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Original Paper

Free Access

Prior Cannabis Use Is Associated with Outcome after Intracerebral Hemorrhage

Di Napoli M.a, b · Zha A.M.c · Godoy D.A.d, e · Masotti L.f · Schreuder F.H.B.M.g · Popa-Wagner A.h, i · Behrouz R.j · from the MNEMONICH Registry

Author affiliations

aNeurological Service, San Camillo de' Lellis General Hospital, Rieti, bNeurological Section, SMDN - Center for Cardiovascular Medicine and Cerebrovascular Disease Prevention, Sulmona, L'Aquila, Italy; cDepartment of Neurology, Ohio State University College of Medicine, Columbus, Ohio, USA; dThe Neurointensive Care Unit, Sanatorio Pasteur and eIntensive Care Unit, Hospital Interzonal de Agudos ‘San Juan Bautista', Catamarca, Argentina; fDepartment of Internal Medicine, Santa Maria Nuova Hospital, Florence, Italy; gDepartment of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands; hDepartment of Psychiatry, Rostock University Medical School, Rostock, Germany; iUniversity of Medicine and Pharmacy, Craiova, Romania; jDepartment of Neurology, School of Medicine, University of Texas Health Science Center San Antonio, San Antonio, Tex., USA

Corresponding Author

Mario Di Napoli, MD

Neurological Section, SMDN - Center for Cardiovascular Medicine and Cerebrovascular Disease Prevention

Via Trento, 41, 67039-Sulmona, L'Aquila (Italy)

E-Mail mariodinapoli@katamail.com

Related Articles for ""

Cerebrovasc Dis 2016;41:248-255

Abstract

Objective: Recent evidence suggests that a potential harmful relationship exists between cannabis use and ischemic stroke. The purpose of this study was to determine the implications of cannabis use in intracerebral hemorrhage (ICH) patients. Methods: An analysis of an international, multicenter, observational database of consecutive patients with spontaneous ICH was conducted. We extracted the following characteristics on presentation: demographics, risk factors, antiplatelet or anticoagulant use, Glasgow Coma Scale, ICH score, neuroimaging parameters, and urine toxicology screen (UTS) results. Modified Rankin Scale (mRS) score was utilized for determination of outcome at discharge. Adjusted logistic ordinal regression was used as shift analysis to assess the impact of cannabis use on mRS score at discharge. The adjusted common OR measured the likelihood that cannabis use would lead to lower mRS scores. Results: Within a cohort of 725 spontaneous ICH patients, UTS was positive for cannabinoids in 8.6%. Cannabinoids-positive (CB+) patients were more frequently Caucasian (p < 0.001), younger (p < 0.001), and had lower median ICH scores on admission (p = 0.017) than those who were cannabinoids-negative. CB+ patients also showed a shift toward better outcome in the distribution of mRS categories, with an adjusted common OR of 0.544 (95% CI 0.330-0.895, p = 0.017). Conclusion: In this multinational cohort, cannabis use was discovered in nearly 10% of patients with spontaneous ICH. Although there was no relationship between cannabis use and specific ICH characteristics, CB+ patients had milder ICH presentation and less disability at discharge.

© 2016 S. Karger AG, Basel


Introduction

With approximately 146 million users worldwide, marijuana, or Δ9-tetrahydrocannabinol (cannabis), is the most widely used illicit drug [1]. Cannabis has now been declared legal for medicinal purposes and/or recreational use in Europe and several states throughout the United States. Many proponents of cannabis consumption claim a lack of harmful health effects. Recent reports, however, suggest that cannabis use may increase the risk of ischemic stroke, especially in young adults [2]. The incidence and significance of cannabis use in intracerebral hemorrhage (ICH) patients have never been systematically investigated. In this study, we compared the demographics, clinical/radiological characteristics, and outcomes between spontaneous ICH patients who consumed cannabis and those who did not.

Methods

Study Design

This study was approved by the Institutional Review Board for each participating center. Data were extracted from the Multi-National Survey on Epidemiology, Morbidity and Outcomes in Intracerebral Hemorrhage (MNEMONICH) registry over a period of 5 years (January 1, 2009 through December 31, 2014). MNEMONICH (NCT2567162 ClinicalTrials.gov) is an ongoing, international, multicenter, observational, collaborative database of consecutive spontaneous ICH patients from participating centers in South America, Europe, and the United States [3]. This registry consists of existing and ongoing datasets from international collaborators who have agreed to mutual peer-to-peer exchange of collected data on spontaneous ICH patients aged ≥18. Data collection and retention are based upon informed consent provided by the patients or their legal representatives. In MNEMONICH, spontaneous ICH is defined as acute intraparenchymal bleeding confirmed by CT scan, in the absence of secondary etiology (e.g. brain tumors, vascular malformations, aneurysms, and trauma). Patients with anticoagulant-associated ICH were also included. Information from different databases was anonymized and recorded in a unique format before inclusion in the registry. Registered data included demographics, clinical, laboratory, anatomic/histo-pathological, and neuroradiological findings collected at the participating centers. Quality control and consistency of methodology and data such as, for instance, agreement on CT scan interpretation between centers were monitored and checked regularly by the coordinating center. Any inconsistency were discussed and resolved with agreement. Special approval by the Ethics Committee was obtained where required.

Subjects

Spontaneous ICH patients aged ≥18 presenting within 24 h of symptom onset, who had complete clinical and imaging data and urine toxicology screen (UTS) at study entry, comprised our study cohort. To avoid the confounding effects of surgery, we excluded patients who had undergone emergency craniotomy for hematoma evacuation.

Clinical and Radiological Variables

The following patient data were collected at the time of admission: age, gender, ethnicity, Glasgow Coma Scale (GCS) score, UTS results, ICH volume, location, intraventricular hemorrhage (IVH), antiplatelet or anticoagulant use, history of arterial hypertension (HTN), regular alcohol use (≥2 drinks, at least 3 times per week), and active cigarette smoking. The ICH score was used to estimate presenting severity [4]. Hematoma volume on the initial head CT scan was measured using the ABC/2 method [5]. All ICH patients were managed in accordance with the Guidelines of the American Heart Association/American Stroke Association or the European Stroke Initiative [6,7].

UTS Assay

At each center, UTS was performed using routine laboratory-based panel for detection of common substances (amphetamines, benzodiazepines, cocaine, methadone, opiates, cannabinoids (CB), barbiturates, and tricyclic antidepressants). The decision for obtaining UTS varied between centers and was based on each center's protocol for acute stroke. Given the differences in assay sensitivities between the participating centers (ranging from 20 to 50 ng/ml), UTS results in this study were recorded as ‘negative' or ‘positive', according to detection cut-offs specific to each site.

Primary and Secondary Outcomes

The primary outcome was the score on the modified Rankin Scale (mRS) at discharge. mRS is a stroke outcome scale with scores ranging from 0 (no symptoms at all) to 6 (dead). A score of 2 or less indicates functional independence [8]. For secondary outcomes, we examined the following dichotomizations of the mRS: score 0-1 vs. 2-6, 0-2 vs. 3-6, and 0-3 vs. 4-6.

Statistical Analysis

Statistical analyses were performed using SPSS® 22.0 (IBM® Inc.). Continuous variables were reported as means ± SD when the distribution was normal, and medians with interquartile range (IQR) when not normally distributed. Categorical variables were analyzed using χ2 and Fisher's exact tests when appropriate. Non-normally distributed continuous variables were analyzed using Mann-Whitney U test.

Because mRS is an ordered categorical variable, for primary analysis, we assessed the association of cannabinoids-positive (CB+) UTS with outcomes using a multivariable ordinal logistic regression model [9]. We estimated the adjusted common OR for a shift in the direction of better outcome on the mRS, and reported the results as unadjusted and adjusted OR with 95% CI [10]. Adjusted OR for all possible cutoff values on the mRS was utilized to assess the consistency of effect and the plausibility of proportionality of the OR with outcome. Adjustment was made for pre-specified baseline characteristics known to be associated with worse outcome in ICH. In that aspect, age, log-transformed ICH volume, and GCS were used as continuous variables, and gender, infratentorial location, anticoagulant use, and intraventricular extension as binary variables.

For secondary analysis, we used classical dichotomous analysis with pre-specified dichotomizations of the mRS (0-1 vs. 2-6, 0-2 vs. 3-6, and 0-3 vs. 4-6) [9]. Binary outcomes were analyzed using logistic regression. The adjusted common ORs were corrected for potential imbalances using the same variables included in the ordinal logistic regression model.

Finally, in order to avoid any possible confounding effect of other illicit drugs, we reworked the same analysis exclusively in patients whose UTS was positive only for CB. The two-sided threshold for statistical significance was set at p = 0.05, with no correction for multiple comparisons justified by the exploratory nature of this analysis.

Results

Of the 2,413 consecutive spontaneous ICH patients in the MNEMONICH registry, 2,371 satisfied our inclusion criteria; 725 (30.6%) were screened via UTS for the presence of illegal drugs (fig. 1). Forty-two patients underwent emergency craniotomy for hematoma evacuation and were therefore excluded from the analysis (38 were screened for the presence of illicit drugs and 3 had UTS positive for CB). Patients who were not screened tended to be older (77 vs. 66 years, p < 0.001) and women (44.1 vs. 33.9%, p < 0.001), without differences in GCS scores, neuroimaging findings, and risk factors (all p > 0.05; online suppl. table 1, see www.karger.com/doi/10.1159/​443532). UTS was positive in 99 (13.7%) patients, including 62 (8.6%) who tested positive for CB. Cocaine metabolites were detected in 20, opioids in 9, amphetamines in 6, and heroin in 2 patients. Among the 62 CB+ patients, 14 tested positive for other substances besides CB: 11 for cocaine, 3 for opiates. They were included in the primary analysis as cannabis users. Table 1 compares the baseline characteristics of CB+ vs. cannabinoids-negative (CB-) ICH patients.

Table 1

Demographics and hemorrhage characteristics of CB+ vs. CB- ICH patients

http://www.karger.com/WebMaterial/ShowPic/492324

Fig. 1

Study flowchart.

http://www.karger.com/WebMaterial/ShowPic/492321

Compared with patients who tested negative, CB+ patients were more often Caucasian (40.3 vs. 27.8%, p < 0.001) and younger (69 vs. 47 years, p < 0.001). Nineteen (27.9%) of the CB+ patients were under the age of 45. There was no significant difference between CB+ and CB- patients in hematoma volume and location. Although IVH was not statistically associated with CB+ status, there was a trend toward a lower occurrence in CB+ patients (33.9 vs. 46.2%, p = 0.063). Furthermore, there were no significant differences in gender, tobacco smoking, baseline HTN, or the use of antiplatelet and anticoagulants drugs between the 2 groups. Although no difference was noted in median score for the initial GCS (13 vs. 13, p = 0.338) between CB+ and CB- patients, median ICH score was significantly lower in the former (0 vs. 2, p = 0.017). The median hospital length of stay was 8 days (IQR 5-13), with no significant difference between CB+ and CB- patients (p = 0.325), although for CB+ patients, median hospital stay was 1 day less (7 vs. 8 days). Data on the primary outcome (the score on the mRS at discharge) were available in all patients.

In univariable ordinal regression analysis, there was a significant difference toward better outcome between the CB+ group and the CB- group in the overall distribution of mRS scores (common OR 0.414, 95% CI 0.261-0.656). After adjustment for age, gender, log-transformed ICH volume, GCS, infratentorial location, anticoagulant use, and IVH in a multivariable ordinal regression model, the difference between the CB+ group and the CB- group in the overall distribution of mRS scores remained significant (adjusted common OR 0.544, 95% CI 0.330-0.895; table 2). Overall, there was a shift in the distribution of the primary outcome scores in favor of a better outcome in the CB+ group (fig. 2). Clinically, CB+ patients showed an improvement of 1 point on the median mRS score when compared to CB- patients.

Table 2

Primary and secondary outcomes in all CB+ vs. CB- ICH patients

http://www.karger.com/WebMaterial/ShowPic/492323

Fig. 2

Comparison of hospital discharge mRS scores between ICH patients who were CB+ or CB- on the initial UTS. The distribution of scores on the mRS is shown. Scores range from 0 to 6, with 0 indicating no symptoms, 1 no clinically significant disability, 2 slight disability (patient is able to look after own affairs without assistance but is unable to carry out all previous activities), 3 moderate disability (patient requires some help but is able to walk unassisted), 4 moderately severe disability (patient is unable to attend to bodily needs without assistance and unable to walk unassisted), 5 severe disability (patient requires constant nursing care and attention), and 6 death. Note the shift to good outcome in CB+ patients.

http://www.karger.com/WebMaterial/ShowPic/492320

Figure 3 shows the percentile-percentile (P-P) plot of cumulative distributions of mRS scores in CB+ patients when compared to CB- patients. CB+ patients show a better outcome (because the curve is completely above the diagonal line), albeit with only a small effect (area under the curve (AUC) 0.621; 95% CI 0.538-0.703, p = 0.002). The graph illustrates practically no difference between groups at high mRS values, which represent severe disability or death; only scores in the range 0-4 show a difference. The overall in-hospital mortality rate was not different between CB+ and CB- patients (32.7 vs. 26.2%; OR 0.714, 95% CI 0.395-1.292, p = 0.264). No significant difference in secondary outcomes was noted between the 2 subgroups of patients (table 2). Because there was a significant association between cannabis use and ethnicity, we also ran a post-hoc analysis using Caucasian as independent dummy variable in the logistic ordinal regression model. The inclusion of ethnicity in the model did not change the strength of association between CB+ status and functional outcome (OR 0.669, 95% CI 0.409-1.004, p = 0.052). Furthermore, because the frequency of cannabis use varied by not only ethnicity but also by country, we examined the influence of country of origin in the final logistic regression model. The inclusion of country in the model did not alter the association between CB+ status and functional outcome (OR 0.619, 95% CI 0.363-1.057, p = 0.079).

Fig. 3

Percentile-percentile (P-P) plot (AUC) between ICH patients who were CB+ or CB- on the initial UTS. Dotted lines represent 95% CIs.

http://www.karger.com/WebMaterial/ShowPic/492319

Repeating the analysis separately with patients who were positive for CB alone (n = 47) did not alter the key findings of our primary analysis (table 3). The OR estimate remained similar in both primary and secondary outcomes.

Table 3

Primary and secondary outcomes in CB+ vs. CB- ICH patients

http://www.karger.com/WebMaterial/ShowPic/492322

Discussion

To the best of our knowledge, our study is the first and the largest to address the effects of cannabis use in ICH patients. Our observational, international, multicenter study showed that apparently cannabis use adversely affects neither clinical/radiological characteristics nor in-hospital survival of ICH patients. The CB+ patients did, however, present with less severe ICH and less disability at discharge than CB- patients, which is evident by lower ICH scores and mRS, respectively. The mRS for CB+ subjects was 3, as compared to 4 for CB- patients; this difference means that CB+ patients can walk without assistance and attend to their own bodily needs, whereas CB- patients cannot. A combination of factors could be responsible for this finding, including age, race, genetic and socioeconomic factors, stroke care inequalities, and lower prevalence of IVH. CB+ patients were younger than CB-patients by approximately 20 years, mainly due to the potentially different age-specific incidence of cannabis use [11]. Because advanced age is associated with worse clinical outcomes in ICH [12], the apparently beneficial effect of cannabis could be due to the confounding effect of younger age of cannabis users. However, in our cohort, the effect of CB remained significant even after adjusting for age, making this less likely. Similarly, the inclusion of ethnicity and country of origin in the model did not change the strength of association between CB+ status and functional outcome. Obviously, it is not possible to exclude the confounding effects of complex socio-demographic correlates of lifetime cannabis use [11.]

Nonetheless, we can argue the possibility that pharmacological properties of CB itself may also have contributed to milder stroke and better functional outcomes. The association between CB+ and better functional outcome at discharge remained significant even after taking into account known confounders.

The role of endogenous CB in the central nervous system and their potential as symptomatic or neuro-protective therapies has been a topic of interest for the last few years. There are no clinical trials using CB in stroke. In experimental stroke models, however, CB have been shown to significantly reduce infarct volume and improve functional outcome [13]. Data from a recent systematic review and meta-analysis suggest that CB reduce infarct volume in transient and permanent ischemia, improve early and late functional outcome without effects on survival [13]. Similarly, in our ICH cohort, CB+ patients showed, lower ICH severity as assessed by the ICH score, improved functional outcome at discharge without effect on survival, and, although not significant, a reduced hematoma volume. There are theories that indicate neuro-protective properties of CB. Investigations regarding the utility of CB as a remedy for neurological diseases are in progress and too nascent for any conclusions specifically pertaining to our findings. In experimental studies of rat cortical neuronal cultures exposed to toxic levels of glutamate, cannabidiol and other CBs have been shown to function as antioxidants, downregulating the activity of this excitatory neurotransmitter [14]. In other animal models, CBs have been shown to suppress the production of tumor necrosis factor-α and interleukin (IL)-1β, and enhance the expression of brain-derived neurotrophic factor [15,16,17]. ICH is associated with a marked upregulation of tumor necrosis factor-α and IL-1β in the brain, leading to secondary brain injury [18,] while the brain-derived neurotrophic factor promotes neural regeneration and angiogenesis, reduced tissue loss, and improved functional recovery in an experimental ICH model [19]. This effect is more pronounced in older age and after inflammatory reactions [20]. CBs show multiple pleiotropic effects against acute post-stroke inflammation acting neuroprotectively on the ischemic penumbra, cerebral vasculature, blood-brain barrier integrity, and acute inflammatory [13,21,22]. All these aspects could be implicated in determining a better prognosis in our cohort of CB+ patients. Finally, it is interesting to note that cannabis smoking shows an immunomodulatory effect evident by a reduction in C-reactive protein concentrations [23]. Lower C-reactive protein concentrations in the acute phase of ICH are associated with reduced hematoma growth and improved outcomes [24,25]. From this standpoint, synthetic CB and endocannabinoids could represent promising therapeutic compounds for neuroprotective and antinflammatory strategies in ICH patients.

There are also some data regarding the positive effects of CB in clinical settings of acute brain injury. For instance, in a cohort of 446 traumatic brain injury patients, the mortality rate in the CB+ group was significantly lower, compared with that of the CB- patients (2.4 vs. 11.5%, p = 0.012) [26]. However, we must underline some potential weaknesses inherent in our observational study design. Although our cohort represented a prospectively accumulated registry, data were retrospectively analyzed, preventing any further characterization and quantification of drug use. We did not have information on the timing of marijuana consumption, latency from exposure to onset of symptoms, and consumption amount or frequency. The UTS information available to us did not allow differentiating new cannabis use from residual drug excretion, considering that CB may persist in the urine for several days to weeks. A single positive toxicology screen is neither indicative of chronic use nor evidence of a link between the drug and an event. However, only a small percentage of patients in our cohort admitted to chronic substance abuse. Because of the possibility of inaccurate history given by some patients, we relied on UTS to verify drug use. The decision for submitting a patient to UTS was left to the discretion of the participating centers and the attending physicians, and perhaps influenced by local and national policies, as well as other unmeasured factors not included in the multivariable model. Screening rates may also be very different by centers, further complicating data interpretation. These unmeasured factors may have contributed to the observed association between better outcome and CB+ status. Similarly, the use of UTS with variable sensitivities and the presence of false positives due to concomitant medications could have affected the strength of the measured association between CB+ status and outcome. Although this could be true, the use of a well-validated UTS with low percentage of false positive UTS [27], and categorizing UTS positivity above the cut-offs specific to each site should have minimized this confounding effect. We decided to exclude patients who underwent emergency craniotomy; this may have decreased the number of CB+ patients. However, we are not of the opinion that this had a large influence on our results, since the percentage of patients tested positive for CB was nearly similar (3/38) to that of the included number of subjects (62/725). Other factors specific to each center (such as the use of other interventions and level of supportive care, or ethnic composition) could also have influenced survival. The CB+ group consisted largely of patients from centers in the United States; thus, there may be unmeasured confounding factors related to the characteristics of the local population or aspects of clinical care that could account for the observed difference. The numbers in each center are small, and we thus face the risk of both overmodeling and type II errors. However, we performed a post hoc analysis, which within its limitations, suggested that the differences in outcome were not explained by ethnic specific differences. Finally, the lack of follow-up beyond discharge represents another intrinsic limitation of our study.

In conclusion, we found no connection between marijuana consumption and any specific clinical or imaging characteristics in ICH patients. Our findings support the hypothesis that cannabis use could be associated with milder ICH presentation and less disability at discharge. The clinical significance of our preliminary finding of improved functional outcome at discharge in CB+ patients requires further investigation.

Disclosure Statement

The authors report no conflicts of interest.


References

  1. Prevalence of Drug Use among the General Population. World Drug Report 2012. United Nations Office on Drugs and Crime. http://www.unodc.org/unodc/en/data-and-analysis/WDR-2012.html (accessed March 9, 2015).
  2. Wolff V, Armspach JP, Lauer V, et al: Cannabis-related stroke: myth or reality? Stroke 2013;44:558-563.
  3. Behrouz R, Azarpazhooh MR, Godoy DA, et al; MNEMONICH Steering Committee: The multi-national survey on epidemiology, morbidity, and outcomes in intracerebral haemorrhage (MNEMONICH). Int J Stroke 2015;10:e86.
  4. Hemphill JC 3rd, Bonovich DC, Besmertis L, et al: The ICH score: a simple, reliable grading scale for intracerebral hemorrhage. Stroke 2001;32:891-897.
  5. Kothari RU, Brott T, Broderick JP, et al: The ABCs of measuring intracerebral hemorrhage volumes. Stroke 1996;27:1304-1305.
  6. Morgenstern LB, Hemphill JC 3rd, Anderson C, Becker K, et al: Guidelines for the management of spontaneous intracerebral hemorrhage: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 2010;41:2108-2129.
  7. Steiner T, Kaste M, Forsting M, et al: Recommendations for the management of intracranial haemorrhage - part I: spontaneous intracerebral haemorrhage. The European Stroke Initiative Writing Committee and the Writing Committee for the EUSI Executive Committee. Cerebrovasc Dis 2006;22:294-316.
  8. van Swieten JC, Koudstaal PJ, Visser MC, et al: Interobserver agreement for the assessment of handicap in stroke patients. Stroke 1988;19:604-607.
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  12. Camacho EJ, LoPresti MA, Bruce S, et al: The role of age in intracerebral hemorrhage: an intricate relationship. Austin J Cerebrovasc Dis Stroke 2014;1:1022.
  13. England TJ, Hind WH, Rasid NA, O'Sullivan SE: Cannabinoids in experimental stroke: a systematic review and meta-analysis. J Cereb Blood Flow Metab 2015;35:348-358.
  14. Hampson AJ, Grimaldi M, Lolic M, et al: Neuroprotective antioxidants from marijuana. Ann N Y Acad Sci 2000;899:274-282.
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  19. Guan J, Zhang B, Zhang J, et al: Nerve regeneration and functional recovery by collagen-binding brain-derived neurotrophic factor in an intracerebral hemorrhage model. Tissue Eng Part A 2015;21:62-74.
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Author Contacts

Mario Di Napoli, MD

Neurological Section, SMDN - Center for Cardiovascular Medicine and Cerebrovascular Disease Prevention

Via Trento, 41, 67039-Sulmona, L'Aquila (Italy)

E-Mail mariodinapoli@katamail.com


Article / Publication Details

First-Page Preview
Abstract of Original Paper

Received: August 18, 2015
Accepted: December 21, 2015
Published online: January 29, 2016
Issue release date: April 2016

Number of Print Pages: 8
Number of Figures: 3
Number of Tables: 3

ISSN: 1015-9770 (Print)
eISSN: 1421-9786 (Online)

For additional information: https://www.karger.com/CED


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References

  1. Prevalence of Drug Use among the General Population. World Drug Report 2012. United Nations Office on Drugs and Crime. http://www.unodc.org/unodc/en/data-and-analysis/WDR-2012.html (accessed March 9, 2015).
  2. Wolff V, Armspach JP, Lauer V, et al: Cannabis-related stroke: myth or reality? Stroke 2013;44:558-563.
  3. Behrouz R, Azarpazhooh MR, Godoy DA, et al; MNEMONICH Steering Committee: The multi-national survey on epidemiology, morbidity, and outcomes in intracerebral haemorrhage (MNEMONICH). Int J Stroke 2015;10:e86.
  4. Hemphill JC 3rd, Bonovich DC, Besmertis L, et al: The ICH score: a simple, reliable grading scale for intracerebral hemorrhage. Stroke 2001;32:891-897.
  5. Kothari RU, Brott T, Broderick JP, et al: The ABCs of measuring intracerebral hemorrhage volumes. Stroke 1996;27:1304-1305.
  6. Morgenstern LB, Hemphill JC 3rd, Anderson C, Becker K, et al: Guidelines for the management of spontaneous intracerebral hemorrhage: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 2010;41:2108-2129.
  7. Steiner T, Kaste M, Forsting M, et al: Recommendations for the management of intracranial haemorrhage - part I: spontaneous intracerebral haemorrhage. The European Stroke Initiative Writing Committee and the Writing Committee for the EUSI Executive Committee. Cerebrovasc Dis 2006;22:294-316.
  8. van Swieten JC, Koudstaal PJ, Visser MC, et al: Interobserver agreement for the assessment of handicap in stroke patients. Stroke 1988;19:604-607.
  9. Bath PM, Lees KR, Schellinger PD, et al; European Stroke Organisation Outcomes Working Group: Statistical analysis of the primary outcome in acute stroke trials. Stroke 2012;43:1171-1178.
  10. Saver JL: Novel end point analytic techniques and interpreting shifts across the entire range of outcome scales in acute stroke trials. Stroke 2007;38:3055-3062.
  11. Degenhardt L, Chiu WT, Sampson N, et al: Toward a global view of alcohol, tobacco, cannabis, and cocaine use: findings from the WHO world mental health surveys. PLoS Med 2008;5:e141.
  12. Camacho EJ, LoPresti MA, Bruce S, et al: The role of age in intracerebral hemorrhage: an intricate relationship. Austin J Cerebrovasc Dis Stroke 2014;1:1022.
  13. England TJ, Hind WH, Rasid NA, O'Sullivan SE: Cannabinoids in experimental stroke: a systematic review and meta-analysis. J Cereb Blood Flow Metab 2015;35:348-358.
  14. Hampson AJ, Grimaldi M, Lolic M, et al: Neuroprotective antioxidants from marijuana. Ann N Y Acad Sci 2000;899:274-282.
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