# Prehospital survival of patients with ST-elevation myocardial infarction requiring out-of-hospital cardiopulmonary resuscitation - a nationwide, real-world observational study

**Authors:** Dominika Szabó, András Szabó, Andrea Székely

PMC · DOI: 10.1186/s12873-025-01292-y · 2025-07-18

## TL;DR

This study examines the survival rates of patients with heart attacks requiring CPR before hospital admission, using nationwide data to identify factors affecting outcomes.

## Contribution

The study introduces a predictive model for hospital admission success after CPR in STEMI patients with out-of-hospital cardiac arrest.

## Key findings

- A logistic regression model with a c-statistic of 0.844 effectively predicts hospital admission outcomes.
- The model shows strong predictor-outcome relationships with a Nagelkerke R2 of 0.445.
- Internal validation confirmed good model fit and calibration.

## Abstract

The mortality risk of patients presenting with ST-elevation myocardial infarction (STEMI) has been extensively researched. Even though STEMI can be diagnosed before hospital admission, prehospital mortality has been less frequently studied. We aimed to analyze the outcomes of patients with STEMI requiring out-of-hospital cardiopulmonary resuscitation (CPR).

From a large, nationwide prehospital case report database, we collected data from 668 patients requiring CPR because of ambulance-witnessed OHCA (out-of-hospital cardiac arrest) who were diagnosed with STEMI by ECG before cardiac arrest. Utstein-style consensus reporting guidelines were followed. The endpoint was hospital admission with spontaneous circulation. In addition to descriptive statistics, we also aimed to identify predictors of the outcome using multivariable logistic regression. Model performance was characterized by c-statistics and multiple fitting methods. Internal validation was performed using calibration intercept and slope.

Using CPR initial rhythm, age, initial heart rate, initial systolic blood pressure, and ECG localization of STEMI as predictors, we found that the constructed logistic regression model showed good discriminative ability, with a c-statistic of 0.844 (95% CI = 0.8105–0.8787). The overall model fit was good, with Hosmer & Lemeshow p = 0.979. The value of Nagelkerke R2 test of 0.445 indicated a strong relationship between predictors and outcome. The Z-value of calibration slope was relative to slope = 1 (95% CI = 0.85–1.16).

This model can be used to estimate the probability of hospital admission following resuscitation due to ambulance-witnessed OHCA in patients with STEMI. Further studies are needed to improve the possibility of definitive in-hospital treatment for a better survival rate.

Not applicable.

## Linked entities

- **Diseases:** ST-elevation myocardial infarction (MONDO:0041656)

## Full-text entities

- **Diseases:** cardiac arrest (MESH:D006323), ST-elevation myocardial infarction (MESH:D000072657), OHCA (MESH:D058687)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12275280/full.md

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Source: https://tomesphere.com/paper/PMC12275280