Predicting Mortality in Sepsis

Predicting mortality in adult patients with sepsis in the emergency ...

Sepsis can be detected in an early stage in the emergency department (ED) by biomarkers and clinical scoring systems. A combination of multiple biomarkers ...

Deep learning-based prediction of in-hospital mortality for sepsis

We refine the core indicators for mortality risk assessment of sepsis from massive clinical electronic medical records with machine learning.

Predictors of mortality of severe sepsis among adult patients in the ...

Low platelet count, elevated serum levels of CRP, APACHE score >25, and the need for invasive mechanical ventilation were found to be independent predictors of ...

Machine learning for the prediction of sepsis-related death

Conclusion. The predictive value of clinical scoring tools is controversial and needs further improvement. Machine learning has an ideal ...

Screening tools for predicting mortality of adults with suspected sepsis

We evaluated the performance of commonly used sepsis screening tools across prospective sepsis cohorts in the USA, Cambodia and Ghana.

Review of the Predictive Value of Biomarkers in Sepsis Mortality

This research concentrates on the significance of CAR in the pathological process of sepsis, its association with prognosis, and the latest developments.

Machine learning algorithm to predict mortality in critically ill patients ...

This study aimed to establish and validate a machine learning (ML) model for predicting in-hospital mortality in patients with sepsis-associated acute kidney ...

Risk factors and a prediction model for sepsis - ScienceDirect.com

Risk factors for 28-day sepsis mortality include age, D-dimer, creatinine, PT, and albumin. A decrease in albumin level may exacerbate immunosuppression in ...

Predicting mortality among septic patients presenting to the ...

The aim of the current study was to identify variables predictive of 7- and 30-day mortality among septic patients presenting to the ED based on the clinical ...

Development and Validation of a Sepsis Mortality Risk Score for ...

Similarly, many studies have indicated that a strong predictor of mortality for septic patients is serum lactate (30, 31), which, however, was ...

Artificial Intelligence for Predicting Mortality Due to Sepsis

The proposed model predicted mortality due to sepsis in 164 out of 208 mortality group (sensitivity: 73.81%) and survival in 438 out of 577 survival group ( ...

Predicting Sepsis Mortality in a Population-Based National Database

Background: Although machine learning (ML) algorithms have been applied to point-of-care sepsis prognostication, ML has not been used to ...

Predicting mortality risk in sepsis patients in hospital | IDR

The continuous decline of serum cholinesterase in liver function indicators and the elevation of total bilirubin level were directly related to ...

A Severe Sepsis Mortality Prediction Model and Score for Use With...

These nonnegative integers are the point values that make up the sepsis severity score when summed. A summary score was created for each observation in the ...

Sepsis mortality score for the prediction of mortality in septic patients

Sepsis remains an ongoing challenge in intensive care medicine largely because of the high mortality rate despite the provision of optimal care [1]. Initial ...

1444: machine learning models for predicting mortality in sepsis

A diverse range of predictive ML models was utilized to predict in-hospital or in-ICU mortality in sepsis patients.

Machine learning models for predicting in-hospital mortality in ...

Conclusion: By analyzing dynamic vital sign data, machine learning models can predict mortality in septic patients within 6 to 48 h of admission. The ...

Sepsis mortality prediction based on predisposition, infection and ...

A modified PIRO (predisposition, insult, response, and organ dysfunction) concept could be applied to predict mortality in patients with infection and sepsis.

Predicting Mortality in Sepsis: The Role of Dynamic Biomarker ...

Background: The prognostic value of baseline inflammatory markers in sepsis remains controversial, with conflicting evidence regarding their association ...

Machine-learning models for prediction of sepsis patients mortality

Models built with light GBM algorithm from real-world sepsis patients from electronic health records accurately predict whether sepsis patients are dead and can ...