ArticleFrontiers in neurology2022
A New Nomogram for Predicting the Risk of Intracranial Hemorrhage in Acute Ischemic Stroke Patients After Intravenous Thrombolysis.
Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.
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15 citing papers in PubMed, 3 syntheses or guidelines pooled it, 22 citations in OpenAlex.
- Early Predictive Accuracy of Machine Learning for Hemorrhagic Transformation in Acute Ischemic Stroke: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Traditional and machine learning models for predicting haemorrhagic transformation in ischaemic stroke: a systematic review and meta-analysis.Systematic reviews · 2025Pooled it
- Risk prediction models for intracranial hemorrhage in acute ischemic stroke patients receiving intravenous alteplase treatment: a systematic review.Frontiers in neurology · 2023Pooled it
- Integrated single cell-RNA sequencing and Mendelian randomization for ischemic stroke and metabolic syndrome.iScience · 2024Article
- Development and validation of outcome prediction model for reperfusion therapy in acute ischemic stroke using nomogram and machine learning.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024Article
- Development of a predictive nomogram for 28-day mortality risk in non-traumatic or post-traumatic subarachnoid hemorrhage patients.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024Article
- Development and external validation of a novel score for predicting postoperative 30‑day mortality in tumor craniotomy patients: A cross‑sectional diagnostic study.Oncology letters · 2024Article
- Cuproptosis-related genes are involved in immunodeficiency following ischemic stroke.Archives of medical science : AMS · 2024Article
- Application and risk prediction of thrombolytic therapy in cardio-cerebrovascular diseases: a review.Thrombosis journal · 2023Article
- A nomogram for predicting risk of death during hospitalization in elderly patients with Alzheimer's disease at the time of admission.Frontiers in neurology · 2023Article
- Development and validation of a novel clinical prediction model to predict the 90-day functional outcome of spontaneous intracerebral hemorrhage.Frontiers in neurology · 2023Article
- A Novel Nomogram to Predict Symptomatic Intracranial Hemorrhage in Ischemic Stroke Patients After Intravenous Thrombolysis.Therapeutics and clinical risk management · 2023Article
- Prediction of Hemorrhagic Complication after Thrombolytic Therapy Based on Multimodal Data from Multiple Centers: An Approach to Machine Learning and System Implementation.Journal of personalized medicine · 2022Article
- Intravenous Thrombolysis for Acute Ischemic Stroke in Patients with End-Stage Renal Disease on Hemodialysis: A Narrative Review.Journal of cardiovascular development and disease · 2022Review
- Prognostic nomogram for the outcomes in acute stroke patients with intravenous thrombolysis.Frontiers in neuroscience · 2022Article
Corrections and comments
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: We aimed to develop and validate a new nomogram for predicting the risk of intracranial hemorrhage (ICH) in patients with acute ischemic stroke (AIS) after intravenous thrombolysis (IVT). Methods: A retrospective study enrolled 553 patients with AIS treated with IVT. The patients were randomly divided into two cohorts: the training set (70%, Results: After multivariable logistic regression analysis, certain factors, such as smoking, National Institutes of Health of Stroke Scale (NIHSS) score, blood urea nitrogen-to-creatinine ratio (BUN/Cr), and neutrophil-to-lymphocyte ratio (NLR), were found to be independent predictors of ICH and were used to construct a nomogram. The AUC-ROC values of the nomogram were 0.887 (95% CI: 0.842-0.933) and 0.776 (95% CI: 0.681-0.872) in the training and testing sets, respectively. The AUC-ROC of the nomogram was higher than that of the Multicenter Stroke Survey (MSS), Glucose, Race, Age, Sex, Systolic blood Pressure, and Severity of stroke (GRASPS), and stroke prognostication using age and NIH Stroke Scale-100 positive index (SPAN-100) scores for predicting ICH in both the training and testing sets ( Conclusions: The new nomogram, which included smoking, NIHSS, BUN/Cr, and NLR as variables, had the potential for predicting the risk of ICH in patients with AIS after IVT.
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