Trial reportBMC medical informatics and decision making2022
A novel nomogram to predict mortality in patients with stroke: a survival analysis based on the MIMIC-III clinical database.
Trial report in BMC medical informatics and decision making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
29 citing papers in PubMed, 2 syntheses or guidelines pooled it, 44 citations in OpenAlex.
- Predictive Value of Machine Learning for Poststroke Mortality Risk: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Risk prediction models for short-term mortality in ICU stroke patients: a systematic review and meta-analysis.Frontiers in neurology · 2025Pooled it
- Observational
- Development and validation of predicting hospital mortality of acute ischemic stroke patients over 80 years in ICU: a retrospective study.BMC geriatrics · 2026Article
- A predictive model for low-dose rituximab response in anti-acetylcholine receptor antibody-positive myasthenia gravis: establishment and validation.Frontiers in immunology · 2026Article
- Construction of a Risk Prediction Model for Stroke Occurrence in Septic Shock Patients: A Combined Analysis Using LASSO and Multivariate Logistic Regression.International journal of general medicine · 2026Article
- Comprehensive analysis of risk factors and nomogram development for predicting hepatic metastasis following radical resection of adenocarcinoma of the esophagogastric junction.BMC gastroenterology · 2025Article
- A comprehensive analysis of stroke risk factors and development of a predictive model using machine learning approaches.Molecular genetics and genomics : MGG · 2025Article
- Development of a machine learning-based predictive nomogram for screening children with juvenile idiopathic arthritis: a pseudo-longitudinal study of 223,195 children in the United States.Frontiers in public health · 2025Article
- Article
- Multimodal Metaverse Healthcare: A Collaborative Representation and Adaptive Fusion Approach for Generative Artificial-Intelligence-Driven Diagnosis.Research (Washington, D.C.) · 2025Article
- In-Hospital Mortality Prediction among Intensive Care Unit Patients with Acute Ischemic Stroke: A Machine Learning Approach.Health data science · 2025Article
- Construction of a nomogram for predicting the prognosis of patients with cervical spondylotic myelopathy: a retrospective study.Scientific reports · 2024Article
- Artificial intelligence-based personalized clinical decision-making for patients with localized prostate cancer: surgery versus radiotherapy.The oncologist · 2024Article
- Article
- Development of m6A/m5C/m1A regulated lncRNA signature for prognostic prediction, personalized immune intervention and drug selection in LUAD.Journal of cellular and molecular medicine · 2024Article
- Indian Society of Critical Care Medicine and Indian Association of Palliative Care Expert Consensus and Position Statements for End-of-life and Palliative Care in the Intensive Care Unit.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2024Article
- Constructing a Nomogram Model to Estimate the Risk of Ventilator-Associated Pneumonia for Elderly Patients in the Intensive Care Unit.Advances in respiratory medicine · 2024Article
- Single-center nomogram model for sepsis complicated by acute lung injury.American journal of translational research · 2024Article
- Development and validation of a nomogram for predicting 28-day mortality in patients with ischemic stroke.PloS one · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStroke is a disease characterized by sudden cerebral ischemia and is the second leading cause of death worldwide. We aimed to develop and validate a nomogram model to predict mortality in intensive care unit patients with stroke.
methodsAll data involved in this study were extracted from the Medical Information Mart for Intensive Care III database (MIMIC-III). The data were analyzed using multivariate Cox regression, and the performance of the novel nomogram, which assessed the patient's overall survival at 30, 180, and 360 days after stroke, was evaluated using Harrell's concordance index (C-index) and the area under the receiver operating characteristic curve. A calibration curve and decision curve were introduced to test the clinical value and effectiveness of our prediction model.
resultsA total of 767 patients with stroke were randomly divided into derivation (n = 536) and validation (n = 231) cohorts at a 7:3 ratio. Multivariate Cox regression showed that 12 independent predictors, including age, weight, ventilation, cardiac arrhythmia, metastatic cancer, explicit sepsis, Oxford Acute Severity of Illness Score or OASIS score, diastolic blood pressure, bicarbonate, chloride, red blood cell and white blood cell counts, played a significant role in the survival of individuals with stroke. The nomogram model was validated based on the C-indices, calibration plots, and decision curve analysis results.
conclusionsThe plotted nomogram accurately predicted stroke outcomes and, thus may contribute to clinical decision-making and treatment as well as consultation services for patients.
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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.