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Article

Epidemiology, Prevalence, and Predictors of Intracranial Hemorrhage with Sickle Cell Anemia †

1
Department of Internal Medicine, Trinity Health Oakland Hospital, Pontiac, MI 48341, USA
2
Department of Internal Medicine, Kansas University Medical Center, Wichita, KS 67214, USA
3
Department of Internal Medicine, Texas Tech University Health Sciences at El Paso, El Paso, TX 79905, USA
4
Department of Hematology Oncology, Lincoln Memorial University, Harrogate, TN 37752, USA
5
Department of Hematology Oncology, Karmanos Cancer Institute, Detroit, MI 48201, USA
*
Author to whom correspondence should be addressed.
This article is a revised and expanded version of a paper entitled “Intracranial Bleeding in Adults with Sickle Cell Disease: Unveiling the Hidden Dangers”, which was presented at the 66th ASH Annual Meeting and Exposition in San Diego, CA, USA, December 2024 and published in Blood on 5 November 2024, Volume 144, Supplement 1, 23 November 2024, Page 5323.
Hemato 2025, 6(4), 37; https://doi.org/10.3390/hemato6040037
Submission received: 16 September 2025 / Revised: 12 October 2025 / Accepted: 17 October 2025 / Published: 21 October 2025

Abstract

Introduction: Sickle cell anemia (SCA) is a hereditary hemoglobinopathy caused by a mutation in the beta-globin gene, resulting in the production of hemoglobin S. Intracranial hemorrhage (ICH) is a severe complication for patients with SCA, but there is a paucity of literature on its epidemiology, risk factors, and clinical outcomes. To address this knowledge gap, we conducted a comprehensive analysis using the Nationwide Inpatient Sample (NIS) database to evaluate the epidemiology, prevalence, predictors, and clinical outcomes of ICH in adults with SCA. Methods: We conducted a retrospective cohort study using the NIS database from 2016 to 2020 to identify hospitalizations with SCA, using the ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) codes. Subsequently, we derived the prevalence and predictors of ICH in SCA adults. Results: Out of 468,070 admissions of adult hospitalizations (Aged ≥ 18 years) with SCA between 2016 and 2020 in the United States, 825 (0.17%) had ICH (nontraumatic intraparenchymal and/or subarachnoid bleeding). 410 (49.7%) were males, and 380 (46.0%) belonged to the age group of more than 45 years. The mean length of stay was 14.9 days, and 210 deaths occurred during the index hospitalization, resulting in a 25.4% inpatient mortality rate as compared to 0.6% in SCA-non-ICH patients (p < 0.001). Across all adult SCA hospitalizations during 2016–2020 (n = 468,070), ICH accounted for 210 of 2940 inpatient SCA deaths (7.1%). On multivariate logistic regression analysis, hypertension (OR:2.08, 95% CI: 1.2–3.3), prior history of ischemic stroke (OR: 17.06, 95% CI: 7.5–38.5), and a Charlson comorbidity index of more than one (OR: 2.9, 95% CI: 2.4–3.5) are significant predictors of ICH in adults with SCA. Conclusions: This study highlights the high prevalence of ICH in addition to the well-known thrombotic phenomenon among SCA patients. Stroke prevention and hypertension control are of paramount importance for the prevention of this catastrophic event in patients with SCA.

1. Introduction

Sickle cell anemia (SCA) is a hereditary hemoglobinopathy caused by a mutation in the beta-globin gene, resulting in the production of hemoglobin S. This abnormal hemoglobin polymerizes under deoxygenated conditions, leading to the sickling of erythrocytes. These sickled cells exhibit reduced deformability, increased cellular adhesion, and a propensity to cause aggregation, which leads to vaso-occlusion and hemolysis. These repetitive events of vaso-occlusion trigger a range of acute and chronic complications, such as acute chest syndrome, vaso-occlusive pain crises, chronic anemia, and osteonecrosis of the femoral head (ONFH) [1] Additionally, SCA is recognized as a hypercoagulable condition, increasing the risk of ischemic strokes and venous thromboembolism (VTE) [2,3]. While SCA is not directly linked to known hemostatic defects, specific bleeding complications have been reported, particularly in neurological, renal, and ocular systems. These bleeding events are likely driven by recurrent vascular occlusion, ischemic damage, and compensatory neovascularization. For example, intracranial hemorrhage (ICH) often stems from bleeding in fragile, abnormal blood vessels formed through neovascularization, typically secondary to arterial stenosis, ischemic stroke, or cerebral aneurysms [4]. These are collectively referred to as “Intracranial arteriopathy,” which typically occurs in 30–40% of SCA patients [5]. Similarly, vitreous and retinal hemorrhages are associated with proliferative and non-proliferative retinopathy, respectively, arising in the context of vascular blockage and subsequent revascularization. In the kidneys, hematuria may result from ischemic papillary necrosis and rupture of renal capillaries [6].
Although bleeding complications in SCA are rare, their clinical significance is considerable due to their association with substantial morbidity and mortality. Among these, ICH is particularly feared, yet data on its prevalence, risk factors, and outcomes in adult patients with SCA remain limited. In various studies, it has been observed that the prevalence of ICH varies widely, ranging from 1.3% to 11%, depending on the type of modality used for diagnosis [7,8]. Recent prospective imaging work in SCA reports an intracranial aneurysm prevalence of ~17%, with aneurysm presence independently associated with older age and higher cerebral blood flow (CBF), representing the volume of blood delivered to brain tissue per unit time and a surrogate marker of cerebral hemodynamic stress. These observations align with non-SCA data implicating shear stress and endothelial injury in aneurysm pathogenesis. They may help explain the younger age at presentation and smaller rupture thresholds described in SCA. Given that hypertension remains a key modifiable cerebrovascular risk in SCA, its interaction with age-related vascular remodeling and heightened flow demands warrants specific emphasis in ICH prevention frameworks [9].
There is limited evidence guiding the management of acute intracerebral hemorrhage ICH in patients, aside from blood pressure control and potential surgical intervention. The use of blood transfusions remains controversial, as it may increase blood viscosity and potentially worsen the hemorrhage. Key aspects of hemorrhagic stroke in SCA, such as specific risk factors and ideal treatment approaches, are still not well understood. More multicentre prospective studies are necessary to clarify ICH incidence, develop effective screening strategies, and investigate innovative treatments to enhance outcomes. Additionally, the implementation of standardized care protocols is crucial. To address this knowledge gap, we conducted a comprehensive analysis using the Nationwide Inpatient Sample (NIS) database to evaluate epidemiology, prevalence, clinical outcomes, and predictors of ICH in adults with SCA.

2. Materials and Methods

2.1. Data Source and Population

This retrospective cohort study utilized the NIS database from 2016 and 2020 to identify hospitalizations with the primary diagnosis of SCA using the appropriate ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) code D57. NIS is an administrative database developed by the Agency for Healthcare Research and Quality (AHRQ) for the Healthcare Cost and Utilization Project (HCUP). It is a large, publicly available database consisting of approximately 35 million hospital discharges after applying weights. NIS contains both patient- and hospital-level information. Data elements comprise, but are not confined to, diagnoses, procedures, patient demographics (such as sex and age), primary payer of hospitalization, discharge month, quarter, and year, total charges, length of stay, and essential data elements pertinent to readmission analyses. It is crucial to note that the data elements that could directly or indirectly disclose the identity of individuals are omitted. As the database contains publicly available, depersonalized information, the study was exempt from review by the Institutional Review Board.

2.2. Baseline Variables and Comparison Groups

All adult patients (≥18 years) with a primary discharge diagnosis of SCA and ICH were included in the study. The focus of our investigation is limited to non-traumatic ICH, which includes both intraparenchymal and subarachnoid hemorrhage. Baseline variables included various patient demographics (including age, sex, primary payer, and median household income of residents in the patient’s ZIP code), hospital characteristics such as hospital size, teaching status, ownership, urban–rural designation, and hospital volume), complications during hospitalization, comorbidities (like hypertension, type 2 diabetes mellitus (Type 2 DM), dyslipidemia, obesity, coronary artery disease (CAD), congestive heart failure (CHF), chronic liver disease, chronic kidney disease (CKD), prior stroke, sequalae of Cerebro vascular accident (CVA), chronic obstructive pulmonary disease (COPD), Carotid artery disease, aortic disease, pulmonary hypertension, deep venous thrombosis (DVT), pulmonary embolism (PE), transient ischemic attack (TIA)) and outcome variables including in-hospital mortality, length of stay, and total hospital charges. Comorbidities listed above were identified using ICD-10-CM codes. ICD-10 codes used in the study are listed in the Supplementary Materials (Table S1).

2.3. Statistical Analysis

Weights were applied to produce national estimates, and analysis was performed with Stata software version 18 (Stata Corporation, College Station, TX, USA) using methodology provided by HCUP. Descriptive analysis was performed to compare demographics, hospital characteristics, various comorbid conditions, and complications between the two groups. We used Pearson’s chi-square test to obtain percentages for categorical variables and adjusted the Wald test to compare continuous values. Univariate analyses for between-group comparisons used the Rao-Scott Chi-square test for categorical variables (e.g., comorbidities) and weighted simple linear regression for continuous variables (e.g., age). Subsequently, multivariate logistic regression was carried out, including demographic and comorbid conditions to derive predictors of mortality. The results were reported as the adjusted odds ratio (aOR), 95% confidence intervals (CI), and p values. A p-value of less than 0.05 was considered significant.

3. Results

3.1. Baseline Demographics

Out of 468,070 hospitalizations of adult patients (aged ≥ 18 years) with SCA between 2016 and 2020 in the United States, 825 patients had ICH (nontraumatic intraparenchymal and/or subarachnoid bleeding) with a prevalence of 0.17%. 410 (49.7%) were males, and 380 (46.0%) belonged to the age group of more than 45 years. The majority were admitted to a teaching hospital (86.7%), with all of them (100%) being in urban areas with at least 1 million residents. Compared with non-ICH admissions (n = 467,245), the ICH cohort was markedly older (44.6 years vs. 34.3 years), with 46.1% ≥45 years vs. 19.2% (p < 0.001), while sex distribution was similar (p = 0.10). African Americans constitute a major proportion of the study population; whites were higher in the IC bleed group than those without IC bleed (7.2% vs. 1.7%, p < 0.001). Hypertension, CKD, dyslipidemia, cerebrovascular disease, PAD, aortic and carotid disease, atrial fibrillation, prior stroke, pulmonary hypertension, and prior DVT/PE were all significantly more common in the ICB cohort (all p < 0.05), whereas diabetes, CHF, obesity, cirrhosis, alcohol use disorder, and hypothyroidism did not differ significantly (Table 1).

3.2. Univariate Analysis

On univariable analysis, although 13.3% had sequelae to prior stroke, only 29.8% of patients had an Elixhauser comorbidity index of ≥3. The incidence of various comorbid conditions like hypertension, CHF, dyslipidemia, prior stroke of any form, hypothyroidism, Carotid artery atherosclerosis, aortic atherosclerotic disease, atrial fibrillation, and peripheral arterial disease was significantly higher in the SCA-ICH category compared to the non-ICH category (p < 0.05) (Table 1).

3.3. Subgroup Analysis

On subgroup analysis in patients with ICH, the mean age was significantly higher in patients with hypertension as compared to patients without hypertension (50 vs. 38.8 years, p = 0.005). Similar trends were observed in patients with CKD; however, the difference is not statistically significant. (55.5 vs. 41.2, p = 0.07) (Table 2).

3.4. Outcomes

Among 825 patients with SCA-ICH, the mean length of stay was 14.9 days, and 210 in-hospital deaths occurred, corresponding to a 25.4% inpatient mortality rate. In contrast, mortality in the 467,245 SCA patients without ICH was 0.6% (p < 0.001). Thus, ICH accounted for 210 of the total 2940 inpatient SCA deaths (7.1%) during the study period. Patients with ICH also had a significantly longer mean length of stay (14.9 vs. 5.3 days, p < 0.001) and higher mean total hospitalization charges ($263,440 vs. $43,599, p < 0.001). (Table 3).

3.5. Multivariate Analysis to Derive Predictors of ICH in SCA

Multivariate analysis was performed to derive the predictors of ICH among patients with SCA. Age was not found to be a predictor of ICH (p = 0.203). However, comorbid illnesses like a history of ischemic stroke (OR: 17.06, 95% CI: 7.5–38.5), hypertension (OR: 2.08, 95% CI: 1.2–3.3), and a higher Charlson comorbidity index > 1 (OR: 2.9, 95% CI: 2.4–3.5) predicted the development of ICH in patients with SCA (Table 4).

3.6. Multivariate Analysis to Derive Predictors of In-Hospital Mortality

Multivariate analysis was performed to derive the predictors of in-hospital mortality among all sickle cell hospitalizations. Patients with ICH have significantly higher mortality with odds of 10.9 (95% CI: 4.3–27.3, p < 0.01). Prior ischemic stroke (OR 10.4, 95% CI 5.4–19.8), history of pulmonary embolism (OR 13.2, 95% CI 8.6–20.2), higher comorbidity burden (Charlson index per point: OR 1.6, 95% CI 1.4–1.8), chronic liver disease (OR 2.4, 95% CI 1.7–3.2) and congestive heart failure (OR 1.6, 95% CI 1.1–2.3) were additional independent predictors (Table S2).

4. Discussion

This nationwide study is, to our knowledge, the first to investigate ICH in patients with SCA. Utilizing a comprehensive nationwide database, this research provides critical insights into the epidemiology, prevalence, outcomes, and predictors of ICH among adult patients with SCA. The findings underscore the substantial burden of ICH in this population, reflecting significant clinical and economic implications, and highlight the necessity for targeted interventions and resource allocation.
Our results are in alignment with emerging data that intracranial aneurysms are relatively common in SCA (~17%) and that older age and elevated CBF, a tissue-level surrogate of hemodynamic stress, are independently associated with aneurysm presence. These findings support a working model in which aging vasculopathy, hypertension, and flow-mediated endothelial injury synergize to increase hemorrhagic susceptibility in SCA [9,10]. ICH, a relatively rare complication with a prevalence of 0.17% among hospitalized adult SCA patients, is associated with alarmingly high morbidity and mortality rates, consistent with prior research emphasizing the heightened vascular fragility in SCA due to chronic ischemic insults and inflammation [1]. Demographically, patients experiencing ICH were older (mean age of 44.6 years) compared to their non-ICH counterparts, but on a multivariable analysis, age alone was not a predictor of ICH, indicative of the role of other comorbid conditions in the pathophysiology of ICH. Furthermore, a disproportionate representation of white patients in the ICH subgroup (7.2% vs. 1.7%, p < 0.001) raises important questions regarding genetic, environmental, and healthcare disparities [4]. The concentration of cases in urban teaching hospitals (86.7%) emphasizes the critical role of specialized care facilities in managing these complications. Clinically, ICH was strongly associated with comorbid conditions such as hypertension, dyslipidemia, prior stroke, and atherosclerotic cardiovascular disease, which aligns with existing literature on the interplay of vascular comorbidities in exacerbating cerebrovascular risks [6].
In multivariate analysis, hypertension and prior ischemic stroke are significant predictors of ICH. In an age-stratified analysis, the median age for patients with hypertension who had ICH was higher compared to patients without hypertension. Hypertensive intracranial hemorrhages are small vessel hemorrhages in deep brain regions; it is beyond the scope of this study to identify what proportion of patients in our study had truly hypertensive hemorrhage. The pathophysiology of ICH in SCA appears multifactorial, involving chronic vascular damage, neovascularization, and increased vascular fragility driven by repeated ischemic events and exacerbated by the inherent hypercoagulable state associated with SCA [11]. Notably, aneurysms in SCA have been reported to rupture at smaller sizes and at younger ages than in the general population, suggesting that conventional size thresholds for intervention may underestimate risk in SCA [12]. Given hypertension as an established risk factor for cerebrovascular injury in SCA, including hemorrhagic stroke risk, aggressive blood pressure control remains central to mitigation strategies [8].
In-hospital outcomes are concerning, with a mortality rate of 25.4% in ICH patients compared to 0.6% in non-ICH SCA patients (p < 0.001), compounded by significant healthcare costs averaging $263,000 per hospitalization. Importantly, within the nationwide SCA inpatient population, ICH accounted for 7.1% of all in-hospital deaths, highlighting its disproportionate lethality relative to its incidence. Future directions should prioritize aggressive management of modifiable cardiovascular risk factors, such as hypertension and dyslipidemia, alongside research into racial and genetic disparities, as well as the development of biomarkers for early detection and prevention of vascular instability in SCA populations [13,14].
This data brings an important question regarding the necessity of an imaging-based screening test for patients at high risk of ICH and the potential role of early intervention in improving outcomes. Recent prospective cohorts show a meaningful 3-year rate of de novo aneurysm formation in SCA, predominantly in the anterior circulation and associated with higher CBF. While universal adult MRA screening is not a guideline standard, these data support targeted imaging in older patients and in those with hypertension or prior ischemic cerebrovascular disease. Prospective studies integrating CBF with vessel-wall imaging should define who benefits and when to screen [9,15,16]. This comprehensive approach could significantly mitigate the burden of ICH in this vulnerable group and improve long-term outcomes. In conclusion, while rare, ICH in SCA patients is a serious complication with a high mortality rate, substantial comorbidity burden, and significant healthcare costs. Identifying high-risk individuals and significant risk factor control, like stroke prevention strategies and blood pressure control, will be key steps toward improving outcomes [17].

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/hemato6040037/s1, Table S1: ICD-10-CM codes of all comorbid conditions; Table S2: Predictors of Mortality in patients with SCA hospitalizations.

Author Contributions

Conceptualization: N.V., R.N.S., L.K., N.M., G.K. and V.S.; methodology: N.V. and R.N.S.; software, resources and formal analysis, N.V. and R.N.S.; validation, N.V., R.N.S., L.K. and V.S.; data curation: N.V. and R.N.S.; writing—original draft preparation: N.V., R.N.S. and L.K.; writing—review and editing: N.V., R.N.S., L.K., N.M., G.K. and V.S.; supervision: N.M., G.K. and V.S.; project administration: N.V. and V.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

As the database contains publicly available, depersonalized information, the study was exempt from review by the Institutional Review Board.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data used in this study are available upon request from the authors.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Ohene-Frempong, K.; Weiner, S.J.; Sleeper, L.A.; Miller, S.T.; Embury, S.; Moohr, J.W.; Wethers, D.L.; Pegelow, C.H.; Gill, F.M. Cerebrovascular accidents in sickle cell disease: Rates and risk factors. Blood J. Am. Soc. Hematol. 1998, 91, 288–294. [Google Scholar]
  2. Ataga, K.I.; Orringer, E.P. Hypercoagulability in sickle cell disease: A curious paradox. Am. J. Med. 2003, 115, 721–728. [Google Scholar] [CrossRef] [PubMed]
  3. Zedde, M.; Quaresima, M.; Capodanno, I.; Grisendi, I.; Assenza, F.; Napoli, M.; Moratti, C.; Pavone, C.; Bonacini, L.; Di Cecco, G.; et al. Neurovascular Manifestations of Sickle Cell Disease. Hemato 2024, 5, 277–320. [Google Scholar] [CrossRef]
  4. Oyesiku, N.M.; Barrow, D.L.; Eckman, J.R.; Tindall, S.C.; Colohan, A.R. Intracranial aneurysms in sickle-cell anemia: Clinical features and pathogenesis. J. Neurosurg. 1991, 75, 356–363. [Google Scholar] [CrossRef] [PubMed]
  5. Russell, M.O.; Goldberg, H.I.; Hodson, A.; Kim, H.C.; Halus, J.; Reivich, M.; Schwartz, E. Effect of transfusion therapy on arteriographic abnormalities and on recurrence of stroke in sickle cell disease. Blood 1984, 63, 162–169. [Google Scholar] [CrossRef] [PubMed]
  6. Nath, K.A.; Hebbel, R.P. Sickle cell disease: Renal manifestations and mechanisms. Nat. Rev. Nephrol. 2015, 11, 161–171. [Google Scholar] [CrossRef] [PubMed]
  7. Allali, S.; Taylor, M.; Brice, J.; de Montalembert, M. Chronic organ injuries in children with sickle cell disease. Haematologica 2021, 106, 1535–1544. [Google Scholar] [CrossRef] [PubMed]
  8. Birkeland, P.; Gardner, K.; Kesse-Adu, R.; Davies, J.; Lauritsen, J.; Rom Poulsen, F.; Tolias, C.M.; Thein, S.L. Intracranial Aneurysms in Sickle-Cell Disease Are Associated with the Hemoglobin SS Genotype But Not with Moyamoya Syndrome. Stroke 2016, 47, 1710–1713. [Google Scholar] [CrossRef] [PubMed]
  9. Wang, Y.; Garland, J.S.; Fellah, S.; Reis, M.N.; Parsons, M.S.; Guilliams, K.P.; Fields, M.E.; Mirro, A.E.; Lewis, J.B.; Ying, C.; et al. Intracranial aneurysms in sickle cell disease are associated with hemodynamic stress and anemia. Blood Adv. 2024, 8, 4823–4831. [Google Scholar] [CrossRef] [PubMed]
  10. Strouse, J.J.; Lanzkron, S.; Urrutia, V. The epidemiology, evaluation and treatment of stroke in adults with sickle cell disease. Expert. Rev. Hematol. 2011, 4, 597–606. [Google Scholar] [CrossRef] [PubMed]
  11. Sharma, A.; Dahiya, A.; Alavi, A.; Woldie, I.; Sharma, A.; Karson, J.; Singh, V. Patterns of Blood Transfusion in Sickle Cell Disease Hospitalizations. Hemato 2024, 5, 26–34. [Google Scholar] [CrossRef]
  12. Fox, C.K.; Leykina, L.; Hills, N.K.; Kwiatkowski, J.L.; Kanter, J.; Strouse, J.J.; Voeks, J.H.; Fullerton, H.J.; Adams, R.J. Hemorrhagic Stroke in Children and Adults with Sickle Cell Anemia: The Post-STOP Cohort. Stroke 2022, 53, e463–e466. [Google Scholar] [CrossRef] [PubMed]
  13. Kato, G.J.; Hebbel, R.P.; Steinberg, M.H.; Gladwin, M.T. Vasculopathy in sickle cell disease: Biology, pathophysiology, genetics, translational medicine, and new research directions. Am. J. Hematol. 2009, 84, 618. [Google Scholar] [CrossRef] [PubMed]
  14. Darbari, D.S.; Kple-Faget, P.; Kwagyan, J.; Rana, S.; Gordeuk, V.R.; Castro, O. Circumstances of death in adult sickle cell disease patients. Am. J. Hematol. 2006, 81, 858–863. [Google Scholar] [CrossRef] [PubMed]
  15. Padilha, I.G.; Guilbert, F.; Létourneau-Guillon, L.; Forté, S.; Nelson, K.; Bélair, M.; Raymond, J.; Soulières, D. Should Magnetic Resonance Angiography Be Used for Screening of Intracranial Aneurysm in Adults with Sickle Cell Disease? J. Clin. Med. 2022, 11, 7463. [Google Scholar] [CrossRef] [PubMed]
  16. DeBaun, M.R.; Jordan, L.C.; King, A.A.; Schatz, J.; Vichinsky, E.; Fox, C.K.; McKinstry, R.C.; Telfer, P.; Kraut, M.A.; Daraz, L.; et al. American Society of Hematology 2020 guidelines for sickle cell disease: Prevention, diagnosis, and treatment of cerebrovascular disease in children and adults. Blood Adv. 2020, 4, 1554–1588. [Google Scholar] [CrossRef]
  17. Vojjala, N.; Kyasa, S.B.; Sharma, A.; Kotla, N.K.; Prabhu, R.; Singh, V. Intracranial Bleeding in Adults with Sickle Cell Disease: Unveiling the Hidden Dangers. Blood 2024, 144, 5323. [Google Scholar] [CrossRef]
Table 1. Baseline characteristics of the study population.
Table 1. Baseline characteristics of the study population.
Baseline VariableSCA with ICH (n = 825)SCA Without ICH (n = 467,245)p-Value
Age, years(mean)44.634.3<0.001
18–44 years53.9%80.8%
45–64 years30.4%16.1%<0.001
≥65 years15.7%3.1%
Gender
Male49.7%43.2%0.100
Female50.3%56.7%
Race
Whites7.2%1.7%
African American82.4%90.2%
Hispanics4.2%4.0%<0.001
Others6.0%4.1%
Charlson comorbidity index
01.0%59.0%
144.0%25.0%<0.001
220.0%8.0%
≥335.0%8.0%
Insurance
Medicare44.3%33.7%
Medicaid26.8%45.1%
Private insurance25.0%16.9%<0.001
Self-pay/uninsured3.7%4.1%
Household income
Quartile 138.7%51.0%
Quartile 226.2%22.7%0.009
Quartile 323.7%16.2%
Quartile 411.2%10.3%
Hospital Region
Northeast15.7%19.1%
Midwest17.5%17.9%0.006
Southeast50.5%54.0%
West16.3%8.8%
Bed size of a hospital
Small10.9%17.5%
Medium23.0%26.6%0.202
Large55.8%5.5%
Type of hospital
Not teaching13.3%19.0%0.080
Teaching86.7%81.0%
Location
Rural0%3.9%
Urban100%97.1%0.017
Comorbidities
Diabetes mellitus8.4%6.6%0.341
HTN53.3%25.7%<0.001
Active smoking29.7%27.2%0.476
CHF18.7%9.6%0.0001
Obesity5.4%7.0%0.419
CKD23.0%10.8%<0.001
Dyslipidemia12.1%4.4%<0.001
CAD5.4%4.1%0.3837
Sequelae of CVA13.3%2.6%<0.001
PAD2.4%0.08%0.028
Aortic disease1.2%0.01%<0.001
Carotid artery dx3.6%0.2%<0.001
COPD5.4%3.8%0.2997
Cirrhosis of the Liver2.4%1.5%0.338
Alcohol use disorder2.4%1.1%0.139
Hypothyroidism4.8%2.4%0.045
Prior stroke15.1%10.1%0.037
Pulmonary HTN1.2%0.6%0.384
Past DVT/PE14.5%19.1%0.133
Atrial fibrillation9.01%2.01%<0.001
Active cancer1.1%0.9%0.685
Abbreviations: SCA—sickle cell anemia, ICH—Intracranial Hemorrhage, HTN—Hypertension, CHF—Congestive heart failure, CKD—Chronic Kidney disease, CAD—Coronary artery disease, CVA—Cerebrovascular accident, PAD—Peripheral arterial disease, COPD—Chronic Obstructive pulmonary disease, Pulmonary HTN—Pulmonary hypertension, DVT/PE—Deep Venous thrombosis/Pulmonary embolism, Mean LOS—Mean length of stay. CCI = Charlson Comorbidity Index; higher scores reflect greater comorbidity burden. CCI categories are presented as 0, 1, 2, and ≥3.
Table 2. Mean age stratification based on hypertension and CKD in patients with ICH.
Table 2. Mean age stratification based on hypertension and CKD in patients with ICH.
Baseline FeatureMean Age (±SE) with HTN or CKDMean Age (±SE) Without HTN or CKDp-Value
Hypertension50.0 (±2.6)38.8 (±1.7)0.005
CKD55.5 (±7.8)41.2 (±1.5)0.07
Table 3. Mortality and Hospital utilization metrics during index hospitalization.
Table 3. Mortality and Hospital utilization metrics during index hospitalization.
ParameterSCA ICH Group
(n = 825)
SCA-Non-ICH Group
(n = 467,245)
p-Value
Mortality rates25.4%0.6%<0.001
Mean LOS14.9 days5.29 days<0.001
Mean total charges263,440.5 $43,599.1 $<0.001
LOS: length of stay; SCA: Sickle Cell Anemia; ICH: Intracranial hemorrhage.
Table 4. Multivariate logistic regression of predictors of intracranial hemorrhage in patients with SCA.
Table 4. Multivariate logistic regression of predictors of intracranial hemorrhage in patients with SCA.
ParameterOdds Ratio95% Confidence Interval
Age1.00.9–1.02
Female sex1.10.7–1.6
Hypertension2.081.2–3.3
Prior ischemic stroke17.07.5–38.5
Chronic kidney disease0.750.2–2.1
Chronic liver disease0.970.42–2.2
Type 2 DM0.430.2–1.4
Hyperlipidemia1.00.5–2.0
Obesity0.40.1–1.1
Peripheral arterial disease0.50.1–2.3
Coronary artery disease0.60.2–1.5
Congestive heart failure0.40.2–1.2
Atrial fibrillation1.80.8–3.9
Pulmonary hypertension0.50.2–1.1
History of DVT2.90.8–10.1
History of PE1.10.1–9.7
Alcohol use disorder1.10.2–5.0
Smoking0.90.6–1.5
Charlson comorbidity index2.92.4–3.5
Age, sex, and comorbid illnesses like type 2 DM, hypertension, dyslipidemia, obesity, presence of CAD, CHF, CLD, CKD, pulmonary hypertension, prior history of DVT, PE, alcohol use disorder, smoking, and the Charlson comorbidity index were included in the logistic regression model. DM: Diabetes mellitus, DVT: Deep venous thrombosis, PE: Pulmonary embolism, CAD: Coronary artery disease, CLD: Chronic liver disease, CKD: Chronic kidney disease, CHF: Congestive heart failure.
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Vojjala, N.; Shah, R.N.; Kattamuri, L.; Moka, N.; Krishnamoorthy, G.; Singh, V. Epidemiology, Prevalence, and Predictors of Intracranial Hemorrhage with Sickle Cell Anemia. Hemato 2025, 6, 37. https://doi.org/10.3390/hemato6040037

AMA Style

Vojjala N, Shah RN, Kattamuri L, Moka N, Krishnamoorthy G, Singh V. Epidemiology, Prevalence, and Predictors of Intracranial Hemorrhage with Sickle Cell Anemia. Hemato. 2025; 6(4):37. https://doi.org/10.3390/hemato6040037

Chicago/Turabian Style

Vojjala, Nikhil, Raj N. Shah, Lakshmi Kattamuri, Nagaishwarya Moka, Geetha Krishnamoorthy, and Vijendra Singh. 2025. "Epidemiology, Prevalence, and Predictors of Intracranial Hemorrhage with Sickle Cell Anemia" Hemato 6, no. 4: 37. https://doi.org/10.3390/hemato6040037

APA Style

Vojjala, N., Shah, R. N., Kattamuri, L., Moka, N., Krishnamoorthy, G., & Singh, V. (2025). Epidemiology, Prevalence, and Predictors of Intracranial Hemorrhage with Sickle Cell Anemia. Hemato, 6(4), 37. https://doi.org/10.3390/hemato6040037

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