Mittal and Goel: Predictors of <strong>stroke</strong> mortality Table 2: Contd... Sum of squares df Mean square F Significance (P ) K Between Groups 3.001 1 3.001 7.115 0.008 With <strong>in</strong> Groups 78.014 185 0.422 Total 81.015 186 Table 3: Parameters selected for scor<strong>in</strong>g system SN Parameters Score 1 for each Score 2 for each Score 3 for each 1 NIHSS 0-5 6-14 >15 2 mRS 0-2 3-4 5 3 GCS 13-15 9-12 3-8 4 Random glucose at admissiom 200 5 HS-CRP 15 M<strong>in</strong>imum to Maximum <strong>score</strong> 5 10 15 Table 4: Distribution of all patients accord<strong>in</strong>g to various scales Score Number of patients Deaths 5-6 0 0 7-8 20 0 9-10 82 0 11-12 37 5 (13.5%) 13 26 19 (73%) 14 18 18 (100%) 15 5 5 (100%) Table 5: P values of significant f<strong>in</strong>d<strong>in</strong>gs Factor P Onset to Presentat on Duration 0.006 NIHSS <strong>score</strong> at Admission 0.0001 MRS <strong>score</strong> at Admission 0.0001 GCS <strong>score</strong> at Admission 0.0001 RBS at Admission 0.0001 HS CRP at Admission 0.0001 propose a new system for predict<strong>in</strong>g <strong>in</strong>-hospital mortality of patients suffer<strong>in</strong>g from <strong>ischemic</strong> <strong>stroke</strong>, titled as <strong>Mortality</strong> <strong>in</strong> Ischemic Stroke “MIS” <strong>score</strong>. A <strong>score</strong> of 14 with worst <strong>in</strong> <strong>ischemic</strong> <strong>stroke</strong>. [15,16] In our study, 25% patients expired dur<strong>in</strong>g hospital admission after acute <strong>ischemic</strong> <strong>stroke</strong> that was higher as compared to Western data (Northern Manhattan Stroke Study, 2001, found a mortality of 5% at 1 month) but similar to another Indian study. In‐hospital mortality is related to <strong>stroke</strong> severity and related complications. [10,11] That is why three of our parameters <strong>in</strong> scor<strong>in</strong>g system were related to cl<strong>in</strong>ical severity ‐ NIHSS, mRS, and GCS ‐ that are directly l<strong>in</strong>ked to early deaths <strong>in</strong> <strong>ischemic</strong> <strong>stroke</strong>. NIHSS more than 15, mRS more than 3, and GCS
Mittal and Goel: Predictors of <strong>stroke</strong> mortality <strong>stroke</strong> society. Multivariable predictors of 30‐day and 1‐year mortality <strong>in</strong>cluded older age, male sex, severe <strong>stroke</strong>, nonlacunar <strong>stroke</strong> subtype, glucose ≥7.5 mmol/L (135 mg/dL), history of atrial fibrillation, coronary artery disease, congestive heart failure, cancer, dementia, kidney disease on dialysis, and dependency before the <strong>stroke</strong>. Based on these factors, a risk <strong>score</strong> <strong>in</strong>dex stratified the risk of death at 30 days and 1 year and identified low‐ and high‐risk <strong>in</strong>dividuals. [24] This system <strong>in</strong>cludes all parameters for short as well as long‐term mortality, so it is more extensive and therefore little lengthy for bedside utility and is more useful for long‐term mortality. The mortality <strong>in</strong> <strong>ischemic</strong> <strong>stroke</strong> <strong>score</strong> (MISS) system is applicable for prediction of <strong>in</strong>‐hospital mortality <strong>in</strong> <strong>stroke</strong> patients at presentation. It is short, simple, and easy to apply as it uses bedside cl<strong>in</strong>ical scales and simple <strong>in</strong>vestigations whose results are quickly available. The selected parameters for MISS are related to cl<strong>in</strong>ical severity of <strong>stroke</strong> and are helpful for early prediction of MIS. The radiological assessment of bra<strong>in</strong> parenchyma <strong>in</strong>volvement is not relied upon s<strong>in</strong>ce different recoveries with similar parenchyma <strong>in</strong>volvement have been noted. Besides size of the <strong>in</strong>farct may not accurately def<strong>in</strong>e, the severity as a small‐sized <strong>in</strong>farct <strong>in</strong> a crucial area may do more harm than a large <strong>in</strong>farct <strong>in</strong> a relatively less critical area. Conclusion Our MIS system can effectively predict the mortality <strong>in</strong> patients with <strong>ischemic</strong> <strong>stroke</strong> at the time of presentation and thereby help physicians and neurologists predict the outcome of patients at the presentation to the hospital. F<strong>in</strong>ancial support and sponsorship Nil. Conflicts of <strong>in</strong>terest There are no conflicts of <strong>in</strong>terest. References 1. Jencks SF, Daley J, Draper D, Thomas N, Lenhart G, Walker J. Interpret<strong>in</strong>g hospital mortality data. The role of cl<strong>in</strong>ical risk adjustment. JAMA 1988;260:3611‐6. 2. 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Circulation 2011;123:739‐49. 34 Bra<strong>in</strong> Circulation - Volume 3, Issue 1, January-March 2017