Real-time machine learning model to predict short-term mortality in critically ill patients: development and international validation

L Lim, U Gim, K Cho, D Yoo, HG Ryu, HC Lee - Critical Care, 2024 - Springer
Background A real-time model for predicting short-term mortality in critically ill patients is
needed to identify patients at imminent risk. However, the performance of the model needs …

Prioritising deteriorating patients using time-to-event analysis: prediction model development and internal–external validation

R Blythe, R Parsons, AG Barnett, D Cook, SM McPhail… - Critical Care, 2024 - Springer
Background Binary classification models are frequently used to predict clinical deterioration,
however they ignore information on the timing of events. An alternative is to apply time-to …

Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy

MW Kang, J Kim, DK Kim, KH Oh, KW Joo, YS Kim… - Critical Care, 2020 - Springer
Background Previous scoring models such as the Acute Physiologic Assessment and
Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment …

Prediction of cardiac arrest in critically ill patients presenting to the emergency department using a machine learning score incorporating heart rate variability …

MEH Ong, CH Lee Ng, K Goh, N Liu, ZX Koh… - Critical Care, 2012 - Springer
Introduction A key aim of triage is to identify those with high risk of cardiac arrest, as they
require intensive monitoring, resuscitation facilities, and early intervention. We aim to …

A deep learning model for real-time mortality prediction in critically ill children

SY Kim, S Kim, J Cho, YS Kim, IS Sol, Y Sung, I Cho… - Critical care, 2019 - Springer
Background The rapid development in big data analytics and the data-rich environment of
intensive care units together provide unprecedented opportunities for medical …

Multicenter derivation and validation of an early warning score for acute respiratory failure or death in the hospital

MA Dziadzko, PJ Novotny, J Sloan, O Gajic… - Critical Care, 2018 - Springer
Background Acute respiratory failure occurs frequently in hospitalized patients and often
starts before ICU admission. A risk stratification tool to predict mortality and risk for …

Development of a new score for early mortality prediction in trauma ICU patients: RETRASCORE

L Serviá, JA Llompart-Pou, M Chico-Fernández… - Critical Care, 2021 - Springer
Background Severity scores are commonly used for outcome adjustment and benchmarking
of trauma care provided. No specific models performed only with critically ill patients are …

Artificial neural networks improve early outcome prediction and risk classification in out-of-hospital cardiac arrest patients admitted to intensive care

J Johnsson, O Björnsson, P Andersson, A Jakobsson… - Critical care, 2020 - Springer
Background Pre-hospital circumstances, cardiac arrest characteristics, comorbidities and
clinical status on admission are strongly associated with outcome after out-of-hospital …

Assessment of performance of four mortality prediction systems in a Saudi Arabian intensive care unit

Y Arabi, S Haddad, R Goraj, A Al-Shimemeri… - Critical care, 2002 - Springer
Introduction The purpose of this study is to assess the performance of Acute Physiology and
Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II …

Optimized diagnosis-based comorbidity measures for all-cause mortality prediction in a national population-based ICU population

A Aronsson Dannewitz, B Svennblad, K Michaëlsson… - Critical Care, 2022 - Springer
Background We aimed to optimize prediction of long-term all-cause mortality of intensive
care unit (ICU) patients, using quantitative register-based comorbidity information assessed …