ArticleBMC cardiovascular disorders2026
Development, validation and visualization of a nomogram for the prediction of in-hospital cardiac arrest in patients after successful primary PCI for STEMI.
Article in BMC cardiovascular disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Development and validation of a risk prediction model for myocardial hypoperfusion after primary PCI in ST-segment elevation myocardial infarction.Frontiers in cardiovascular medicine · 2026Article
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16 authors.
Funding
Abstract
backgroundIn-hospital cardiac arrest (IHCA) is an infrequent but lethal complication in patients with ST-elevation myocardial infarction (STEMI). Data on the characteristics and predictors of IHCA in STEMI patients after successful primary percutaneous coronary intervention (PPCI) are limited. This study aimed to identify the risk factors of IHCA and construct a predictive nomogram.
methodA total of 5121 STEMI patients treated with successful PPCI from January 2018 to July 2023 at Beijing Anzhen Hospital were retrospectively enrolled in our study. Subjects were randomly divided into a development group and a validation group in a 7:3 ratio. Optimal predictive variables were selected using the least absolute shrinkage and selection operator (Lasso) and logistic regression models. A nomogram based on these predictors was then created to estimate IHCA probability.
resultsAmong them, 94 patients (1.8% [95% CI: 1.4%-2.1%]) experienced IHCA after PPCI, and the in-hospital mortality rate was 35.1% in these patients. Lasso regression was implemented to identify predictors of IHCA, including age, Killip III-IV, systolic blood pressure, and moderate to severe calcification, with non-zero coefficients. A nomogram model for predicting the risk of IHCA after PPCI in STEMI patients was constructed with the above independent predictors, with a C-index of 0.823 (95%CI 0.764–0.881). The model’s calibration curve closely aligned with the ideal reference, indicating strong agreement between predicted and actual outcomes, and the internal validation showed a C-index of 0.828 (95%CI 0.751–0.905). Clinical decision analysis further confirmed that the nomogram model demonstrated good clinical effectiveness.
conclusionOur study identified several independent risk factors for IHCA in STEMI patients after successful PPCI based on a Lasso-logistic regression model, offering individualized and reliable cardiac arrest risk predictions during hospitalization.
trial registrationNot applicable.
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