ArticleClinical interventions in aging2024
Development and Validation of a New Nomogram Model for Predicting Acute Ischemic Stroke in Elderly Patients with Non-Valvular Atrial Fibrillation: A Single-Center Cross-Sectional Study.
Article in Clinical interventions in aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.
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Who cites it
4 citing papers in PubMed, 2 syntheses or guidelines pooled it, 4 citations in OpenAlex.
- Evaluation of machine learning models for stroke risk prediction in atrial fibrillation: a systematic review and meta-analysis.BMC cardiovascular disorders · 2026Pooled it
- Predictive value of neutrophil to lymphocyte ratio for clinical outcome in patients with atrial fibrillation: a systematic review and meta-analysis.Frontiers in cardiovascular medicine · 2024Pooled it
- A model based on high-resolution magnetic resonance vessel wall imaging for predicting stroke recurrence in patients with symptomatic intracranial atherosclerosis.Quantitative imaging in medicine and surgery · 2025Article
- Enhancing the evaluation of acute ischemic stroke risk in individuals with non-valvular atrial fibrillation by including laboratory indicators.Scientific reports · 2024Article
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aims: Non-valvular atrial fibrillation (NVAF) patients face a 3-5 times greater risk of acute ischemic stroke (AIS) compared to those without NVAF. This study aims to establish a novel clinical prediction model for AIS in elderly patients with NVAF by incorporating relevant biomarker indicators. Methods: A total of 301 individuals diagnosed with NVAF were selected for this investigation at the Third Affiliated Hospital of Anhui Medical University. Based on the presence of AIS, patients were categorized into two groups: the Stroke Cohort and the Non-Stroke Cohort. Predictor screening was performed using the least absolute shrinkage and selection operation (LASSO) regression algorithm. The binary logistic regression equation was applied to fit the model, followed by internal validation using the bootstrap resampling method (1000 times). Receiver operating characteristic (ROC) curve, calibration degree curve plots, and clinical decision curve analysis (DCA) were generated, respectively. Finally, a nomogram was constructed to present the prediction model. Results: The final results of this study revealed that neutrophil-to-lymphocyte ratio (NLR), red cell distribution width (RDW), lipoprotein(a) (Lp(a)), systolic pressure, history of stroke, hyperlipidemia were independent risk factors for AIS in elderly patients with NVAF ( Conclusion: NLR, RDW, Lp(a), SP, history of stroke, hyperlipidemia, and HDL-C emerge as independent prognostic factors for acute ischemic stroke in elderly patients with non-valvular atrial fibrillation. The predictive utility of the nomogram model may potentially surpass that of the CHA2DS2-VASc scoring system.
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