Identification of the high-risk patient in primary percutaneous coronary intervention: development and validation of a novel predictive index

Blake, S, Proscia, C, Eleuteri, A ORCID: 0000-0003-0718-6672, Groves, D and Stables, RH ORCID: 0000-0002-9244-7015
(2020) Identification of the high-risk patient in primary percutaneous coronary intervention: development and validation of a novel predictive index. PhD thesis, University of Liverpool.

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The aim of treatment in STEMI is to improve outcomes for patients in terms of mortality and quality of life. Mortality rates have improved with increased use of PPCI as first-line therapy however in-hospital mortality remains 5-8%. There are multiple therapies that may be beneficial for some patients, as adjuncts to PPCI. There is limited evidence for the use of these therapies and deciding which patients should receive them is challenging. If operators could identify patients during the acute MI who may be at high risk of adverse outcomes, they may decide to administer adjunctive therapies or increase the length of critical care admissions, which could improve outcomes. Invasive methods, such as IMR, can identify patients with poor reperfusion following PPCI. However, clinical and angiographic variables that are easily recorded during PPCI could be used to risk assess patients, avoiding the need for extra invasive tests. Clinical and angiographic variables that are readily available during PPCI were examined for associations with a composite outcome of 28-day mortality or subsequent severe impairment of left ventricular function (ejection fraction ≤35%). These variables included age, gender, culprit location, TIMI flow grade, myocardial blush grade, thrombus burden and corrected TIMI frame count. Variables with an association with the outcome were included in a multivariate logistic regression analysis to develop a predictive model – the Liverpool MI Risk Model. Independent variables included in the Liverpool MI Risk Model were age, culprit vessel location and myocardial blush grade. The model accurately predicts the outcome of death within 28 days or subsequent severe impairment of left ventricular function (c statistic 0.79; 95% CI 0.75 to 0.83). External validation of the model using an independent cohort of patients showed good discrimination (c statistic 0.837; 95% CI 0.723 to 0.951) although the model overestimated the risk of outcome events in the new cohort. The model was accurate in predicting adverse events in the validation cohort after simple recalibration. The Liverpool MI Risk Model is a practical tool that uses information available during PPCI to accurately predict the occurrence of an adverse outcome. Using this model could help operators to make decisions regarding adjunctive therapies and duration of stay in critical care areas. External validation of the risk model overestimated the occurrence of an outcome in the validation cohort, prior to recalibration, likely due to differences in measurement methods, eligibility criteria and risk profiles between the two cohorts. A study including unselected STEMI patients using the same measurement methods as the derivation cohort should be used to validate the Liverpool MI Risk Model.

Item Type: Thesis (PhD)
Divisions: Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences > School of Medicine
Depositing User: Symplectic Admin
Date Deposited: 08 Jun 2020 13:09
Last Modified: 18 Jan 2023 23:53
DOI: 10.17638/03084755
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