Related Experiment Video
Updated: Feb 4, 2026

Optimized Management of Endovascular Treatment for Acute Ischemic Stroke
Published on: January 18, 2018
Mortality in ischemic stroke score: A predictive score of mortality for acute ischemic stroke
Saumya H Mittal1,2, Deepak Goel2
1Department of Neurology, KMC Hospital, Mangalore, Karnataka, India.
Insights
A new Mortality in Ischemic Stroke (MIS) score predicts in-hospital deaths. Factors like late presentation, fever, low blood pressure, hypoxia, and high NIHSS scores indicate higher mortality risk in stroke patients.
Area of Science:
- Neurology
- Clinical Medicine
- Biostatistics
Background:
- Acute ischemic stroke poses a significant threat to patient survival.
- Predicting in-hospital mortality is crucial for timely intervention and resource allocation.
Purpose of the Study:
- To develop and validate a predictive scoring system for in-hospital mortality in acute ischemic stroke patients.
- To identify key clinical and laboratory parameters associated with stroke mortality.
Main Methods:
- A prospective study included 188 ischemic stroke patients, excluding those with renal failure or malignancy.
- Clinical assessments included Glasgow Coma Scale (GCS), National Institute of Health Science scale (NIHSS), and modified Rankin score (mRS).
- Laboratory tests (TLC, blood sugar, HS-CRP) and investigations (ECG, neuroimaging) were performed. Statistical analysis identified independent predictors of mortality.
Main Results:
- Late presentation, pyrexia, low diastolic blood pressure, hypoxia, NIHSS score >15, mRS >3, GCS <8, hyperglycemia, elevated TLC, and HS-CRP >10 mg/L were identified as positive predictors of mortality.
- A simple and applicable Mortality in Ischemic Stroke (MIS) score was developed based on these factors.
- The MIS score aims to quantify the risk of in-hospital mortality in ischemic stroke patients.
Conclusions:
- The developed MIS score provides a valuable tool for clinicians to assess mortality risk in acute ischemic stroke.
- This score can aid in optimizing patient management and improving communication with patient families regarding prognosis.
Objective:
This prospective study was planned to formulate and evaluate a predictive score for in-hospital mortality in cases of acute ischemic stroke.
Materials And Methods:
In this study, 188 consecutive patients of ischemic stroke were included over 19 months. Only patients with renal failure and malignancy were excluded from the study. All patients were subjected to clinical evaluation along with Glasgow Coma Scale (GCS), National Institute of Health Science scale (NIHSS) score, and modified Rankin score (mRS). Investigations total leukocyte count (TLC), capillary blood sugar at admission, high-sensitivity C-reactive protein (HS-CRP), and troponin I, electrocardiogram, and neuroimaging were performed. The patients were followed up till their outcome in the hospital, and patients who expired were grouped as "mortality group" and the rest as "discharged group." One-way anova analysis was carried out among the significant parameters to identify independent predictors of mortality in cases of ischemic stroke.
Results:
After statistical analysis, it was found that late presentation to the hospital, pyrexia (temperature >99F), low diastolic blood pressure at the time of admission, hypoxia (saturation of oxygen <94%), NIHSS score >15, mRS >3, GCS <8, hyperglycemia (random blood sugar >200 mg/dL), raised TLC, and HS-CRP (>10 mg/L) are positive predictive factors of mortality in cases of ischemic stroke. Based on the above findings, a simple and easily applicable mortality in ischemic stroke (MIS) score is developed.
Conclusion:
This MIS score system will help the clinicians in better management of the patient and improved counseling the relatives of patients with ischemic stroke.
More Related Videos
Related Concept Videos
Introduction to z Scores
z scores...
Introduction to z Scores
z scores...
z Scores and Area Under the Curve
z Scores and Unusual Values
This score indicates how far a value is from the mean in terms of standard deviation. For example, if a data value has a z score of +1, the researcher can infer that the particular data value is one standard deviation above the mean. If another data...
Regulation of Stroke Volume
Preload refers to the degree of stretch on the heart before it contracts. It's analogous to the stretching of a rubber band; the more it's stretched, the more forcefully it snaps back. This concept is encapsulated in the Frank-Starling law of the...
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

