"Never doubt that a small group of thoughtful, committed citizens can change the world. Indeed, it is the only thing that ever has."

Margaret Mead

Original article
peer-reviewed

Risk Factors and Incidence of Acute Ischemic Stroke: A Comparative Study Between Young Adults and Older Adults



Abstract

Introduction

Approximately 5-10% of strokes occur in adults of less than 45 years of age. The rising prevalence of stroke risk factors may increase stroke rates in young adults (YA). We aimed to compare risk factors and outcomes of acute ischemic stroke (AIS) among YA.

Methods

Adult hospitalizations for AIS and concurrent risk factors were found in the Nationwide Inpatient Sample database. Weighted analysis using chi-square and multivariable survey logistic regression was performed to evaluate AIS-related outcomes and risk factors among YA (18-45 years) and older patients.

Results

A total of 4,224,924 AIS hospitalizations were identified from 2003 to 2014, out of which 198,378 (4.7%) were YA. Prevalence trend of YA with AIS showed incremental pattern over time (2003: 4.36% to 2014: 4.7%; pTrend<0.0001). In regression analysis, the risk factors associated with AIS in YA were obesity (adjusted odds ratio {aOR}: 2.26; p<0.0001), drug abuse (aOR: 2.56; p<0.0001), history of smoking (aOR: 1.20; p<0.0001), infective endocarditis (aOR: 2.08; p<0.0001), cardiomyopathy (aOR: 2.11; p<0.0001), rheumatic fever (aOR: 4.27; p=0.0014), atrial septal disease (aOR: 2.46; p<0.0001), ventricular septal disease (aOR: 4.99; p<0.0001), HIV infection (aOR: 4.36; p<0.0001), brain tumors (aOR: 7.89; p<0.0001), epilepsy (aOR: 1.43; p<0.0001), end stage renal disease (aOR: 2.19; p<0.0001), systemic lupus erythematous (aOR: 3.76; p<0.0001), polymyositis (aOR: 2.72; p=0.0105), ankylosis spondylosis (aOR: 2.42; p=0.0082), hypercoagulable state (aOR: 4.03; p<0.0001), polyarteritis nodosa (aOR: 5.65; p=0.0004), and fibromuscular dysplasia (aOR: 2.83; p<0.0001).

Conclusion

There is an increasing trend in AIS prevalence over time among YA. Both traditional and non-traditional risk factors suggest that greater awareness is needed, with prevention strategies for AIS among young adults.

Introduction

Stroke is the second leading cause of death globally, and although it is most common in the elderly, a significant number of young adults (YA) suffer from it every year [1,2]. The risk of stroke increases with age, but can occur at any age. In 2009, 34% of people hospitalized for stroke were less than 65 years old [3]. Approximately 5-10% of strokes occur in adults <45 years of age [4-8]. Despite considerable improvements in primary prevention, diagnostic workup, and treatment, stroke still remains a major cause of morbidity, serious physical and cognitive long-term disability, and loss in work-related productivity especially when it occurs in the younger population [9,10].

In a systematic review of stroke incidence in YA, the proportion of ischemic strokes ranged between 21.0% and 77.9% in patients under 45 years of age with first-ever stroke [11]. There were 59,077 deaths in YA in the United States from 1989 through 2009 due to stroke, contributing to 2868 deaths per year on average with an average annual mortality rate among YA being 0.93 per 100,000 persons for intracerebral hemorrhage (ICH), 1.1 per 100,000 persons for subarachnoid hemorrhage (SAH), and 0.70 per 100,000 persons for ischemic stroke [12]. In a single-center study comparing characteristics of stroke between younger and older patients, there were significant differences in risk factors, etiology, and distribution of sex between these groups [13]. Edwards et al. from the Canadian Institute for Health Information Discharge Abstract Database (n = 26,366) described a higher hazard for recurrent stroke at one year (hazard ratio {HR}: 6.8), at five years (HR: 5.1), stroke survivors had higher mortality and morbidity, and patients with TIA had a higher prevalence (31.5%; 1789/5677) of an adverse event within the first five years [14].

Our study aimed to provide estimates on the burden of stroke among YA in the United States. We performed a comprehensive assessment to compare traditional and non-traditional risk factors and ischemic stroke-related mortality, morbidity, discharge disposition, disability, and risk of death among young adults (YA: 18-45 years) vs. old adults (OA: >45 years) between 2003 and 2014.

Materials & Methods

Data were obtained from the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) files from January 2003 to December 2014. The NIS is the largest publicly available all-payer inpatient care database in the United States and contains discharge-level data provided by states that participate in the HCUP (including a total of 46 states in 2011). This administrative dataset contains data on approximately eight million hospitalizations in 1000 hospitals that were chosen to approximate a 20% stratified sample of all US community hospitals, representing more than 95% of the national population. Discharge weights are provided for each patient discharge record, which helps to obtain national estimates. Each hospitalization is treated as an individual entry in the database and is coded with one principal diagnosis, up to 24 secondary diagnoses, and 15 procedural diagnoses associated with that stay (detailed information on NIS is available at http://www.hcup-us.ahrq.gov/db/nation/nis/nisdde.jsp). The NIS is a de-identified database, so informed consent or IRB approval was not needed for the study. The HCUP Data Use Agreement and training (HCUP-4Q28K90CU) for the data utilized in this study were obtained.

Study population

We used the ninth revision of the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes to identify adult patients admitted with a primary diagnosis of AIS (ICD-9-CM codes 433.01, 433.11, 433.21, 433.31, 433.81, 433.91, 434.01, 434.11, 434.91). These codes have been previously validated and are 35% sensitive, 99% specific, with 96% positive predictive value (PPV), and 79% negative predictive value for the diagnosis of ischemic stroke [15]. We used ICD-9-CM codes to identify traditional and non-traditional risk factors. Table 1 lists all ICD-9-CM codes that were used for this study. Age <18 years and admissions with missing data for age, sex, and race were excluded.

Disease ICD9-CM codes nationwide inpatient sample
Infective endocarditis 421.0
Cardiomyopathy 425.1 Primary CM, 425.20 Obscure cardiomyopathy of Africa, 425.30 Endocardial fibroelastosis, 425.40 Other primary cardiomyopathies, 425.50 Alcoholic cardiomyopathy, 425.70 Nutritional and metabolic cardiomyopathy, 425.80-429.83 Cardiomyopathy in other diseases classified Takotsubo, 425.90, 674.5, 414.8 Secondary cardiomyopathy, unspecified Peripartum cardiomyopathy Ischemic
Rheumatic fever 390, 391.9, 391.1, 391.8, 391.2, 391.0
IHD 410.00, 410.01, 410.02, 410.10, 410.11, 410.12, 410.20, 410.21, 410.22, 410.30, 410.31, 410.32, 410.40, 410.41, 410.42, 410.50, 410.51, 410.52, 410.60, 410.61, 410.62, 410.70, 410.71, 410.72, 410.80, 410.81, 410.82, 410.90, 410.91, 410.92, CAD: 414.00-414.07, old MI - 412
ASD  745.5, 745.61
VSD 745.4
PDA 747.0
Rheumatoid arthritis 714.0, 714.1, 714.2
Ankylosing spondylitis 720.0
Psoriatic arthritis 696.0
SLE 710.0
Scleroderma 701.0
Sjogren’s syndrome 710.2
Polymyositis 710.4
Dermatomyositis 710.3
Hypercoagulable disorders (factor V Leiden mutation, antiphospholipid antibodies, protein S deficiency, antithrombin III deficiency 286.53, 289.81, 795.79
Polycythemia rubra 238.4
Pneumonia Viral - 480.0, 480.1, 480.2, 480.3, 480.8, 480.9, Pneumococcal- 481 Other - bacterial pneumonia- 482.0, 482.1, 482.2, 482.3, Strep - 482.30, 482.31, 482.32, 482.39, Staph - 482.40, 482.41, 482.42, 482.49, Other specified bacteria - 482.81, 482.82, 482.83, 482.84, 482.89, 482.9, 483.0, 483.1, 483.8 486
Urinary tract infection 599.0
TB meningitis 013.00
Tuberculoma 013.20
Neurosyphilis 094.0 Tabes dorsalis, 094.1 General paresis, 094.2 Syphilitic meningitis, 094.3 Asymptomatic neurosyphilis, 094.81 Syphilitic encephalitis, 094.82 Syphilitic parkinsonism, 094.83 Syphilitic disseminated, 094.84 Syphilitic optic atrophy, 094.85 Syphilitic retrobulbar neuritis, 094.86 Syphilitic acoustic neuritis, 094.87 Syphilitic ruptured cerebral aneurysm, 094.89 Other specified neurosyphilis, 094.9 Neurosyphilis, unspecified 
Cryptococcal meningitis 321.0
Seizure  345.01 generalized nonconvulsive epilepsy 345.0 nonconvulsive/absence 345.1 Gen convulsion 345.2 Petit mal status 345.3 Grand mal status 345.4 Partial epi w impairment of consciousness 345.5 partial epi w/o impairment of cons 780.3 Convulsion excluding epileptic convulsion & of newborn 780.39 other convulsion 780.31 febrile convulsion 345.6 infantile spasms 345.81 Intractable epilepsy
CNS tumors 191.0, Cerebrum, except lobes and ventricles 191.1, Frontal lobe. 191.2, Temporal lobe 191.3, Parietal lobe. 191.4, Occipital lobe. 191.5, Ventricles, 191.6, Cerebellum, 191.7, Brain stem. 191.8, Other parts of brain, 191.9, Brain unspecified and cranial fossa unspecified.
AVM brain 747.81
Moyamoya 437.5
Giant cell arteritis 446.5
PAN 446.0
Takayasu's disease 446.7
Thromboangiitis obliterans 443.1
HIV  042, V08
Fabry's 272.7
Fibromuscular dysplasia 447.8 447.3
Sickle cell disease 282.60, 282.62 Hb SS with crisis 282.61 Hb SS without crisis 282.63 SC/HbC w/o crisis 282.64 SC/HbC w crisis 282.68 other SCD without crisis 282.69 other SCD with crisis 282.41 Sickle cell-thalassemia without crisis 282.42 Sickle cell-thalassemia with crisis
 Pregnancy V22.0, V22.1, V22.2, V23.9
Pregnancy-related conditions/complications Hyperemesis 643.10, 643.11, 643.13 Preterm labor 644.00, 644.03, 644.10, 644.13, 644.20, 644.21 Antepartum hemorrhage, 641.10, 641.11, 641.13, 641.30, 641.31, 641.33, 641.80, 641.83, 641.90, 641.93 Preeclampsia and gestational hypertension 642.40, 642.41, 642.42, 642.43, 642.44, 642.50, 642.51, 642.52, 642.53, 642.54, 642.60, 642.61, 642.62, 642.63, 642.64, 642.70, 642.71, 642.72, 642.73, 642.74, 642.90, 642.91, 642.92, 642.93, 642.94, diabetes - 648.00, 648.01, 648.02, 648.03, 648.04, 648.80, 648.81, 648.82, 648.83, 648.84, Postpartum hemorrhage 666.00, 666.02, 666.04, 666.10, 666.12, 666.14, 666.20, 666.22, 666.24, 666.30, 666.32, 666.34, Puerperial septic thrombophlebitis: 670.30, 670.32, 670.34
Alcohol 303.00, 303.01, 303.02, 303.03 303.90, 303.91, 303.92, 303.93 305.0
substance abuse 305.90, 305.20, 305.21, 305.22, 305.23, 305.30, 305.31, 305.32, 305.33, 305.40, 305.41, 305.42, 305.43 305.50, 305.51, 305.52, 305.53 305.60, 305.61, 305.62, 305.63 305.70, 305.71, 305.72, 305.73 305.80, 305.81, 305.82, 305.83 305.90, 305.91, 305.392, 305.93
Smoking 305.1, V15.82
Hypertension 401.0, 401.9, Complications - 402.00, 402.10, 402.90, 403.00, 403.10, 403.90, 404.00, 404.10, 404.90, 404.01, 404.11, 404.91, 404.93, 404.13, 404.93
 DM  250.00, 250.01, 250.02, 250.03, 250.10, 250.11, 250.12, 250.13, 250.20, 250.21, 250.22, 250.23, 250.30, 250.31, 250.32, 250.33, 250.40, 250.41, 250.42, 250.43, 250.50, 250.51, 250.52, 250.53, 250.60, 250.61, 250.62, 250.63, 250.70, 250.71, 250.72, 250.73,
A.fib 427.31
Hypercholesterolemia 272.0, 272.1, 272.2

Patient and hospital characteristics

Patient characteristics of interest were age, sex, race, insurance status, and concomitant diagnoses as defined above. The race was defined by white (referent), African American, Hispanic, Asian or Pacific Islander, and Native American. Insurance status was defined by Medicare (referent), Medicaid, Private Insurance, and Other/Self-pay/No charge. We defined the severity of co-morbid conditions using Deyo's modification of the Charlson Comorbidity Index (CCI) (Table 2).

Condition ICD-9-CM codes Charlson score
Myocardial infarction 410-410.9 1
Congestive heart failure 428-428.9 1
Peripheral vascular disease 433.9, 441-441.9, 785.4, V43.4 1
Cerebrovascular disease 430-438 1
Dementia 290-290.9 1
Chronic pulmonary disease 490-496, 500-505, 506.4 1
Rheumatologic disease 710.0, 710.1, 710.4, 714.0-714.2, 714.81, 725 1
Peptic ulcer disease 531-534.9 1
Mild liver disease 571.2, 571.5, 571.6, 571.4 –571.49 1
Diabetes 250-250.3, 250.7 1
Diabetes with chronic complications 250.4-250.6 2
Hemiplegia or paraplegia 344.1, 342-342.9 2
Renal disease 582-582.9, 583-583.7, 585, 586, 588-588.9 2
Any malignancy including leukemia and lymphoma 140-172.9, 174-195.8, 200-208.9 2
Moderate or severe liver disease 572.2-572.8 3
Metastatic solid tumor 196-199.1 6
AIDS 042-044.9 6

Outcomes

Our primary interest was to compare the prevalence of traditional and non-traditional risk factors of AIS among YA (18-45 years) and OA (>45 years). The secondary interest was to compare outcomes of AIS in YA and OA. The outcomes were all-cause mortality during hospitalization, morbidity (length of stay >10 days {>90th percentile of AIS hospitalization} and discharge to non-home {transfer to short-term hospital, skilled nursing facility, intermediate care facility, or home health care}), discharge disposition (discharge to home vs. non-home), All Patients Refined Diagnosis Related Groups (APR-DRG) risk of mortality, APR-DRG severity of illness (disability), length of stay (LoS), and cost of hospitalization [16]. APR-DRGs were assigned using software developed by 3M Health Information Systems, where score 1 indicates minor loss of function, 2-moderate, 3-major, 4-extreme loss of function or likelihood of death. APR-DRG coding system used in this study to assess the risk of mortality and severity of illness is externally validated. It is a reliable method with accurate and consistent results and is widely used by hospitals, consumers, payers, and regulators [17,18].

Statistical analysis

All statistical analyses were performed using the weighted survey methods in Statistical Analysis System (SAS) Version 9.4 (SAS Institute Inc., Cary, NC). Weighted values of patient-level observations were generated to produce a nationally representative estimate of the entire US population of hospitalized patients. Univariate analysis of differences between categorical variables (including demographics, comorbidities, risk factors, and concurrent conditions) and outcomes was tested using the chi-square test and analysis of differences between continuous variables (LoS and cost of hospitalization) was tested using unpaired student's t-test. Among AIS hospitalizations, the prevalence and mortality trends from 2003 to 2014 for YA and OA were tested and plotted using the Jonckheere trend test.

 In order to examine the relationship of age groups (YA vs. OA) with AIS-related risk factors and the relationship of age groups with AIS-related outcomes, we used mixed-effects multivariable survey logistic regression models. The models were weighted and adjusted for demographics (age, sex, race), patient-level hospitalization variables (admission day, primary payer, admission type, median household income category), hospital-level variables (hospital region, teaching versus nonteaching hospital, hospital bed size), comorbidities, traditional and non-traditional risk factors, and CCI in order to estimate the adjusted odds ratio (aOR) and 95% confidence interval (CI). Common conditions covered as risk factors and CCIs were adjusted only once in order to avoid over-adjustment. For each model, the c-index was calculated. All statistical tests used were two-sided, and p<0.05 was deemed statistically significant. No statistical power calculation was conducted prior to the study.

Results

We have described prevalence trends and characteristics of AIS. We have also compared demographics, patient and hospital characteristics, comorbidities, and outcomes of AIS amongst YA and OA below.

Disease hospitalizations

There were 4,224,924 hospitalizations due to AIS from 2003 to 2014 after excluding patients with age <18 years and admissions with missing data for age, sex, and race (Figure 1). Out of 4,224,924 AIS hospitalizations, 198,378 (4.7%) were YA (≤45 years) and 4,026,546 (95.3%) were OA. As shown in Figure 2, the percentage of YA among AIS hospitalizations increased from 4.36% in 2003 to 4.7% in 2014. (pTrend<0.0001)

Demographics, patient and hospital characteristics, and comorbidities

There was a higher proportion of females among OA with AIS than YA (53.1% vs. 48.5%; p<0.0001) (Table 3). There was a higher proportion of African Americans (29.95% vs. 16.14%; p<0.0001) and Hispanics (12.17% vs. 7.35%; p<0.0001) among YA. Utilization of recombinant tissue plasminogen activator (6.32% vs. 4.34%; p<0.0001) and endovascular mechanical thrombectomy (1.22% vs. 0.58%; p<0.0001) were higher amongst YA with AIS compared to OA with AIS. OA with AIS had a higher prevalence of current long-term use of aspirin therapy compared to YA (8.79% vs. 5.12%; p<0.0001). Several co-morbidities like chronic blood loss anemia (0.7% vs. 0.45%; p<0.0001), liver disease (1.34% vs. 1.06%; p<0.0001), paralysis (5.48% vs. 3.7%; p<0.0001), psychosis (4.57% vs. 2.91%; p<0.0001) and chronic neurologic disorders (0.88% vs. 0.48%; p<0.0001) were higher among YA than OA. 

  Young adults (18-45 years) Older adults (>45 years) Total p-Value
AIS hospitalizations (%) 198,378 (4.7) 4,026,546 (95.3) 4,224,924 (100)  
Demographics of patients
Gender (%)   <0.0001
Female 96,233 (48.51) 2,138,020 (53.1) 2,234,253 (52.88)  
Male 102,145 (51.49) 1,888,457  (46.9) 1,990,602 (47.12)  
Race (%)   <0.0001
White 104,485 (54.54) 2,881,643 (73.4) 2,986,128 (72.53)  
African American 57,382 (29.95) 633,708 (16.14) 691,090 (16.78)  
Hispanic 23,310 (12.17) 288,462 (7.35) 311,772 (7.57)  
Asian or Pacific Islander 5158 (2.69) 103,386 (2.63) 108,544 (2.64)  
Native American 1233 (0.64) 18,600 (0.47) 19,833 (0.48)  
Characteristics of patients
Median household income category for patient's ZIP code (%)*   <0.0001
 0-25th percentile 66,609 (34.44) 1,175,425 (29.82) 1,242,034 (30.04)  
26-50th percentile 49,480 (25.58) 1,015,750 (25.77) 1,065,230 (25.76)  
51-75th percentile 42.785 (22.12) 920,665 (23.36) 963,450 (23.3)  
76-100th percentile 34,548 (17.86) 829,372 (21.04) 863,920 (20.89)  
Primary payer (%)   <0.0001
Medicare 18,906 (9.56) 2,804,887 (69.78) 2,823,793 (66.95)  
Medicaid 46,516 (23.52) 239,588 (5.96) 286,104 (6.78)  
Private insurance 87,892 (44.44) 711,337 (17.7) 799,229 (18.95)  
Other/self-pay/no charge 44,470 (22.48) 263,983 (6.57) 308,453 (7.31)  
Admission type (%)   <0.0001
Non- elective 190,181 (96.06) 3,833,377 (95.41) 4,023,557 (95.44)  
Elective 7806 (3.94) 184,578 (4.59) 192,384 (4.56)  
Admission day (%)   0.0018
Weekday 148,268 (74.74) 2,996,820 (74.43) 3,145,089 (74.44)  
Weekend 50,110 (25.26) 1,029,725 (25.57) 1,079,835 (25.56)  
Characteristics of hospitals
Bedsize of hospital (%)**   <0.0001
Small 17,009 (8.63) 481,564 (12.01) 498,573 (11.85)  
Medium 47,805 (24.26) 1,030,840 (25.71) 1,078,644 (25.64)  
Large 132,226 (67.11) 2,497,587 (62.28) 2,629,813 (62.51)  
Hospital location & teaching status (%)   <0.0001
Rural 14,062 (7.14) 481,027 (12) 495,089 (11.77)  
Urban non-teaching 72,265 (36.68) 1,710,411 (42.65) 1,782,676 (42.37)  
Urban teaching 110,712 (56.19) 1,818,553 (45.35) 1,929,265 (45.86)  
Hospital region (%)   <0.0001
Northeast 37,829 (19.07) 858,527 (21.32) 896,356 (21.22)  
Midwest 32,990 (16.63) 697,196 (17.31) 730,186 (17.28)  
South 90,734 (45.74) 1,719,665 (42.71) 1,810,399 (42.85)  
West 36,826 (18.56) 751,158 (18.66) 787,983 (18.65)  
Stroke related medications (%)
Current long-term use of Aspirin therapy 10,165 (5.12) 353,886 (8.79) 364,051 (8.62) <0.0001
Use of recombinant tissue plasminogen activator (rtPA) 12,534 (6.32) 174,855 (4.34) 187,388 (4.44) <0.0001
Use of endovascular mechanical thrombectomy 2413 (1.22) 23,411 (0.58) 25,824 (0.61) <0.0001
Comorbidities of patients (%)
Deficiency anemias 19,652 (9.94) 467,108 (11.65) 486,759 (11.57) <0.0001
Rheumatoid arthritis/collagen vascular diseases 5321 (2.69) 94,806 (2.37) 100,127 (2.38) <0.0001
Chronic blood loss anemia 1381 (0.7) 17,913 (0.45) 19294.6 (0.46) <0.0001
Congestive heart failure 12,425 (6.28) 578,171 (14.43) 590,596 (14.04) <0.0001
Chronic pulmonary disease 17,442 (8.82) 602,466 (15.03) 619,908 (14.74) <0.0001
Hypothyroidism 8535 (4.32) 514,168 (12.83) 522,703 (12.43) <0.0001
Liver disease 2654 (1.34) 42,508 (1.06) 45,162 (1.07) <0.0001
Lymphoma 632 (0.32) 20,836 (0.52) 21,468 (0.51) <0.0001
Fluid and electrolyte disorders 30,624 (15.49) 800,738 (19.98) 831,362 (19.77) <0.0001
Metastatic cancer 1116 (0.56) 58,488 (1.46) 59,604 (1.42) <0.0001
Paralysis 10,826 (5.48) 148,241 (3.7) 159,067 (3.78) <0.0001
Psychoses 9036 (4.57) 116,737 (2.91) 125,774 (2.99) <0.0001
Peptic ulcer disease excluding bleeding 25 (0.01) 1416 (0.04) 1441 (0.03) <0.0001
Valvular disease 13,434 (6.8) 413,319 (10.31) 426,752 (10.15) <0.0001
Weight loss 3289 (1.66) 125,944 (3.14) 129,233 (3.07) <0.0001
Pulmonary circulation disorders 3317 (1.68) 115,370 (2.88) 118,687 (2.82) <0.0001
Peripheral vascular disease 14,352 (7.26) 359,101 (8.96) 373,453 (8.88) <0.0001
Coagulopathy 5614 (2.84) 110,457 (2.76) 116,071 (2.76) 0.0267
Solid tumor without metastasis 884 (0.45) 70,634 (1.76) 71,518 (1.7) <0.0001
Depression 18,818 (9.52) 370,045 (9.23) 388,863 (9.25) <0.0001
Other neurological disorders 1743 (0.88) 19,275 (0.48) 21,018 (0.5) <0.0001
Concurrent conditions or risk factors (%)
Diabetes 49,279 (24.84) 1,394,654 (34.64) 1,443,933 (34.18) <0.0001
Hypertension (combined uncomplicated and complicated) 109,951 (55.42) 3,246,458 (80.63) 3,356,409 (79.44) <0.0001
Obesity 31,797 (16.03) 306,293 (7.61) 338,091 (8) <0.0001
Hypercholesterolemia 16,298 (8.22) 435,347 (10.81) 451,645 (10.69) <0.0001
Drug abuse/dependence 21,714 (10.95) 67,645 (1.68) 89,359 (2.12) <0.0001
Alcohol abuse/dependence 13,067 (6.59) 149,261 (3.71) 162,328 (3.84) <0.0001
Past history of smoking 9262 (4.67) 379,316 (9.42) 388,579 (9.2) <0.0001
Current tobacco dependence 61,720 (31.11) 574,046 (14.26) 635,766 (15.05) <0.0001
Cardiac diseases 45,679 (23.03) 1,896,107 (47.09) 1,941,786 (45.96) <0.0001
Ischemic heart disease 17,934 (9.04) 1,147,546 (28.5) 1,165,481 (27.59) <0.0001
Infective endocarditis 965 (0.49) 6262 (0.16) 7227 (0.17) <0.0001
Atrial Fibrillation 5926 (2.99) 947,502 (23.53) 953,428 (22.57) <0.0001
Cardiomyopathy 10,203 (5.14) 144,888 (3.6) 155,091 (3.67) <0.0001
Rheumatic fever 50 (0.03) 368 (0.01) 418 (0.01) <0.0001
Rheumatoid heart disease 3859 (1.95) 133,365 (3.31) 137,224 (3.25) <0.0001
Atrial septal disease 15,181 (7.65) 69,403 (1.72) 84,584 (2) <0.0001
Ventricular septal disease 230 (0.12) 550 (0.01) 781 (0.02) <0.0001
Patent ductus arteriosus 37 (0.02) 249 (0.01) 286 (0.01) <0.0001
Infectious diseases 16,980 (8.56) 626,884 (15.57) 643,864 (15.24) <0.0001
Urinary tract infection 11,209 (5.65) 509,319 (12.65) 520,528 (12.32) <0.0001
HIV infection 2425 (1.22) 5679 (0.14) 8104 (0.19) <0.0001
Pneumonia 4179 (2.11) 144,646 (3.59) 148,825 (3.52) <0.0001
Neurosyphilis 133 (0.07) 1857 (0.05) 1989 (0.05) <0.0001
CNS tuberculosis 16 (0.01) 25 (0) 41 (0) <0.0001
Meningitis 75 (0.04) 276 (0.01) 352 (0.01) <0.0001
CMV encephalitis 57 (0.03) 202 (0.01) 259 (0.01) <0.0001
Toxoplasmosis <10 0 <10 <0.0001
CNS lymphoma <10 84 94 0.0142
Progressive multifocal encephalopathy 43 (0.02) 98 141 <0.0001
Non-infective CNS diseases 30,110 (15.18) 618,165 (15.35) 648,274 (15.34) 0.0355
Brain tumors 336 (0.17) 2442 (0.06) 2778 (0.07) <0.0001
Epilepsy 16,641 (8.39) 235,995 (5.86) 252,636 (5.98) <0.0001
Hemorrhagic stroke 3165 (1.6) 67,054 (1.67) 70,219 (1.66) 0.0172
Arterial-venous malformation 576 (0.29) 3919 (0.1) 4496 (0.11) <0.0001
History of transient ischemic attack 11,304 (5.7) 338,425 (8.4) 349,728 (8.28) <0.0001
Traumatic brain injury 217 (0.11) 7861 (0.2) 8078 (0.19) <0.0001
Renal diseases 19,855 (10.01) 652,927 (16.22) 672,783 (15.92) <0.0001
Chronic kidney diseases 7427 (3.74) 342,859 (8.51) 350,286 (8.29) <0.0001
Acute renal failure 9328 (4.7) 279,229 (6.93) 288,557 (6.83) <0.0001
End-stage renal disease 3787 (1.91) 61,935 (1.54) 65,722 (1.56) <0.0001
Connective tissue diseases 5121 (2.58) 79,066 (1.96) 84,187 (1.99) <0.0001
Systemic lupus erythematous 3959 (2) 14,170 (0.35) 18,129 (0.43) <0.0001
Scleroderma 20 (0.01) 215 (0.01) 235 (0.01) 0.0051
Systemic sclerosis 230 (0.12) 3995 (0.1) 4226 (0.1) 0.0203
Rheumatoid arthritis 1022 (0.51) 59,416 (1.48) 60,438 (1.43) <0.0001
Polymyositis 60 (0.03) 770 (0.02) 830 (0.02) 0.0007
Dermatomyositis 25 (0.01) 394 (0.01) 419 (0.01) 0.1855
Ankylosis spondylosis 91 (0.05) 971 (0.02) 1063 (0.03) <0.0001
Psoriatic arthritis 124 (0.06) 2469 (0.06) 2593 (0.06) 0.8566
Coagulopathy 9792 (4.94) 34,353 (0.85) 44,145 (1.04) <0.0001
Hypercoagulable state 9057 (4.57) 22,625 (0.56) 31,682 (0.75) <0.0001
Polycythemia vera 784 (0.4) 11,921 (0.3) 12,705 (0.3) <0.0001
Vasculitis 222 (0.11) 6278 (0.16) 6500 (0.15) <0.0001
Giant cell arteritis 30 (0.01) 5576 (0.14) 5605 (0.13) <0.0001
Polyarteritis nodosa 47 (0.02) 288 (0.01) 335 (0.01) <0.0001
Takayasu disease 85 (0.04) 166 (0) 250 (0.01) <0.0001
Thromboangiitis obliterans 66 (0.03) 248 (0.01) 314 (0.01) <0.0001
Amyloidosis 19 (0.01) 3957 (0.1) 3976 (0.09) <0.0001
Sickle cell disease 894 (0.45) 1772 (0.04) 2666 (0.06) <0.0001
Moya-moya 1270 (0.64) 1020 (0.03) 2291 (0.05) <0.0001
Fibromuscular dysplasia 560 (0.28) 2957 (0.07) 3517 (0.08) <0.0001

Primary outcome

The prevalence of obesity (16.03% vs. 7.61%; p<0.0001), drug abuse (10.95% vs. 1.68%; p<0.0001), alcohol abuse (6.59% vs. 3.71%; p<0.0001), tobacco dependence (31.11% vs. 14.26%; p<0.0001), cardiomyopathy (5.14% vs. 3.6%; p<0.0001), atrial septal disease (7.56% vs. 1.72%; p<0.0001), epilepsy (8.39% vs. 5.36%; p<0.0001), and hypercoagulable state (4.57% vs. 0.56%; p<0.0001) were higher among YA in compare to OA.

The OA with AIS had higher prevalence of diabetes (34.64% vs. 24.84%; p<0.0001), hypertension (80.63% vs. 55.42%; p<0.0001), hypercholesterolemia/triglyceridemia (10.81% vs. 8.22%; p<0.0001) history of smoking (9.42% vs. 4.67%; p<0.0001), ischemic heart disease (28.5% vs. 9.04%; p<0.0001), atrial fibrillation (23.53% vs. 2.99%; p<0.0001), rheumatoid heart disease (3.31% vs. 1.95%; p<0.0001), urinary tract infection (12.65% vs. 5.65%; p<0.0001), pneumonia (3.59% vs. 2.11%; p<0.0001), history of transient ischemic attack (8.4% vs. 5.7%; p<0.0001), chronic kidney diseases (8.51% vs. 3.74%; p<0.0001), and acute renal failure (6.93% vs. 4.7%; p<0.0001).

Multivariable regression model derivation for the age-group specific risk factors

Table 4 shows multivariable models evaluating the odds of risk factors of AIS among YA and OA population. The obesity (aOR: 2.26; p<0.0001), drug abuse (aOR: 2.56; p<0.0001), past history of smoking (aOR: 1.20; p<0.0001), infective endocarditis (aOR: 2.08; p<0.0001), cardiomyopathy (aOR: 2.11; p<0.0001), rheumatic fever (aOR: 4.27; p=0.0014), atrial septal disease (aOR: 2.46; p<0.0001), ventricular septal disease (aOR: 4.99; p<0.0001), HIV infection (aOR: 4.36; p<0.0001), brain tumors (aOR: 7.89; p<0.0001), epilepsy (aOR: 1.43; p<0.0001), arterial-venous malformation (aOR: 1.81; p<0.0001), end-stage renal disease (aOR: 2.19; p<0.0001), systemic lupus erythematous (aOR: 3.76; p<0.0001), polymyositis (aOR: 2.72; p=0.0105), ankylosis spondylosis (aOR: 2.42; p=0.0082), hypercoagulable state (aOR: 4.03; p<0.0001), polyarteritis nodosa (aOR: 5.65; p=0.0004), and fibromuscular dysplasia (aOR: 2.83; p<0.0001) were significantly associated with YA population with AIS.

  Association of risk factors with young adults Association of risk factors with old adults
  aOR 95% CI (LL-UL) p-Value aOR 95% CI (LL-UL) p-Value
Gender
Female Reference <0.0001 Reference <0.0001
Male 0.89 0.87-0.91   1.12 1.09-1.15  
Race
White Reference <0.0001   <0.0001
African American 1.53 1.48-1.57   0.66 0.64-0.68  
Hispanic 1.47 1.42-1.53   0.68 0.65-0.71  
Asian or Pacific Islander 1.08 1.00-1.16   0.93 0.87-1.00  
Native American 1.27 1.08-1.48   0.79 0.67-0.93  
Median household income category for patient's ZIP code
0-25th percentile Reference 0.0002 Reference 0.0002
26-50th percentile 1.05 1.02-1.08   0.96 0.93-0.99  
51-75th percentile 1.01 0.98-1.04   0.99 0.96-1.03  
76-100th percentile 0.97 0.93-1.01   1.03 1.00-1.07  
Primary Payer
Medicare Reference <0.0001 Reference <0.0001
Medicaid 15.69 14.99-16.42   0.06 0.06-0.07  
Private insurance 11.10 10.69-11.53   0.06 0.09-0.09  
Other/self-pay/no charge 13.70 13.11-14.32   0.07 0.07-0.08  
Admission type
Non-elective Reference 0.0003 Reference 0.0003
Elective 0.90 0.84-0.95   1.12 1.05-1.19  
Admission day
Weekday Reference 0.1418 Reference 0.1418
Weekend 0.98 0.95-1.01   1.02 0.99-1.05  
Bedsize of hospital
Small Reference <0.0001 Reference <0.0001
Medium 1.16 1.11-1.21   0.86 0.82-0.90  
Large 1.25 1.20-1.30   0.80 0.77-0.78  
Hospital location & teaching status
Rural Reference <0.0001 Reference <0.0001
Urban non-teaching 1.16 1.11-1.20   0.86 0.82-0.90  
Urban teaching 1.34 1.28-1.41   0.74 0.71-0.78  
Hospital region
Northeast Reference <0.0001 Reference <0.0001
Midwest 1.16 1.11-1.20   0.87 0.83-0.90  
South 1.12 1.09-1.16   0.89 0.86-0.92  
West 1.02 0.98-1.06   0.98 0.94-1.02  
Concurrent conditions and risk factors
Diabetes 0.71 0.69-0.74 <0.0001 1.40 1.36-1.45 <0.0001
Hypertension 0.32 0.32-0.33 <0.0001 3.09 3.01-3.17 <0.0001
Obesity 2.26 2.18-2.34 <0.0001 0.44 0.43-0.46 <0.0001
Hypercholesterolemia/triglyceridemia 0.80 0.77-0.84 <0.0001 1.24 1.19-1.30 <0.0001
Drug abuse 2.56 2.44-2.68 <0.0001 0.39 0.37-0.41 <0.0001
Alcohol abuse 0.75 0.71-0.78 <0.0001 1.34 1.28-1.41 <0.0001
Past history of smoking 1.20 1.17-1.24 <0.0001 0.83 0.81-0.86 <0.0001
Current tobacco dependence 0.64 0.61-0.67 <0.0001 1.56 1.48-1.65 <0.0001
Ischemic heart disease 0.46 0.44-0.47 <0.0001 2.20 2.11-2.28 <0.0001
Infective endocarditis 2.08 1.67-2.58 <0.0001 0.48 0.39-0.60 <0.0001
Atrial fibrillation 0.24 0.23-0.26 <0.0001 4.18 3.93-4.45 <0.0001
Cardiomyopathy 2.11 1.99-2.24 <0.0001 0.47 0.45-0.50 <0.0001
Rheumatic fever 4.27 1.76-10.36 0.0014 0.23 0.10-0.57 0.0014
Rheumatoid heart disease 0.86 0.78-0.95 0.0027 1.16 1.05-1.28 0.0027
Atrial septal disease 2.46 2.34-2.58 <0.0001 0.41 0.39-0.43 <0.0001
Ventricular septal disease 4.99 3.09-8.05 <0.0001 0.20 0.12-0.32 <0.0001
Patent ductus arteriosus 1.37 0.59-3.19 0.4681 0.73 0.31-1.70 0.4681
Urinary tract infection 0.64 0.61-0.67 <0.0001 1.56 1.49-1.64 <0.0001
HIV infection 4.36 3.62-5.26 <0.0001 0.23 0.19-0.28 <0.0001
Pneumonia 0.80 0.73-0.87 <0.0001 1.26 1.16-1.37 <0.0001
Neurosyphilis 0.62 0.38-1.00 0.0487 1.62 1.00-2.60 0.0487
Meningitis 1.93 0.84-4.45 0.1223 0.52 0.23-1.19 0.1223
CNS lymphoma 1.55 0.29-8.42 0.6096 0.64 0.12-3.49 0.6096
Brain tumors 7.89 5.48-11.36 <0.0001 0.13 0.09-0.18 <0.0001
Epilepsy 1.43 1.37-1.50 <0.0001 0.70 0.67-0.73 <0.0001
Hemorrhagic stroke 0.98 0.89-1.08 0.6444 1.02 0.93-1.13 0.6444
Arterial-venous malformation 1.81 1.43-2.28 <0.0001 0.55 0.44-0.70 <0.0001
History of transient ischemic attack 0.82 0.78-0.87 <0.0001 1.21 1.16-1.28 <0.0001
Traumatic brain injury 0.70 0.50-0.97 0.0328 1.43 1.03-2.00 0.0328
Chronic kidney diseases 0.63 0.57-0.71 <0.0001 1.58 1.42-1.75 <0.0001
Acute renal failure 0.84 0.79-0.89 <0.0001 1.19 1.12-1.26 <0.0001
End-stage renal disease 2.19 1.92-2.51 <0.0001 0.46 0.40-0.52 <0.0001
Systemic lupus erythematous 3.76 2.99-4.73 <0.0001 0.27 0.21-0.34 <0.0001
Scleroderma 2.25 0.50-10.18 0.2937 0.45 0.10-2.02 0.2937
Systemic sclerosis 1.18 0.79-1.77 0.4183 0.85 0.57-1.27 0.4183
Rheumatoid arthritis 0.44 0.34-0.56 <0.0001 2.29 1.79-2.93 <0.0001
Polymyositis 2.72 1.26-4.69 0.0105 0.37 0.17-0.79 0.0105
Dermatomyositis 1.06 0.39-2.91 0.9061 0.94 0.34-2.58 0.9061
Ankylosis spondylosis 2.42 1.26-4.69 0.0082 0.41 0.21-0.80 0.0082
Psoriatic arthritis 1.10 0.69-1.76 0.6998 0.91 0.57-1.46 0.6998
Hypercoagulable state 4.03 3.72-4.36 <0.0001 0.25 0.23-0.27 <0.0001
Polycythemia vera 1.10 0.91-1.33 0.3335 0.91 0.75-1.10 0.3335
Giant cell arteritis 0.24 0.11-0.54 0.0004 4.11 1.87-9.03 0.0004
Polyarteritis nodosa 5.65 2.16-14.81 0.0004 0.18 0.07-0.46 0.0004
Thromboangiitis obliterans 1.86 0.83-4.15 0.1304 0.54 0.24-1.20 0.1304
Amyloidosis 0.11 0.04-0.31 <0.0001 9.09 3.25-25.39 <0.0001
Fibromuscular dysplasia 2.83 2.20-3.65 <0.0001 0.35 0.27-0.45 <0.0001
Comorbidities of patients            
Deficiency anemias 1.15 1.11-1.20 <0.0001 0.87 0.83-0.90 <0.0001
Rheumatoid arthritis/collagen vascular diseases 0.96 0.77-1.19 0.6861 1.05 0.84-1.30 0.6861
Chronic blood loss anemia 1.82 1.56-2.13 <0.0001 0.55 0.47-0.64 <0.0001
Congestive heart failure 0.86 0.81-0.91 <0.0001 1.17 1.11-1.23 <0.0001
Chronic pulmonary disease 0.73 0.70-0.76 <0.0001 1.37 1.32-1.44 <0.0001
Hypothyroidism 0.55 0.52-0.58 <0.0001 1.83 1.73-1.93 <0.0001
Liver disease 0.76 0.68-0.85 <0.0001 1.32 1.18-1.47 <0.0001
Lymphoma 0.81 0.65-0.99 0.0410 1.24 1.01-1.53 0.0410
Fluid and electrolyte disorders 0.91 0.88-0.95 <0.0001 1.09 1.06-1.13 <0.0001
Metastatic cancer 0.38 0.32-0.45 <0.0001 2.63 2.23-3.12 <0.0001
Paralysis 1.45 1.36-1.53 <0.0001 0.69 0.65-0.73 <0.0001
Psychoses 1.48 1.39-1.57 <0.0001 0.68 0.64-0.72 <0.0001
Peptic ulcer disease excluding bleeding 0.43 0.16-1.17 0.0984 2.35 0.85-6.45 0.0984
Valvular disease 1.08 1.02-1.14 0.0090 0.93 0.88-0.98 0.0090
Weight loss 0.65 0.59-0.71 <0.0001 1.55 1.41-1.70 <0.0001
Pulmonary circulation disorders 0.90 0.82-0.99 0.0273 1.11 1.01-1.23 0.0273
Coagulopathy 1.05 0.97-1.13 0.2226 0.95 0.88-1.03 0.2226
Solid tumor without metastasis 0.22 0.18-0.26 <0.0001 4.65 3.81-5.68 <0.0001
Depression 1.14 1.09-1.19 <0.0001 0.88 0.84-0.92 <0.0001
Peripheral vascular disease 1.18 1.13-1.24 <0.0001 0.84 0.81-0.88 <0.0001
Other neurological disorders 1.25 1.08-1.44 0.0028 0.80 0.69-0.93 0.0028
Deyo-Charlson Comorbidity Index (CCI) 0.94 0.93-0.95 <0.0001 1.06 1.05-1.08 <0.0001
c-Index 0.898 0.898

The odds of having diabetes (aOR: 1.40; p<0.0001), hypertension (aOR: 3.09; p<0.0001), hypercholesterolemia/triglyceridemia (aOR: 1.24; p<0.0001), alcohol abuse (aOR: 1.34; p<0.0001), current tobacco dependence (aOR: 1.56; p<0.0001), ischemic heart disease (aOR: 2.20; p<0.0001), atrial fibrillation (aOR: 4.18; p<0.0001), rheumatoid heart disease (aOR: 1.16; p=0.0027), urinary tract infection (aOR: 1.56; p<0.0001), pneumonia (aOR: 1.26; p<0.0001), history of transient ischemic attack (aOR: 1.21; p<0.0001), traumatic brain injury (aOR: 1.43; p=0.0328), chronic kidney diseases (aOR: 1.58; p<0.0001), acute renal failure (aOR: 1.19; p<0.0001), rheumatoid arthritis (aOR: 2.29; p<0.0001), giant cell arteritis (aOR: 4.11; p=0.0004), amyloidosis (aOR: 9.09; p<0.0001), solid tumor without metastasis (aOR: 4.65; p<0.0001) and with metastasis (aOR: 2.63; p<0.0001) were significantly higher among OA patients admitted with AIS. The c statistic was 0.898 (>0.5) which indicate good models.

Secondary outcomes

Table 5 includes outcomes of AIS hospitalizations, comparing YA to OA. The all-cause in-hospital mortality (2.73% vs. 5.33; p<0.0001), morbidity (7.15% vs. 7.73; p<0.0001), major/extreme loss of function (30.7% vs. 37.21%; p<0.0001), and major/extreme likelihood of death (13.43% vs. 21.62%; p<0.0001) were lower among YA than OA AIS hospitalizations. YA AIS hospitalizations had a higher prevalence of discharge to home (64.59% vs. 36.15%; p<0.0001) than OA. The trend of all-cause in-hospital mortality in YA decreased from 4.11% in 2003 to 2.19% in 2014 (pTrend<0.0001) and decreased from 7.05% in 2003 to 4.47% in 2014 (P-Trend<0.0001) in OA AIS hospitalizations (Figure 3). Mean length of stay (5.6 days vs. 5.4 days; p<0.0001) and total cost of hospitalization were higher ($47,365 vs. $37,669; p<0.0001) in YA AIS hospitalizations than OA AIS hospitalizations (Table 5).

  Acute ischemic stroke hospitalizations  
  Young adults (18-45 years) Older adults (>45-years) Total p-Value
All-cause in-hospital mortality (%) 5410 (2.73) 214,154 (5.33) 219,564 (5.21) <0.0001
Morbidity* (%) 13,781 (7.15) 294,109 (7.33) 307,890 (7.70) <0.0001
Discharge disposition (%)   <0.0001
Routine/home 121,623 (64.59) 1,364,958 (36.15) 1,486,581 (37.5)  
Transfer to short-term hospital 9593 (5.09) 117,357 (3.11) 126,950 (3.2)  
Transfer to SNF/ICF/another type of facility 42,160 (22.39) 1,772,822 (46.95) 1,814,981 (45.79)  
Home health care 14,913 (7.92) 520,542 (13.79) 535,455 (13.51)  
Total discharge other than home (%) 66,666 (35.41) 2,410,720 (63.85) 2,477,386 (62.5)  
APR-DRG severity/ loss of function (%)   <0.0001
Minor loss of function 34,616 (18.02) 425,141 (11.22) 459,756 (11.55)  
Moderate loss of function 98,510 (51.28) 1,953,248 (51.56) 2,051,758 (51.55)  
Major loss of function 47,274 (24.61) 1,173,725 (30.99) 1,220,999 (30.68)  
Extreme loss of function 11,687 (6.08) 235,835 (6.23) 247,522 (6.22)  
Total major/extreme loss of function (%) 58,961 (30.7) 1,409,560 (37.21) 1,468,522 (36.9) <0.0001
APR-DRG risk mortality (%)   <0.0001
Minor likelihood of death 123,776 (64.44) 1,171,879 (30.94) 1,295,655 (32.55)  
Moderate likelihood of death 42,510 (22.13) 1,797,239 (47.45) 1,839,749 (46.22)  
Major likelihood of death 16,590 (8.64) 617,641 (16.31) 634,231 (15.94)  
Extreme likelihood of death 9210 (4.79) 201,191 (5.31) 210,401 (5.29)  
Total major/extreme likelihood of death (%) 25,800 (13.43) 818,832 (21.62) 844,632 (21.22) <0.0001
Length of stay (mean) ± SE (days) 5.6 ± 0.04 5.4 ± 0.01   <0.0001
Cost of hospitalization (mean) ± SE ($) 47,365 ± 347 37,669 ± 58   <0.0001
 

Regression model derivation for the outcomes of YA

Table 6 includes multivariable regression analysis to predict outcomes of AIS among YA and OA population. All-cause in-hospital mortality (aOR: 0.56; 95%CI: 0.52-0.60), morbidity (aOR: 0.87; 95%CI: 0.83-0.91), discharge disposition to non-home (aOR: 0.60; 95%CI: 0.58-0.61), and major/extreme likelihood of death (aOR: 0.83; 95%CI: 0.81-0.86) were lower among YA than OA admitted with AIS with the c-statistic of 0.672, 0.690, 0.722, and 0.713, respectively (>0.5) which indicate good fit.

Odds ratio 95% confidence interval p-Value c-Index
  Lower limit Upper limit    
All-cause in-hospital mortality in young adults (reference: older adults)
0.56 0.52 0.60 <0.0001 0.672
Morbidity in young adults (reference: older adults)*
0.87 0.83 0.91 <0.0001 0.690
Discharge disposition to non-home in young adults (reference: older adults)
0.60 0.58 0.61 <0.0001 0.722
APR-DRG major/extreme loss of function in young adults (reference: older adults)
1.02 0.998 1.05 0.0672 0.730
APR-DRG major/extreme risk of death in young adults (reference: older adults)
0.83 0.81 0.86 <0.0001 0.713

Discussion

We performed a population-based retrospective analysis of the nationally-representative NIS database to identify adult AIS hospitalizations and risk factors. Stroke in YA has been observed to be uncommon, and cerebrovascular disease reaches peak incidence later in life [19]. This observation has been confirmed in our study as we identified only 4.7% YA AIS hospitalizations, while 95.3% of hospitalizations were in patients who were 45 years or older. Thus, stroke is not a common health condition among YA. However, for those YA who do suffer a stroke, it is a considerable cause of morbidity and has an impact on the loss of work productivity in these patients [9]. Despite the small number of YA who suffer from stroke, we found an increasing prevalence among YA with AIS. From 2003 to 2014, hospitalizations for AIS in young adults increased from 4.36% to 4.70%. This stands in contrast to previous reports of stable rates of stroke incidence and decreasing rates of stroke hospitalization among adults [9]. A possible reason for this seemingly increasing incidence could be due to rising rates of stroke risk factors, including obesity, hypertension, diabetes, tobacco, and alcohol use [9].

Many risk factors among YA are traditional and modifiable, so screening and treatment are possible. These include obesity, drug abuse, history of smoking, infective endocarditis, cardiomyopathy, rheumatic fever, atrial septal disease, ventricular septal disease, HIV infection, and epilepsy. Some of the non-traditional risk factors like arterial-venous malformation, brain tumors, end-stage renal disease, systemic lupus erythematosus, polymyositis, ankylosis spondylosis, hypercoagulable state, polyarteritis nodosa, and fibromuscular dysplasia are significantly associated with YA with AIS.

Notably, in our study, all-cause in-hospital mortality was lower among YA. The prevalence rate of in-hospital mortality decreased from 2003 to 2014 (YA: 4.11% to 2.19% and OA: 7.05% to 4.47%), similar to Lee et al. (1998: 7.0% to 2007: 5.4%; p<0.0001) [20]. A possible explanation for this could be more effective treatment guidelines and strategies when presenting to the hospital. Young people may still be participating in high-risk factors that can lead to an increase in AIS hospitalizations, as shown in our study; however, treatment may have improved, with a concomitant decrease in mortality. Our study also indicated that YA with AIS hospitalizations had a lower chance of morbidity, discharge to short/long-term care, and the likelihood of death. YA and OA AIS hospitalizations had a similar mean LoS. However, the cost of hospitalizations was higher in YA ($47365 vs. $37669, p<0.0001). Stroke is thus an important cause of morbidity in young patients, and although having a small prevalence in the population, it affects hospitalization costs and dramatic impacts on quality of life in survivors. YA are also associated with higher long-term cumulative mortality due to stroke compared to the general population [21]. Stroke causes numerous physical and cognitive problems, long-term consequences, and work-related productivity losses especially in younger populations [21].

A major strength of this study was the findings that were nationally representative for the United States. However, there are limitations to this study. AIS was analyzed as a whole, rather than by identifying AIS patients according to subtype or by comparing other types of stroke. Perhaps, YA with AIS hospitalizations were due to a certain cause or presented as a subtype of AIS; however, this could not be elicited through this study. Additionally, being a retrospective study, we have associations between certain concurrent diagnoses and co-morbidities and AIS, yet we do not know if there is a temporal relationship between the two. We have evaluated in-hospital outcomes and do not have post-discharge records of these patients. Likewise, we are missing other details like stroke location, NIH Stroke Scale, concurrent medication use, the severity of risk factors, etc.

Conclusions

AIS has been shown to be an uncommon problem in YA with better outcomes; however, with the rising prevalence trend of AIS over the past decade in young populations, prevention and treatment strategies need to be examined. Young adults have modifiable risk factors such as obesity, drug and smoking abuse, and heart conditions that can be screened. Besides that, non-traditional risk factors suggest that more awareness and prevention strategies can be targeted to the YA population. Further studies should be done to test whether modifying these factors lowers stroke risk in the young population or to determine if awareness campaigns differ based on the age of the patient targeted.


References

  1. Kochanek KD, Murphy SL, Xu J, Arias E: Mortality in the United States, 2013. NCHS Data Brief. 2014, 1-8.
  2. Mozaffarian D, Benjamin EJ, Go AS, et al.: Heart disease and stroke statistics-2016 update: a report from the American Heart Association. Circulation. 2016, 133:38-360. 10.1161/CIR.0000000000000350
  3. Hall MJ, Levant S, DeFrances CJ: Hospitalization for stroke in U.S. hospitals, 1989-2009. NCHS Data Brief. 2012, 1-8.
  4. Putaala J, Metso AJ, Metso TM, et al.: Analysis of 1008 consecutive patients aged 15 to 49 with first-ever ischemic stroke: the Helsinki young stroke registry. Stroke. 2009, 40:1195-1203. 10.1161/STROKEAHA.108.529883
  5. Adams HP Jr, Kappelle LJ, Biller J, Gordon DL, Love BB, Gomez F, Heffner M: Ischemic stroke in young adults. Experience in 329 patients enrolled in the Iowa Registry of stroke in young adults. Arch Neurol. 1995, 52:491-495. 10.1001/archneur.1995.00540290081021
  6. Kittner SJ, Stern BJ, Wozniak M, et al.: Cerebral infarction in young adults: the Baltimore-Washington Cooperative young stroke study. Neurology. 1998, 50:890-894. 10.1212/wnl.50.4.890
  7. Jacobs BS, Boden-Albala B, Lin IF, Sacco RL: Stroke in the young in the northern Manhattan stroke study. Stroke. 2002, 33:2789-2793. 10.1161/01.str.0000038988.64376.3a
  8. Naess H, Nyland HI, Thomassen L, Aarseth J, Nyland G, Myhr KM: Incidence and short-term outcome of cerebral infarction in young adults in western Norway. Stroke. 2002, 33:2105-2108. 10.1161/01.str.0000023888.43488.10
  9. George MG, Tong X, Kuklina EV, Labarthe DR: Trends in stroke hospitalizations and associated risk factors among children and young adults, 1995-2008. Ann Neurol. 2011, 70:713-721. 10.1002/ana.22539
  10. George MG, Tong X, Bowman BA: Prevalence of cardiovascular risk factors and strokes in younger adults. JAMA Neurol. 2017, 74:695-703. 10.1001/jamaneurol.2017.0020
  11. Smajlović D: Strokes in young adults: epidemiology and prevention. Vasc Health Risk Manag. 2015, 11:157-164. 10.2147/VHRM.S53203
  12. Poisson SN, Glidden D, Johnston SC, Fullerton HJ: Deaths from stroke in US young adults, 1989-2009. Neurology. 2014, 83:2110-2115. 10.1212/WNL.0000000000001042
  13. Fromm A, Waje-Andreassen U, Thomassen L, Naess H: Comparison between ischemic stroke patients <50 years and ≥50 years admitted to a single centre: the Bergen stroke study. Stroke Res Treat. 2011, 2011:183256. 10.4061/2011/183256
  14. Edwards JD, Kapral MK, Fang J, Swartz RH: Long-term morbidity and mortality in patients without early complications after stroke or transient ischemic attack. CMAJ. 2017, 189:954-961. 10.1503/cmaj.161142
  15. Birman-Deych E, Waterman AD, Yan Y, Nilasena DS, Radford MJ, Gage BF: Accuracy of ICD-9-CM codes for identifying cardiovascular and stroke risk factors. Med Care. 2005, 43:480-485. 10.1097/01.mlr.0000160417.39497.a9
  16. Thirumala PD, Nguyen FD, Mehta A, et al.: Perioperative stroke, in-hospital mortality, and postoperative morbidity following transcatheter aortic valve implantation: a nationwide study. J Clin Neurol. 2017, 13:351-358. 10.3988/jcn.2017.13.4.351
  17. McCormick PJ, Lin HM, Deiner SG, Levin MA: Validation of the All Patient Refined Diagnosis Related Group (APR-DRG) risk of mortality and severity of illness modifiers as a measure of perioperative risk. J Med Syst. 2018, 42:81. 10.1007/s10916-018-0936-3
  18. Baram D, Daroowalla F, Garcia R, et al.: Use of the All Patient Refined-Diagnosis Related Group (APR-DRG) risk of mortality score as a severity adjustor in the medical ICU. Clin Med Circ Respirat Pulm Med. 2008, 2:19-25. 10.4137/ccrpm.s544
  19. Burns RJ, Blumbergs PC, Sage MR: Brain infarction in young men. Clin Exp Neurol. 1979, 16:69-79.
  20. Lee LK, Bateman BT, Wang S, Schumacher HC, Pile-Spellman J, Saposnik G: Trends in the hospitalization of ischemic stroke in the United States, 1998-2007. Int J Stroke. 2012, 7:195-201. 10.1111/j.1747-4949.2011.00700.x
  21. Maaijwee NA, Rutten-Jacobs LC, Schaapsmeerders P, van Dijk EJ, de Leeuw FE: Ischaemic stroke in young adults: risk factors and long-term consequences. Nat Rev Neurol. 2014, 10:315-325. 10.1038/nrneurol.2014.72

Original article
peer-reviewed

Risk Factors and Incidence of Acute Ischemic Stroke: A Comparative Study Between Young Adults and Older Adults


Author Information

Urvish K. Patel Corresponding Author

Public Health and Neurology, Icahn School of Medicine at Mount Sinai, New York, USA

Mihir Dave

Internal Medicine, University of Nevada Reno, School of Medicine, Reno, USA

Anusha Lekshminarayanan

Internal Medicine, Richmond University Medical Center, Staten Island, USA

Rehabilitation Medicine, New York Medical College and Metropolitan Hospital Center, New York, USA

Preeti Malik

Public Health, Icahn School of Medicine at Mount Sinai, New York, USA

Neurology, Massachusetts General Hospital, Boston, USA

Matthew DeMasi

Internal Medicine, Albert Einstein College of Medicine, Bronx, USA

Sangeetha Chandramohan

Public Health, Icahn School of Medicine at Mount Sinai, New York, USA

Shreejith Pillai

Internal Medicine, Henry Ford Health System, Detroit, USA

Raghavendra Tirupathi

Internal Medicine, Keystone Health, Chambersburg, USA

Shamik Shah

Neurology, Stormont Vail Health, Topeka, USA

Vishal B. Jani

Neurology, Creighton University School of Medicine, Omaha, USA

Mandip S. Dhamoon

Neurology, Icahn School of Medicine at Mount Sinai, New York, USA


Ethics Statement and Conflict of Interest Disclosures

Human subjects: Consent was obtained or waived by all participants in this study. Health Care Utilization Project (HCUP) issued approval N/A. The data has been taken from Nationwide Inpatient Sample, which is a deidentified database from “Health Care Utilization Project (HCUP)” sponsored by the Agency for Healthcare Research and Quality, so informed consent or IRB approval was not needed for the study. The relevant ethical oversight and HCUP Data Use Agreement (HCUP-4Q28K90CU) were obtained by Urvish Patel for the data used in this study. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.



Original article
peer-reviewed

Risk Factors and Incidence of Acute Ischemic Stroke: A Comparative Study Between Young Adults and Older Adults


Figures etc.

SIQ
7.1
RATED BY 5 READERS
CONTRIBUTE RATING

Scholary Impact Quotient™ (SIQ™) is our unique post-publication peer review rating process. Learn more here.