ArticleEuropean journal of medical research2025
Development and validation of a nomogram for in-hospital mortality prediction in acute myocardialinfarction patients with cardiac arrest undergoing percutaneous coronary intervention supported by veno-arterial extracorporeal membrane oxygenation.
Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundThe combination of percutaneous coronary intervention (PCI) and veno-arterial extracorporeal membrane oxygenation (VA-ECMO) has become a widely used approach for resuscitating patients with acute myocardial infarction (AMI) complicated by cardiac arrest (CA). Nonetheless, limited research has focused on predicting in-hospital mortality in affected patients. This study aims to identify factors associated with in-hospital mortality and develop a clinical prediction model for these patients.
methodsClinical presentations of AMI patients with CA undergoing PCI supported by VA-ECMO at two hospitals in Zhengzhou were evaluated. Patients were stratified based on their survival status at discharge. A comprehensive analysis, which included univariate logistic regression, LASSO regression, and multivariate logistic regression, was conducted to identify predictors and develop a nomogram for in-hospital mortality. The nomogram's predictive performance was subsequently compared to that of existing models.
resultsThe study included 139 patients, of whom 84 died during hospitalization. Using factors such as age, current smoking, left main culprit vessel, lactic acid levels, and serum creatinine, a nomogram model was developed. The model demonstrated good predictive performance, with an area under the curve of 0.826 (95% CI 0.757-0.894) in the training dataset and 0.783 (95% CI 0.706-0.859) in the internal validation dataset, indicating high accuracy and stability. Clinical decision curve analysis confirmed the model's utility, particularly for risk thresholds above 20%, outperforming existing models.
conclusionsThis study identified independent predictors of in-hospital mortality in AMI patients with CA undergoing PCI supported by VA-ECMO and developed a clinically applicable prediction model.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.