ArticleFrontiers in microbiology2021
Development and Validation of a Nomogram for the Prediction of Hospital Mortality of Patients With Encephalopathy Caused by Microbial Infection: A Retrospective Cohort Study.
Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers.
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15 citing papers in PubMed, 22 citations in OpenAlex.
- Prognostic Factors and Risk Stratification in Malignant Tumor Patients With Sepsis: A Retrospective Cohort Study.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
- Prognostic Nutritional Index as a Novel Biomarker for Predicting Prognosis in Sepsis-Associated Encephalopathy: A Multicenter Retrospective Cohort Study.Emergency medicine international · 2026Article
- Online Clinical Calculator for Predicting 28-Day Mortality in Older Adult Patients With Sepsis-Associated Encephalopathy: Retrospective Study Using MIMIC-IV.JMIR medical informatics · 2025Article
- Impact of Pathogen Status on Sepsis-Associated Acute Respiratory Distress Syndrome Outcomes.Medical science monitor : international medical journal of experimental and clinical research · 2025Article
- Microbiological and clinical predictors of sepsis-associated encephalopathy in bloodstream infections: a retrospective cohort study.Frontiers in cellular and infection microbiology · 2025Article
- Comprehensive risk factor-based nomogram for predicting one-year mortality in patients with sepsis-associated encephalopathy.Scientific reports · 2024Article
- Prognostic role of urinary ketone body in patients with sepsis-associated encephalopathy without hepatic failure: a retrospective cohort study.Internal and emergency medicine · 2024Article
- Development and validation of a nomogram to predict the risk of sepsis-associated encephalopathy for septic patients in PICU: a multicenter retrospective cohort study.Journal of intensive care · 2024Article
- A simple nomogram for predicting the mortality of PICU patients with sepsis-associated encephalopathy: a multicenter retrospective study.Frontiers in neurology · 2024Article
- Paediatric sepsis-associated encephalopathy (SAE): a comprehensive review.Molecular medicine (Cambridge, Mass.) · 2023Review
- Establishment and Validation of Models for the Risk of Multi-Drug Resistant Bacteria Infection and Prognosis in Elderly Patients with Pulmonary Infection: A Multicenter Retrospective Study.Infection and drug resistance · 2023Article
- New Strategies to Optimize Hemodynamics for Sepsis-Associated Encephalopathy.Journal of personalized medicine · 2022Article
- Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated encephalopathy.BMC medical research methodology · 2022Article
- Development of a Novel Nomogram Incorporating Red Blood Cell Distribution Width-Albumin Ratio for the Prediction of 30-day Mortality in Acute Pancreatitis Patients.Emergency medicine international · 2022Article
- Prognostic role of serum ammonia in patients with sepsis-associated encephalopathy without hepatic failure.Frontiers in public health · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHospital mortality is high for patients with encephalopathy caused by microbial infection. Microbial infections often induce sepsis. The damage to the central nervous system (CNS) is defined as sepsis-associated encephalopathy (SAE). However, the relationship between pathogenic microorganisms and the prognosis of SAE patients is still unclear, especially gut microbiota, and there is no clinical tool to predict hospital mortality for SAE patients. The study aimed to explore the relationship between pathogenic microorganisms and the hospital mortality of SAE patients and develop a nomogram for the prediction of hospital mortality in SAE patients.
methodsThe study is a retrospective cohort study. The lasso regression model was used for data dimension reduction and feature selection. Model of hospital mortality of SAE patients was developed by multivariable Cox regression analysis. Calibration and discrimination were used to assess the performance of the nomogram. Decision curve analysis (DCA) to evaluate the clinical utility of the model.
resultsUnfortunately, the results of our study did not find intestinal infection and microorganisms of the gastrointestinal (such as: Escherichia coli) that are related to the prognosis of SAE. Lasso regression and multivariate Cox regression indicated that factors including respiratory failure, lactate, international normalized ratio (INR), albumin, SpO
conclusionThe prognosis of SAE patients has nothing to do with intestinal and microbial infections. We developed a nomogram that predicts hospital mortality in patients with SAE according to clinical data. The nomogram exhibited excellent discrimination and calibration capacity, favoring its clinical utility.
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