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Epidemiology, Risk Factors, and Predictors of Disability in a Cohort of Jordanian Patients with the First Ischemic Stroke.

1. Introduction

Stroke is an important cause of mortality and morbidity worldwide. Recent studies recognize this disease to be the second leading cause of death and 3rd major cause of disability globally [1, 2]. Despite a decline in stroke incidence in high-income countries, the global burden of stroke is increasing. This trend is largely attributable to an increase in stroke incidence and prevalence as well as stroke-related deaths and disability in low and middle-income countries, reflecting suboptimal preventive strategies [3, 4]. Stroke risk factors include nonmodifiable factors such as age, sex, and race, as well as modifiable ones like hypertension, smoking, alcohol, obesity, physical inactivity, diabetes mellitus, hyperlipidemia, and atrial fibrillation [5, 6].

In Jordan, stroke is believed to be the 2nd leading non-communicable cause of death in the country, tracking closely behind ischemic heart disease [7]. In a study in 2004, which evaluated 200 patients with ischemic stroke in Jordan University Hospital "JUH", the mean age of patients was 61.2 years, while the most common stroke etiology identified was lacunar infarct (51.5%). Hypertension, diabetes mellitus, and smoking were the most common risk factors for atherosclerotic noncardioembolic strokes identified by that study [8]. A more recent study in 2015 evaluated ischemic stroke etiologies and risk factors in 100 patients, who were observed at JUH over a one-year-period. In this study, the mean age was 66 years, and lacunar stroke remained the most common stroke etiology identified (36%). The most common risk factor was hypertension, followed by hyperlipidemia, and diabetes mellitus [9].

However, there are no published studies that have measured stroke severity or poststroke disability among patients with ischemic stroke in Jordan. Measuring stroke severity and stroke-related disability is very important for weighing the economic burden of this disease and also for efforts to design evidence-based preventive and rehabilitation strategies.

2. Methodology

2.1. Study Design and Population. This is a retrospective cohort study that was conducted at King Abdullah University Hospital "KAUH", the largest tertiary teaching hospital located in the north of Jordan. KAUH has over 680 beds. It offers outpatient and inpatient health care services to residents of all provinces in the northern part of the country, who constitute over 25% of the total population of the country [10]. It, also, receives referrals from other hospitals in the north of Jordan. Ethical approval for this study was granted by the institutional review board committee at Jordan University of Science and Technology "JUST".

2.2. Study Population and Case Identification. The study population consisted of patients above the age of sixteen who were admitted to the Neurology Department at KAUH between July 1st, 2017, and March 31st, 2018, with the primary diagnosis of first-time ischemic stroke. The study used secondary data that were extracted from the hospital's electronic medical record system.

2.3. Data Collection. Data for all patients who were admitted to KAUH with stroke as the primary diagnosis were extracted. After that, data on patients who did not meet the inclusion criteria for the study were excluded, which consisted of patients with a final diagnosis other than an ischemic stroke (e.g., hemorrhagic strokes, transient ischemic attacks, or others), patients with previous strokes, and patients in whom the ischemic stroke occurred in the setting of another major acute illness. All records with missing essential data fields were excluded. Finally, data for patients in the study sample (patients who met the inclusion criteria) were purged of all unnecessary fields. Retained data fields included age, sex, length of stay "LOS", reason for prolonged hospitalization, NIHSS scores on admission and discharge, mRS score on discharge, and relevant risk factors (hypertension, diabetes mellitus, hyperlipidemia, smoking status, ischemic heart disease, atrial fibrillation, and heart failure). Thrombophilia and/or vasculitis test results--if performed--were also retained. Radiology images were reviewed by the research team, and data were also collected from the database and were compared with the official radiology reports. The imaging modalities used and the findings on brain imaging and brain and neck angiography were all documented.

2.4. Key Measures. For the purpose of this study, ischemic stroke was defined according to the 2013 AHA definition [11]. Etiology was identified according to TOAST criteria [12]. Stroke due to large artery atherosclerosis was determined in cases associated with proximal intracranial or extracranial atherosclerosis causing luminal stenosis ([greater than or equal to] 50%) or occlusion in arteries that correspond to the ischemic area [12]. Cardioembolic stroke was defined as cases where a definite cardiac source of embolism was documented in the absence of significant ipsilateral large vessel disease [12, 13]. Lacunar stroke was defined as a noncortical stroke smaller than 16 mm without a cardioembolic source or significant large vessel stenosis [12,13]. Stroke in the young was defined as ischemic stroke occurring in patients 50 years of age or younger [14]. Hypertension, diabetes mellitus, and hyperlipidemia were defined according to standard guidelines [15-17] or if the patient has been on drug treatment for these conditions. Atrial fibrillation "AF" was ascertained from ECG on admission or on previous visits and from Holter monitoring reports. Ischemic heart disease and heart failure were identified based on cardiologist notes from previous visits, history of cardiac catheterization with stenting, or from recent consultation and/or echocardiography findings. Severity and disability scores were documented using admission and discharge NIHSS and mRS scores, respectively. Several cutoff points for stroke severity exist in the literature. Our institution's local protocol was used, which divides ischemic stroke into mild (NIHSS less than 6), moderate (NIHSS 6-15), severe (16-25), and very severe (more than 25). Favorable stroke outcome was defined as mRS scores [less than or equal to] 2, and poor outcome as scores between 3-6 [18]. Prolonged length of stay (LOS) was defined as hospitalizations >75th percentile of the hospitalization length for the cohort (>6 days) [19, 20]. Finally, TOAST criteria were implemented and each stroke case assigned an appropriate category. Embolism from aortic atheromatous plaques was classified under category 4 (other determined etiology) [21]. Cases with two or more possible etiologies or a negative/incomplete work up were assigned under category 5 (undetermined etiology) [12].

2.5. Statistical Analysis. Analysis of the sample demographics and descriptive statistics were done first. The frequency of the prevalence of independent variables (risk factors) was then analyzed. In addition, the frequency of stroke etiology workup was reported. Chi-square analysis was used to investigate the relationship between categorical risk factors and type of stroke, and univariate analysis of variance "ANOVA" was used to measure the association of continuous risk factors and type of stroke. LOS is represented in graphs and tables using median and interquartile range "IQR" [22], while both the mean and median were used in the text. Logistic regression analysis was then used to measure the contribution of each of the independent variables (including age, sex, NIHSS score on admission, smoking, atrial fibrillation, heart failure, hyperlipidemia, ischemic heart disease, diabetes mellitus, hypertension, and length of hospitalization) to the mRS score at discharge. Lastly, between-group mean difference analysis was done to investigate the relationship between stroke etiology and LOS. All statistical analyses were run in SPSS software. The significance level a was set at 0.05.

3. Results

3.1. Cohort Characteristics. The research team's primary search identified 191 potential cases, of which 142 were included in the final analysis, 13 were excluded due to a better alternative diagnosis, and 36 had a previous stroke.

Of the study population, 76 (53.52%) were males and 66 (46.47%) were females. The mean age for the study population was 66.5 years (SD 12). The age range was 31-94 years. The mean age for males was 66.55 years (SD [+ or -] 11.48), and for females was 68.59 years (SD [+ or -] 12.53). Stroke in the young was observed in 15 patients (10.56%), of which 10 were males and 5 were females.

3.2. Risk Factors. As far as comorbidities are concerned, 112 (78.87%) patients had a previous diagnosis of hypertension, 86 (60.56%) had diabetes mellitus, 53 (37.32%) had hyperlipidemia, 42 (29.47%) had ischemic heart disease, 20 (14.08%) had atrial fibrillation, and 20 (14.08%) had heart failure. Thirty-five (24.64%) of patients were current smokers. See Table 1.

3.3. Etiology. Small vessel occlusion was the most commonly identified etiology (54.22%) followed by large artery atherosclerosis (21.83%) and cardioembolic stroke (7.04%). Other causes were determined in 9 cases (6.33%), while 15 cases (10.56%) remain of no definitively determined etiology.

As shown in Table 2, standard stroke work-up consisted of ECG, transthoracic echocardiogram "TTE", angiography (magnetic resonance angiography "MRA", Computed tomography angiography "CTA", and/or Carotid Doppler), and Holter monitoring with transesophageal echocardiogram "TEE" in cases where suspicion of cardioembolism remained high but TTE was inconclusive.

Initial angiography identified 49 patients with significant extra-or intracranial atherosclerotic changes, of whom 31 were ultimately assigned to the large-artery stroke category. Vasculitis was diagnosed in 2 cases. In the remaining patients, the atherosclerosis was either excluded upon definitive testing or corresponded to a different vascular territory. Vascular imaging was not done or suboptimal in 13 cases.

Atrial fibrillation was documented in 20 patients, of whom 10 were ultimately assigned to the cardioembolic category, while the remaining cases were assigned to other categories according to the results of further work up (based on the definitions provided in the methodology section).

The etiologies identified in TOAST category 4 were aortic atherosclerosis (4 cases), vasculitis (3 cases), thrombophilia (1 case), and aortic valve elastochondroma (1 case).

Table 3 illustrates the frequency of each ischemic stroke category, mean age, median LOS, and sex distribution for each group. Table 4 illustrates the frequency of stroke risk factors for each category.

The left side of the brain was affected by the stroke in 94 cases (66.19%), while strokes affecting the right side of the brain occurred in 46 (32.39%) cases, and 2 cases (1.4%) suffered multiple bilateral strokes.

3.4. Severity, Residual Disability, and Their Predictors. Index events resulted in 742 hospitalization days (mean LOS 5.2 days, SD [+ or -] 5.1 days; median LOS 4 days, IQR 2.75-6). The mean LOS for males was 5.75 days (SD [+ or -] 6.45) and for females was 4.62 (SD [+ or -] 3.00). The difference between the two means was statistically significant at P <0.05 (F = 6.706, P = 0.011).

Prolonged LOS was observed in 33 (23.23%) cases. The commonest cause for prolonged LOS was persistent dysphagia (57.57%), followed by nosocomial infection "NI" (39.39%), or both (21.21%). All patients who suffered from NI had prolonged LOS. Table 5 illustrates the causes of prolonged LOS and their percentages.

The mean NIHSS score on admission was 7.94 (SD 6.11). Sixty-six (46.15%) patients had a NIHSS score on admission of 5 or less, 57 (40.14%) patients had a score of 5-15, 17 (11.97%) patients had a score of 15-24, while 2 (1.40%) had a score of 25 or more. All patients were offered the same medical care according to the stroke protocol at KAUH. Four patients (2.81%) died in the hospital (immediate mortality), all of whom had a NIHSS score upon admission of 15 or more. Mean discharge NIHSS score for the remaining 138 patients was 5.76 (SD 5.06), of which 86 (60.56%) patients had a score of 5 or less, 44 (30.98%) patients had a score 6-15, 7 (4.92%) patients had a score of 16-25, and 1 (0.70%) had a score higher than 25.

The mean discharge mRS score for the cohort was 2.47 (SD [+ or -] 1.79). Patients who are current smokers had the highest mean mRS score compared to patients with medical comorbidities, with a mean of 2.83 (SD [+ or -] 1.82). Mean mRS score was, also, compared among the different stroke etiologies (Table 6). Large artery atherosclerosis was associated with the highest residual disability with a mean score of 3.67 (SD [+ or -] 1.88), while the stroke of undetermined etiology was associated with the lowest residual disability with a mean score of 1.60 (SD [+ or -] 1.78).

To investigate the relationship between the type of stroke and prognosis, Chi-square analysis showed a statistically significant association between different types of stroke and mRS score (P 0.007). Table 6 shows that large artery atherosclerosis has the worse disability prognosis, while stroke of undetermined etiology had the best prognosis.

Table 7 shows that even though small vessel occlusion was the most frequent stroke etiology, the severity of stroke was worse in the large-artery etiology group compared with all other types of stroke. The difference between the mean NIHSS score on admission was statistically significant between large artery atherosclerosis and all other types (F14.22, P 0.000). The table, also, shows that admission NIHSS score is a significant predictor of mRS score (t 9.979, P 0.000).

As for risk factors, smokers had a significantly higher admission NIHSS scores than nonsmokers (t 3.24, P < 0.001). Age, also, was significantly correlated with NIHSS on admission, as patients above the age of 50 were more likely to have a higher mean score of NIHSS admission score compared with younger patients (t 1.98, P < 0.049). Finally, there was a statistically significant association between admission NIHSS score and the patients' length of stay, with a Pearson correlation coefficient of 0.299, P 0.000.

Finally, logistic regression analysis was done to investigate the significant predictors of mRS score. As shown in Table 8, gender was a significant predictor of mRS score, as female patients were more likely to have higher mRS scores than male patients, with an odds ratio of 0.259 (P 0.046). Age was, also, a significant predictor of mRS score. Patients above the age of 50 were more likely to have higher mRS score, with an odds ratio of 29.74 (P 0.022).

In addition, patients with a stroke due to a small vessel occlusion were more liable than patients with a stroke of undetermined etiology to get mRS score of 3-6 with an odds ratio of 8.335 (P 0.45), while patients with a stroke of other determined etiology were more likely to get mRS 3-6 compared to patients with stroke of undetermined etiology by an odds ratio of 2.399. Meanwhile, the other causes of stroke had no significant difference in comparison with each other. NIHSS score on admission was, also, a strong predictor of discharge mRS score, with an odds ratio of 1.99 (P 0.000). Other factors were not found to be significant predictors of mRS score.

Table 9 provides a glance at the findings of this study in comparison to the findings of other published local studies.

4. Discussion

The findings of this study underscore the central role of hypertension in the pathophysiology of ischemic stroke.

The study shows that hypertension was the most prevalent modifiable risk factor (78.87%), both overall and for each TOAST category (except for cardioembolic stroke where it came second to AF). This is consistent with the findings of two previous local studies [8, 9], and with findings of published studies in other countries [6, 23]. The second most common risk factor identified was diabetes mellitus (60.56%), while hyperlipidemia came third, in contrast to the recent survey by Bahou et al., where hyperlipidemia was the second most common. Hypertension (66%) and diabetes mellitus (38%) were also the commonest two risk factors identified in a recent multinational prospective study evaluating stroke characteristics in countries from the Middle East and North Africa "MENA" region compared with patients from non-MENA countries [24].

The results of this study are consistent with previous local studies that showed that lacunar stroke is the most prevalent ischemic stroke etiology in the country. This trend was also noted in recent studies from our region as well as from other regions [25-28]. The prevalence of stroke due to large artery atherosclerosis in our study is also within the range of previous local studies and the global range [8, 9, 29]. The prevalence of cardioembolic stroke (7.04%) was consistent with the previously published local studies which reported an incidence between 6%-8% of stroke etiology. Meanwhile, studies from other regions reported that cardioembolic strokes may account for up to one fifth to one-quarter of ischemic strokes [30-32]. This discrepancy may be a result of poorer control of traditional ischemic stroke risk factors such as hypertension and hyperlipidemia in Jordan in comparison to that in high-income countries. Also, hypertension and diabetes mellitus both have a higher prevalence in Jordan compared with global figures [33, 34]. The discrepancy may, also, reflect the scarcity of resources that compromise the availability or accessibility to investigational techniques, and/or feasibility of patient follow-up in hospitals in low- and middle-income countries. Moreover, differences in methodology may contribute to the noted discrepancy. Some studies list aortic atherosclerosis under the cardioembolic category [35], while the emergence in recent years of the concept of Embolic Stroke of Undetermined Source "ESUS" resulted in a portion of cases being shifted from the undetermined etiology to the cardioembolic category [36]. Another possible reason could be a low level of awareness about the lacunar stroke category as a consequence of uncontrolled hypertension among patients due to either lower educational level or lack of appropriate disease-specific educational programs offered by physicians about hypertension and its complications. Lastly, the retrospective nature of this study could have also contributed to the discrepancy.

The mean age of patients with the first ischemic stroke in Jordan increased over time (Table 9), but it remains younger than the mean age of first stroke reported from high-income countries [37-38]. This is in spite of the population in Jordan being younger [39], which also is attributable--at least in part--to the effects of the limitations in diagnostic, treatment, and prevention modalities in Jordan.

Atrial fibrillation was documented in 20 patients in our study (14%), while the previous local studies in 2004 and 2015 reported atrial fibrillation in 6% and 4% of patients in their cohorts, respectively. This could be partially related to the greater commercial and logistical availability of ambulatory cardiac monitors nowadays. Also, the medical registry at KAUH is completely electronic, which offered the advantage of retrieving previously documented paroxysmal atrial fibrillation in some patients who presented with acute stroke while having a sinus rhythm. Furthermore, our findings are in line with other recent studies in the region. For instance, atrial fibrillation was found in 13% of the patients in a Saudi study published in 2016 [28], while older studies from the same region reported lower numbers (5% and 10%) [40, 41]. Upon reviewing the dates of the referenced studies, the reader can observe the temporal trend of increasing detection of atrial fibrillation in stroke cohorts in the region.

On the other hand, smoking was documented in 24.6% of patients in our cohort, while the previous studies from Jordan reported a higher prevalence (35% and 40%). This may be in part due to the interim introduction of new tobacco taxes over the past decade [42]. Also, smoking is more prevalent among Jordanian males, and the male to female ratio in our study was lower than the other studies [42]. Further, no clear trends are delineated when smoking statistics between the years 2000-2016 are compared, but the overall reported percentages of daily smokers had a wide range between 24-32% among Jordanians [42].

Twenty (14.08%) of the patients in our cohort developed NI, mainly pneumonia (8 patients, 5.63%), UTI (8 patients, 5.63%), and both (2 patients, 1.40%). Studies in other regions that sought to determine the rate of NI after acute ischemic stroke reported a wide range (6-48.3%), with pneumonia and UTI being the most frequently encountered NIs [43-48], while studies evaluating NI after strokes due to ischemic and hemorrhagic etiologies combined reported an even higher incidence (up to 65%) [49-52]. Meanwhile, a retrospective cohort study conducted at KAUH in 2019 which evaluated NI in patients with intracranial hemorrhage found the incidence of NI to be 40.3% overall and 46% among patients with intracerebral hemorrhage "ICH" [53]. The incidence of NIs in our study falls within the range that has been reported in other published studies.

Age, smoking, and large-artery etiology were significantly associated with higher stroke severity on admission. Age was also a significant predictor of a higher residual disability, in addition to female sex and stroke severity on admission. These relations have been reported in previous studies [54-59]. Logistic regression also demonstrated that lacunar strokes and strokes due to other determined etiologies predicted worse outcomes when compared with strokes due to undetermined etiology, but similar associations could not be drawn upon comparing the other etiologies. On the other hand, our analysis demonstrated an association between large-artery etiology and residual disability, and as mentioned above, the large-artery etiology was also associated with higher severity on presentation. Together, these findings point indirectly towards an association between large artery atherosclerosis and unfavorable stroke outcome.

The strengths of this study include the rigorous case ascertainment and data collection process, which allowed for a deeper insight into the epidemiology and prevalence of risk factors among patients with a first ischemic stroke in Jordan. It is also the first study to shed light on stroke severity, stroke-related disability, and its predictors among Jordanian patients, which can be viewed as a platform to launch larger and prospective future studies. At the same time, this study has several limitations. It is a single-center study that included patients from KAUH only, which has led to a relatively small sample, and consequently limited the type of statistical analysis techniques that could have been used. Also, it was a pure retrospective study, where patient follow-up was not feasible. Finally, cardioembolic work-up could have been more comprehensive. Future studies could include a more complete and rigorous evaluation of possible cardiovascular etiologies by having cardiologists as a part of the investigation team.

5. Conclusion

Ischemic strokes have different etiologies that are associated with different levels of impact on the patient's clinical status and prognosis. Hypertension is the most common comorbidity found in patients admitted for stroke. Small-vessel occlusion was the most frequent stroke etiology. However, large artery atherosclerosis was associated with the highest residual disability. Regarding predictors of prognosis, current smoking status, and age above 50 were and NIHSS on admission appear to be the strongest predictors of prognosis. Finally, higher NIHSS score on admission resulted in a longer hospital stay.

Data Availability

Study data is available upon reasonable request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.


The study team would like to acknowledge Samah Elamassie, MD, MPH, for her assistance with statistical interpretation of the data and critical revision of the study.


[1] V. L. Feigin, B. Norrving, and G. A. Mensah, "Global Burden of Stroke," Circulation Research, vol. 120, no. 3, pp. 439-448, 2017.

[2] M. Katan and A. Luft, "Global Burden of Stroke," Seminars in Neurology, vol. 38, no. 2, pp. 208-211, 2018.

[3] V. L. Feigin, C. M. Lawes, D. A. Bennett, S. L. Barker-Collo, and V. Parag, "Worldwide stroke incidence and early case fatality reported in 56 population- based studies: a systematic review," Lancet Neurology, vol. 8, no. 4, pp. 355-369, 2009.

[4] The GBD 2016 Lifetime Risk of Stroke Collaborators, "Global, Regional, and Country-Specific Lifetime Risks of Stroke, 1990 and 2016," New England Journal of Medicine, vol. 379, no. 25, pp. 2429-2437, 2018.

[5] A. K. Boehme, C. Esenwa, and M. S. Elkind, "Stroke Risk Factors, Genetics, and Prevention," Circulation Research, vol. 120, no. 3, pp. 472-495, 2017.

[6] M. J. O'Donnell, D. Xavier, L. Liu et al., "Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study," Lancet, vol. 376, no. 9735, pp. 112-123, 2010.

[7] Jordan, Institute for Health Metrics and Evaluation, 2017, October 2019,

[8] Y. Bahou, H. Hamid, and A. Hadidi, "Ischaemic stroke in Jordan: a 2-year hospital-based study of subtypes and risk factors," Eastern Mediterranean Health Journal, vol. 10, no. 1-2, pp. 138-146, 2004.

[9] Y. A. M. Bahou and M. Jaber, "Ischemic stroke at Jordan University Hospital: a one-year hospital-based study of subtypes and risk factors," SM Journal of Neurology and Neuroscience, vol. 1, no. 1, p. 1003, 2015.

[10] Estimated Population of the Kingdom by Governorate and Sex, Department of Statistics-Jordan, 2017, October 2019, path=Population%20and%20Housing__Demographic% 20Statistics&px_tableid=Table%201.px&px_language13 = en&px_db = Population%20and%20Housing&rxid = d8467649-5faf-4b4c-8c29-f629d95a188e.

[11] R. L. Sacco, S. E. Kasner, J. P. Broderick et al., "An updated definition of stroke for the 21st century: a statement for healthcare professionals from the American Heart Association/American Stroke Association," Stroke, vol. 44, no. 7, pp. 2064-2089, 2013.

[12] H. P. Adams Jr., B. H. Bendixen, L. J. Kappelle et al., "Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment," Stroke, vol. 24, no. 1, pp. 35-41, 1993.

[13] H. White, B. Boden-Albala, C. Wang et al., "Ischemic stroke subtype incidence among whites, blacks, and Hispanics," Circulation, vol. 111, no. 10, pp. 1327-1331, 2005.

[14] M. G. George, "Risk Factors for Ischemic Stroke in Younger Adults," Stroke, vol. 51, no. 3, pp. 729-735, 2020.

[15] P. A. James, S. Oparil, B. L. Carter et al., "2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the Eighth Joint National Committee (JNC 8)," Journal of the American Medical Association, vol. 311, no. 5, pp. 507-520, 2014.

[16] American Diabetes Associations, "Diagnosis and classification of diabetes mellitus," Diabetes Care, vol. 33, Suppl 1, pp. S62-S69, 2009.

[17] M. Nayor and R. S. Vasan, "Recent Update to the US Cholesterol Treatment Guidelines," Circulation, vol. 133, no. 18, pp. 1795-1806, 2016.

[18] P. M. Bath, K. R. Lees, P. D. Schellinger et al., "Statistical analysis of the primary outcome in acute stroke trials," Stroke, vol. 43, no. 4, pp. 1171-1178, 2012.

[19] R. W. Krell, M. E. Girotti, and J. B. Dimick, "Extended length of stay after surgery: complications, inefficient practice, or sick patients?," JAMA Surgery, vol. 149, no. 8, pp. 815-820, 2014.

[20] I. Gyalai-Korpos, O. Ancusa, T. Dragomir, M. C. Tomescu, and I. Marincu, "Factors associated with prolonged hospitalization, readmission, and death in elderly heart failure patients in western Romania," Clinical Interventions in Aging, vol. 10, pp. 561-568, 2015.

[21] Y. Ueno, A. Okuzumi, M. Watanabe et al., "Cerebral small artery diseases may be associated with aortic arch calcification in stroke patients," Journal of Atherosclerosis and Thrombosis, vol. 21, no. 10, pp. 1011-1021, 2014.

[22] A. H. Lee, W. K. Fung, and B. Fu, "Analyzing hospital length of stay: mean or median regression?," Medical Care, vol. 41, no. 5, pp. 681-686, 2003.

[23] A. Arboix, "Cardiovascular risk factors for acute stroke: Risk profiles in the different subtypes of ischemic stroke," World Journal of Clinical Cases, vol. 3, no. 5, pp. 418-429, 2015.

[24] S. A. Rukn, M. V. Mazya, F. Hentati et al., "Stroke in the Middle-East and North Africa: A 2-year prospective observational study of stroke characteristics in the region--Results from the Safe Implementation of Treatments in Stroke (SITS)-Middle-East and North African (MENA)," International Journal of Stroke, vol. 14, no. 7, pp. 715-722, 2019.

[25] F. I. Hsieh and H. Y. Chiou, "Stroke: morbidity, risk factors, and care in Taiwan," Journal Stroke, vol. 16, no. 2, pp. 59-64, 2014.

[26] T. C. Turin, Y. Kita, N. Rumana et al., "Ischemic stroke subtypes in a Japanese population: Takashima Stroke Registry, 1988-2004," Stroke, vol. 41, no. 9, pp. 1871-1876, 2010.

[27] J. Y. Al-Hashel, A.-A. Al-Sabah, S. F. Ahmed et al., "Risk Factors, Subtypes, and Outcome of Ischemic Stroke in Kuwait: A National Study," Journal of Stroke and Cerebrovascular Diseases, vol. 25, no. 9, pp. 2145-2152, 2016.

[28] A. Zafar, F. A. al-Khamis, A. I. al-Bakr, A. A. Alsulaiman, and A. H. Msmar, "Risk factors and subtypes of acute ischemic stroke. A study at King Fahd Hospital of the University," Neurosciences, vol. 21, no. 3, pp. 246-251, 2016.

[29] E. Marulanda-Londono and S. Chaturvedi, "Stroke due to large vessel atherosclerosis: Five new things," Neurology: Clinical Practice, vol. 6, no. 3, pp. 252-258, 2016.

[30] B. Murtagh and R. W. Smalling, "Cardioembolic stroke," Current Atherosclerosis Reports, vol. 8, no. 4, pp. 310-316, 2006.

[31] J. M. Ferro, "Cardioembolic stroke: an update," Lancet Neurology, vol. 2, no. 3, pp. 177-188, 2003.

[32] R. V. Krishnamurthi, S. Barker-Collo, V. Parag et al., "Stroke Incidence by Major Pathological Type and Ischemic Subtypes in the Auckland Regional Community Stroke Studies," Stroke, vol. 49, no. 1, pp. 3-10, 2018.

[33] Y. Khader, A. Batieha, H. Jaddou et al., "Hypertension in Jordan: Prevalence, Awareness, Control, and Its Associated Factors," International Journal of Hypertension, vol. 2019, Article ID 3210617, 8 pages, 2019.

[34] A. Alghadir, A. A. Alghwiri, H. Awad, and S. Anwer, "Ten-year Diabetes Risk Forecast in the Capital of Jordan," Medicine, vol. 95, no. 12, article e3181, 2016.

[35] M. Marnane, C. A. Duggan, O. C. Sheehan et al., "Stroke subtype classification to mechanism-specific and undetermined categories by TOAST, A-S-C-O, and causative classification System," Stroke, vol. 41, no. 8, pp. 1579-1586, 2010.

[36] G. Tsivgoulis, A. H. Katsanos, M. Kohrmann et al., "Embolic strokes of undetermined source: theoretical construct or useful clinical tool?," Therapeutic Advances in Neurological Disorders, vol. 12, p. 175628641985138, 2019.

[37] B. M. Kissela, J. C. Khoury, K. Alwell et al., "Age at stroke: temporal trends in stroke incidence in a large, biracial population," Neurology, vol. 79, no. 17, pp. 1781-1787, 2012.

[38] O. O. Seminog, P. Scarborough, F. L. Wright, M. Rayner, and M. J. Goldacre, "Determinants of the decline in mortality from acute stroke in England: linked national database study of 795 869 adults," BMJ, vol. 365, p. l1778, 2019.

[39] L. Mossuto-Agatiello, "Caudal paramedian midbrain syndrome," Neurology, vol. 66, no. 11, pp. 1668-1671, 2006.

[40] S. Al-Shammri, Z. Shahid, A. Ghali et al., "Risk factors, subtypes and outcome of ischaemic stroke in Kuwait-a hospital-based study," Medical Principles and Practice, vol. 12, no. 4, pp. 218-223, 2003.

[41] D. Deleu, J. Inshasi, N. Akhtar et al., "Risk factors, management and outcome of subtypes of ischemic stroke: a stroke registry from the Arabian Gulf," Journal of the Neurological Sciences, vol. 300, no. 1-2, pp. 142-147, 2011.

[42] Jordan, Overview of tobacco use, tobacco control, legislation and taxation, World Bank Group, May 2019, http://documents Taxation.pdf.

[43] C. Weimar, M. P. Roth, G. Zillessen et al., "Complications following acute ischemic stroke," European Neurology, vol. 48, no. 3, pp. 133-140, 2002.

[44] K. C. Johnston, J. Y. Li, P. D. Lyden et al., "Medical and neurological complications of ischemic Stroke," RANTTAS Investigators Stroke, vol. 29, no. 2, pp. 447-453, 1998.

[45] A. J. Grau, F. Buggle, P. Schnitzler, M. Spiel, C. Lichy, and W. Hacke, "Fever and infection early after ischemic stroke," Journal of the Neurological Sciences, vol. 171, no. 2, pp. 115-120, 1999.

[46] P. U. Heuschmann, P. L. Kolominsky-Rabas, B. Misselwitz et al., "Predictors of in-hospital mortality and attributable risks of death after ischemic stroke: the German Stroke Registers Study Group," Archives of Internal Medicine, vol. 164, no. 16, pp. 1761-1768, 2004.

[47] B. B. Hamidon, A. A. Raymond, M. I. Norlinah, and S. B. Jefferelli, "The predictors of early infection after an acute ischaemic stroke," Singapore Medical Journal, vol. 44, no. 7, pp. 344-346, 2003.

[48] K. Grabska, G. Gromadzka, and A. Czlonkowska, "Infections and ischemic stroke outcome," Neurology Research International, vol. 2011, Article ID 691348, 8 pages, 2011.

[49] R. J. Davenport, M. S. Dennis, I. Wellwood, and C. P. Warlow, "Complications after acute stroke," Stroke, vol. 27, no. 3, pp. 415-420, 1996.

[50] W. F. Westendorp, P. J. Nederkoorn, J. D. Vermeij, M. G. Dijkgraaf, and D. van de Beek, "Post-stroke infection: a systematic review and meta-analysis," BMC Neurology, vol. 11, no. 1, p. 110, 2011.

[51] P. Langhorne, D. J. Stott, L. Robertson et al., "Medical complications after Stroke," Stroke, vol. 31, no. 6, pp. 1223-1229, 2000.

[52] M. Vargas, J. P. Horcajada, V. Obach et al., "Clinical consequences of infection in patients with acute stroke: is it prime time for further antibiotic trials?," Stroke, vol. 37, no. 2, pp. 461-465, 2006.

[53] R. W. Jaradat, A. B. Lahlouh, O. Y. Alshogran, B. A. Aldabbour, and A. A. Balusha, "Nosocomial Infections among Patients with Intracranial Hemorrhage: A Retrospective Data Analysis of Predictors and Outcomes," Clinical Neurology and Neurosurgery, vol. 182, pp. 158-166, 2019.

[54] A. Wouters, C. Nysten, V. Thijs, and R. Lemmens, "Prediction of Outcome in Patients With Acute Ischemic Stroke Based on Initial Severity and Improvement in the First 24 h," Frontiers in Neurology, vol. 9, p. 308, 2018.

[55] S. Sato, K. Toyoda, T. Uehara et al., "Baseline NIH Stroke Scale Score predicting outcome in anterior and posterior circulation strokes," Neurology, vol. 70, Issue 24, Part 2, pp. 2371-2377, 2008.

[56] D. Sablot, F. Belahsen, F. Vuillier et al., "Predicting acute ischaemic stroke outcome using clinical and temporal thresholds," ISRN Neurology, vol. 2011, Article ID 354642, 9 pages, 2011.

[57] N. S. Rost, A. Bottle, J. M. Lee et al., "Stroke Severity Is a Crucial Predictor of Outcome: An International Prospective Validation Study," Journal of the American Heart Association, vol. 5, no. 1, 2016.

[58] S. Shrestha, R. S. Poudel, D. Khatiwada, and L. Thapa, "Stroke subtype, age, and baseline NIHSS score predict ischemic stroke outcomes at 3 months: a preliminary study from Central Nepal," Journal of Multidisciplinary Healthcare, vol. 8, pp. 443-448, 2015.

[59] V. Caso, M. Paciaroni, G. Agnelli et al., "Gender differences in patients with acute ischemic stroke," Womens Health, vol. 6, no. 1, pp. 51-57, 2010.

Majdi Al Qawasmeh [ID], Belal Aldabbour [ID], Aiman Momani, Deema Obiedat, Kefah Alhayek, Raid Kofahi, Ahmed Yassin, and Khalid El-Salem

Department of Neurology, King Abdullah University Hospital (KAUH) of Jordan University of Science and Technology (JUST), Irbid, Jordan

Correspondence should be addressed to Majdi Al Qawasmeh;

Received 25 November 2019; Revised 17 May 2020; Accepted 23 May 2020; Published 4 June 2020

Academic Editor: Halvor Naess
Table 1: Stroke risk factors and their distribution by sex.
Abbreviations: ischemic heart disease: IHD.

Risk factor              Number              Gender
                                        Male         Female

Hypertension          112 (78.87%)   55 (72.36%)   57 (86.36%)
Diabetes mellitus     86 (60.56%)    45 (59.21%)   41 (62.12%)
IHD                   42 (29.47%)    32 (42.1%)    10 (15.15%)
Hyperlipidemia        53 (37.32%)    29 (38.15%)   24 (36.36%)
Smoking               35 (24.64%)    29 (38.15%)    6 (9.09%)
Atrial fibrillation   20 (14.08%)     7 (9.21%)    13 (19.69%)
Heart failure         20 (14.08%)    10 (13.15%)   10 (15.15%)

Table 2: Frequency of procedures performed under stroke work-up
(Note: numbers are not mutually exclusive).

Type of procedure             Number     Percentage
                             performed   of patients

Electrocardiogram (ECG)         141        99.29%
Transthoracic Echo (TTE)        138        97.18%
Holter and transesophageal      16         11.26%
  Echo (TEE)
MRA                             59         41.54%
CTA                             72         50.70%
Carotid Doppler                 11          7.74%
4-vessel angiography             1          0.70%

Table 3: Stroke categories and their frequency by sex.

TOAST category      Number (%)        Mean
                                    age (SD)

Large-artery        31 (21.83%)    70.7 (10.2)
Cardioembolism      10 (7.04%)     72.5 (7.91)
Small-vessel        77 (54.22%)   66.03 (10.84)
Other determined     9 (6.33%)    52.33 (16.68)
Undetermined        15 (10.56%)   65.13 (12.67)

TOAST category         Mean LOS (SD)       Median

Large-artery        7.61 ([+ or -] 5.84)      6
Cardioembolism      4.20 ([+ or -] 1.47)      4
Small-vessel        4.72 ([+ or -] 5.42)      3
Other determined    5.55 ([+ or -] 3.81)      4
Undetermined        3.33 ([+ or -] 2.66)      2

TOAST category                Sex

                     Male (%)     Female (%)

Large-artery        16 (21.05%)   15 (22.72%)
Cardioembolism       4 (5.26%)     6 (9.09%)
Small-vessel        47 (61.84%)   30 (45.45%)
Other determined     4 (5.26%)     5 (7.57%)
Undetermined         5 (6.57%)    10 (15.15%)

Table 4: Prevalence (n) and percentage (%) of stroke risk factors
for each stroke category. Abbreviations: Ischemic heart disease:
IHD; atrial fibrillation: AF; heart failure: HF.

TOAST category      Hypertension    Diabetes         IHD

Large-artery        27 (87.09%)    19 (61.29%)   7 (22.58%)
Cardioembolism        8 (80%)        5 (50%)       3 (30%)
Small-vessel        60 (77.92%)    50 (64.93%)   25 (32.46%)
Other determined     4 (44.44%)    3 (33.33%)    3 (33.33%)
Undetermined        13 (86.67%)      9 (60%)     4 (26.67%)

TOAST category      Hyperlipidemia     Smoking

Large-artery          12 (38.7%)     11 (35.48%)
Cardioembolism         2 (20%)         2 (20%)
Small-vessel         31 (40.25%)     17 (22.07%)
Other determined      3 (33.33%)     2 (22.22%)
Undetermined          5 (33.33%)       3 (20%)

TOAST category          AF           HF

Large-artery        6 (19.35%)   6 (19.35%)
Cardioembolism      10 (100%)     5 (50%)
Small-vessel        2 (2.59%)    7 (9.09%)
Other determined      0 (0%)       0 (0%)
Undetermined        2 (13.33%)   2 (13.33%)

Table 5: Reasons for prolonged LOS. Abbreviations: urinary tract
infection: UTI; Percutaneous endoscopic gastrostomy: PEG. Note:
classification is not mutually exclusive.

Reason for prolonged LOS

Nosocomial infection                      13 (39.39%)
  Pneumonia                               5 (38.46%)
  UTI                                     4 (30.76%)
  Both pneumonia and UTI                  2 (15.38%)
  Other infections                        2 (15.38%)
Dysphagia                                 19 (57.57%)
  Dysphagia requiring PEG tube            12 (63.15%)
  Dysphagia resolving during admission    7 (36.85%)
Both dysphagia and nosocomial infection   7 (21.21%)
  Pneumonia                               3 (42.85%)
  UTI                                     4 (57.14%)
  Both pneumonia and UTI                    0 (0%)
  Other infections                          0 (0%)
  Dysphagia requiring PEG tube             7 (100%%)
  Dysphagia resolving during admission      0 (0%)
  Decreased consciousness                  2 (6.06%)
  Optimization of anticoagulation          3 (9.09%)
  Hemorrhagic transformation               2 (6.06%)
  Observation for other complications     5 (15.15%)
  Pending further investigations           3 (9.09%)

Table 6: Mean mRS score for each stroke etiology and the
correlation between stroke etiology and mRS scores.

TOAST category              Mean

Large-artery               3.6774
Cardioembolism             2.6000
Small-vessel               2.2078
Other determined           1.8889
Undetermined               1.6000
All categories             2.4718

Chi-square              Type of stroke

mRS score
                         1       2
0-2                 N    7       5
                    %   22.6     50

3-6                 N    24      5
                    %   77.4     50

TOAST category              Number

Large-artery                  31
Cardioembolism                10
Small-vessel                  77
Other determined              9
Undetermined                  15
All categories                142

Chi-square              Type of stroke

mRS score
                           3      4
0-2                 N     42      6
                    %     54.5   66.7

3-6                 N     35      3
                    %     45.5   33.3

TOAST category             Standard

Large-artery                1.88657
Cardioembolism              1.64655
Small-vessel                1.58395
Other determined            1.69148
Undetermined                1.72378
All categories              1.78923

Chi-square               Type of   Sig:
                         stroke    0.007
mRS score
                          5        Total
0-2                 N     11        71
                    %     73.3

3-6                 N     4         71
                    %     26.7

Table 7: Variables with statistically significant correlation with
the admission NIHSS score.

Variables              N    Mean NIHSS   Standard    Factor
                            admission    deviation

Type of stroke
  Large artery        31      14.098      7.95133
  Cardioembolism      10      8.4000      6.97199
  Small vessel        77      5.9870      3.59639      F
  Stroke of other      9      5.4444      4.45724
  Stroke of           15      6.4667      4.68838
  Yes                 35     10.7714      7.55406      T
  No                  107     7.0187      5.32169
mRS score
  0-2                 71        4         2.23607      T
  3-6                 71     11.8873      6.27364
  Less than 50        15      5.000       4.69586      T
    years old
  More than 50        127     8.2913      6.21329
    years old

Variables              N    Value     Sig

Type of stroke
  Large artery        31
  Cardioembolism      10
  Small vessel        77    14.228   0.000
  Stroke of other      9
  Stroke of           15
  Yes                 35    3.244    0.001
  No                  107
mRS score
  0-2                 71    9.979    0.000
  3-6                 71
  Less than 50        15    1.984    0.049
    years old
  More than 50        127
    years old

Table 8: Logistic regression on the impact of independent
variables on mRS score.

Variables                  B        Wald      Significance    Odds

Gender                   -1.352     3.965        0.046       0.259
Age (reference less      3.393      5.216        0.022       29.746
  than 50)
Smoking                  0.180      0.057        0.811       1.197
Dyslipidemia             -0.046     0.006        0.940       0.955
Atrial fibrillation      0.100      0.005        0.945       1.105
Diabetes                 0.582      0.841        0.359       1.790
Hypertension             -0.055     0.005        0.946       0.946
Ischemic heart disease   -0.876     1.507        0.220       0.416
TOAST-subtype                       5.515        0.238
  (1) Large artery       1.736      1.524         .217       5.674
  (2) Cardioembolism     0.672      0.117         .733       1.958
  (3) Small-vessel       2.120      4.037         .045       8.335
  (4) Stroke of other    3.346      3.908         .048       2.399
NIHSS-admission          0.645     25.021        0.000       1.907
Length of stay           0.074      1.253        0.263       1.077
  per days
Heart failure            0.945      0.985        0.321

Table 9: Prevalence of risk factors, mean age, male prevalence, and
stroke categories in 3 local studies from Jordan.

                        Our data (2017-2018)   Bahou et al., 2015

Risk factors
  Hypertension                 78.87%                 85%
  Diabetes mellitus            60.56%                 65%
  IHD                          29.47%                 39%
  Hyperlipidemia               37.32%                 71%
  Smoking                      24.64%                 40%
  Atrial fibrillation          14.08%                  4%
  Heart failure                14.08%             Not reported
Male prevalence (%)            53.52%                 62%
Mean age (years)                66.5                   66
TOAST category
  Large-artery                 21.83%                 28%
  Cardioembolism               7.04%                   6%
  Small-vessel                 54.22%                 36%
  Other determined             6.33%              Not reported
  Undetermined                 10.56%                 30%

                        Bahou et al., 2004

Risk factors
  Hypertension                 76%
  Diabetes mellitus            44%
  IHD                         20.5%
  Hyperlipidemia               33%
  Smoking                      35%
  Atrial fibrillation           6%
  Heart failure            Not reported
Male prevalence (%)            56%
Mean age (years)               61.2
TOAST category
  Large-artery                 20%
  Cardioembolism                8%
  Small-vessel                51.5%
  Other determined         Not reported
  Undetermined                19.5%
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Title Annotation:Research Article
Author:Qawasmeh, Majdi Al; Aldabbour, Belal; Momani, Aiman; Obiedat, Deema; Alhayek, Kefah; Kofahi, Raid; Y
Publication:Stroke Research and Treatment
Date:Jun 30, 2020
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