Related Experiment Video
Updated: Sep 17, 2025
Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
Published on: September 25, 2019
Prediction of First-Onset Cerebral Infarction Risk in Patients with Acute Myocardial Infarction: A Retrospective
Zifeng Zeng1,2, Rongtai Luo1,2, Weiyong Xu1,2
1Center for Cardiovascular Diseases, Meizhou People's Hospital, Meizhou, People's Republic of China.
Insights
This study developed a new tool to predict stroke risk in heart attack patients. The nomogram helps doctors identify high-risk individuals for better care.
Area of Science:
- Cardiology
- Neurology
- Medical Informatics
Background:
- Cerebral infarction (CI) increases major adverse cardiovascular events in acute myocardial infarction (AMI) patients.
- Early identification and intervention are crucial, but validated risk stratification tools are lacking.
- This study addresses the need for individualized risk assessment of CI in AMI patients.
Purpose of the Study:
- To identify the most valuable predictors (MVPs) of in-hospital first-onset CI in AMI patients.
- To construct and validate a nomogram for individualized risk stratification of CI in AMI patients.
Main Methods:
- Retrospective cohort study of 1,350 AMI patients.
- Least Absolute Shrinkage and Selection Operator (LASSO) regression for MVP selection.
- Nomogram development and validation of discrimination, calibration, and clinical utility.
Main Results:
- CI occurred in 4.44% of patients.
- Key predictors included Killip classification, PCI therapy, C-reactive protein (CRP), blood urea nitrogen (BUN), and neutrophil-to-lymphocyte ratio (NLR).
- The nomogram demonstrated good discriminatory ability (0.804), calibration, and clinical utility, with an optimal cutoff of 0.035.
Conclusions:
- A novel nomogram integrating multimodal predictors for in-hospital CI in AMI patients was developed and validated.
- This tool can assist clinicians in decision-making for risk stratification.
- The nomogram provides a valuable aid for identifying AMI patients at risk of developing CI during hospitalization.
Background:
The occurrence of cerebral infarction significantly increases the risk of major adverse cardiovascular events in patients with acute myocardial infarction (AMI), highlighting the importance of early identification and intervention. Currently, no validated tools exist for individualized risk stratification of cerebral infarction (CI) in patients with AMI.
Objective:
This study aimed to identify the most valuable predictors (MVPs) of in-hospital first-onset CI in AMI patients and construct a nomogram for risk stratification.
Methods:
This retrospective cohort study enrolled 1,350 AMI patients admitted to the Cardiovascular Center of Meizhou People's Hospital between January and December 2022. Clinical characteristics and laboratory parameters were analyzed. Least Absolute Shrinkage and Selection Operator regression (LASSO) was used to select MVPs. The nomogram was developed by integrating coefficients of MVPs from logistic regression, and its discrimination, calibration, and clinical utility were validated in the cohort. The optimal cutoff value of the nomogram probability was determined.
Results:
CI occurred in 60 patients (4.44%). MVPs included Killip classification (OR = 1.42, 95% CI 1.05-1.93), PCI therapy (OR = 0.29, 95% CI 0.16-0.51), C-reactive protein (CRP: OR = 1.01, 95% CI 1.00-1.01), blood urea nitrogen (BUN: OR = 1.03, 95% CI 0.99-1.07), and neutrophil-to-lymphocyte ratio (NLR: OR = 1.02, 95% CI 0.99-1.05). The discriminatory ability of the nomogram was up to 0.804(95% CI 0.749-0.859). Additionally, the nomogram showed good calibration and clinical utility in the cohort. Furthermore, the optimal cutoff value of the nomogram probability for distinguishing those who will experience in-hospital first-onset CI was 0.035 (sensitivity 78.3%, specificity 71.1%).
Conclusion:
The first nomogram integrating multimodal predictors for discerning AMI patients who will experience in-hospital first-onset CI was developed and validated, which will aid clinicians in clinical decision-making.
More Related Videos
18:11A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
Published on: December 28, 2012
07:25Predicting Amputation using Local Circulating Mononuclear Progenitor Cells in Angioplasty-treated Patients with Critical Limb Ischemia
Published on: September 22, 2020
Related Concept Videos
01:30Acute Coronary Syndrome III: Diagnostic Studies
01:25Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT
01:20Blood Studies for Cardiovascular System I: Cardiac Biomarkers
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
01:30Acute Coronary Syndrome I: Introduction
01:28Acute Coronary Syndrome IV: Interprofessional Care
01:19Acute Coronary Syndrome II: Pathophysiology and Clinical Manifestations