2022
DOI: 10.1186/s40001-022-00925-3
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Early predicting 30-day mortality in sepsis in MIMIC-III by an artificial neural networks model

Abstract: Objective Early identifying sepsis patients who had higher risk of poor prognosis was extremely important. The aim of this study was to develop an artificial neural networks (ANN) model for early predicting clinical outcomes in sepsis. Methods This study was a retrospective design. Sepsis patients from the Medical Information Mart for Intensive Care-III (MIMIC-III) database were enrolled. A predictive model for predicting 30-day morality in sepsis … Show more

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Cited by 13 publications
(8 citation statements)
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“…Further analysis revealed generally higher levels of HOTTIP in deaths than in survivors. Furthermore, elevated HOTTIP, as well as APACHE II and SOFA scores [ 33 , 34 ], predicted the appearance of death in patients with sepsis and were both independent predictors of death in the patients with sepsis. However, HOTTIP has its unique advantages over the two scores in terms of predictive value, firstly given that HOTTIP, as an ncRNA, may already be resentful in early changes in the disease and its prediction may be earlier than the two scores.…”
Section: Discussionmentioning
confidence: 99%
“…Further analysis revealed generally higher levels of HOTTIP in deaths than in survivors. Furthermore, elevated HOTTIP, as well as APACHE II and SOFA scores [ 33 , 34 ], predicted the appearance of death in patients with sepsis and were both independent predictors of death in the patients with sepsis. However, HOTTIP has its unique advantages over the two scores in terms of predictive value, firstly given that HOTTIP, as an ncRNA, may already be resentful in early changes in the disease and its prediction may be earlier than the two scores.…”
Section: Discussionmentioning
confidence: 99%
“…Several methods have been concurrently developed to predict mortality for ICU patients with Sepsis [13,16]. However, to the best of our knowledge there is only one research focusing on prediction of mortality for ICU patients of Sepsis-3 using MIMIC-III database [15].…”
Section: Discussion Existing Model Compilation Summarymentioning
confidence: 99%
“…By incorporating diverse information sources, the model enhances healthcare professionals' predictive abilities, fostering a more comprehensive understanding of patient outcomes. [14][15][16][17][18][19][20][21].…”
Section: Introduction:mentioning
confidence: 99%