ArticleAnnals of translational medicine2021
A nomogram for predicting the risk of no-reflow after primary percutaneous coronary intervention in elderly patients with ST-segment elevation myocardial infarction.
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Predicting the no-reflow phenomenon in ST-elevation myocardial infarction patients undergoing primary percutaneous coronary intervention: a systematic review of clinical prediction models.Therapeutic advances in cardiovascular diseasePooled it
- Effects of nicorandil on systemic inflammation and oxidative stress induced by percutaneous coronary intervention in patients with coronary heart disease.The Journal of international medical research · 2021Trial
- Changes and Diagnostic Significance of miR-542-3p Expression in Patients with Myocardial Infarction.Molecular biotechnology · 2025Article
- Machine learning prediction of no reflow in patients with ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention.Cardiovascular diagnosis and therapy · 2024Article
- A Nomogram model for predicting the occurrence of no-reflow phenomenon after percutaneous coronary intervention using the lncRNAJournal of thoracic disease · 2022Article
- A nomogram risk prediction model for no-reflow after primary percutaneous coronary intervention based on rapidly accessible patient data among patients with ST-segment elevation myocardial infarction and its relationship with prognosis.Frontiers in cardiovascular medicine · 2022Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe purpose of this study was to screen the predictive factors of no-reflow after a percutaneous coronary intervention (PCI) in elderly patients with ST-segment elevation myocardial infarction (STEMI), and to construct a nomogram model, to guide clinical treatment.
methodsA total of 551 elderly STEMI patients (age >65) underwent direct PCI were randomly classified into training group (n=386, 70%) and validation group (n=165, 30%). All patients in the two groups were divided into a no-reflow group and a normal blood flow group according to whether there was a no-reflow phenomenon. Univariable and multivariable logistic regression analysis was used to analyze the relevant data, including demographic characteristics, clinical characteristics, coronary angiography results, electrocardiogram (ECG) results, and biochemical indicators. Then, a nomogram model was constructed on the screened risk factors. The performance of the nomogram was evaluated in terms of discrimination and calibration. The nomogram was further confirmed in the internal validation group. Additionally, decision curve analysis (DCA) was applied to assess the clinical usefulness of the nomogram.
resultsFive remarkable risk factors were determined: preoperative TIMI blood flow, the diameter of the target lesion, collateral circulation, pulse pressure, and the number of leads for ST-segment elevation. The nomogram involving these five risk factors showed full calibration and discrimination in the training group, with an AUC of 0.71 (95% CI: 0.66-0.77). It was confirmed in the validation group, and the entire cohort and the AUC were 0.64 (95% CI: 0.56-0.73) and 0.69 (95% CI: 0.65-0.74), respectively. Whether in the training group or the verification group, the calibration curve for the probability of no-reflow phenomenon all showed considerable consistency between prediction by nomogram and actual observation. The decision curve revealed a specific role in our nomogram in clinical practice.
conclusionsWe set up a nomogram that showed absolute accuracy for the prediction of the risk of no-reflow after primary PCI in elderly STEMI patients.
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