ArticleComputational and mathematical methods in medicine2015
Mortality Prediction Model of Septic Shock Patients Based on Routinely Recorded Data.
Article in Computational and mathematical methods in medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 22 citations in OpenAlex.
- Low vasopressin and progression of neonatal sepsis to septic shock: a prospective cohort study.European journal of pediatrics · 2020Trial
- Characteristics and In-Hospital Outcomes of Patients With Septic Shock in the Adult Medical Intensive Care Unit of a Tertiary Hospital in Ethiopia: A Prospective Observational Study.Health science reports · 2025Article
- Prediction of mortality in patients with secondary pulmonary embolism based on primary admission indication: A short communication.Biomolecules & biomedicine · 2024Article
- Article
- DYNAMIC PREDICTION OF RESIDUAL LIFE WITH LONGITUDINAL COVARIATES USING LONG SHORT-TERM MEMORY NETWORKS.The annals of applied statistics · 2023Article
- Analysis of the correlation between the longitudinal trajectory of SOFA scores and prognosis in patients with sepsis at 72 hour after admission based on group trajectory modeling.Journal of intensive medicine · 2022Article
- Understanding the complexity of sepsis mortality prediction via rule discovery and analysis: a pilot study.BMC medical informatics and decision making · 2021Article
- A Predictive Model Based on Machine Learning for the Early Detection of Late-Onset Neonatal Sepsis: Development and Observational Study.JMIR medical informatics · 2020Article
- Myocardial Strain and Cardiac Output are Preferable Measurements for Cardiac Dysfunction and Can Predict Mortality in Septic Mice.Journal of the American Heart Association · 2019Article
- Building Computational Models to Predict One-Year Mortality in ICU Patients with Acute Myocardial Infarction and Post Myocardial Infarction Syndrome.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We studied the problem of mortality prediction in two datasets, the first composed of 23 septic shock patients and the second composed of 73 septic subjects selected from the public database MIMIC-II. For each patient we derived hemodynamic variables, laboratory results, and clinical information of the first 48 hours after shock onset and we performed univariate and multivariate analyses to predict mortality in the following 7 days. The results show interesting features that individually identify significant differences between survivors and nonsurvivors and features which gain importance only when considered together with the others in a multivariate regression model. This preliminary study on two small septic shock populations represents a novel contribution towards new personalized models for an integration of multiparameter patient information to improve critical care management of shock patients.
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