in elderly patients.J Stroke Cerebrovasc Dis. 2016; 25:1389–1395. doi: 10.1016/j.jstrokecerebrovasdis.2015.12.034CrossrefMedlineGoogle Scholar
Hacke W, Schwab S, Horn M, Spranger M, De Georgia M, von Kummer R. ‘Malignant’ middle cerebral artery territory infarction: clinical course and prognostic signs.Arch Neurol. 1996; 53:309–315.CrossrefMedlineGoogle Scholar
Jo K, Bajgur SS, Kim H, Choi HA, Huh PW, Lee K. A simple prediction score system for malignant brain edema progression in large hemispheric infarction.PLoS One. 2017; 12:e0171425. doi: 10.1371/journal.pone.0171425CrossrefMedlineGoogle Scholar
Kasner SE, Demchuk AM, Berrouschot J, Schmutzhard E, Harms L, Verro P,. Predictors of fatal brain edema in massive hemispheric ischemic stroke.Stroke. 2001; 32:2117–2123.LinkGoogle Scholar
Kucinski T, Koch C, Grzyska U, Freitag HJ, Krömer H, Zeumer H. The predictive value of early CT and angiography for fatal hemispheric swelling in acute stroke.AJNR Am J Neuroradiol. 1998; 19:839–846.MedlineGoogle Scholar
Lee SH, Oh CW, Han JH, Kim CY, Kwon OK, Son YJ,. The effect of brain atrophy on outcome after a large cerebral infarction.J Neurol Neurosurg Psychiatry. 2010; 81:1316–1321. doi: 10.1136/jnnp.2009.197335CrossrefMedlineGoogle Scholar
Lee SJ, Lee KH, Na DG, Byun HS, Kim YB, Shon YM,. Multiphasic helical computed tomography predicts subsequent development of severe brain edema in acute ischemic stroke.Arch Neurol. 2004; 61:505–509. doi: 10.1001/archneur.61.4.505CrossrefMedlineGoogle Scholar
Limburg M, van Royen EA, Hijdra A, de Bruïne JF, Verbeeten BWSingle-photon emission computed tomography and early death in acute ischemic stroke.Stroke. 1990; 21:1150–1155.LinkGoogle Scholar
Lou JH, Wang J, Liu LX, He LY, Yang H, Dong WW. Measurement of brain edema by noninvasive cerebral electrical impedance in patients with massive hemispheric cerebral infarction.Eur Neurol. 2012; 68:350–357. doi: 10.1159/000342030CrossrefMedlineGoogle Scholar
Minnerup J, Wersching H, Ringelstein EB, Heindel W, Niederstadt T, Schilling M,. Prediction of malignant middle cerebral artery infarction using computed tomography-based intracranial volume reserve measurements.Stroke. 2011; 42:3403–3409. doi: 10.1161/STROKEAHA.111.619734LinkGoogle Scholar
Moldes O, Sobrino T, Millán M, Castellanos M, Pérez de la Ossa N, Leira R,. High serum levels of endothelin-1 predict severe cerebral edema in patients with acute ischemic stroke treated with t-PA.Stroke. 2008; 39:2006–2010. doi: 10.1161/STROKEAHA.107.495044LinkGoogle Scholar
Mori K, Aoki A, Yamamoto T, Horinaka N, Maeda M. Aggressive decompressive surgery in patients with massive hemispheric embolic cerebral infarction associated with severe brain swelling.Acta Neurochir (Wien). 2001; 143:483–491; discussion 491.CrossrefMedlineGoogle Scholar
Ong CJ, Gluckstein J, Laurido-Soto O, Yan Y, Dhar R, Lee JM. Enhanced detection of Edema in Malignant Anterior Circulation Stroke (EDEMA) score: a risk prediction tool.Stroke. 2017; 48:1969–1972. doi: 10.1161/STROKEAHA.117.016733LinkGoogle Scholar
Oppenheim C, Samson Y, Manaï R, Lalam T, Vandamme X, Crozier S,. Prediction of malignant middle cerebral artery infarction by diffusion-weighted imaging.Stroke. 2000; 31:2175–2181.LinkGoogle Scholar
Park J, Goh DH, Sung JK, Hwang YH, Kang DH, Kim Y. Timely assessment of infarct volume and brain atrophy in acute hemispheric infarction for early surgical decompression: strict cutoff criteria with high specificity.Acta Neurochir (Wien). 2012; 154:79–85. doi: 10.1007/s00701-011-1178-zCrossrefMedlineGoogle Scholar
Shimoyama T, Kimura K, Uemura J, Yamashita S, Saji N, Shibazaki K,. The DASH score: a simple score to assess risk for development of malignant middle cerebral artery infarction.J Neurol Sci. 2014; 338:102–106. doi: 10.1016/j.jns.2013.12.024CrossrefMedlineGoogle Scholar
Song SY, Ahn SY, Rhee JJ, Lee JW, Hur JW, Lee HK. Extent of contrast enhancement on non-enhanced computed tomography after intra-arterial thrombectomy for acute infarction on anterior circulation: as a predictive value for malignant brain edema.J Korean Neurosurg Soc. 2015; 58:321–327. doi: 10.3340/jkns.2015.58.4.321CrossrefMedlineGoogle Scholar
Sykora M, Steiner T, Rocco A, Turcani P, Hacke W, Diedler J. Baroreflex sensitivity to predict malignant middle cerebral artery infarction.Stroke. 2012; 43:714–719. doi: 10.1161/STROKEAHA.111.632778LinkGoogle Scholar
Thomalla G, Hartmann F, Juettler E, Singer OC, Lehnhardt FG, Köhrmann M,; Clinical Trial Net of the German Competence Network Stroke. Prediction of malignant middle cerebral artery infarction by magnetic resonance imaging within 6 hours of symptom onset: a prospective multicenter observational study.Ann Neurol. 2010; 68:435–445. doi: 10.1002/ana.22125CrossrefMedlineGoogle Scholar
Thomalla GJ, Kucinski T, Schoder V, Fiehler J, Knab R, Zeumer H,. Prediction of malignant middle cerebral artery infarction by early perfusion- and diffusion-weighted magnetic resonance imaging.Stroke. 2003; 34:1892–1899. doi: 10.1161/01.STR.0000081985.44625.B6LinkGoogle Scholar
Mian AZ, Edasery D, Sakai O, Mustafa Qureshi M, Holsapple J, Nguyen T. Radiological imaging features of the basal ganglia that may predict progression to hemicraniectomy in large territory middle cerebral artery infarct.Neuroradiology. 2017; 59:477–484. doi: 10.1007/s00234-017-1823-1CrossrefMedlineGoogle Scholar
Haring HP, Dilitz E, Pallua A, Hessenberger G, Kampfl A, Pfausler B,. Attenuated corticomedullary contrast: an early cerebral computed tomography sign indicating malignant middle cerebral artery infarction. A case-control study.Stroke. 1999; 30:1076–1082.LinkGoogle Scholar
Jaramillo A, Góngora-Rivera F, Labreuche J, Hauw JJ, Amarenco P. Predictors for malignant middle cerebral artery infarctions: a postmortem analysis.Neurology. 2006; 66:815–820. doi: 10.1212/01.wnl.0000203649.60211.0eCrossrefMedlineGoogle Scholar
Krieger DW, Demchuk AM, Kasner SE, Jauss M, Hantson L. Early clinical and radiological predictors of fatal brain swelling in ischemic stroke.Stroke. 1999; 30:287–292.LinkGoogle Scholar
Serena J, Blanco M, Castellanos M, Silva Y, Vivancos J, Moro MA,. The prediction of malignant cerebral infarction by molecular brain barrier disruption markers.Stroke. 2005; 36:1921–1926. doi: 10.1161/01.STR.0000177870.14967.94LinkGoogle Scholar
Kim JM, Moon J, Ahn SW, Shin HW, Jung KH, Park KY. The etiologies of early neurological deterioration after thrombolysis and risk factors of ischemia progression.J Stroke Cerebrovasc Dis. 2016; 25:383–388. doi: 10.1016/j.jstrokecerebrovasdis.2015.10.010CrossrefMedlineGoogle Scholar
Albert AF, Kirkman MA. Clinical and radiological predictors of malignant middle cerebral artery infarction development and outcomes.J Stroke Cerebrovasc Dis. 2017; 26:2671–2679. doi: 10.1016/j.jstrokecerebrovasdis.2017.06.041CrossrefMedlineGoogle Scholar
Fadel WA, Abo-El-Safa AA, Rashed KH, El-Saleet GA, Morad MA. Role of serum S100B protein in prediction of outcome of malignant middle cerebral artery infarction: clinical and laboratory study.Egypt J Neurol Psychiatr Neurosurg. 2012; 49:157–164.Google Scholar
Barber PA, Demchuk AM, Zhang J, Kasner SE, Hill MD, Berrouschot J,. Computed tomographic parameters predicting fatal outcome in large middle cerebral artery infarction.Cerebrovasc Dis. 2003; 16:230–235. doi: 10.1159/000071121CrossrefMedlineGoogle Scholar
Kim H, Jin ST, Kim YW, Kim SR, Park IS, Jo KW. Predictors of malignant brain edema in middle cerebral artery infarction observed on CT angiography.J Clin Neurosci. 2015; 22:554–560. doi: 10.1016/j.jocn.2014.08.021CrossrefMedlineGoogle Scholar
Gerriets T, Stolz E, Modrau B, Fiss I, Seidel G, Kaps M. Sonographic monitoring of midline shift in hemispheric infarctions.Neurology. 1999; 52:45–49.CrossrefMedlineGoogle Scholar
Albers GW, von Kummer R, Truelsen T, Jensen JK, Ravn GM, Grønning BA,; DIAS-3 Investigators. Safety and efficacy of desmoteplase given 3-9 h after ischaemic stroke in patients with occlusion or high-grade stenosis in major cerebral arteries (DIAS-3): a double-blind, randomised, placebo-controlled phase 3 trial.Lancet Neurol. 2015; 14:575–584. doi: 10.1016/S1474-4422(15)00047-2CrossrefMedlineGoogle Scholar
Cheripelli BK, Huang X, MacIsaac R, Muir KW. Interaction of recanalization, intracerebral hemorrhage, and cerebral edema after intravenous thrombolysis.Stroke. 2016; 47:1761–1767. doi: 10.1161/STROKEAHA.116.013142LinkGoogle Scholar
Ciccone A, Valvassori L, Nichelatti M, Sgoifo A, Ponzio M, Sterzi R,; SYNTHESIS Expansion Investigators. Endovascular treatment for acute ischemic stroke.N Engl J Med. 2013; 368:904–913. doi: 10.1056/NEJMoa1213701CrossrefMedlineGoogle Scholar
Hacke W, Kaste M, Bluhmki E, Brozman M, Dávalos A, Guidetti D,; ECASS Investigators. Thrombolysis with alteplase 3 to 4.5 hours after acute ischemic stroke.N Engl J Med. 2008; 359:1317–1329. doi: 10.1056/NEJMoa0804656CrossrefMedlineGoogle Scholar
Hacke W, Kaste M, Fieschi C, Toni D, Lesaffre E, von Kummer R,. Intravenous thrombolysis with recombinant tissue plasminogen activator for acute hemispheric stroke. The European Cooperative Acute Stroke Study (ECASS).JAMA. 1995; 274:1017–1025.CrossrefMedlineGoogle Scholar
Kimberly WT, Dutra BG, Boers AMM, Alves HCBR, Berkhemer OA, van den Berg L,; MR CLEAN Investigators. Association of reperfusion with brain edema in patients with acute ischemic stroke: a secondary analysis of the MR CLEAN Trial.JAMA Neurol. 2018; 75:453–461. doi: 10.1001/jamaneurol.2017.5162CrossrefMedlineGoogle Scholar
Kleine JF, Kaesmacher M, Wiestler B, Kaesmacher J. Tissue-selective salvage of the white matter by successful endovascular stroke therapy.Stroke. 2017; 48:2776–2783. doi: 10.1161/STROKEAHA.117.017903LinkGoogle Scholar
Mori E, Minematsu K, Nakagawara J, Hasegawa Y, Nagahiro S, Okada Y,; DIAS-J Investigators. Safety and tolerability of desmoteplase within 3 to 9 hours after symptoms onset in Japanese patients with ischemic stroke.Stroke. 2015; 46:2549–2554. doi: 10.1161/STROKEAHA.115.009917LinkGoogle Scholar
Ogawa A, Mori E, Minematsu K, Taki W, Takahashi A, Nemoto S,; MELT Japan Study Group. Randomized trial of intraarterial infusion of urokinase within 6 hours of middle cerebral artery stroke: the middle cerebral artery embolism local fibrinolytic intervention trial (MELT) Japan.Stroke. 2007; 38:2633–2639. doi: 10.1161/STROKEAHA.107.488551LinkGoogle Scholar
Sandercock P, Wardlaw JM, Lindley RI, Dennis M, Cohen G, Murray G,. The benefits and harms of intravenous thrombolysis with recombinant tissue plasminogen activator within 6 h of acute ischaemic stroke (the third international stroke trial [IST-3]): a randomised controlled trial.Lancet. 2012; 379:2352–2363CrossrefMedlineGoogle Scholar
Dohmen C, Galldiks N, Bosche B, Kracht L, Graf R. The severity of ischemia determines and predicts malignant brain edema in patients with large middle cerebral artery infarction.Cerebrovasc Dis. 2012; 33:1–7. doi: 10.1159/000330648CrossrefMedlineGoogle Scholar
Beck C, Kruetzelmann A, Forkert ND, Juettler E, Singer OC, Köhrmann M,. A simple brain atrophy measure improves the prediction of malignant middle cerebral artery infarction by acute DWI lesion volume.J Neurol. 2014; 261:1097–1103. doi: 10.1007/s00415-014-7324-9CrossrefMedlineGoogle Scholar
Bosche B, Dohmen C, Graf R, Neveling M, Staub F, Kracht L,. Extracellular concentrations of non-transmitter amino acids in peri-infarct tissue of patients predict malignant middle cerebral artery infarction.Stroke. 2003; 34:2908–2913. doi: 10.1161/01.STR.0000100158.51986.EBLinkGoogle Scholar
Burghaus L, Hilker R, Dohmen C, Bosche B, Winhuisen L, Galldiks N,. Early electroencephalography in acute ischemic stroke: prediction of a malignant course?Clin Neurol Neurosurg. 2007; 109:45–49. doi: 10.1016/j.clineuro.2006.06.003CrossrefMedlineGoogle Scholar
Burghaus L, Liu WC, Dohmen C, Haupt WF, Fink GR, Eggers C. Prognostic value of electroencephalography and evoked potentials in the early course of malignant middle cerebral artery infarction.Neurol Sci. 2013; 34:671–678. doi: 10.1007/s10072-012-1102-1CrossrefMedlineGoogle Scholar
Dohmen C, Bosche B, Graf R, Reithmeier T, Ernestus RI, Brinker G,. Identification and clinical impact of impaired cerebrovascular autoregulation in patients with malignant middle cerebral artery infarction.Stroke. 2007; 38:56–61. doi: 10.1161/01.STR.0000251642.18522.b6LinkGoogle Scholar
Kruetzelmann A, Hartmann F, Beck C, Juettler E, Singer OC, Köhrmann M,; Clinical Trial Net of the German Competence Network Stroke. Combining magnetic resonance imaging within six-hours of symptom onset with clinical follow-up at 24 h improves prediction of ‘malignant’ middle cerebral artery infarction.Int J Stroke. 2014; 9:210–214. doi: 10.1111/ijs.12060CrossrefMedlineGoogle Scholar