Association of NPAC score with survival after acute myocardial infarction
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AbstractBackground and aims
Risk stratification in acute myocardial infarction (AMI) is important for guiding clinical management. Current risk scores are mostly derived from clinical trials with stringent patient selection. We aimed to establish and evaluate a composite scoring system to improve short-term mortality classification after index episodes of AMI, independent of electrocardiography (ECG) pattern, in a large real-world cohort.

Methods
Using electronic health records, patients admitted to our regional teaching hospital (derivation cohort, n = 1747) and an independent tertiary care center (validation cohort, n = 1276), with index acute myocardial infarction between January 2013 and December 2017, as confirmed by principal diagnosis and laboratory findings, were identified retrospectively.

Results
Univariate logistic regression was used as the primary model to identify potential contributors to mortality. Stepwise forward likelihood ratio logistic regression revealed that neutrophil-to-lymphocyte ratio, peripheral vascular disease, age, and serum creatinine (NPAC) were significant for 90-day mortality (Hosmer- Lemeshow test, p = 0.21). Each component of the NPAC score was weighted by beta-coefficients in multivariate analysis. The C-statistic of the NPAC score was 0.75, which was higher than the conventional Charlson's score (C-statistic = 0.63). Judicious application of a deep learning model to our dataset improved the accuracy of classification with a C-statistic of 0.81.

Conclusions
The NPAC score comprises four items from routine laboratory parameters to basic clinical information and can facilitate early identification of cases at risk of short-term mortality following index myocardial infarction. Deep learning model can serve as a gatekeeper to facilitate clinical decision-making.
All Author(s) ListLi CK, Xu Z, Ho J, Lakhani I, Liu YZ, Bazoukis G, Liu T, Wong WT, Cheng SH, Chan MTV, Zhang L, Gin T, Wong MCS, Wong ICK, Wu WKK, Zhang Q, Tse G
Journal nameAtherosclerosis
Year2020
Month5
Volume Number301
PublisherElsevier
Pages30 - 36
ISSN0021-9150
eISSN1879-1484
LanguagesEnglish-United Kingdom

Last updated on 2020-19-10 at 00:55