A novel risk score for predicting 6-months mortality at the time of hospital discharge in patients admitted with acute coronary syndrome

Background: In patients with ACS, risk assessment at hospital discharge has not received much consideration in prior risk scoring systems. Hence, there is a need for a reliable and simple tool to identify patients with high mortality risk at discharge form the hospital. Methods: In a 1-year observat...

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Main Authors: Anish John Padiyara, Rajneesh Kumar Calton
Format: Article
Language:English
Published: Elsevier 2021-03-01
Series:Indian Heart Journal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S0019483221000080
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spelling doaj-0497719e86474df88ce5592ab4bfe5872021-04-16T04:47:54ZengElsevierIndian Heart Journal0019-48322021-03-01732190195A novel risk score for predicting 6-months mortality at the time of hospital discharge in patients admitted with acute coronary syndromeAnish John Padiyara0Rajneesh Kumar Calton1Department of Cardiology, Christian Medical College &amp; Hospital, Ludhiana, Punjab, 141008, IndiaCorresponding author.; Department of Cardiology, Christian Medical College &amp; Hospital, Ludhiana, Punjab, 141008, IndiaBackground: In patients with ACS, risk assessment at hospital discharge has not received much consideration in prior risk scoring systems. Hence, there is a need for a reliable and simple tool to identify patients with high mortality risk at discharge form the hospital. Methods: In a 1-year observational, prospective study, 1012 patients admitted with ACS were followed up for 6 months after discharge. From 26 potential variables, a new risk score to predict 6-month mortality was developed. Results: A multi-variant Cox regression analysis with forward stepwise variable selection was performed and 10 highly significant independent predictors of 6-month mortality were identified. These include previous history of ACS, higher Killip class at admission, NYHA class at discharge, recurrent ischemia during hospital stay, heart failure, requiring ionotropic supports, requiring hemodialysis, presence of arrhythmia, left ventricular dysfunction detected on echocardiography and elevated admission blood glucose levels. Points were given to each variable and a total score was calculated. A risk score of 0–4 (low risk) predicted a mortality of 3.7%,a risk score of 5–15 (Intermediate risk) predicted a mortality of 16.4% and a risk score of 11–15 predicted a mortality of 32.0% over a 6-month period. The new risk score was noninferior to GRACE risk score in its predictive accuracy of 6-month mortality in the same cohort of patients (p < 0.05). Conclusion: The risk score developed in our study can be easily calculated at the bedside and is aimed at identifying high risk patients who require more intense follow up after discharge.http://www.sciencedirect.com/science/article/pii/S0019483221000080Acute coronary syndromeHospital dischargeRisk scoreMortality
collection DOAJ
language English
format Article
sources DOAJ
author Anish John Padiyara
Rajneesh Kumar Calton
spellingShingle Anish John Padiyara
Rajneesh Kumar Calton
A novel risk score for predicting 6-months mortality at the time of hospital discharge in patients admitted with acute coronary syndrome
Indian Heart Journal
Acute coronary syndrome
Hospital discharge
Risk score
Mortality
author_facet Anish John Padiyara
Rajneesh Kumar Calton
author_sort Anish John Padiyara
title A novel risk score for predicting 6-months mortality at the time of hospital discharge in patients admitted with acute coronary syndrome
title_short A novel risk score for predicting 6-months mortality at the time of hospital discharge in patients admitted with acute coronary syndrome
title_full A novel risk score for predicting 6-months mortality at the time of hospital discharge in patients admitted with acute coronary syndrome
title_fullStr A novel risk score for predicting 6-months mortality at the time of hospital discharge in patients admitted with acute coronary syndrome
title_full_unstemmed A novel risk score for predicting 6-months mortality at the time of hospital discharge in patients admitted with acute coronary syndrome
title_sort novel risk score for predicting 6-months mortality at the time of hospital discharge in patients admitted with acute coronary syndrome
publisher Elsevier
series Indian Heart Journal
issn 0019-4832
publishDate 2021-03-01
description Background: In patients with ACS, risk assessment at hospital discharge has not received much consideration in prior risk scoring systems. Hence, there is a need for a reliable and simple tool to identify patients with high mortality risk at discharge form the hospital. Methods: In a 1-year observational, prospective study, 1012 patients admitted with ACS were followed up for 6 months after discharge. From 26 potential variables, a new risk score to predict 6-month mortality was developed. Results: A multi-variant Cox regression analysis with forward stepwise variable selection was performed and 10 highly significant independent predictors of 6-month mortality were identified. These include previous history of ACS, higher Killip class at admission, NYHA class at discharge, recurrent ischemia during hospital stay, heart failure, requiring ionotropic supports, requiring hemodialysis, presence of arrhythmia, left ventricular dysfunction detected on echocardiography and elevated admission blood glucose levels. Points were given to each variable and a total score was calculated. A risk score of 0–4 (low risk) predicted a mortality of 3.7%,a risk score of 5–15 (Intermediate risk) predicted a mortality of 16.4% and a risk score of 11–15 predicted a mortality of 32.0% over a 6-month period. The new risk score was noninferior to GRACE risk score in its predictive accuracy of 6-month mortality in the same cohort of patients (p < 0.05). Conclusion: The risk score developed in our study can be easily calculated at the bedside and is aimed at identifying high risk patients who require more intense follow up after discharge.
topic Acute coronary syndrome
Hospital discharge
Risk score
Mortality
url http://www.sciencedirect.com/science/article/pii/S0019483221000080
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