PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of neurologyNeurologyAmerican Academy of Neurology
 
Neurology. 2017 September 5; 89(10): 1011–1019.
PMCID: PMC5589792

Assessment of the interaction of age and sex on 90-day outcome after intracerebral hemorrhage

Michael L. James, MD,corresponding author Carl D. Langefeld, PhD, Padmini Sekar, MS, Charles J. Moomaw, PhD, Mitchell S.V. Elkind, MD, MS, Bradford B. Worrall, MD, MSc, Kevin N. Sheth, MD, Sharyl R. Martini, MD, PhD, Jennifer Osborne, BSN, and Daniel Woo, MD, MS, On behalf of the ERICH Investigators
From the Brain Injury Translational Research Center, Department of Anesthesiology, and Department of Neurology (M.L.J.), Duke University, Durham; Center for Public Health Genomics and Department of Biostatistical Sciences (C.D.L.), Wake Forest School of Medicine, Winston-Salem, NC; Department of Neurology and Rehabilitation Medicine (P.S., C.J.M., J.O., D.W.), University of Cincinnati, OH; Department of Neurology, College of Physicians and Surgeons, and Department of Epidemiology, Mailman School of Public Health (M.S.V.E.), Columbia University, New York, NY; Departments of Neurology and Public Health Sciences (B.B.W.), University of Virginia, Charlottesville; Division of Neurocritical Care & Emergency Neurology, Department of Neurology (K.N.S.), Yale University, New Haven, CT; and Department of Neurology (S.R.M.), Baylor College of Medicine, Houston, TX.
ERICH Investigators, Michael L. "Luke" James, M.D., Bradford B. Worrall, MD, MSc, Tanya Warwick, MD, Ji Y. Chong, MD, Lee Birnbaum, MD, Nicole Gonzales, MD, Christiana Hall, MD, Gene Sung, MD, MPH, Sebastian Koch, MD, Huy Tran, MD, Steven Kittner, MD, Fernando Testai, MD, PhD, Bruce Coull, MD, Jonathan Rosand, MD, Mitchell S. V. Elkind, MD, MS, FAAN, Carl Langefeld, Ph.D., Jacob McCauley, PhD, John P. Hussman, Chelsea Kidwell, MD, and Dan Woo

Abstract

Objective:

Because age affects hormonal production differently in women compared with men, we sought to define sex and age interactions across a multiracial/ethnic population after intracerebral hemorrhage (ICH) to uncover evidence that loss of gonadal hormone production would result in loss of the known neuroprotective effects of gonadal hormones.

Methods:

Clinical and radiographic data from participants in the Ethnic/Racial Variations of Intracerebral Hemorrhage study and the Genetic and Environmental Risk Factors for Hemorrhagic Stroke study prior to December 2013 were used. Relationships among sex, age, and outcome after ICH in 616 non-Hispanic black, 590 Hispanic, and 868 non-Hispanic white participants were evaluated using multivariable logistic regression analysis. Poor outcome was defined as modified Rankin Scale score ≥3 at 90 days after ICH.

Results:

Sex differences were found in multiple variables among the racial/ethnic groups, including age at onset, premorbid neurologic status, and neurologic outcome after ICH. Overall, no sex–age interaction effect was found for mortality (p = 0.183) or modified Rankin Scale score (p = 0.378) at 90 days after ICH. In racial/ethnic subgroups, only the non-Hispanic black cohort provided possible evidence of a sex–age interaction on 90-day modified Rankin Scale score (p = 0.003).

Conclusion:

Unlike in ischemic stroke, there was no evidence that patient sex modified the effect of age on 90-day outcomes after ICH in a large multiracial/ethnic population. Future studies should evaluate biological reasons for these differences between stroke subtypes.

Clinicaltrials.gov identifier:

NCT01202864.

Intracerebral hemorrhage (ICH) results in a greater degree of morbidity, mortality, and loss of quality of life than other forms of stroke.1 ICH remains without any proven therapeutic intervention, as evidenced by several multicenter clinical trials. Successful development of therapeutic interventions may result from our evolving understanding of the role of sex in neurologic recovery.

Although a number of acute brain injuries have demonstrated sex differences in outcome,2,4 sex differences in ICH need to be more fully characterized. No studies have directly addressed sex differences in long-term outcome after ICH while controlling for covariates.5 However, female gonadal steroids demonstrate neuroprotective effects in ongoing preclinical work.6 In addition, age affects sexual dimorphism in the brain,7,8 and lack of gonadal hormones, such as that brought on by aging, significantly worsens recovery in preclinical models of ICH.9,10 Given these results, we sought to determine whether sex and age interact to affect outcome after ICH.

In the present study, sex differences in the effect of age on outcome after ICH were assessed in a multiethnic population with data from 2 multicenter studies: Ethnic/Racial Variations of Intracerebral Hemorrhage (ERICH)11 and Genetic and Environmental Risk Factors for Hemorrhagic Stroke (GERFHS).12 Due to the loss of gonadal hormone effects in women after menopause, the specific hypothesis for the present study was that the risk of unfavorable outcome in women increases with age to a greater degree than in men, as occurs in ischemic stroke. Further, because the ERICH study allows evaluation in multiethnic populations, the influence of race/ethnicity on the potential age and sex interactions on outcome after ICH was examined as a secondary endpoint.

METHODS

Standard protocol approvals, registrations, and patient consents.

Institutional review boards at each participating institution approved both studies prior to initiation of study enrollment. Informed consent was obtained from each enrolled participant or legally authorized representative. A Spanish-language consent form was available for Spanish only–speaking participants or for those who preferred the Spanish consent. Prior to an interview, the patient's capacity to give consent was screened using a consent comprehension questionnaire. If the patient failed this screen, a legally authorized representative was contacted for enrollment with priority to guardian/power of attorney, spouse, adult children, parents, and siblings, in that order.

Study population.

Methods for the ERICH11 and GERFHS12 studies have been described previously. Briefly, the ERICH study is a multicenter, prospective study of ICH designed to recruit 1,000 non-Hispanic white, 1,000 non-Hispanic black, and 1,000 Hispanic patients with spontaneous ICH. The GERFHS study is a prospective study of non-Hispanic white patients with ICH from 16 hospitals in the Greater Cincinnati/Northern Kentucky region. GERFHS and ERICH utilize similar clinical data and neuroimaging collection methods and ICH case ascertainment.

Patients diagnosed with first-ever, spontaneous ICH, who were over 18 years of age, resided within 50 miles of the recruiting center (within 100 miles for population centers fewer than 1 million) for at least 6 months prior to onset of ICH, and provided informed consent (by the patient or legally authorized representative) were eligible for the present study. Cases of ICH due to malignancies that led to coagulopathy, dural venous sinus thrombosis–associated hemorrhage, vascular malformations, aneurysms, tumors, or hemorrhagic conversion of recent ischemic stroke were not eligible for the studies. To determine a patient's eligibility as a study case, study neurologists reviewed the patient's clinical presentation and neuroimaging.

Participant characteristics.

As previously described,11,12 researchers interviewed enrolled participants or their proxies using a standardized form and used standardized chart abstraction for each case to provide additional clinical data, including discharge status and outcome. Each surviving participant was scheduled to be contacted at 90 days for evaluation of modified Rankin Scale (mRS).

From the data collected, items of interest for the present analysis were age, sex, race/ethnicity, body mass index (BMI), Glasgow Coma Scale (GCS) score on admission, mRS prior to stroke, history of alcohol, smoking, and illicit drug use, presence of coagulopathy, and history of hypertension, diabetes, and heart disease. Alcohol abuse was defined as self-report of more than 2 alcoholic drinks per day (on average), binge drinking (>5 drinks in a single setting) in the last 90 days, or history of alcohol abuse. Smoking history was classified as current, former, or never. Illicit drug use was defined as positive urine toxicology screen on admission or self-reported use. Presence of coagulopathy was defined as international normalized ratio greater than 1.5, partial thromboplastin time greater than 40 seconds, or platelet count less than 80,000/μL values on admission. History of heart disease was defined as history of any cardiac disease, including coronary artery disease, valvular disease, aberrant rhythms, or cardiomyopathy.

Imaging.

All neuroimaging obtained from participants is stored on DICOM software, deidentified on site, and uploaded electronically to a dedicated workstation at the neuroimaging repository (Massachusetts General Hospital and University of Arizona–Tucson) using Alice software (Parexel Corporation, Waltham, MA) for centralized analyses by image reviewers blinded to all clinical information. The initial diagnostic CT images were used to measure hematoma volume, hematoma location, and presence of intraventricular hemorrhage (IVH). Hematoma volumes were measured by planimetric analysis as previously published.13,15 This method has high interrater reliability (0.99 test–retest intraclass and interobserver correlation coefficients in 2 independent readers evaluating 20 CT scans).13 Hematoma location was defined as deep (i.e., basal ganglia or thalamus), lobar, brainstem, cerebellum, or primary IVH.

Outcomes.

The primary outcome was defined as unfavorable outcome, based on mRS ≥3 at 90 days after ICH onset. Secondary outcome was death within 90 days.

Statistical analysis.

Descriptive statistics are presented as means, SD, and medians for continuous variables and as percentages for categorical variables. Patient characteristics are compared between men and women with Wilcoxon rank sum test for continuous (age, hematoma volume, BMI) and ordinal variables (GCS), and with χ2 tests for categorical variables (alcohol abuse, smoking, illicit drug use, heart disease, hypertension, and diabetes).

To test for associations with outcome, univariate and multivariable logistic regression models were computed. Covariates were selected a priori based on known associations with outcome. For continuous predictors, the functional form (e.g., linear, quadratic) was tested. Initial analyses demonstrated a nonlinear distribution of hematoma volume and age; thus, all hematoma volumes were fit as the natural logarithm of volume plus 1, and age was modeled with both a linear and quadratic term; the quadratic term was centered by the mean age of the sample. To test for a potential modifying effect of sex on age at ICH onset, the multivariable model adjusted for a priori covariates and modeled the age–sex interaction terms as centered cross products. Odds ratios for the effect of female sex were calculated at selected ages as examples to demonstrate the change in effect with increasing age. In addition, men and women from each racial/ethnic group were modeled in separate multivariable analyses, and the effect of age on outcome was assessed within each subgroup. Collinearity and influence diagnostics were examined.

RESULTS

From July 2008 through January 2013, 502 participants from the GERFHS study, and from September 2010 through December 2013, 2,277 participants from the ERICH study were available for analysis. Due to participants with incomplete data (figure), final analyses were based on 2,074 participants (1,187 men and 887 women), which included 616 non-Hispanic black, 590 Hispanic, and 868 non-Hispanic white participants.

Figure
Total study population

There were significant differences in study characteristics between men and women in the overall study population (table 1). On average, women were 5 years older than men, had higher premorbid mRS, and were less likely to smoke, abuse alcohol, or use illicit drugs. A higher proportion of women had lobar hemorrhages compared with men. Also, a higher proportion of women died within 90 days of onset, and surviving women had higher mRS than men, on average, at both discharge and 90 days. Finally, multiple differences were found across racial/ethnic groups, including age, pre-ICH mRS, history of alcohol abuse, smoking, and illicit drug use, and history of diabetes and heart disease.

Table 1
Study cohort demographic and descriptive statistics

Table 2 contains associations with 90-day outcome. Age, hematoma volume, premorbid and discharge mRS, coagulopathy, history of heart disease, and IVH were directly associated with mRS ≥3 at and mortality through 90 days after ICH. Male sex, admission GCS, and history of alcohol abuse or illicit drug use were inversely associated with mRS ≥3 at and mortality through 90 days after ICH. Stratifying by ethnic/racial background, associations were retained for age, hematoma volume, premorbid and discharge mRS, and presence of IVH in all 3 racial/ethnic groups.

Table 2
Ethnic-specific and combined univariate associations with outcome

Table 3 presents results of the multivariable logistic regression model for mRS ≥3 at and mortality through 90 days after ICH, including a test for sex-by-age interaction. In this model, age, admission GCS, initial hematoma volume, premorbid mRS, and presence of IVH retain significant independent associations in the overall study population. Similar logistic regression models were constructed for each racial/ethnic group. Interestingly, in these models, lobar location of ICH was significantly associated with mortality in Hispanic participants and unfavorable mRS (≥3) in the overall population, Hispanic participants, and white participants. However, there was no association between lobar location and outcomes in black participants. There was no evidence of a sex-by-age interaction effect in the individual ethnic-specific analyses or the joint analyses (table 3). While associations between multiple variables and outcome at 90 days were found in different race/ethnicities, admission GCS and hematoma volume were independently associated with higher mortality and poorer mRS at 90 days after ICH in each racial/ethnic group. There is suggestive evidence of a sex-by-age interaction effect in the non-Hispanic black cohort for mortality (p = 0.003), but not for mRS ≥3 at (p = 0.402), at 90 days after ICH. This pattern was not observed in other analyses: Hispanic participants (p = 0.842 and 0.471; mortality and mRS ≥3, respectively), non-Hispanic white participants (p = 0.756 and 0.342; mortality and mRS ≥3, respectively), or transethnicity (p = 0.183 and 0.378; mortality and mRS ≥3, respectively). In addition, significance of the interaction term in the non-Hispanic black cohort disappears after adjustment for multiple comparisons. Finally, sensitivity analyses were performed for regression modeling with and without patients lost to follow up at 90 days (table e-1 at Neurology.org), and model results did not differ (data not shown).

Table 3
Combined samples and ethnic-specific multiple logistic regression models for outcome

DISCUSSION

As the largest study from a multiracial/ethnic population of patients with ICH, the present study found multiple sex differences in clinically relevant variables and outcomes; however, in multivariable models, neither sex nor sex-by-age interaction was associated with mortality or mRS at 90 days after ICH. While epidemiologic studies have often treated patients with ICH as a subset of total stroke patients rather than as a distinct category, confirmation of sex differences in ICH has been difficult to achieve.1,16,18 Regardless, sexual dimorphism in recovery from brain injury is biologically plausible given that female gonadal steroids have a neuroprotective effect in a variety of preclinical models,19,20 including ICH.21,23 In fact, sex differences in other stroke subtypes are readily apparent in humans.24,25 While gonadal hormones do not completely explain known sex differences in cellular responses, loss of gonadal hormones during menopause in women may mean that age differentially affects women compared with men. Prior publications on sex differences after ICH have reported conflicting results regarding correlations with both mortality26,29 and neurologic recovery.30,33

The effects of aging in ICH have received substantial attention. In the present study, baseline age differed for men and women in each racial/ethnic group and, in fact, was a modifier of 90-day outcome in multivariate models. Incidence, mechanisms, and outcomes of ICH are known to vary by age, and results presented here are not significantly different from prior publications.34 For instance, amyloid angiopathy increases as a cause of ICH in older populations.35 Further, increasing age is strongly associated with poorer outcome after ICH.36 This association may be related to aging effects on hematoma volume37 and neuroinflammation.38,39 However, the present study controlled for differences and effects of age and sex as covariates in multivariable models. Hematoma volume, admission GCS, and (to a slightly lesser degree) premorbid mRS were consistently found to have associations with both 90-day mortality and neurologic recovery across all race/ethnicities.

Although the NIH Stroke Scale was not collected and thus could not be included as a measure of stroke severity in these analyses, the present results are consistent with associations between 90-day outcome and age, admission GCS, hematoma volume, and pre-ICH mRS in all groups. Furthermore, covariates in the analytical model included the individual components of the ICH Score,36 which has been demonstrated to correlate well with long-term outcome after ICH.40 Thus, although we were unable to control directly for stroke severity, accepted predictors of outcome appear to behave as expected in the present study population. In fact, fewer than 10% of data were missing in all variables except presence of coagulopathy, suggesting little potential for bias in measured effects.

Despite using prospectively collected data, the retrospective nature of the analyses limits the current study. The present study was unable to address questions regarding sex differences in quality of life or adequately represent certain patient populations (e.g., patients at the extremes of the age distribution or patients with brainstem hemorrhage or IVH). The present findings do not include other racial/ethnic groups such as Asians or Native Americans, whose outcomes after ICH may behave differently after ICH. Some factors that may influence outcome after ICH were not included in the models. Menopausal status and gonadal hormones concentration (serum and brain) were not measured as the underlying biology for the hypothesis for an age–sex interaction. Although the accepted standard for clinical trials, mRS is not the only metric for assessing recovery after ICH, and 90-day outcome may not accurately reflect outcome at 1 year after ICH. Thus, future work should include these patient populations. Despite these limitations, the present study utilized a large cohort of 3 racial/ethnic groups prominent in the United States, collected prospectively with strict definitions for ICH ascertainment, comorbidities, imaging, and outcomes to assess for a biologically plausible interaction between age and sex. While this sample represents the largest and most statistically powerful test of a sex-by-age interaction to date, existence of sex-by-age interaction effect in each of ethnic/racial cohorts cannot be absolutely excluded. However, given the size of the present sample, any interaction is unlikely to have significant clinical implications. Failure to find an outcome effect from sex or sex–age interaction may be due to study limits; however, the overall worse prognosis after ICH compared to ischemic stroke may limit the potential hormonal effects associated with sex.

In the largest cohort of patients with ICH to date, sex differences were found in multiple study characteristics and racial/ethnic backgrounds; however, there is little evidence that sex interacts with age to affect 90-day mRS and mortality.

Supplementary Material

Data Supplement:
Coinvestigators:

ACKNOWLEDGMENT

The authors thank Kathy Gage, research associate at Duke University, for assistance with medical editing.

GLOSSARY

BMI
body mass index
ERICH
Ethnic/Racial Variations of Intracerebral Hemorrhage
GCS
Glasgow Coma Scale
GERFHS
Genetic and Environmental Risk Factors for Hemorrhagic Stroke
ICH
intracerebral hemorrhage
IVH
intraventricular hemorrhage
mRS
modified Rankin Scale

Footnotes

Supplemental data at Neurology.org

AUTHOR CONTRIBUTIONS

Dr. James designed and conceptualized the study, interpreted the data, and drafted the manuscript. Dr. Langefeld designed the study, analyzed and interpreted the data, and revised the manuscript. P. Sekar designed the study, analyzed and interpreted the data, and revised the manuscript. Dr. Moomaw designed the study, interpreted the data, and revised the manuscript. Dr. Elkind designed the study, interpreted the data, and revised the manuscript. Dr. Worrall designed the study, interpreted the data, and revised the manuscript. Dr. Sheth designed the study, interpreted the data, and revised the manuscript. Dr. Martini designed the study, interpreted the data, and revised the manuscript. J. Osborne designed the study, interpreted the data, and revised the manuscript. Dr. Woo conceptualized and designed the study, interpreted the data, and revised the manuscript.

STUDY FUNDING

This study was funded by the NIH/NINDS U01-NS069763-05 (D.W.).

DISCLOSURE

The authors report no disclosures relevant to the manuscript. Go to Neurology.org for full disclosures.

REFERENCES

1. Lee HY, Hwang JS, Jeng JS, Wang JD Quality-adjusted life expectancy (QALE) and loss of QALE for patients with ischemic stroke and intracerebral hemorrhage: a 13-year follow-up. Stroke 2010;41:739–744. [PubMed]
2. Swartz KR, Fee DB, Joy KM, et al. Gender differences in spinal cord injury are not estrogen-dependent. J Neurotrauma 2007;24:473–480. [PubMed]
3. Ng I, Lee KK, Lim JH, Wong HB, Yan XY Investigating gender differences in outcome following severe traumatic brain injury in a predominantly Asian population. Br J Neurosurg 2006;20:73–78. [PubMed]
4. Simon JA, Hsia J, Cauley JA, et al. Postmenopausal hormone therapy and risk of stroke: the Heart and Estrogen-Progestin Replacement Study (HERS). Circulation 2001;103:638–642. [PubMed]
5. Gokhale S, Caplan LR, James ML Sex differences in incidence, pathophysiology, and outcome of primary intracerebral hemorrhage. Stroke 2015;46:886–892. [PubMed]
6. Lei B, Mace B, Bellows ST, et al. Interaction between sex and apolipoprotein E genetic background in a murine model of intracerebral hemorrhage. Transl Stroke Res 2012;3:94–101. [PMC free article] [PubMed]
7. Engman J, Ahs F, Furmark T, et al. Age, sex and nk1 receptors in the human brain: a positron emission tomography study with [(1)(1)c]gr205171. Eur Neuropsychopharmacol 2012;22:562–568. [PubMed]
8. Guevara R, Gianotti M, Roca P, Oliver J Age and sex-related changes in rat brain mitochondrial function. Cell Physiol Biochem 2011;27:201–206. [PubMed]
9. Hsieh JT, Lei B, Sheng H, et al. Sex-specific effects of progesterone on early outcome of intracerebral hemorrhage. Neuroendocrinology 2016;103:518–530. [PubMed]
10. Lei B, Wang H, Jeong S, et al. Progesterone improves neurobehavioral outcome in models of intracerebral hemorrhage. Neuroendocrinology 2016;103:665–677. [PubMed]
11. Woo D, Rosand J, Kidwell C, et al. The Ethnic/Racial Variations of Intracerebral Hemorrhage (ERICH) study protocol. Stroke 2013;44:e120–e125. [PMC free article] [PubMed]
12. Woo D, Sauerbeck LR, Kissela BM, et al. Genetic and environmental risk factors for intracerebral hemorrhage: preliminary results of a population-based study. Stroke 2002;33:1190–1195. [PubMed]
13. Flibotte JJ, Hagan N, O'Donnell J, Greenberg SM, Rosand J Warfarin, hematoma expansion, and outcome of intracerebral hemorrhage. Neurology 2004;63:1059–1064. [PubMed]
14. Goldstein JN, Fazen LE, Snider R, et al. Contrast extravasation on CT angiography predicts hematoma expansion in intracerebral hemorrhage. Neurology 2007;68:889–894. [PubMed]
15. Kumar MA, Rost NS, Snider RW, et al. Anemia and hematoma volume in acute intracerebral hemorrhage. Crit Care Med 2009;37:1442–1447. [PubMed]
16. Appelros P, Stegmayr B, Terent A Sex differences in stroke epidemiology: a systematic review. Stroke 2009;40:1082–1090. [PubMed]
17. Vaartjes I, Reitsma JB, Berger-van Sijl M, Bots ML Gender differences in mortality after hospital admission for stroke. Cerebrovasc Dis 2009;28:564–571. [PubMed]
18. Thrift AG, Dewey HM, Sturm JW, et al. Incidence of stroke subtypes in the North East Melbourne Stroke Incidence Study (NEMESIS): differences between men and women. Neuroepidemiology 2009;32:11–18. [PubMed]
19. Feldmann E, Broderick JP, Kernan WN, et al. Major risk factors for intracerebral hemorrhage in the young are modifiable. Stroke 2005;36:1881–1885. [PubMed]
20. Roof RL, Zhang Q, Glasier MM, Stein DG Gender-specific impairment on Morris water maze task after entorhinal cortex lesion. Behav Brain Res 1993;57:47–51. [PubMed]
21. Chen Z, Xi G, Mao Y, Keep RF, Hua Y Effects of progesterone and testosterone on ICH-induced brain injury in rats. Acta Neurochir Suppl 2011;111:289–293. [PubMed]
22. Gu Y, Xi G, Liu W, Keep RF, Hua Y Estrogen reduces iron-mediated brain edema and neuronal death. Acta Neurochir Suppl 2010;106:159–162. [PubMed]
23. Nakamura T, Xi G, Keep RF, et al. Effects of endogenous and exogenous estrogen on intracerebral hemorrhage-induced brain damage in rats. Acta Neurochir Suppl 2006;96:218–221. [PubMed]
24. Di Carlo A, Lamassa M, Baldereschi M, et al. ; European BSoSCG. Sex differences in the clinical presentation, resource use, and 3-month outcome of acute stroke in Europe: data from a multicenter multinational hospital-based registry. Stroke 2003;34:1114–1119. [PubMed]
25. Reeves MJ, Bushnell CD, Howard G, et al. Sex differences in stroke: epidemiology, clinical presentation, medical care, and outcomes. Lancet Neurol 2008;7:915–926. [PMC free article] [PubMed]
26. Ayala C, Croft JB, Greenlund KJ, et al. Sex differences in us mortality rates for stroke and stroke subtypes by race/ethnicity and age, 1995–1998. Stroke 2002;33:1197–1201. [PubMed]
27. Nilsson OG, Lindgren A, Brandt L, Saveland H Prediction of death in patients with primary intracerebral hemorrhage: a prospective study of a defined population. J Neurosurg 2002;97:531–536. [PubMed]
28. Sheikh K, Bullock CM Effect of measurement on sex difference in stroke mortality. Stroke 2007;38:1085–1087. [PubMed]
29. Zia E, Engstrom G, Svensson PJ, Norrving B, Pessah-Rasmussen H Three-year survival and stroke recurrence rates in patients with primary intracerebral hemorrhage. Stroke 2009;40:3567–3573. [PubMed]
30. Ganti L, Jain A, Yerragondu N, et al. Female gender remains an independent risk factor for poor outcome after acute nontraumatic intracerebral hemorrhage. Neurol Res Int 2013;2013:219097. [PMC free article] [PubMed]
31. Rodriguez-Luna D, Rubiera M, Ribo M, et al. Ultraearly hematoma growth predicts poor outcome after acute intracerebral hemorrhage. Neurology 2011;77:1599–1604. [PubMed]
32. Umeano O, Phillips-Bute B, Hailey CE, et al. Gender and age interact to affect early outcome after intracerebral hemorrhage. PLoS One 2013;8:e81664. [PMC free article] [PubMed]
33. Wang WJ, Lu JJ, Wang YJ, et al. ; China National Stroke Registry. Clinical characteristics, management, and functional outcomes in Chinese patients within the first year after intracerebral hemorrhage: analysis from China national stroke registry. CNS Neurosci Ther 2012;18:773–780. [PubMed]
34. Kissela B, Schneider A, Kleindorfer D, et al. Stroke in a biracial population: the excess burden of stroke among blacks. Stroke 2004;35:426–431. [PubMed]
35. Vasilevko V, Passos GF, Quiring D, et al. Aging and cerebrovascular dysfunction: contribution of hypertension, cerebral amyloid angiopathy, and immunotherapy. Ann NY Acad Sci 2010;1207:58–70. [PMC free article] [PubMed]
36. Hemphill JC III, Bonovich DC, Besmertis L, Manley GT, Johnston SC The ICH Score: a simple, reliable grading scale for intracerebral hemorrhage. Stroke 2001;32:891–897. [PubMed]
37. Kuramatsu JB, Sauer R, Mauer C, et al. Correlation of age and haematoma volume in patients with spontaneous lobar intracerebral haemorrhage. J Neurol Neurosurg Psychiatry 2011;82:144–149. [PubMed]
38. Lively S, Schlichter LC Age-related comparisons of evolution of the inflammatory response after intracerebral hemorrhage in rats. Transl stroke Res 2012;3:132–146. [PMC free article] [PubMed]
39. Gong Y, He Y, Gu Y, Keep RF, Xi G, Hua Y Effects of aging on autophagy after experimental intracerebral hemorrhage. Acta Neurochir Suppl 2011;111:113–117. [PubMed]
40. Hemphill JC III, Farrant M, Neill TA Jr Prospective validation of the ICH Score for 12-month functional outcome. Neurology 2009;73:1088–1094. [PMC free article] [PubMed]

Articles from Neurology are provided here courtesy of American Academy of Neurology