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Nomogram Predicting In-Hospital Mortality in Patients with Myocardial Infarction Treated with Primary Coronary
Lukasz Gawinski1,2, Anna Milewska3, Michal Marczak4
1Department of Management and Logistics in Healthcare, Medical University of Lodz, 90-419 Lodz, Poland.
Insights
A new risk assessment tool for in-hospital death after myocardial infarction (MI) uses modern angiographic and logistic factors. This validated nomogram aids in predicting mortality risk in patients undergoing primary percutaneous coronary intervention (PCI).
Area of Science:
- Cardiology
- Medical Informatics
- Clinical Risk Prediction
Background:
- Existing risk assessment tools for in-hospital death in myocardial infarction (MI) primarily rely on angiographic, electrocardiographic, and laboratory data.
- There is a lack of risk systems incorporating contemporary angiographic data and logistic variables.
- This study addresses the need for a risk assessment system based on modern predictors for MI patients undergoing primary percutaneous coronary intervention (PCI).
Purpose of the Study:
- To develop and validate a novel risk assessment system for in-hospital mortality in patients with myocardial infarction (MI).
- To identify modern angiographic and logistic predictors of in-hospital death in MI patients treated with primary PCI.
- To create a clinical nomogram for predicting in-hospital mortality after primary PCI across the full spectrum of MI.
Main Methods:
- A multivariate logistic regression model was developed using a subgroup of 603 patients from a single-center MI registry treated with primary PCI (February 2019 - January 2020).
- The patient cohort was divided into a 60% derivation set for model development and a 40% validation set for internal validation.
- The model predicted in-hospital mortality based on logistic and angiographic variables.
Main Results:
- Coronary angiography findings and suboptimal post-PCI flow were significant predictors of in-hospital mortality.
- The timing of PCI and the patient's presentation mode were also identified as contributors to in-hospital mortality.
- The model demonstrated good discrimination (C-statistic = 0.848) and calibration in the derivation set, with satisfactory discrimination (C-statistic = 0.6438) in the validation set.
Conclusions:
- A novel clinical nomogram integrating four logistic and angiographic variables has been developed and validated.
- This tool effectively predicts in-hospital mortality risk in a broad range of myocardial infarction patients undergoing primary PCI.
- The nomogram provides a valuable method for assessing mortality risk in contemporary MI management.
Abstract:
Background: Systems developed in recent years to assess the risk of in-hospital death in patients with myocardial infarction (MI) are mainly based on angiographic, electrocardiographic, and laboratory variables. Risk systems based on contemporary angiographic data and logistic variables have not been reported. The aim of this study was to develop and validate a system to assess the risk of in-hospital death in patients across the entire clinical spectrum of MI treated with primary coronary intervention (PCI) based on modern angiographic and logistic predictors. Methods: A subgroup of patients from the observational single-centre registry of MI treated with PCIs (from 1 February 2019 until 31 January 2020) was used to develop a multivariate logistic regression model predicting in-hospital mortality. The population (603 patients) was divided, with 60% of the sample used for model derivation and the remaining 40% used for internal model validation. Results: The main findings were as follows: (1) coronary angiography results and suboptimal flow after PCI were important predictors of in-hospital mortality; (2) the time of PCI as well as the mode of presentation of patients with MI contributed to in-hospital mortality; and (3) the discrimination (C statistic = 0.848, 95% CI: [0.765, 0.857]) and calibration (χ2 = 2.78, pHL = 0.94) were good in the derivation set, while the discrimination (C statistic = 0.6438, 95% CI: [0.580, 0.703]) in the validation set was satisfactory. Conclusions: A novel clinical nomogram based on four available logistic and angiographic variables was developed and validated for in-hospital mortality after PCIs in a wide range of MIs.
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