ArticleFrontiers in medicine2021
Development of a Nomogram to Predict 28-Day Mortality of Patients With Sepsis-Induced Coagulopathy: An Analysis of the MIMIC-III Database.
Article in Frontiers in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
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Who cites it
32 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- Predicting sepsis onset in ICU using machine learning models: a systematic review and meta-analysis.BMC infectious diseases · 2023Pooled it
- Development and Validation of an Interpretable Machine Learning Model to Predict Mortality in Patients With Sepsis-Induced Coagulopathy: Multicenter Cohort Study.JMIR medical informatics · 2026Article
- Blood Glucose Trajectories and Mortality in Sepsis-Induced Coagulopathy: A Latent Growth Mixture Modeling Analysis.Shock (Augusta, Ga.) · 2026Article
- The prognostic value of CT-quantified visceral and subcutaneous fat areas in sepsis.World journal of emergency medicine · 2026Article
- Association between red blood cell distribution width-platelet ratio and mortality in patients with sepsis-induced coagulopathy from the MIMIC-IV database: a retrospective cohort study.BMC infectious diseases · 2026Article
- Interpretable machine learning for early prediction of sepsis-induced coagulopathy: a multicenter retrospective development and validation study.BMC medical informatics and decision making · 2026Article
- Explainable machine learning model for predicting short-term outcomes in sepsis- induced coagulopathy.BMC medical informatics and decision making · 2026Article
- Sepsis-induced coagulopathy: recent insights on the role and clinical application of neutrophil extracellular trap formation.Scientific reports · 2025Article
- Diagnostic Codes in AI Prediction Models and Label Leakage of Same-Admission Clinical Outcomes.JAMA network open · 2025Article
- Harness machine learning for multiple prognoses prediction in sepsis patients: evidence from the MIMIC-IV database.BMC medical informatics and decision making · 2025Article
- Development and Validation of a Nomogram for Predicting Sepsis-Induced Coagulopathy in Septic Patients: Mixed Retrospective and Prospective Cohort Study.Thrombosis and haemostasis · 2025Article
- Development and validation of a web-based dynamic nomogram to predict individualized risk of severe carotid artery stenosis based on digital subtract angiography.Frontiers in neurology · 2025Article
- Development and validation of a nomogram for early prediction of sepsis-induced coagulopathy: a multicenter study.Frontiers in medicine · 2025Article
- GSDMD-NETs in patients with sepsis-induced coagulopathy and their interaction with glycocalyx damage.Frontiers in immunology · 2025Article
- Article
- Systematic analysis based on bioinformatics and experimental validation identifiesAnnals of medicine · 2024Article
- Association between the use of statins and in-hospital mortality risk in patients with sepsis-induced coagulopathy during ICU stays: a study based on medical information mart for intensive care database.BMC infectious diseases · 2024Article
- Persistent high sepsis-induced coagulopathy and sequential organ failure assessment scores can predict the 28-day mortality of patients with sepsis: A prospective study.BMC infectious diseases · 2024Article
- Association between alkaline phosphatase to albumin ratio and mortality among patients with sepsis.Scientific reports · 2024Article
- Development and validation of a nomogram to predict mortality of patients with DIC in ICU.Frontiers in medicine · 2024Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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Identifiers
What OpenQuestion holds
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.