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| ORIGINAL ARTICLE |
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| Year : 2022 | Volume
: 11
| Issue : 4 | Page : 314-322 |
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A single-center hospital-based prospective study to assess the predictive factors for stoke severity during admission
Mukhesh Lanka Gowtam1, Aravinda Mandalapu1, Sampath Kumar Natuva Sai2, Sunanda Tirupathe3, Madhumitha Rondla4, Sai Sushrutha Mudupulavemula4, Sai Sanjana Natuva4, Ramalingam Krishnan5
1 Department of Neurology, Narayana Medical College, Nellore, Andhra Pradesh, India
2 Research Scholar (PhD), Lincoln University, Malaysia; Department of Neurology, Narayana Medical College and Hospital, Nellore, Andhra Pradesh, India
3 Department of Endocrinology, Narayana Medical College and Hospital, Nellore, Andhra Pradesh, India
4 Department of Neurology, Narayana Medical College and Hospital, Nellore, Andhra Pradesh, India
5 Department of Biochemistry, Narayana Medical College and Hospital, Nellore, Andhra Pradesh, India
| Date of Submission | 01-Feb-2022 |
| Date of Decision | 01-Mar-2022 |
| Date of Acceptance | 11-Mar-2022 |
| Date of Web Publication | 17-Mar-2023 |
Correspondence Address:
Prof. Sampath Kumar Natuva Sai
Department of Neurology, Narayana Medical College, Chintareddypalem, Nellore-3, Andhra Pradesh - 524 003
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jdrntruhs.jdrntruhs_16_22
Background and Objective: Stroke is the most common cause of death and the leading cause of disability worldwide. We aimed to study predictive factors of stroke severity which determine stroke mortality and morbidity.
Methods: It is a prospective observational study to analyze predictors of stroke severity in 653 acute stroke patients performed over a period of 18 months.
Results: The mean age of stroke was 61.66 years, with males being 317 (48.55%). Stroke severity was significantly associated with parameters such as age, gender, education and economic state, awareness of vascular risk factors, risk factors including family history of coronary artery disease/stroke, alcohol intake, symptom timeline including the first evaluated area and time duration between the last known normal and hospital arrival, with respect to symptoms at presentation, including headache, speech difficulty, and dysphagia, examination findings including respiratory rate, Glasgow Coma Scale (GCS) grade, and higher mental function, with respect to laboratory parameters, including total leukocyte count, neutrophil to lymphocyte ratio, and creatinine, and radiological parameters including Doppler findings.
Conclusion: The study has shown that old age, male gender, an increased time duration between the last known normal and hospital arrival, lack of awareness of risk factors, and alcohol consumption for a duration of more than 1 year were independent predictors of increased stroke severity at admission. Headache, dysphagia, low GCS, sub-normal higher mental functions, an abnormal respiratory rate, abnormal Doppler findings, an increased total leukocyte count, and creatinine were independent predictors of stroke severity at admission.
Keywords: Clinical, demographic, NIHSS, predictors, severity, stroke
How to cite this article:
Gowtam ML, Mandalapu A, Natuva Sai SK, Tirupathe S, Rondla M, Mudupulavemula SS, Natuva SS, Krishnan R. A single-center hospital-based prospective study to assess the predictive factors for stoke severity during admission. J NTR Univ Health Sci 2022;11:314-22 |
How to cite this URL:
Gowtam ML, Mandalapu A, Natuva Sai SK, Tirupathe S, Rondla M, Mudupulavemula SS, Natuva SS, Krishnan R. A single-center hospital-based prospective study to assess the predictive factors for stoke severity during admission. J NTR Univ Health Sci [serial online] 2022 [cited 2023 Apr 1];11:314-22. Available from: https://www.jdrntruhs.org/text.asp?2022/11/4/314/371752 |
| Introduction | |  |
The most common clinical manifestation of cerebrovascular disease which represents one of the clinical end points of atherosclerosis is stroke. It is the disease of the cerebral blood vessels nourishing the brain. World Health Organization (WHO) defines stroke as an event caused by the interruption of the blood supply to the brain, usually because a blood vessel bursts or is blocked by a clot. Stroke is a global health problem. It is the second most common cause of death and the fourth leading cause of disability worldwide.[1] More than 80% of deaths because of stroke occur in the low- and middle-income countries.[2] The incidence of stroke increases with increasing age.[3] Population-based studies have shown that in India, the annual incidence and prevalence rates of stroke are 119–145 and 84–262 in rural and 334–424 in urban areas per 100,000 population, respectively.[4]
Stroke is responsible for 3 million deaths and is rising in developing countries,[5] and it is a major cause of mortality and morbidity in Asian countries. Stroke causes >160,000 deaths annually in the United States. In the United States, annually incident strokes are >7 lakhs. Stroke is emerging as a major public health problem in India as population-based studies have shown an annual incidence and prevalence rate of 145 and 545 per 100,000 population, respectively. These results are in contrast to data reported from western countries.[6]
The burden of stroke in Asia is predicted to increase both in absolute terms and as a proportion of total disease burden because of rapid population aging and lifestyle changes (Taqui and Kamal, 2007).[7]
The treatment of stroke is a dynamic process, in which time is the most critical factor impacting the appropriate performance of the interventions held for acute stroke and determining the patient's final prognosis.[8] Many patients do not receive treatment because of the delay in the presentation to the hospital, which results in exceeding the time point at which the treatment is efficacious.
To determine the predictors is of paramount importance for clinicians to identify patients who are at higher risk for more severe strokes and death. The present study was designed to study the epidemiologic, clinical, laboratory, and radiologic factors that predict severity of stroke at admission. In the future, treatments should take into account the effect of these independent predictors of increased severity at admission.
| Materials and Methods | | |
The present study was performed at the Department of Neurology, Narayana Medical College, Nellore, for a period of 18 months from December 2018 to May 2020. The current study was a prospective cross-sectional hospital-based study and was approved by the Institute Ethics Committee. The study was performed on 653 patients with acute stroke of out-patients and in-patients of neurology and emergency departments.
A proforma was prepared, which included detailed history, clinical examination, details of management in hospital, and requisite investigations available at Narayana Hospital.
The history noted from the patient or bystanders (if the patient is unable to interact because of the illness per se) included the demographic data, past medical history, awareness of the risk factors and management details of stroke, and the symptom timeline. A detailed clinical examination was performed, and neurological deficits were identified. Relevant investigations were performed, including laboratory and radiological investigations performed to identify the underlying patho-physiological mechanism and etiology. The stroke severity at admission was assessed based on the National Institute of Health Stroke Scale (NIHSS).[9]
As the stroke severity is assessed based on NIHSS (National Institute of health stroke scale) grading, it is mentioned in materials & methods.
Statistical analysis
The data values have been entered into MS – Excel, and statistical analysis has been performed by using IBM SPSS Version 25.0. For categorical variables, the values are represented as numbers and percentages. To test association between the groups, Chi-square test has been used. For continuous variables, the values are represented as mean and standard deviation. To test the mean difference between three or more groups, ANOVA (Analysis of Variance) test with post hoc (Tukey's) test has been used. All the P values less than 0.05 are considered as statistically significant. Multi-variate analysis has been performed using the logistic regression technique to identify the independent predictors among the studied variables for severity of stroke at admission.
| Results | | |
In this study, the total number of participants was 653, who were acute stroke patients enrolled. All the 653 patients with acute stroke were analyzed to identify the predictors for stroke severity at admission.
On analyzing the stroke severity at the admission of the study population, that is, 653 patients, 564 patients (i.e., 86.37%) had acute ischemic stroke, 79 patients (i.e., 12.09%) had a hemorrhagic stroke, and the remaining 10 patients (i.e., 1.53%) had cerebral venous thrombosis (CVT). The stroke severity among the study population was assessed by dividing the total patients based on the NIHSS score observed at admission. Of the 653 patients who were admitted with acute stroke, 174 patients (i.e., 26.6%) had a MILD NIHSS score, 275 patients (i.e., 42.11%) had a MODERATE NIHSS score, 49 patients (i.e., 7.50%) had a MODERATE TO SEVERE NIHSS score, and the remaining 155 patients (i.e., 23.73%) had a SEVERE NIHSS score.
A total of 94 independent variables, which include epidemiological, clinical, and investigatory parameters, were assessed against stroke severity at admission by uni-variate analysis.
The epidemiological variables included were age, stroke in the young, sex, residence, education, marital status, employment, religion, economic state, awareness of vascular risk factors, stroke/coronary artery disease (CAD), thrombolytics, anti-platelets, physiotherapy, speech therapy, botox therapy, and the presence of risk factors for stroke such as the prior history of stroke, CAD, transient ischemic attack (TIA), family history of stroke/CAD, history of obesity, chronic kidney disease (CKD), dyslipidemia, hypertension, diabetes, migraine, hormone replacement therapy, alcohol intake, smoking, and symptom timeline including details of month- and season-wise incidence of stroke, time of onset, time of arrival to the hospital, time of admission, duration between the last known normal and symptom onset, duration between the last known normal and hospital arrival, duration from ictus to the first medical contact, and basic admission details including the first evaluated area, ambulatory status at ictus, delay of more than 4.5 hours (door to needle time), the first contact with the medical professional, mode of transport to the first medical professional, and mode of transport to the registry hospital.
As illustrated in [Table 1] and [Table 2]; there was a significant difference between participants who had mild, moderate, moderate to severe, and severe NIHSS scores at admission assessing stroke severity with respect to demographic parameters including age, gender, education and economic state, awareness of vascular risk factors, risk factors including family history of CAD/stroke, alcohol intake, symptom timeline including the first evaluated area, and time duration between the last known normal and hospital arrival. | Table 1: Uni-Variate Analysis of Epidemiological Parameters (Categorical Variables) with Statistical Significance for Stroke Severity At Admission
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 | Table 2: Uni-Variate Analysis of Epidemiological Parameters (Continuous Variables) with Statistical Significance for Stroke Severity
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The clinical profile was composed of symptoms at admission including headache, vomiting, giddiness, double vision, blurring of vision, weakness, altered levels of consciousness, seizures, difficulty in speech, difficulty in swallowing, drooping of the upper eyelid, deviation of the mouth, unsteadiness of the gait, tingling and paresthesias, pain over half of the body, dysphagia, hoarseness of voice, symptom evolution, and examination findings at admission including pallor, blood pressure, heart rate, temperature, respiratory rate, Glasgow Coma Scale (GCS) grading, NIHSS at admission, higher mental functions, dysarthria, aphasia, sensory abnormalities, cerebellar system abnormalities, and an abnormal gait. The investigatory profile included carotid Doppler, 2D echocardiography, blood sugars at admission, hemoglobin, total leukocyte count, platelet count, neutrophil to lymphocyte ratio (NL ratio), total cholesterol, tri-glycerides, high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), creatinine, serum sodium, potassium, random glucose, fasting glucose, post-prandial glucose, and glycosylated hemoglobin (HbA1C).
As illustrated in [Table 3], there was a significant difference between participants who had mild, moderate, moderate to severe, and severe NIHSS scores at admission assessing stroke severity with respect to symptoms at presentation, including headache, speech difficulty and dysphagia, and examination findings including respiratory rate, GCS, and higher mental functions. | Table 3: Uni-Variate Analysis of Clinico-Investigatory Profiles (Categorical Variables) with Statistical Significance for Stroke Severity
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As illustrated in [Table 3], there was a significant difference between participants who had mild, moderate, moderate to severe, and severe NIHSS scores at admission assessing stroke severity with respect to laboratory parameters, including total count, neutrophil to lymphocyte ratio, and creatinine, and radiological parameters including Doppler findings.
As illustrated in [Table 4], by multi-variate analysis, older age, male sex, lack of awareness of vascular risk factors, alcohol intake for more than 1 year of duration, prolonged time duration between the last known normal and hospital arrival, symptoms at presentation including headache and dysphagia, examination findings including an abnormal respiratory rate, severe GCS grade, and abnormal higher mental functions, and investigatory profiles including abnormal Doppler findings, an elevated total leukocyte count, and an abnormal creatinine level were independent predictors of increased stroke severity at admission as illustrated in [Table 4], all the above mentioned variables showed significant p value <0.05. | Table 4: Multi-Variate Analysis of All Significant Variables for Stroke Severity with Statistical Significance
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| Discussion | | |
The present study is an observational study conducted in a tertiary care teaching hospital. In the present study, all the patients with acute stroke who satisfied all the inclusion and exclusion criteria and admitted to the Department of Neurology were analyzed to identify the predictive factors for severity of stroke based on the NIHSS score at admission. From multi-variate analysis, old age, male gender, increased time duration between the last known normal and hospital arrival, lack of awareness of vascular risk factors, and alcohol consumption for a duration more than 1 year were independent predictors of increased stroke severity at admission. Similarly, headache, feeding difficulty (nasal regurgitation) as presentation symptoms, low GCS, abnormal higher mental functions, and an abnormal respiratory rate on examination were significant predictors of increased stroke severity at admission. Investigatory parameters including abnormal Doppler findings, an increased total leukocyte count, and creatinine were independent predictors of increased stroke severity at admission from multi-variate analysis.
Older age was independently associated with increased stroke severity, consistent with Ghosh et al.,[10] where old age independently affected stroke severity in patients with the first episode of ischemic stroke. There is an increased risk of frailty and multiple comorbidities in people aged over 80, and they are also more likely to have a severe stroke, which makes their management more complex.[11] There is little evidence of whether treatments are as effective for those under 80 years of age as they were because the very old are often excluded from clinical trials.[12] In Appelros et al.,[13] age showed a significant association for stroke severity in the uni-variate analysis. In P. Santalucia et al.,[14] multi-variate linear regression analysis revealed that age was significantly associated with greater stroke severity at hospital admission.
Male sex was independently associated with increased stroke severity, which may be because of increased risk factors such as cigarette smoking and alcohol consumption among males. The absence of vascular protection of endogenous estrogens in males can be an additional factor. These findings were contrary to P. Santalucia et al.,[14] where stroke severity and functional outcome were worse in women. This may be because of the high use of contraception, pregnancy-related conditions, and migraine-causing stroke among females in these studies. In Khadija Sonda Moalla et al.,[15] male sex was a poor prognostic factor for stroke after 1 month of follow-up.
Lack of awareness of vascular risk factors was independently associated with increased stroke severity. This could be because of an extension in the timeframe between the onset of symptoms and the arrival at the hospital, with one of the main reasons being a lack of knowledge regarding the warning signs and risk factors associated with stroke. Lack of awareness of vascular risk factors also hinders the primordial and primary prevention of stroke, causing increased stroke incidence and stroke severity. In Raúl Soto-Cámara et al.,[16] it was seen that having a higher education level or a history of prior stroke was associated with a greater degree of knowledge of warning signs.
Delay in time between the last known normal and hospital arrival was independently associated with increased stroke severity. It could be because severe stroke may render patients unable to apply for help. The delay in presentation to the hospital results in exceeding the time point at which the treatment is efficacious. Besides, delay causes a further continuation of the ongoing cascade of neuronal cell injury with proceeding perilesional edema, which mounts to severe neuronal injury and more severe neurological impairment. Furthermore, delay in presentation results in delay in treating the precipitating factors, which further worsens the neurological deficits (severity) and thereby the outcome. In Kothari et al.[17] and Zweifler RM et al.,[18] it was noted that longer pre-hospital delays might be associated with the severity of stroke, which is consistent with our study.
History of alcohol consumption was independently associated with increased stroke severity. Ducroquet et al.[19] found that a chronic ethanol consumption of ≥300 g per week is independently associated with higher severity of the neurological deficit. It is noted that heavy alcohol intake is associated with impaired fibrinolysis, increased platelet activation, and an increase in blood pressure and heart rate, thus increasing the risk of stroke.
Headache was found to be an independent factor predicting increased stroke severity. It could be as a result of bi-lateral hemispheric stroke or uni-lateral massive/malignant stroke, in turn leading to increased intra-cranial pressure causing predominantly headache as the presenting feature. In Pollak et al.,[20] the incidence of headache was higher in patients with intra-cerebral hemorrhage (ICH) than in patients with ischemic stroke (IS) regardless of the history of previous headaches.
Dysphagia was independently associated with increased stroke severity. Multiple areas of the brain, notably the brainstem, thalamus, basal ganglia, cerebellum, and motor and sensory cortices, are concerned with the control of spontaneous and involuntary swallowing.[21] Disorders or lesions affecting these areas could lead to abnormal lip closure, in-coordination, delayed or absent triggering of the swallowing reflexes, and subsequently disturbances of both oral and pharyngeal stages of swallowing, which may manifest as incomplete oral clearance, pharyngeal pooling, regurgitation, and aspiration of feeds or secretion.[22] In Abubakar and Jamoh: Dysphagia and stroke outcome,[23] the mean NIHSS score of patients with dysphagia was significantly higher than those without dysphagia. In Otto DM et al.,[24] an association between stroke severity and oropharyngeal dysphagia severity was observed. Stroke severity may be more frequently associated with dysphagia during the acute phase, leading to aspiration pneumonia and further worsening of the stroke outcome.[25]
Severe grade of GCS was independently associated with increased stroke severity. Fluctuations in GCS scores are inversely associated with fluctuations in cerebral oximetry index; as the cerebral oximetry index increases (impaired cerebral auto-regulation), more severe neurological impairment results (severity increases).[26]
Abnormal higher mental function at admission was independently associated with increased stroke severity. Both the number and type of higher cortical function deficits (HCFD) in acute stroke patients are substantial diagnostically and for gauging the extent of neurological deficits.[27]
Abnormal respiratory rate was independently associated with increased stroke severity. Cerebrovascular events (CVEs) are a major cause of morbidity and mortality worldwide. Most patients with CVE do not develop significant respiratory problems, but they may be markers of severe neurologic derangement when present. The regulatory centers for automatic respiration are located in the lower pons and medulla. These centers are constantly influenced by other complex neurogenic as well as metabolic control mechanisms. Thus, the presence of pathological lesions involving these centers may be expected to result in changes in respiratory functions as reflected by alteration of rates and patterns. Bi-lateral hemispheric dysfunction has been typically associated with Cheyne–Stokes respiration,[28] a periodic breathing pattern characterized by progressive hyperpnea, followed by hypopnea and apnea. Cheyne–Stokes respiration is frequently described in patients with hemispheric CVE. In patients with bi-lateral hemispheric lesions, an increased response to carbon dioxide, presumably because of loss of the normal cortical inhibition, has been described.[29] Cheyne–Stokes respiration is typically present in stroke patients with a reduced level of consciousness in the transition from wakefulness to sleep (drowsiness) and the first two stages of non-rapid eye movement sleep. Cheyne–Stokes respiration with hypocapnia has been associated with high mortality.[30],[31] Finally, increased intra-cranial pressure leading to transtentorial herniation produces a typical rostrocaudal deterioration in which normal breathing is replaced with Cheyne–Stokes respiration, followed by neurogenic hyper-ventilation and subsequently ataxic respiration that precedes apnea.[32]
Abnormal findings in the carotid vertebral Doppler study were independently associated with increased severity of stroke. Out of the three major Doppler parameters, peak systolic velocity (PSV), end diastolic velocity (EDV), or PSV ratio, PSV ratio is the most accurate predictor of clinically significant internal carotid artery (ICA) stenosis determining stroke severity as the ratio compensates for a patient to patient physiological variability and instrumental variability. Besides estimating the degree of stenosis, the biggest advantage of sonography is its ability to characterize plaque and identify plaques with a higher risk of embolization. The duplex imaging of complete carotid occlusion was based on the absence of arterial pulsation, lumen filled with an echogenic material, a sub-normal vessel size, and the absence of Doppler flow signals or weak Doppler signals.[33] In Sobrino-Garcia P et al.,[34] arterial occlusion was associated with higher severity of stroke.
Elevated total count was independently associated with increased stroke severity. This can be a direct effect of white cell activity and inflammation in the lesioned brain or whether it is instead a marker of associated conditions (e.g., fever, early infection, or stress response) that may increase stroke severity and worsen outcomes. More severe clinical presentation and worse early stroke outcome have been associated with white cell count.[35] White blood cell count is a crucial component of the severity assessment scores, including APACHE and SAPS.[36],[37]
High serum creatinine was independently associated with increased stroke severity. Kidney disease is associated with a greater neurological deficit following ischemic stroke, a poor functional outcome, and greater mortality.[38] It has a unique impact on stroke risk by impairing cerebral auto-regulation, re-modeling the cerebral vasculature, and reducing cerebral blood flow.
| Conclusion (NO) | | |
Stroke is the second most common cause of death and the fourth leading cause of disability worldwide.[1] Stroke severity at initial presentation is a potential valuable predictor of outcome.[39] To determine the predictors is of paramount importance for clinicians to identify patients who are at higher risk for more severe strokes and death. The epidemiological variables including older age, male gender, lack of awareness of vascular risk factors of stroke, alcohol intake, and symptom timeline including prolonged duration between the last known normal and hospital arrival, the clinical profile of the acute stroke patients at admission including headache, dysphagia, abnormal respiratory rate, severe grade of GCS at admission, and abnormal higher mental functions at admission, and investigatory parameters including abnormal findings in carotid and vertebral doppler studies, elevated total counts on complete hemogram analysis, and increased creatinine on renal function assessment were independently associated with increased stroke severity at admission.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4]
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