Department of Neurology, Calcutta National Medical College, Kolkata PIN-700014, India.
© The Author(s) 2018. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Aim: Stroke is one of the leading causes of death and disability. The proportion of patients receiving recombinant tissue plasminogen activator is low in our country. Biomarkers to identify patients at risk of severe disease, and guide treatment and prognosis would be valuable. This article aims to identify the factors that can independently prognosticate the acute phase of ischemic stroke.
Methods: All patients with the first episode of ischemic stroke admitted to the Neurology Department between 1st December 2017 to 31st March 2018 were included in this pilot study. Stroke severity was evaluated using the National Institute of Health Stroke Scale (NIHSS). Patients being admitted within 4.5 h of onset of symptoms were thrombolysed with injection alteplase. For each patient, 4 serum biomarkers (D-dimer, fibrinogen, C-reactive protein and neuron specific enolase) were evaluated at admission and 24 h later. Discharged patients were assessed on an outpatient basis using the modified Rankin scale. The study primarily aimed to identify the factors predicting the severity and outcome of stroke, and to evaluate the effect of thrombolysis on the outcome. The secondary aim was to evaluate the role of biomarkers to predict the unfavorable outcome and the chance of post thrombolysis hemorrhage.
Results: Out of 30 patients included in the study, 10 had NIHSS 0-4, 12 had NIHSS 5-15 and 8 had NIHSS 16-42. Sixteen patients had unfavorable outcome (mRS score ≥ 2), and 5 patients expired. Old age, history of diabetes, CHADS2 score ≥ 2, and total anterior circulation stroke (TACS) independently affected stroke severity, whereas low ejection fraction < 35%, and TACS, independently predicted unfavorable outcome and mortality. High mean arterial blood pressure (MABP) and capillary blood glucose (CBG) at admission were significant predictors of stroke severity, unfavorable outcome, and mortality. Out of 10 thrombolysed patients, two had mRS score ≥ 2 and 3 had the post-thrombolysis hemorrhage. Thrombolysis significantly reduced the incidence of the unfavorable outcome, but did not significantly affect death. All the biomarker levels at admission were significantly higher among patients with severe stroke and those who subsequently had an unfavorable outcome. D-dimer levels significantly increased and fibrinogen level significantly decreased following thrombolysis. Higher MABP, CBG, and fibrinogen levels at admission predicted significantly higher chance to develop hemorrhagic complications post thrombolysis.
Conclusion: Low ejection fraction, occurrence of TACS and the higher levels of the biomarkers under study predicted poor outcome. Higher mean CBG and MABP and raised fibrinogen levels predicted higher chance of post-thrombolysis hemorrhage.
First-ever ischemic stroke, thrombolysis, biomarkers, total anterior circulation stroke, fibrinogen
Stroke is one of the leading causes of death and disability in India, which is facing the double burden of communicable and non-communicable diseases. The estimated adjusted prevalence rate of stroke range from 84-262/100,000 in rural to 334-424/100,000 in urban areas. The incidence rate is 119-145/100,000 based on the recent population based studies. These values were higher than those of high-income countries. Case fatality rates vary widely, the highest being 42% in Kolkata. Among patients presenting with the first-ever stroke in the Mumbai registry, 80.2% were ischemic strokes and 17.7% were hemorrhagic strokes. In the Trivandrum registry, 83.6% were ischemic strokes, 11.6% were intracerebral hemorrhages, and 4.8% were subarachnoid hemorrhages. Thirty-two percent of the patients in the Kolkata registry had hemorrhagic stroke, the highest reported so far from India. The proportion of patients receiving recombinant tissue plasminogen activator (rtPA) is low in our country, being 11% (104 out of 967 patients) in the on-going Indo USA National stroke registry, due to lack of trained personnel. Intraarterial and mechanical thrombolysis was given in 3.5% (34 out of 967 patients).
Age, stroke severity, stroke mechanism, infarct location, comorbid conditions, clinical findings, and related complications influence stroke prognosis. Interventions such as thrombolysis, stroke unit care, and rehabilitation also influence the outcome of ischemic stroke. Knowledge of these prognostic factors enables the clinician to make a reasonable prediction for each patient, to offer a rational treatment to the patients, and to help the family members understand the disease course. Though clinical examination can excellently assess the stroke patients and the disease progression, biomarkers would be valuable to identify the patients at risk of severe disease, to guide treatment and to reasonably predict the prognosis. Though many such proteins which are markers of brain tissue damage, inflammation, and coagulation/thrombosis are associated with ischemic stroke, their successful translation to a biomarker useful in clinical practice has proven difficult due to the heterogeneity of ischemic stroke. Moreover, they are not specific to ischemic stroke, as many other disease processes can damage brain tissue. The blood- brain barrier restrains the release of these biomarkers into the systemic circulation; hence, their levels may not correlate with the infarct volume, given that the anatomic locations of stroke have different impacts on blood-brain barrier breakdown. Markers of ischemic brain injury include S100 calcium binding protein B (S-100B), neuron-specific enolase (NSE), myelin basic protein, and glial fibrillary acidic protein. Several proteins involved in inflammation and immune response have also been identified as biomarkers of ischemic stroke, including C-reactive protein (CRP), interleukin-6, tissue necrosis factor-alpha, vascular cell adhesion protein 1, intercellular adhesion molecule 1, N-methyl-d-aspartate receptor antibodies and matrix metalloproteinases. Similarly, molecules involved in acute thrombosis have also been associated with ischemic stroke, including fibrinogen, D-Dimer and von-Willebrand factor.
Few studies have systematically evaluated the multimodal factors (demographic, clinical, radiological and biological markers) in unselected consecutive first-ever ischemic stroke patients. This article aims to identify the factors that can independently prognosticate the acute phase of ischemic stroke.
All patients with the first episode of ischemic stroke admitted to the Neurology Department between 1st December 2017 to 30th April 2018 were included in this pilot study and written informed consent was taken from the patients or their family members to participate in the study. Stroke was defined according to the World Health Organisation criteria. Ischemic stroke was diagnosed with a combination of clinical criteria and non contrast computed tomography imaging of brain, which was done for all patients upon admission, to exclude intracerebral hemorrhage. We recorded the medical history prior to the stroke and the congestive heart failure, hypertension, age, diabetes mellitus, prior stroke or transient ischemic attack (TIA), or thromboembolism (CHADS2) scores were calculated for all patients. The following variables were analyzed: gender, age, domestic arrangements (lives with other family members or alone), clinical history, and medications, vascular risk factors including history of hypertension, diabetes mellitus, heart diseases [ischemic heart disease, low ejection fraction and atrial fibrillation (AF), as a history of AF and/or AF diagnosed during the index admission by electrocardiography], TIA, current or former smoking, and hypercholesterolemia. Stroke severity was evaluated in the acute phase of the initial stroke by a neurologist certified in the use of the National Institute of Health Stroke Scale (NIHSS). Stroke severity by NIHSS was categorized as mild (0-4), moderate (5-15), or severe (16-42). Furthermore, strokes were classified according to the Bamford criteria in total anterior circulation stroke (TACS), partial anterior circulation stroke (PACS), posterior circulation stroke (PCS), and lacunar stroke (LS). Patients being admitted within 4.5 h of onset of symptoms were thrombolysed with injection alteplase, provided they did not have the contraindications for thrombolysis. For each patient, 4 serum biomarkers [(D-dimer, fibrinogen, CRP and Neuron specific enolase (NSE)] were evaluated at admission and 24 h later. D-dimer was assessed using enzyme linked immunosorbant assay (ELISA) kits from GenWay Biotech, San Diego, California, USA, and a level of more than 4 µg/mL was considered high. NSE was assessed using human NSE ELISA kit (Elabscience Biotechnology Co. Ltd., Houston, USA) and the normal value at spectrophotometers in the 450 nm wavelength was 7.2-12 ng/mL. Serum concentrations of CRP were quantified using a commercially available turbidimetric immunoassay (Transasia Bio-Medicals Ltd., Erba Diagnostics, Mannheim, Germany) and value < 6 mg/L was considered normal. Fibrinogen was assayed by FibroTek fibrinogen kit (R2 Hemostasis Diagnostics India Private Limited, Indira Puram, Ghaziabad, Uttar Pradesh) and the value of 150-400 mg/dL was considered normal.
Follow-up magnetic resonance imaging examination (1.5 Tesla system providing axial T1, T2, and proton density weighted images) or brain CT scan was repeated 5 days after the index event. Metabolic profile (renal and liver function tests); and hematologic parameters (complete hemograms and coagulation profile) were recorded in the registry on arrival and again at 24-48 h after stroke onset. The cardiological profile (electrocardiogram and transthoracic echocardiography) and a search for vasculitis (antinuclear factor and antiphospholipid antibodies) were also done. Previous infections were excluded by medical history, chest radiograph, routine urinalysis, and complete physical examination. The vital parameters were recorded continuously using multi-parameter monitors. The length of hospital stay was defined from the day of admission to a hospital ward to the day of discharge. Acute stroke management and secondary prevention in these patient followed current European Stroke Organization guidelines. Discharged patients were followed up on a monthly basis through neurological examination and review of records. Their clinical outcomes were assessed using the modified Rankin scale (mRS) and categorized as favorable (score 0-1) or unfavorable (score 2-6). Exclusion criteria included history of recent infection, obvious signs of acquired infection before stroke onset, and an initial CRP level > 10 mg/dL due to presumed infection.
Outcome measures - the primarily aims of the study were the following: (1) to identify the factors independently predicting: i) the severity of stroke; ii) the unfavorable outcome at 30 days post discharge; iii) the mortality; and iv) the chance of post thrombolysis hemorrhage; and (2) to evaluate the effect of thrombolysis on the outcome of ischemic stroke patients. The secondary aim was to evaluate the role of biomarkers to predict the unfavorable outcome and the chance of post thrombolysis hemorrhage and to evaluate the change of biomarker levels post thrombolysis.
The patient characteristics, comorbid risk factors, and hospital investigations were assessed by Chi-square test for categorical variables and independent-samples t test and one way analysis of variance for continuous variables. The variables analyzed were age, gender, body mass index, life conditions, comorbidities, NIHSS at admission, vascular risk factors, therapy prior to stroke, addictions, pathophysiologic and metabolic factors. Multivariate logistic regression models estimated the impact of possible determinants of stroke severity at admission. Differences between groups and effect of patient characteristics on the clinical outcome were assessed using Chi-square test. Statistical tests were considered significant when the value was ≤ 0.05. Statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS) 20.0 software version.
Out of 30 patients admitted with first ischemic stroke, 15 patients arrived at the hospital within 4.5 h. Out of them, 2 patients had NIHSS score > 25, 2 patients had stroke involving > 1/3 cerebral hemisphere, and 1 patient was taking oral anticoagulants for dilated cardiomyopathy - hence they did not receive thrombolysis. The rest 10 patients were thrombolysed with injection alteplase. The mean time (standard deviation or SD) of presentation of patients who were thrombolysed was 3.8 (0.7) and 7.8 (2.4) h for the remaining patients. Twelve patients had a mild stroke, 10 had a moderate stroke and 8 had a severe stroke. Fourteen patients had mRS score < 2, and 16 had mRS score ≥ 2, among whom 5 patients expired. Three out of ten thrombolysed patients developed intracerebral hemorrhage, among whom 1 patient expired. During admission, all the cases of AF were already diagnosed and were on anticoagulants as per the current guidelines. The results have been described in Tables 1-6.
Patient characteristics at time of initial stroke
|Characteristics||Mild stroke (n = 12)||Moderate stroke (n = 10)||Severe stroke (n = 8)||P value|
|BMI (kg/m2)||25.3 (0.3)||26.5 (0.5)||26.9 (0.8)||0.045|
|Age||58.2 (6.2)||62.4 (10.8)||66.3 (6.3)||0.01|
|Lives with family||10||9||5|
|Vascular risk factors|
|Ischemic heart disease||1||1||2||0.53|
|Low EF (< 35%)||1||2||3||0.25|
|MABP at admission||105.4 (8.8)||112 (9.2)||116 (7.8)||0.013|
|CBG at admission||152.1 (8.2)||163.7 (11.8)||181.4 (10.1)||< 0.0001|
Results of multivariate logistic regression analysis model for probability of unfavorable outcome (mRS score ≥ 2)
|Characteristics||mRS score ≥ 2 (n = 16)||OR (95% CI)||RR (95% CI)||P value|
|Female sex (n = 14)||11||0.1636 (0.03-0.83)||0.47 (0.23-0.95)||0.032|
|Hypertension||15||6 (0.58-61.8)||1.3 (0.92-1.8)||0.15|
|Hypercholesterolemia||12||1.2 (0.23-6.0)||1.05 (0.67-1.6)||1.0|
|Diabetes||10||1.25 (0.2-5.4)||1.09 (0.6-1.97)||1.0|
|Previous TIA||4||4.33 (0.4-44.4)||3.5 (0.44-27.7)||0.33|
|Current smoking||9||4.7 (0.9-23.6)||2.6 (0.88-7.8)||0.07|
|Ischemic heart disease||0.85 (0.1-7.4)||0.87 (0.14-5.4)||1.0|
|AF||4||4.33 (0.4-44.4)||3.5 (0.44-27.7||0.33|
|Low EF (< 35%)||6||0.018|
|CHADS2 score ≥ 2||13||10.83 (1.9-59.8)||2.84 (1.2-6.7)||0.008|
|PACS||3||0.84 (1.4-5.07)||0.87 (0.2-3.65)||1|
|PCS||6||3.6 (0.59-21.9)||2.6 (0.62-10.9)||0.22|
|LS||2||0.14 (0.02-0.8)||0.25 (0.06-1.01)||0.045|
Results of multivariate logistic regression analysis model for probability of mortality
|Characteristics||Mortality (n = 5)||OR (95% CI)||RR (95% CI)||P value|
|Female sex (n = 14)||3||1.9 (0.27-13.49)||1.7 (0.33-8.83)||0.64|
|Hypertension||4||0.76 (0.06-8.7)||0.8 (0.11-5.7)||1.0|
|Hypercholesterolemia||4||1.55 (0.14-16.4)||1.45 (0.18-11.14)||1.0|
|Diabetes||3||1.55 (0.14-16.4)||1.45 (0.18-11.14)||1.0|
|Previous TIA||3||17.25 (1.72-172.02)||7.5 (1.65-33.94)||0.02|
|Current smoking||2||1 (0.14-7.69)||1 (0.19-5.12)||1|
|Ischemic heart disease||2||7.66 (0.76-76.45)||5 (0.9-27.06)||0.118|
|AF||2||4.88 (0.96-42.3)||3.33 (0.73-15.08)||0.18|
|Low EF (< 35%)||3||7.33 (1.27-95.18)||4.16 (1.1-15.7)||0.041|
|CHADS2 score ≥ 2||4||3.69 (0.36-37.85)||1.53 (0.86-2.74)||0.35|
|TACS||4||29.33 (2.4-357.86)||6.66 (2.11-21.02)||0.0057|
|PACS||1||1 (0.09-11.02)||1 (1.39-6.8)||1|
|PCS||3||6 (0.78-46.14)||3 (1.03-8.67)||0.1|
Mean (SD) levels of biomarkers at admission among different groups of stroke patients
|Biomarker||Mild stroke |
(n = 12)
|Moderate stroke (n = 10)||Severe stroke|
(n = 8)
|P value||mRS score < 2|
(n = 14)
|mRS score ≥ 2|
(n = 16)
|CRP (mg/L)||4.7 (1.4)||5.7 (2.3)||6.9 (3.1)||0.043||5.6 (0.9)||6.9 (2.1)||0.040|
|Fibrinogen (mg/dL)||390.67 (20.25)||456.4 (40.50)||500.75 (37.86)||< 0.0001||430 (29.75)||478 (37.65)||0.0007|
|D-dimer (μg/mL)||4.7 (0.5)||6.4 (2.2)||8.8 (2.5)||< 0.0001||5.6 (1.4)||7.2 (2.5)||0.043|
|NSE (ng/mL)||24.5 (5.4)||37 (11.9)||56 (20.5)||< 0.0001||30.6 (6.8)||47 (16.87)||0.0021|
Comparison of final outcome and mean (SD) levels of the biomarkers 24 h after admission among thrombolysed vs. non-thrombolysed patients
|Characteristics||Thrombolysed (n = 10)||Non- thrombolysed (n = 20)||P value|
|mRS ≥ 2 (n = 16)||2 (20%)||14 (70%)||0.018|
|Death (n = 5)||1 (10%)||4 (20%)||0.64|
|CRP||5.32 (0.9)||5.87 (2.1)||0.43|
|Fibrinogen||420 (20.5)||479.2 (29.4)||< 0.0001|
|D-dimer||6.6 (3.0)||4.9 (2.0)||0.047|
|NSE||36.5 (14.6)||40.2 (16.8)||0.54|
Comparison of the baseline characteristics and biomarker levels at admission for patients developing hemorrhage (hge.) post thrombolysis
|Characteristics||Patients with hge. complications (n = 3)||Patients without hge. complications (n = 7)||P value|
|BMI (kg/m2)||26.5 (1.1)||26.8 (0.9)||0.66|
|Mean age (SD)||64 (10.8)||63 (8.2)||1.0|
|Vascular risk factors|
|MABP at admission||110.5 (4.2)||118.8 (4.8)||0.032|
|CBG at admission||251.4 (109.4)||143.2 (45.7)||0.048|
|Mean NIHSS at admission (SD)||10.4 (5.8)||20.2 (4.0)||0.0137|
|CRP (mg/L)||5.88 (0.24)||5.64 (0.32)||0.28|
|Fibrinogen (mg/dL)||478.5 (20.85)||421.4 (26.4)||0.01|
|D-dimer (μg/mL)||6.88 (1.4)||6.38 (1.7)||0.5|
|NSE (ng/mL)||42.1 (11.2)||30.8 (4.8)||0.07|
In this study on first-ever ischemic stroke patients, we demonstrated that risk factors such as old age, history of diabetes, CHADS2 score ≥ 2, and TACS independently affected stroke severity, whereas low EF < 35%, and TACS, independently predicted the unfavorable outcome (mRS score ≥ 2) and mortality. High mean arterial blood pressure (MABP) and capillary blood glucose (CBG) at admission were significant predictors for stroke severity, mRS score ≥ 2 and mortality. Female patients had significantly higher incidence of unfavorable outcome, but female gender was not a significant predictor of stroke severity and mortality. CHADS2 score significantly predicted the unfavorable outcome, but it was not a significant predictor when mortality was considered alone. Hypertension, hypercholesterolemia, smoking, ischemic heart disease, and AF showed a non-significant trend to be more prevalent among patients with severe stroke, unfavorable outcome and mortality. History of TIA was significantly associated with higher incidence of severe stroke and mortality. Home medications, living conditions, PACS and PCS did not significantly contribute to the severity and outcome of the stroke. However, patients of LS had a significantly lesser risk of having an unfavorable outcome. In the previous population-based studies, old age was found to be a strong independent predictor of ischemic stroke severity, outcome and mortality[7,15]. In Corso’s study, patients > 85 years of age had 2.9 times higher risk for having a severe stroke. In our study, out of 3 patients > 80 years of age, 2 had a severe stroke [odds ratio (OR) = 7 (0.53-91.11), P = 0.16]. Previous reviews reported that female gender has more severe strokes than men, with a 1-month case fatality of 24.7% vs. 19.7% for males. The case fatality rates were lower in our study - 21.4% among females and 12.5 % among males. In Corso's study, the female patients were older and suffered more frequently from AF; hence, females had a more severe stroke. Previous studies have reported that stroke patients with AF mostly present with large cortical infarcts, and less frequently with lacunar infarcts compared with patients without AF due to the lack of collateral vessels, which develop and compensate for acute arterial occlusion in patients with gradual occlusion of arteries, such as in atherosclerosis of cervical or cerebral arteries. Steger et al. reported that for AF patients with ischemic stroke, the in-hospital mortality was higher (25% vs. 14%, P < 0.0004) and neurological outcome was poorer (65 vs. 90 Barthel index, P < 0.0004). But in our study, multivariate analysis did not establish AF as an independent predictor of mortality. AF was non-significantly more frequent among patients with severe stroke, unfavorable outcome, and among those who expired. Ntaios et al. reported that compared with CHADS2 score 0, patients with CHADS2 score 1 and CHADS2 score > 1 had higher risks of ischemic stroke [hazard ratio 2.38 (95% CI: 1.41-4.00) and 2.72 (95% CI: 1.68-4.40), respectively] and death [hazard ratio 3.58; (95% CI: 1.80-7.12), and 5.45 (95% CI: 2.86-10.40) respectively]. In our study, CHADS2 score ≥ 2 significantly predicted stroke severity but did not predict mortality. Di Tullio et al. in their “Reduced Ejection Fraction Trial”, demonstrated that baseline left ventricular EF < 15% was inversely and linearly associated with the primary outcome, and mortality. Even in warfarin-treated patients, each 5% EF decrement significantly increased the stroke risk [adjusted hazard ratio 2.125 (95% CI: 1.182-3.818)]. In our study, EF < 35% [mean (SD) EF = 26.8 (5.8)] significantly predicted unfavorable outcome and mortality. Although Nedeltchev et al. and Musolino et al. reported current smoking, followed by hypercholesterolemia, family history of cerebrovascular disease, and hypertension to be the most prevalent risk factors among young ischemic stroke patients, these factors were non-significant predictors of stroke severity and outcome in our study. Osmani et al. reported that TACS had the worst outcome with the highest number of mortalities (72.2%). The LS had a better outcome, i.e. 65.7% of the patients were functionally independent by the end of 6 months compared to 15% of TACS patients. In our study, patients with TACS had a significantly higher incidence of severe stroke (57.14%), unfavorable outcome (100%) and mortality (57.14%). Huang et al. also described that TACS was associated with a poor functional outcome, but patients had a better outcome with LS. Medications use like statins, anticoagulants and antihypertensives did not affect stroke prognosis, similar to Corso’s study. Koton et al. described that systolic blood pressure (SBP) at admission was associated with stroke severity and disability at discharge or in-hospital death with an adjusted OR of 1.06 (95% CI: 1.04-1.08) per 10 mmHg change in SBP. In our study too, the higher MABP at admission was significantly associated with the stroke severity, the unfavorable outcome, and mortality. Bruno et al. described that in all strokes combined (P = 0.03) and in non-LSs (P = 0.02), higher admission blood glucose levels were associated with the worse outcomes at 3 months according to multivariate logistic regression analysis adjusted for stroke severity, diabetes mellitus, and other vascular risks, thereby, corroborating with our findings.
Our study demonstrated that thrombolysis significantly reduced the incidence of the unfavorable outcome, which is evidenced by the fact that only 20% of thrombolysed patients and 70% of non-thrombolysed patients had the unfavorable outcome. Mehta et al. reported 67.1% good outcome and 32.9% unfavorable outcome post thrombolysis; diabetes, dyslipidemia, NIHSS at admission > 15, blood sugar > 250 mg/dL, dense cerebral artery sign and occlusion of large artery being significant predictors of the poor outcomes on multivariate analysis. Liu et al. reported that age ≥ 70 years, NIHSS score > 20, serum glucose on admission > 9.0 mmol/L and cardioembolism were independent predictors of hemorrhage after thrombolysis in Chinese patients with acute ischemic stroke. Thirty percent patients in our study had post-thrombolysis hemorrhage. Blood glucose, MABP, higher mean NIHSS score and serum fibrinogen level at admission correlated significantly with post-thrombolysis hemorrhage. Higher NIHSS score increases the risk of hemorrhages since severe ischemic stroke is reflected by large areas of injured brain tissue, including injured blood vessels, which are prone to bleeding after rtPA treatment.
Our study demonstrated that the mean values of all the 4 biomarkers-CRP, fibrinogen, D-dimer, and NSE were significantly higher among patients with severe stroke. Fibrinogen level decreased and D-dimer level increased significantly following thrombolysis. Fibrinogen was the only biomarker, whose elevated levels could significantly predict post-thrombolysis hemorrhage. Results of a meta-analysis indicated a significant association between the elevated baseline CRP and unfavorable long-term functional outcome. Although our study is based on the CRP values at admission, interestingly, two studies of the meta-analysis[32,33] showed a stronger association of poor outcome with hs-CRP measurements at 24-48 h and 7 days reflecting impairment of the recovery process due to prolonged inflammation after ischemic stroke.
Rothwell et al. described that fibrinogen predicted ischemic stroke, with the association tending to be stronger in patients with nonlacunar than lacunar syndromes. Moreover, fibrinogen levels were found to be an independent predictor of early neurological deterioration among diabetic patients. The Alteplase-Tenecteplase Trial Evaluation for Stroke Thrombolysis study demonstrated that alteplase was associated with prolongation of prothrombin time, reduced fibrinogen and plasminogen, elevated fibrin degradation products and d-dimer level. Following ischemic stroke, tissue responds with mitochondrial dysfunction and increased nitric oxide (NO) production which vasodilates and maintains blood perfusion. In turn this leads to a burst in free radical production and the generation of peroxynitrite, which irreversibly nitrates proteins. Fibrinogen’s up-regulation as an acute-phase reactive protein and increased permeability of the blood-brain barrier during ischemic stroke allowing extravasation of different plasma proteins into the brain parenchyma further potentiates fibrinogen nitrotyrosination. At early stages nitro-fibrinogen delays clot formation, but in the long term, it becomes harmful due to the production of fibrinolysis resistant clots and the induction of neuronal damage. Hence, possibly more elevation in the fibrinogen level produces more cellular and local vascular damage, resulting in a higher chance of post-thrombolysis hemorrhage.
Previous studies demonstrated that acute ischemic stroke patients had significantly higher plasma median D-dimer levels as compared to healthy controls. D-dimer levels increased with increasing severity of stroke and infarct volume and the positive trends existed even after correcting for possible confounding factors. Thus, D-dimer concentrations may be considered a direct consequence of marked cerebral infarction. Although D-dimer levels are significantly associated with cardioembolic stroke, the significance of D-dimer levels in relation to the severity and functional outcomes of other stroke subtypes was investigated by Kim et al.. Patients with higher D-dimer levels had significantly worse initial functional outcomes, and these worse outcomes were maintained throughout the 9-month follow-up period compared with the low D-dimer group. However, regardless of stroke subtype, D-dimer levels did not influence long-term longitudinal temporal changes of functional outcomes over the 9-month follow-up period. In our study too, patients with significantly higher D-dimer levels at admission, had an unfavorable outcome.
In 2005, Anand and Stead described that serum NSE level was significantly higher in stroke patients than in controls, and correlated with infarct tissue volume, but did not correlate with the functional outcome. This was explained by the disparity in sampling time because the NSE level has been shown to peak after 4-8 h and hence, a better correlation was expected from delayed sampling. However, in 2013, Zaheer et al. found that NSE level in day 1 positively correlated with infarct volume and functional neurological outcome at day 30 and negatively correlated with Glasgow Coma Score at presentation. In our study, the mean (SD) time of presentation of the patients who underwent thrombolysis was 3.8 (0.7) h, and they also had elevated serum NSE levels. This signifies the requirement of more multicentre research with a larger sample size to determine the optimum time needed for NSE level to elevate in serum following an acute ischemic stroke.
Small sample size confounded the results of factors predicting the severity and outcome of stroke and resulted in wider CI. Even important risk factors like hypertension, hypercholesterolemia, smoking, and AF could not be established as significant predictors. The short follow up time of 1 month, hindered the evaluation of the long-term neuro-disabilities. The computed tomography machine at our institution does not have the software to determine the infarct volume and so the correlation of the levels of the biomarkers with the volume of infarcted tissue could not be done.
What this study adds: (1) EF between 15%-35% also independently predicts severity and the outcome of ischemic stroke; (2) MABP and CBG at admission significantly predict severity and outcome of ischemic stroke, and meticulous management of these factors may improve the outcome; (3) serum NSE level can rise earlier than 4 h - this fact needs to be validated by other larger studies; (4) fibrinogen level > 478.5 mg/dL at admission significantly predicts the higher chance of post-thrombolysis haemorrhage; and (5) there is no significant difference in the efficacy of intravenous thrombolysis on stroke in various arterial territories.
Provided intellectual inputs: Ghosh KC, Bhattacharya R, Mondal GP
Collected data: Ghosh S, Das S, Mahata M
Prepared the manuscript and acted for correspondence: Das SAvailability of data and materials
The data and material could be available to readers upon request.Financial support and sponsorship
None.Conflicts of interest
All authors declare that there are no conflicts of interest.Ethical approval and consent to participate
The study was approved by Institutional Ethicals Committee, Calcutta National Medical College, Kolkata and consent was obtained from the patients.Consent for publication
© The Author(s) 2018.
1. Pandian JD, Sudhan P. Stroke epidemiology and stroke care services in India. J Stroke 2013;15:128-34.DOIPubMedPMC
2. Gourie-Devi M. Epidemiology of neurological disorders in India: review of background, prevalence and incidence of epilepsy, stroke, Parkinson's disease and tremors. Neurol India 2014;62:588-98.DOIPubMed
3. Dalal PM, Malik S, Bhattacharjee M, Trivedi ND, Vairale J, Bhat P, Deshmukh S, Khandelwal K, Mathur VD. Population-based stroke survey in Mumbai, India: incidence and 28-day case fatality. Neuroepidemiology 2008;31:254-61.DOIPubMed
4. Sridharan SE, Unnikrishnan JP, Sukumaran S, Sylaja PN, Nayak SD, Sarma PS, Radhakrishnan K. Incidence, types, risk factors, and outcome of stroke in a developing country: the Trivandrum Stroke Registry. Stroke 2009;40:1212-8.DOIPubMed
5. Das SK, Banerjee TK, Biswas A, Roy T, Raut DK, Mukherjee CS, Chaudhuri A, Hazra A, Roy J. A prospective community-based study of stroke in Kolkata, India. Stroke 2007;38:906-10.DOIPubMed
6. Pandian JD, Bhullar RS, Kaur P, Dhillon S, Toor G, Singh Y. Trends in the use of intravenous recombinant tissue plasminogen activator from northwest India. Int J Stroke 2012;7:363-4.DOIPubMed
7. Corso G, Bottacchi E, Tosi P, Caligiana L, Lia C, Veronese Morosini M, Dalmasso P. Outcome predictors in first-ever ischemic stroke patients: a population-based study. Int Sch Res Notices 2014;2014:904647.
8. Jickling GC, Sharp FR. Biomarker panels in ischemic stroke. Stroke 2015;46:915-20.DOIPubMedPMC
9. Maas MB, Furie KL. Molecular biomarkers in stroke diagnosis and prognosis. Biomark Med 2009;3:363-83.DOIPubMedPMC
10. Jickling GC, Sharp FR. Blood biomarkers of ischemic stroke. Neurotherapeutics 2011;8:349-60.DOIPubMedPMC
11. Stroke--1989. Recommendations on stroke prevention, diagnosis, and therapy. Report of the WHO task force on stroke and other cerebrovascular disorders. Stroke 1989;20:1407-31.DOIPubMed
12. Brott T, Marler JR, Olinger CP, Adams HP Jr, Tomsick T, Barsan WG, Biller J, Eberle R, Hertzberg V, Walker M. Measurements of acute cerebral infarction: lesion size by computed tomography. Stroke 1989;20:871-5.DOIPubMed
13. Bamford J, Sandercock P, Dennis M, Burn J, Warlow C. Classification and natural history of clinically identifiable subtypes of cerebral infarction. Lancet 1991;337:1521-6.DOI
14. European Stroke Organisation (ESO) Executive Committee, ESO Writing Committee. Guidelines for management of ischaemic stroke and transient ischaemic attack 2008. Cerebrovasc Dis 2008;25:457-507.DOIPubMed
15. Kammersgaard LP, Olsen TS. Cardiovascular risk factors and 5-year mortality in the Copenhagen Stroke Study. Cerebrovasc Dis 2006;21:187-93.DOIPubMed
16. Appelros P, Stegmayr B, Terént A. Sex differences in stroke epidemiology: a systematic review. Stroke 2009;40:1082-90.DOIPubMed
17. Corso G, Bottacchi E, Giardini G, Di Giovanni M, Meloni T, Pesenti Campagnoni M, Veronese Morosini M. Epidemiology of stroke in northern Italy: the Cerebrovascular Aosta Registry, 2004-2008. Neurol Sci 2013;34:1071-81.DOIPubMedPMC
18. Appelros P, Nydevik I, Viitanen M. Poor outcome after first-ever stroke: predictors for death, dependency, and recurrent stroke within the first year. Stroke 2003;34:122-6.DOIPubMed
19. Steger C, Pratter A, Martinek-Bregel M, Avanzini M, Valentin A, Slany J, Stöllberger C. Stroke patients with atrial fibrillation have a worse prognosis than patients without: data from the Austrian Stroke registry. Eur Heart J 2004;25:1734-40.DOIPubMed
20. Ntaios G, Vemmos K, Lip GY, Koroboki E, Manios E, Vemmou A, Rodríguez-Campello A, Cuadrado-Godia E, Giralt-Steinhauer E, Arnao V, Caso V, Paciaroni M, Diez-Tejedor E, Fuentes B, Pérez Lucas J, Arauz A, Ameriso SF, Hawkes MA, Pertierra L, Gómez-Schneider M, Bandini F, Chavarria Cano B, Iglesias Mohedano AM, García Pastor A, Gil-Nú-ez A, Putaala J, Tatlisumak T, Barboza MA, Athanasakis G, Makaritsis K, Papavasileiou V. Risk stratification for recurrence and mortality in embolic stroke of undetermined source. Stroke 2016;47:2278-85.DOIPubMed
21. Di Tullio MR, Qian M, Thompson JL, Labovitz AJ, Mann DL, Sacco RL, Pullicino PM, Freudenberger RS, Teerlink JR, Graham S, Lip GY, Levin B, Mohr JP, Buchsbaum R, Estol CJ, Lok DJ, Ponikowski P, Anker SD, Homma S; WARCEF Investigators. Left ventricular ejection fraction and risk of stroke and cardiac events in heart failure: data from the warfarin versus aspirin in reduced ejection fraction trial. Stroke 2016;47:2031-7.DOIPubMedPMC
22. Nedeltchev K, der Maur TA, Georgiadis D, Arnold M, Caso V, Mattle HP, Schroth G, Remonda L, Sturzenegger M, Fischer U, Baumgartner RW. Ischaemic stroke in young adults: predictors of outcome and recurrence. J Neurol Neurosurg Psychiatry 2005;76:191-5.DOIPubMedPMC
23. Musolino R, La Spina P, Granata A, Gallitto G, Leggiadro N, Carerj S, Manganaro A, Tripodi F, Epifanio A, Gangemi S, Di Perri R. Ischaemic stroke in young people: a prospective and long-term follow-up study. Cerebrovasc Dis 2003;15:121-8.DOIPubMed
24. Osmani AH, Durrani RK, Ara J. Comparison of outcome in different types of stroke due to cerebral ischemia. J Coll Physicians Surg Pak 2010;20:42-6.PubMed
25. Huang WY, Weng WC, Chien YY, Wu CL, Peng TI, Chen KH. Predictive factors of outcome and stroke recurrence in patients with unilateral atherosclerosis-related internal carotid artery occlusion. Neurol India 2008;56:173-8.DOIPubMed
26. Koton S, Eizenberg Y, Tanne D, Grossman E. Trends in admission blood pressure and stroke outcome in patients with acute stroke and transient ischemic attack in a national acute stroke registry. J Hypertens 2016;34:316-22.DOIPubMed
27. Bruno A, Biller J, Adams HP Jr, Clarke WR, Woolson RF, Williams LS, Hansen MD. Acute blood glucose level and outcome from ischemic stroke. Trial of ORG 10172 in Acute Stroke Treatment (TOAST) Investigators. Neurology 1999;52:280-4.DOIPubMed
28. Mehta A, Mahale R, Buddaraju K, Majeed A, Sharma S, Javali M, Acharya P, Srinivasa R. Intravenous thrombolysis for acute ischemic stroke: review of 97 patients. J Neurosci Rural Pract 2017;8:38-43.DOIPubMedPMC
29. Liu M, Pan Y, Zhou L, Wang Y. Predictors of post-thrombolysis symptomatic intracranial hemorrhage in Chinese patients with acute ischemic stroke. PLoS One 2017;12:e0184646.DOIPubMedPMC
30. Emberson J, Lees KR, Lyden P, Blackwell L, Albers G, Bluhmki E, Brott T, Cohen G, Davis S, Donnan G, Grotta J, Howard G, Kaste M, Koga M, von Kummer R, Lansberg M, Lindley RI, Murray G, Olivot JM, Parsons M, Tilley B, Toni D, Toyoda K, Wahlgren N, Wardlaw J, Whiteley W, del Zoppo GJ, Baigent C, Sandercock P, Hacke W; Stroke Thrombolysis Trialists' Collaborative Group. Effect of treatment delay, age, and stroke severity on the effects of intravenous thrombolysis with alteplase for acute ischaemic stroke: a meta-analysis of individual patient data from randomised trials. Lancet 2014;384:1929-35.DOI
31. VanGilder RL, Davidov DM, Stinehart KR, Huber JD, Turner RC, Wilson KS, Haney E, Davis SM, Chantler PD, Theeke L, Rosen CL, Crocco TJ, Gutmann L, Barr TL. C-reactive protein and long-term ischemic stroke prognosis. J Clin Neurosci 2014;21:547-53.DOIPubMedPMC
32. Winbeck K, Poppert H, Etgen T, Conrad B, Sander D. Prognostic relevance of early serial C-reactive protein measurements after first ischemic stroke. Stroke 2002;33:2459-64.DOIPubMed
33. Song IU, Kim YD, Kim JS, Lee KS, Chung SW. Can high-sensitivity C-reactive protein and plasma homocysteine levels independently predict the prognosis of patients with functional disability after first-ever ischemic stroke? Eur Neurol 2010;64:304-10.DOIPubMed
34. Rothwell PM, Howard SC, Power DA, Gutnikov SA, Algra A, van Gijn J, Clark TG, Murphy MF, Warlow CP. Fibrinogen concentration and risk of ischemic stroke and acute coronary events in 5113 patients with transient ischemic attack and minor ischemic stroke. Stroke 2004;35:2300-5.DOIPubMed
35. Lee SJ, Hong JM, Lee SE, Kang DR, Ovbiagele B, Demchuk AM, Lee JS. Association of fibrinogen level with early neurological deterioration among acute ischemic stroke patients with diabetes. BMC Neurol 2017;17:101.DOIPubMedPMC
36. Huang X, Moreton FC, Kalladka D, Cheripelli BK, MacIsaac R, Tait RC, Muir KW. Coagulation and fibrinolytic activity of tenecteplase and alteplase in acute ischemic stroke. Stroke 2015;46:3543-6.DOIPubMed
37. Ill-Raga G, Palomer E, Ramos-Fernández E, Guix FX, Bosch-Morató M, Guivernau B, Tajes M, Valls-Comamala V, Jiménez-Conde J, Ois A, Pérez-Asensio F, Reyes-Navarro M, Caballo C, Gil-Gómez G, Lopez-Vilchez I, Galan AM, Alameda F, Escolar G, Opazo C, Planas AM, Roquer J, Valverde MA, Mu-oz FJ. Fibrinogen nitrotyrosination after ischemic stroke impairs thrombolysis and promotes neuronal death. Biochim Biophys Acta 2015;1852:421-8.DOIPubMed
38. Zi WJ, Shuai J. Plasma D-dimer levels are associated with stroke subtypes and infarction volume in patients with acute ischemic stroke. PLoS One 2014;9:e86465.DOIPubMedPMC
39. Kim TW, Song IU, Chung SW. Prognostic value of serum D-Dimer in noncardioembolic ischemic stroke. Can J Neurol Sci 2017;44:404-9.DOIPubMed
40. Anand N, Stead LG. Neuron-specific enolase as a marker for acute ischemic stroke: a systematic review. Cerebrovasc Dis 2005;20:213-9.DOIPubMed
41. Zaheer S, Beg M, Rizvi I, Islam N, Ullah E, Akhtar N. Correlation between serum neuron specific enolase and functional neurological outcome in patients of acute ischemic stroke. Ann Indian Acad Neurol 2013;16:504-8.DOIPubMedPMC
Eliot B. Blatt et al., Cancer Drug Resistance, 2019
Bologna, Italy; 23-25 Jul 2018; Published: 18 Apr 2019 et al., Journal of Cancer Metastasis and Treatment, 2019
Tiong Sun Chia et al., Hepatoma Research, 2019
Werner Krause et al., Cancer Drug Resistance, 2019
Jing-Yuan Cao et al., Journal of Translational Genetics and Genomics, 2019
Vladimir Zaichick et al., Journal of Cancer Metastasis and Treatment, 2018
Michael Fraser et al., Journal of Translational Genetics and Genomics, 2018
Kaina Chen et al., Hepatoma Research, 2018
Suebpong Tanasanvimon et al., Journal of Cancer Metastasis and Treatment, 2018
Georgios Zacharakis et al., Hepatoma Research, 2018